U.S. patent application number 11/200822 was filed with the patent office on 2006-02-23 for methods of classifying, diagnosing, stratifying and treating cancer patients and their tumors.
Invention is credited to David Botstein, Patrick O. Brown, Charles M. Perou, Brian Ring, Douglas Ross, Rob Seitz, Jan Matthijs van de Rijn.
Application Number | 20060040302 11/200822 |
Document ID | / |
Family ID | 22825782 |
Filed Date | 2006-02-23 |
United States Patent
Application |
20060040302 |
Kind Code |
A1 |
Botstein; David ; et
al. |
February 23, 2006 |
Methods of classifying, diagnosing, stratifying and treating cancer
patients and their tumors
Abstract
The invention provides a variety of reagents for use in the
diagnosis and management of cancer, particularly breast cancer.
cDNA microarray technology was used to identify genes whose
expression profile across a large group of tumor samples correlates
with that of cytokeratin 5 and cytokeratin 17, markers for basal
cells of the normal mammary lactation gland. The invention
demonstrates that tumors that express cytokeratin 5/6 and/or 17
have a poor prognosis relative to tumors overall. The invention
provides basal marker genes and their expression products and uses
of these genes for diagnosis of cancer and for identification of
therapies for cancer. In particular, the invention provides basal
marker genes including cadherin3, matrix metalloproteinase 14, and
cadherin EGF LAG seven-pass G-type receptor 2. The invention
provides antibodies to the polypeptides expressed by these genes
and methods of use thereof.
Inventors: |
Botstein; David; (Belmont,
CA) ; Brown; Patrick O.; (Stanford, CA) ;
Perou; Charles M.; (Carrboro, NC) ; Ring; Brian;
(Foster City, CA) ; Ross; Douglas; (Burlingame,
CA) ; Seitz; Rob; (Huntsville, AL) ; van de
Rijn; Jan Matthijs; (Redwood City, CA) |
Correspondence
Address: |
CHOATE, HALL & STEWART LLP
TWO INTERNATIONAL PLACE
BOSTON
MA
02110
US
|
Family ID: |
22825782 |
Appl. No.: |
11/200822 |
Filed: |
August 10, 2005 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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09916849 |
Jul 26, 2001 |
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11200822 |
Aug 10, 2005 |
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60220967 |
Jul 26, 2000 |
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Current U.S.
Class: |
435/6.18 ;
435/6.1; 435/7.23 |
Current CPC
Class: |
C07K 16/18 20130101;
C07K 14/4748 20130101; A61K 38/00 20130101 |
Class at
Publication: |
435/006 ;
435/007.23 |
International
Class: |
C12Q 1/68 20060101
C12Q001/68; G01N 33/574 20060101 G01N033/574 |
Goverment Interests
GOVERNMENT SUPPORT
[0002] The U.S. Government has a paid-up license in this invention
and the right in limited circumstances to require the patent owner
to license others on reasonable terms as provided for by the terms
of Grant No. NIH CA 77097 awarded by the National Cancer Institute.
Claims
1. A method of classifying a tumor comprising the steps of:
providing a tumor sample; detecting expression or activity of a
gene encoding the polypeptide of SEQ ID NO:1 in the sample; and
classifying the tumor as belonging to a tumor subclass based on the
results of the detecting step.
2. A method of classifying a tumor comprising the steps of:
providing a tumor sample; detecting expression or activity of a
gene encoding the polypeptide of SEQ ID NO:2 in the sample; and
classifying the tumor as belonging to a tumor subclass based on the
results of the detecting step.
3. A method of classifying a tumor comprising the steps of:
providing a tumor sample; detecting expression or activity of a
gene encoding the polypeptide of SEQ ID NO:3 in the sample; and
classifying the tumor as belonging to a tumor subclass based on the
results of the detecting step.
4. A method of classifying a tumor comprising the steps of:
providing a tumor sample; detecting expression or activity of at
least two genes selected from the group consisting of: a gene
encoding the polypeptide of SEQ ID NO:1, SEQ ID NO:2, and SEQ ID
NO:3 in the sample; and classifying the tumor as belonging to a
tumor subclass based on the results of the detecting step.
5. The method of any of claims 1, 2, 3, or 4, wherein the detecting
step comprises detecting the polypeptide or polypeptides.
6. The method of claim 5, wherein the polypeptide is detected by
performing immunohistochemical analysis on the sample using an
antibody that specifically binds to the polypeptide.
7. The method of claim 5, wherein the polypeptide is detected by
performing an ELISA assay using an antibody that specifically binds
to the polypeptide.
8. The method of claim 5, wherein the polypeptide is detected using
an antibody array comprising an antibody that specifically binds to
the polypeptide.
9. The method of claim 5, wherein the detecting step comprises:
detecting modification of a substrate by the polypeptide.
10. The method of any of claims 1, 2, 3, or 4, wherein classifying
a tumor comprises: stratifying a subject having the tumor for a
clinical trial.
11. The method of claim 10, wherein the tumor is a breast
tumor.
12. The method of any of claims 1, 2, 3, or 4, wherein the tumor is
a breast tumor and the tumor subclass is a basal tumor
subclass.
13. The method of claim 1, further comprising: providing
diagnostic, prognostic, or predictive information based on the
classifying step.
14. The method of claim 2, further comprising: providing
diagnostic, prognostic, or predictive information based on the
classifying step.
15. The method of claim 3, further comprising: providing
diagnostic, prognostic, or predictive information based on the
classifying step.
16. The method of claim 4, further comprising: providing
diagnostic, prognostic, or predictive information based on the
classifying step.
17. The method of claim 5, further comprising: providing
diagnostic, prognostic, or predictive information based on the
classifying step.
18. The method of claim 17, wherein the polypeptide is detected by
performing immunohistochemical analysis on the sample using an
antibody that specifically binds to the polypeptide.
19. The method of claim 17, wherein the polypeptide is detected by
performing an ELISA assay using an antibody that specifically binds
to the polypeptide.
20. The method of claim 17, wherein the polypeptide is detected
using an antibody array comprising an antibody that specifically
binds to the polypeptide.
21. The method of claim 17, wherein the detecting step comprises:
detecting modification of a substrate by the polypeptide.
22. The method of any of claims 13, 14, 15, or 16, wherein the
tumor is a breast tumor and the tumor subclass is a basal tumor
subclass.
23. The method of claim 1, further comprising: selecting a
treatment based on the classifying step.
24. The method of claim 2, further comprising: selecting a
treatment based on the classifying step.
25. The method of claim 3, further comprising: selecting a
treatment based on the classifying step.
26. The method of claim 4, further comprising: selecting a
treatment based on the classifying step.
27. The method of claim 5, further comprising: selecting a
treatment based on the classifying step.
28. The method of claim 27, wherein the polypeptide is detected by
performing immunohistochemical analysis on the sample using an
antibody that specifically binds to the polypeptide.
29. The method of claim 27, wherein the polypeptide is detected by
performing an ELISA assay using an antibody that specifically binds
to the polypeptide.
30. The method of claim 27, wherein the polypeptide is detected
using an antibody array comprising an antibody that specifically
binds to the polypeptide.
31. The method of claim 27, wherein the detecting step comprises:
detecting modification of a substrate by the polypeptide.
32. The method of any of claims 23, 24, 25, or 26, wherein the
tumor is a breast tumor and the tumor subclass is a basal tumor
subclass.
33. A method of testing a subject comprising the steps of:
providing a sample isolated from a subject; detecting expression or
activity of a gene encoding the polypeptide of SEQ ID NO:1 in the
sample; and providing diagnostic, prognostic, or predictive
information based on the detecting step.
34. A method of testing a subject comprising the steps of:
providing a sample isolated from a subject; detecting expression or
activity of a gene encoding the polypeptide of SEQ ID NO:2 in the
sample; and providing diagnostic, prognostic, or predictive
information based on the detecting step.
35. A method of testing a subject comprising the steps of:
providing a sample isolated from a subject; detecting expression or
activity of a gene encoding the polypeptide of SEQ ID NO:3 in the
sample; and providing diagnostic, prognostic, or predictive
information based on the detecting step.
36. A method of testing a subject comprising the steps of:
providing a sample isolated from the subject; detecting expression
or activity of at least two genes selected from the group
consisting of: a gene encoding the polypeptide of SEQ ID NO:1, SEQ
ID NO:2, and SEQ ID NO:3 in the sample; and providing diagnostic,
prognostic, or predictive information based on the detecting
step.
37. The method of any of claims 33, 34, 35, or 36, wherein the
detecting step comprises detecting the polypeptide or
polypeptides.
38. The method of claim 37, wherein the polypeptide is detected by
performing immunohistochemical analysis on the sample using an
antibody that specifically binds to the polypeptide.
39. The method of claim 37, wherein the polypeptide is detected by
performing an ELISA assay using an antibody that specifically binds
to the polypeptide.
40. The method of claim 37, wherein the polypeptide is detected
using an antibody array comprising an antibody that specifically
binds to the polypeptide.
41. The method of claim 37, wherein the detecting step comprises:
detecting modification of a substrate by the polypeptide.
42. The method of any of claims 33, 34, 35, or 36, wherein the
sample is selected from the group consisting of: a blood sample, a
urine sample, a serum sample, an ascites sample, a saliva sample, a
cell, and a portion of tissue.
43. The method of any of claims 33, 34, 35, or 36, wherein the
sample is a tumor sample.
44. The method of claim 43, wherein the tumor sample is a breast
tumor sample.
45. A method of testing a subject comprising the steps of:
providing a sample isolated from a subject; detecting expression or
activity of a gene encoding the polypeptide of SEQ ID NO:1 in the
sample; and stratifying the subject for a clinical trial based on
the detecting step.
46. A method of testing a subject comprising the steps of:
providing a sample isolated from a subject; detecting expression or
activity of a gene encoding the polypeptide of SEQ ID NO:2 in the
sample; and stratifying the subject for a clinical trial based on
the detecting step.
47. A method of testing a subject comprising the steps of:
providing a sample isolated from a subject; detecting expression or
activity of a gene encoding the polypeptide of SEQ ID NO:3 in the
sample; and stratifying the subject for a clinical trial based on
the detecting step.
48. A method of testing a subject comprising the steps of:
providing a sample isolated from the subject; detecting expression
or activity of at least two genes selected from the group
consisting of: a gene encoding the polypeptide of SEQ ID NO:1, SEQ
ID NO:2, and SEQ ID NO:3 in the sample; and stratifying the subject
for a clinical trial based on the detecting step.
49. The method of any of claims 45, 46, 47, or 48, wherein the
detecting step comprises detecting the polypeptide or
polypeptides.
50. The method of claim 49, wherein the polypeptide is detected by
performing immunohistochemical analysis on the sample using an
antibody that specifically binds to the polypeptide.
51. The method of claim 49, wherein the polypeptide is detected by
performing an ELISA assay using an antibody that specifically binds
to the polypeptide.
52. The method of claim 49, wherein the polypeptide is detected
using an antibody array comprising an antibody that specifically
binds to the polypeptide.
53. The method of claim 49, wherein the detecting step comprises:
detecting modification of a substrate by the polypeptide.
54. The method of any of claims 45, 46, 47, or 48, wherein the
sample is selected from the group consisting of: a blood sample, a
urine sample, a serum sample, an ascites sample, a saliva sample, a
cell, and a portion of tissue.
55. The method of any of claims 45, 46, 47, or 48, wherein the
sample is a tumor sample.
56. The method of claim 55, wherein the tumor sample is a breast
tumor sample.
57. A method of testing a subject comprising the steps of:
providing a sample isolated from a subject; detecting expression or
activity of a gene encoding the polypeptide of SEQ ID NO:1 in the
sample; and selecting a treatment based on the detecting step.
58. A method of testing a subject comprising the steps of:
providing a sample isolated from a subject; detecting expression or
activity of a gene encoding the polypeptide of SEQ ID NO:2 in the
sample; and selecting a treatment based on the detecting step.
59. A method of testing a subject comprising the steps of:
providing a sample isolated from a subject; detecting expression or
activity of a gene encoding the polypeptide of SEQ ID NO:3 in the
sample; and selecting a treatment based on the detecting step.
60. A method of testing a subject comprising the steps of:
providing a sample isolated from the subject; detecting expression
or activity of at least two genes selected from the group
consisting of: a gene encoding the polypeptide of SEQ ID NO:1, SEQ
ID NO:2, and SEQ ID NO:3 in the sample; and selecting a treatment
based on the detecting step.
61. The method of any of claims 57, 58, 59, or 60, wherein the
detecting step comprises detecting the polypeptide or
polypeptides.
62. The method of claim 61, wherein the polypeptide is detected by
performing immunohistochemical analysis on the sample using an
antibody that specifically binds to the polypeptide.
63. The method of claim 61, wherein the polypeptide is detected by
performing an ELISA assay using an antibody that specifically binds
to the polypeptide.
64. The method of claim 61, wherein the polypeptide is detected
using an antibody array comprising an antibody that specifically
binds to the polypeptide.
65. The method of claim 61, wherein the detecting step comprises:
detecting modification of a substrate by the polypeptide.
66. The method of any of claims 57, 58, 59, or 60, wherein the
sample is selected from the group consisting of: a blood sample, a
urine sample, a serum sample, an ascites sample, a saliva sample, a
cell, and a portion of tissue.
67. The method of any of claims 57, 58, 59, or 60, wherein the
sample is a tumor sample.
68. The method of claim 67, wherein the tumor sample is a breast
tumor sample.
69. An antibody that specifically binds to an epitope found in a
polypeptide whose amino acid sequence the amino acid sequence of
SEQ ID NO:1, and wherein the antibody recognizes basal cells in
normal mammary lactation glands.
70. The antibody of claim 69, wherein the antibody distinguishes
basal cells from luminal cells in normal mammary lactation
glands.
71. The antibody of claim 69, wherein the antibody is a monoclonal
antibody.
72. The antibody of claim 69, wherein the antibody is a polyclonal
antibody.
73. The antibody of claim 69, wherein the antibody recognizes an
epitope found in a peptide having an amino acid sequence selected
from the group consisting of SEQ ID NO:4, SEQ ID NO:5, and SEQ ID
NO:6.
74. An antibody that specifically binds to an epitope found in a
polypeptide whose amino acid sequence comprises the amino acid
sequence of SEQ ID NO:2, and wherein the antibody recognizes basal
cells in normal mammary lactation glands.
75. The antibody of claim 73, wherein the antibody distinguishes
basal cells from luminal cells in normal mammary lactation
glands.
76. The antibody of claim 73, wherein the antibody is a monoclonal
antibody.
77. The antibody of claim 73, wherein the antibody is a polyclonal
antibody.
78. The antibody of claim 73, wherein the antibody recognizes an
epitope found in a peptide having an amino acid sequence selected
from the group consisting of SEQ ID NO:7, SEQ ID NO:8, and SEQ ID
NO:9.
79. An antibody that specifically binds to an epitope found in a
polypeptide whose amino acid sequence comprises the amino acid
sequence of SEQ ID NO:3, and wherein the antibody recognizes basal
cells in normal mammary lactation glands.
80. The antibody of claim 79, wherein the antibody distinguishes
basal cells from luminal cells in normal mammary lactation
glands.
81. The antibody of claim 79, wherein the antibody is a monoclonal
antibody.
82. The antibody of claim 79, wherein the antibody is a polyclonal
antibody.
83. The antibody of claim 79, wherein the antibody recognizes an
epitope found in a peptide having an amino acid sequence selected
from the group consisting of SEQ ID NO:10, SEQ ID NO:11, and SEQ ID
NO:12.
84. A kit for tumor diagnosis comprising: one or more of the
antibodies of any of claims 68 through 82; instructions for use of
the kit; and a control slide comprising breast tissue samples for
testing reagents in the kit.
85. A method of testing a compound or a combination of compounds
for activity against tumors comprising steps of: obtaining or
providing tumor samples taken from subjects who have been treated
with the compound or combination of compounds, wherein the tumors
fall within a tumor subclass; comparing the response rate of tumors
that fall within the tumor subclass and have been treated with the
compound with the overall response rate of tumors that have been
treated with the compound or combination of compounds or with the
response rate of tumors that do not fall within the subclass and
have been treated with the compound or combination of compounds;
and identifying the compound or combination of compounds as having
selective activity against tumors in the tumor subclass if the
response rate of tumors in the subclass is greater than the overall
response rate or the response rate of tumors that do not fall
within the subclass.
86. The method of claim 85, wherein the tumors are breast
tumors.
87. The method of claim 86, wherein the tumor subclass is a basal
tumor subclass.
88. The method of claim 86, wherein the tumors are classified
according to the method of any of claims 1, 2, 3, or 4.
89. The method of claim 86, wherein the tumor subclass is a basal
tumor subclass and wherein a tumor is identified as belonging to
the tumor subclass based on evidence of expression of one or more
basal marker genes in the sample.
90. The method of claim 89, wherein evidence of expression
comprises presence of a protein encoded by a basal marker gene, and
wherein the evidence of expression is obtained using an antibody
that binds to the protein.
91. The method of claim 90, wherein the basal marker gene encodes a
polypeptide comprising the amino acid sequence of SEQ ID NO:1.
92. The method of claim 90, wherein the basal marker gene encodes a
polypeptide comprising the amino acid sequence of SEQ ID NO:2.
93. The method of claim 90, wherein the basal marker gene encodes a
polypeptide comprising the amino acid sequence of SEQ ID NO:3.
94. The method of claim 85, wherein the samples are present within
a tissue array.
95. A method of testing a compound or a combination of compounds
for activity against tumors comprising steps of: treating subjects
in need of treatment for tumors with the compound or combination of
compounds; comparing the response rate of tumors that fall within a
tumor subclass with the overall response rate of tumors or with the
response rate of tumors that do not fall within the subclass; and
identifying the compound or combination of compounds as having
selective activity against tumors in the tumor subclass if the
response rate of tumors in the subclass is greater than the overall
response rate or the response rate of tumors that do not fall
within the subclass.
96. The method of claim 95, further comprising the steps of:
providing tumor samples from subjects in need of treatment for
tumors; determining whether the tumors fall within a tumor
subclass; and stratifying the subjects based on the results of the
determining step prior to performing the treating step.
97. The method of claim 95, further comprising the steps of:
providing tumor samples from subjects in need of treatment for
tumors; detecting expression or activity of a gene encoding the
polypeptide of SEQ ID NO:1 in the samples; and stratifying the
subjects based on the results of the detecting step prior to
performing the the treating step.
98. The method of claim 95, further comprising the steps of:
providing tumor samples from subjects in need of treatment for
tumors; detecting expression or activity of a gene encoding the
polypeptide of SEQ ID NO:2 in the samples; and stratifying the
subjects based on the results of the detecting step prior to
performing the treating step.
99. The method of claim 95, further comprising the steps of:
providing tumor samples from subjects in need of treatment for
tumors; detecting expression or activity of a gene encoding the
polypeptide of SEQ ID NO:3 in the samples; and stratifying the
subjects based on the results of the detecting step prior to
performing the treating step.
100. The method of claim 95, further comprising the steps of:
providing tumor samples from subjects in need of treatment for
tumors; detecting expression or activity of at least two genes,
wherein each of the genes encodes a polypeptide whose sequence
comprises a sequence selected from the group consisting of SEQ ID
NO:1, SEQ ID NO:2, and SEQ ID NO:3 in the samples; and stratifying
the subjects based on the results of the detecting step prior to
performing the treating step.
101. A method of testing a compound or a combination of compounds
for activity against tumors comprising steps of: treating subjects
in need of treatment for tumors with the compound or combination of
compounds or with an alternate compound, wherein the tumors fall
within a tumor subclass; comparing the response rate of tumors
treated with the compound or combination of compounds with the
response rate of tumors treated with the alternate compound; and
identifying the compound or combination of compounds as having
superior activity against tumors in the tumor subclass, as compared
with the alternate compound, if the response rate of tumors treated
with the compound or combination of compounds is greater than the
response rate of tumors treated with the alternate compound.
102. The method of claim 101, further comprising the steps of:
providing tumor samples from subjects in need of treatment for
tumors; determining whether the tumors fall within a tumor
subclass; and stratifying the subjects based on the results of the
determining step prior to performing the treating step.
103. The method of claim 101, further comprising the steps of:
providing tumor samples from subjects in need of treatment for
tumors; detecting expression or activity of a gene encoding the
polypeptide of SEQ ID NO:1 in the samples; and stratifying the
subjects based on the results of the detecting step prior to
performing the treating step.
104. The method of claim 101, further comprising the steps of:
providing tumor samples from subjects in need of treatment for
tumors; detecting expression or activity of a gene encoding the
polypeptide of SEQ ID NO:2 in the samples; and stratifying the
subjects based on the results of the detecting step prior to
performing the treating step.
105. The method of claim 101, further comprising the steps of:
providing tumor samples from subjects in need of treatment for
tumors; detecting expression or activity of a gene encoding the
polypeptide of SEQ ID NO:3 in the samples; and stratifying the
subjects based on the results of the detecting step prior to
performing the treating step.
106. The method of claim 101, further comprising the steps of:
providing tumor samples from subjects in need of treatment for
tumors; detecting expression or activity of at least two genes,
wherein each of the genes encodes a polypeptide whose sequence
comprises a sequence selected from the group consisting of SEQ ID
NO:1, SEQ ID NO:2, and SEQ ID NO:3 in the samples; and stratifying
the subjects based on the results of the detecting step prior to
performing the treating step.
107. The method of any of claims 101, 102, 103, 104, 105, or 106,
wherein the alternate compound is a compound approved by the U.S.
Food and Drug administration for treatment of tumors.
108. A method of treating a subject comprising steps of:
identifying a subject as having a tumor in a basal tumor subclass;
and administering a compound identified according to the method of
any of claims 85, 86, 87, or 90 to the subject.
109. A method of treating a subject comprising steps of:
identifying a subject as having a tumor in a basal tumor subclass;
and administering a compound identified according to the method of
any of claims 95, 96, 97, 98, 99, or 100 to the subject.
110. A method of treating a subject comprising steps of:
identifying a subject as having a tumor in a basal tumor subclass;
and administering a compound identified according to the method of
any of claims 101, 102, 103, 104, 105, or 106 to the subject.
111. A method of treating a subject comprising steps of: providing
a subject in need of treatment for cancer; administering to the
subject an antibody that specifically binds to a polypeptide having
an amino acid sequence comprising the sequence of SEQ ID NO:1.
112. A method of treating a subject comprising steps of: providing
a subject in need of treatment for a tumor; administering to the
subject an antibody that specifically binds to a polypeptide having
an amino acid sequence comprising the sequence of SEQ ID NO:2.
113. A method of treating a subject comprising steps of: providing
a subject in need of treatment for a tumor; administering to the
subject an antibody that specifically binds to a polypeptide having
an amino acid sequence comprising the sequence of SEQ ID NO:3.
114. The method of any of claims 111, 112, or 113, wherein the
tumor is a breast tumor, and wherein the method further comprises
the step of: identifying the tumor as belonging to a basal tumor
subclass.
115. The method of any of claims 111, 112, or 113, wherein the
antibody is conjugated with a toxic molecule.
116. A method of treating a subject comprising steps of: providing
a subject in need of treatment for cancer; administering to the
subject a compound that activates or inhibits a gene that encodes
an amino acid having a sequence comprising the sequence of SEQ ID
NO:1, or that activates or inhibits an expression product of the
gene.
117. A method of treating a subject comprising steps of: providing
a subject in need of treatment for a tumor; administering to the
subject a compound that activates or inhibits a gene that encodes
an amino acid having a sequence comprising the sequence of SEQ ID
NO:2, or that activates or inhibits an expression product of the
gene.
118. A method of treating a subject comprising steps of: providing
a subject in need of treatment for a tumor; administering to the
subject a compound that activates or inhibits a gene that encodes
an amino acid having a sequence comprising the sequence of SEQ ID
NO:3, or that activates or inhibits an expression product of the
gene.
119. A composition comprising: two or more compounds identified
according to the method of any of claims 85, 95, or 101.
120. A pharmaceutical composition comprising: the composition of
claim 119; and a pharmaceutically acceptable carrier.
121. A composition comprising: a compound identified according to
the method of any of claims 85, 95, or 101; a second compound,
wherein the second compound is approved by the U.S. Food and Drug
administration for the treatment of cancer or has shown potential
efficacy against cancer in pre-clinical studies.
122. A pharmaceutical composition comprising: the composition of
claim 121, and a pharmaceutically acceptable carrier.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a divisional application of U.S. Ser.
No. 09/916,849, filed Jul. 26, 2001 which claims priority to
provisional application U.S. Ser. No. 60/220,967, filed Jul. 26,
2000, each of which is incorporated herein by reference.
REFERENCE TO MATERIAL PRESENTED IN APPENDICES
[0003] This patent application refers to material comprising tables
and data that were presented as appendices on CD-ROM in parent
application U.S. Ser. No. 09/916,849, filed Jul. 26, 2001. A
duplicate CD-ROM is not being presented with this divisional
application; instead the entire contents of Appendices A-H are
incorporated herein by reference via parent application U.S. Ser.
No. 09/916,849, filed Jul. 26, 2001. A paper copy of Appendix H,
Tables 3-16 are also being presented with this divisional. The 24
files on the CD-ROM are entitled Appendix A (4,651 kb), Appendix B
(481 kb), Appendix C (7,810 kb), Appendix D (3,721 kb), Appendix E
(1238 kb), Appendix F (540 kb), Appendix G (377 kb),
AppendixH_Table1 (2,102 kb), AppendixH_Table2 (760 kb),
AppendixH_Table3 (22 kb), AppendixH_Table4 (25 kb),
AppendixH_Table5 (27 kb), AppendixH_Table6 (655 kb),
AppendixH_Table7 (88 kb), AppendixH_Table8 (28 kb),
AppendixH_Table9-1 (22 kb), AppendixH_Table9-2 (22 kb),
AppendixH_Table10 (21 kb), AppendixH_Table11 (22 kb),
AppendixH_Table12 (23 kb), AppendixH_Table13 (21 kb),
AppendixH_Table14 (23 kb), AppendixH_Table15 (21 kb),
AppendixH_Table16 (21 kb). The size of each file in kilobytes is
listed following the file name. The total number of bytes is
23,164,507. All files were created on Jul. 25, 2001. The format is
IBM-PC. The operating system is Windows. The 24 files on the CD-ROM
are incorporated herein by reference.
BACKGROUND OF THE INVENTION
[0004] A major challenge of cancer treatment is to target specific
therapies to distinct tumor types in order to maximize efficacy and
minimize toxicity. A related challenge lies in the attempt to
provide accurate diagnostic, prognostic, and predictive
information. At present, tumors are described with the
tumor-node-metastasis (TNM) system. This system, which uses the
size of the tumor, the presence or absence of tumor in regional
lymph nodes, and the presence or absence of distant metastases, to
assign a stage to the tumor is described in the American Joint
Committee on Cancer: AJCC Cancer Staging Manual. Philadelphia, Pa.:
Lippincott-Raven Publishers, 5th ed., 1997, pp 171-180, and in
Harris, J R: "Staging of breast carcinoma" in Harris, J. R.,
Hellman, S., Henderson, I. C., Kinne D. W. (eds.): Breast Diseases.
Philadelphia, Lippincott, 1991. The assigned stage is used as a
basis for selection of appropriate therapy and for prognostic
purposes. In addition to the TNM parameters, morphologic appearance
is used to further classify tumors and thereby aid in selection of
appropriate therapy. However, this approach has serious
limitations. Tumors with similar histopathologic appearance can
exhibit significant variability in terms of clinical course and
response to therapy. For example, some tumors are rapidly
progressive while others are not. Some tumors respond readily to
hormonal therapy or chemotherapy while others are resistant.
[0005] Assays for cell surface markers, e.g., using
immunohistochemistry, have provided means for dividing certain
tumor types into subclasses. For example, one factor considered in
prognosis and in treatment decisions for breast cancer is the
presence or absence of the estrogen receptor (ER) in tumor samples.
ER-positive breast cancers typically respond much more readily to
hormonal therapies such as tamoxifen, which acts as an
anti-estrogen in breast tissue, than ER-negative tumors. Though
useful, these analyses only in part predict the clinical behavior
of breast tumors. There is phenotypic diversity present in breast
cancers that current diagnostic tools fail to detect. Therefore,
there exists a need for improved methods for classifying
tumors.
[0006] Mutation or dysregulation of any of a large number of genes
contributes to the development and progression of cancer as
discussed in Hanahan, D. and Weinberg, R., The Hallmarks of Cancer,
Cell, 100, 57-70, 2000. Genes that play a role in cancer can be
divided into a number of broad classes including oncogenes, tumor
suppressor genes, and genes that regulate apoptosis. Oncogenes such
as ras typically encode proteins whose activities promote cell
growth and/or division, a function that is necessary for normal
physiological processes such as development, tissue regeneration,
and wound healing. However, inappropriate activity or expression of
oncogenes can lead to the uncontrolled cell proliferation that is a
feature of cancer. Tumor suppressor genes such as Rb act as
negative regulators of cell proliferation. Loss of their activity,
e.g., due to mutations or decreased expression at the level of mRNA
or protein, can lead to unrestrained cell division. A number of
familial cancer syndromes and inherited susceptibility to cancer
are believed to be caused by mutations in tumor suppressor genes.
Apoptosis, or programmed cell death, plays important roles both in
normal development and in surveillance to eliminate cells whose
survival may be deleterious to the organism, e.g., cells that have
acquired DNA damage. Many chemotherapeutic agents are believed to
work by activating the endogenous apoptosis pathway in tumor
cells.
[0007] Although a substantial number of genes have been implicated
as playing important roles in cancer, the factors responsible for
the phenotypic diversity of tumors remain largely unknown. In
particular, understanding of the underlying differences in gene
expression that may contribute to tumor phenotype is limited.
Understanding the differences in gene expression between normal and
cancerous tissue and between different tumors of the same tissue
type is of significant diagnostic, prognostic, and therapeutic
utility. There is therefore a need for the identification of genes
exhibiting differential expression between tumors. In particular,
there is a need for the identification of additional genes and
proteins that can be used to classify tumors, especially genes and
proteins that can provide diagnostic, prognostic, and/or predictive
information in cancer. There is also a need for antibodies and
other reagents for the detection and measurement of such genes and
proteins.
[0008] Most of the commonly used chemotherapeutic agents act
relatively nonselectively. Rather than specifically killing tumor
cells, these agents target any dividing cell, resulting in a
variety of adverse effects. In addition, current therapeutic
strategies are of limited efficacy, and the mortality rate of
breast cancer remains high. There is therefore a need for the
identification of additional genes and proteins that can be used as
targets for the treatment of cancer. There is also a need for
antibodies and other reagents that can modulate, regulate, or
interact with these genes and proteins to provide new method of
treatment for cancer.
SUMMARY OF THE INVENTION
[0009] The present invention relates to the identification of
markers that are useful in classifying tumors, particularly breast
tumors. The markers identify a class of tumors whose cells have
characteristics of basal cells of normal breast lactation ducts.
The markers were identified based on their expression profiles in
human breast tumor samples, normal breast tissue, and cell lines as
assessed using cDNA microarrays. In particular, the basal cell
markers of the present invention were identified based on the
similarity of their mRNA expression patterns to the expression
patterns of markers previously known to identify breast duct basal
cells, e.g., cytokeratin 5 and cytokeratin 17, across a set of
breast tumor samples. The basal markers include the three genes
known as cadherin 3 or P-cadherin (SEQ ID NO:1; GenBank protein
accession number NP.sub.--001784; GenBank cDNA accession number
NM.sub.--001793), matrix metalloproteinase 14 (SEQ ID NO:2; GenBank
protein accession number NP.sub.--004986; GenBank cDNA accession
number NM.sub.--004995); and cadherin EGF LAG seven-pass G-type
receptor 2 or EGF-Like Domain, Multiple 2 (SEQ ID NO:3; GenBank
protein accession number NP.sub.--001399; GenBank cDNA accession
number NM.sub.--001408). The invention further provides antibodies
that specifically bind to the polypeptides encoded by the basal
marker genes identified herein. The antibodies recognize basal
cells of normal mammary lactation glands.
[0010] The invention provides various diagnostic methods based on
the reagents mentioned above. The diagnostic methods include
methods for classifying a tumor. In particular, the invention
allows classification of a breast tumor as belonging to a basal
class of breast tumors. According to certain of the inventive
methods the presence or amount of a gene product, e.g., a
polypeptide or a nucleic acid, encoded by a basal marker gene is
detected in a sample derived from a subject (e.g., a sample of
tissue or cells obtained from a tumor or a blood sample obtained
from a subject). In general the subject is a human, however the
subject may also be an animal of any other kind. The subject may be
an individual who has or may have a tumor. The sample may be
subjected to various processing steps prior to or in the course of
detection. In certain embodiments of the invention the gene product
is a polypeptide that is detected using an antibody capable of
binding to the polypeptide. In certain embodiments of the invention
the antibody is used to perform immunohistochemical staining on a
sample obtained from a subject. In certain embodiments of the
invention basal marker gene mRNA expression is measured using a
microarray. In other embodiments of the invention basal marker gene
mRNA expression is measured by quantitative PCR using a set of
primers designed to amplify a portion of the gene. Additional
detection means that may be employed in the present invention are
described in U.S. Pat. No. 6,057,105. In any of the methods for
tumor classification and diagnosis, it may be advantageous to
detect and/or measure expression of a set of basal markers rather
than expression of a single marker.
[0011] By providing reagents that may reliably be used to classify
tumors as belonging to a basal subclass, the invention enables a
variety of methods for improving therapeutic options for patients
with breast cancer. Much effort has and continues to be expended on
the discovery of new chemotherapeutic agents. These agents are
tested for efficacy in clinical trials. In many such trials it is
noticed that a small number of patients stabilize or improve while
receiving the treatment, while most patients do not appear to
benefit. Most such agents are not further developed for a number of
reasons. For example, the clinical trial results may not be
adequate to gain approval by the Food and Drug Administration. In
addition, a pharmaceutical company may determine that the potential
market for the drug is too small to justify further efforts.
However, if it were possible to identify those patients likely to
respond to the treatment, then it would be possible to design
clinical trials that would show efficacy, and it would be possible
to appropriately select patients who would benefit from the
treatment. In addition, the availability of markers that can be
used to classify breast tumors enables the retrospective
examination of the thousands of breast tumor samples archived in
hospitals and pathology labs. These samples can be classified using
the inventive reagents and classification scheme, and the results
can be correlated with the clinical outcome, based on medical
records. Thus it is possible to determine whether tumors that fall
into a particular tumor class, e.g., a basal tumor class, are
responsive to a particular treatment. This will enable the
re-evaluation of drugs that failed in clinical trials and may
identify a subset of tumors that are likely to respond to a
particular drug, and thus a subset of patients that are likely to
benefit from treatment with that drug.
[0012] The inventors have recognized that in order to achieve these
goals it is necessary to develop new and improved methods for
classifying breast tumors. The inventive methods provide a
molecular basis for classifying tumors, based on their underlying
biology. While not wishing to be bound by any theory, the inventors
postulate that tumors arising from a particular cell type within
the breast are likely to display common features. Such features may
include the prognosis (e.g., predicted survival time or likelihood
that a patient's life expectancy exceeds a given length of time) or
likelihood that a tumor will respond to a particular therapy.
[0013] In particular, tumors that display characteristics of basal
cells of the normal breast lactation duct (also referred to herein
as breast basal cells) form a distinct subclass (referred to herein
as the basal subclass). Inventors have confirmed that patients with
breast tumors whose cells display characteristics of breast basal
cells, e.g., expression of cytokeratin 5 and/or cytokeratin 17,
have a poor clinical outcome relative to patients with breast
tumors that do not express these markers. However, antibodies to
these cytokeratins have been found (by the inventors and by other
investigators) to give spotty, focal staining patterns when used to
perform immunohistochemistry on breast tumor samples. Thus the
utility of cytokeratins 5 and 17 as markers and the utility of
antibodies that bind to cytokeratin 5 or 17 for determining whether
a tumor is a member of the basal subclass has been limited. The
inventors have therefore identified genes whose mRNA expression
profiles across a large set of tumor samples correlate with, i.e.
are similar to, the expression profiles of the known basal cell
markers cytokeratins 5 and 17. These genes include the basal
markers of the present invention mentioned above. As described in
Examples 10 and 13, the inventors have generated antibodies to the
proteins expressed by these genes and shown that the antibodies
stain basal cells of normal mammary lactation glands. Thus
detection of one or more expression products of these genes may be
used to identify tumors that fall within the basal tumor
subclass.
[0014] The invention further provides therapeutic agents based on
the identification of breast basal cell markers. The therapeutic
agents include compounds that modulate these genes or that modulate
polypeptides encoded by these genes. In particular, the therapeutic
agents include antibodies that bind to polypeptides encoded by the
basal cell marker genes. The invention further includes agonists
and antagonists to the basal marker genes, to the polynucleotides
transcribed from those genes, and to their encoded polypeptides.
The invention also provides methods for identifying such agonists
and antagonists. The invention further includes pharmaceutical
compositions comprising such antibodies, agonists, and antagonists
as well as methods of use of the pharmaceutical compositions in the
treatment of cancer, particularly breast cancer.
[0015] According to one aspect, the invention provides a method of
classifying a tumor comprising the steps of (i) providing a tumor
sample, (ii) detecting expression or activity of a gene encoding
the polypeptide of SEQ ID NO:1 in the sample; and (iii) classifying
the tumor as belonging to a tumor subclass based on the results of
the detecting step. The invention also provides a method of
classifying a tumor comprising the steps of (i) providing a tumor
sample, (ii) detecting expression or activity of a gene encoding
the polypeptide of SEQ ID NO:2 in the sample, and (iii) classifying
the tumor as belonging to a tumor subclass based on the results of
the detecting step. In addition, the invention provides a method of
classifying a tumor comprising the steps of (i) providing a tumor
sample, (ii) detecting expression or activity of a gene encoding
the polypeptide of SEQ ID NO:3 in the sample, and (iii) classifying
the tumor as belonging to a tumor subclass based on the results of
the detecting step. The invention further includes a method of
classifying a tumor comprising the steps of (i) providing a tumor
sample, (ii) detecting expression or activity of at least two genes
selected from the group consisting of: a gene encoding the
polypeptide of SEQ ID NO:1, SEQ ID NO:2, and SEQ ID NO:3 in the
sample, and (iii) classifying the tumor as belonging to a tumor
subclass based on the results of the detecting step. In any of the
foregoing methods the detecting step may comprise detecting the
polypeptide or polypeptides encoded by the genes. A variety of
detection techniques may be employed including, but not limited to,
immunohistochemical analysis, ELISA assay, antibody arrays, or
detecting modification of a substrate by the polypeptide.
[0016] In certain embodiments of the methods the tumor is a breast
tumor and the tumor subclass is a basal tumor subclass. The methods
may further comprise providing diagnostic, prognostic, or
predictive information based on the classifying step. Classifying
may include stratifying the tumor (and thus stratifying a subject
having the tumor), e.g., for a clinical trial. The methods may
further comprise selecting a treatment based on the classifying
step.
[0017] In another aspect, the invention provides a method of
testing a subject comprising the steps of (i) providing a sample
isolated from a subject, (ii) detecting expression or activity of a
gene encoding the polypeptide of SEQ ID NO:1 in the sample, and
(iii) providing diagnostic, prognostic, or predictive information
based on the detecting step. The invention further provides a
method of testing a subject comprising the steps of (i) providing a
sample isolated from a subject, (ii) detecting expression or
activity of a gene encoding the polypeptide of SEQ ID NO:2 in the
sample (iii) and providing diagnostic, prognostic, or predictive
information based on the detecting step. The invention further
provides a method of testing a subject comprising the steps of (i)
providing a sample isolated from a subject, (ii) detecting
expression or activity of a gene encoding the polypeptide of SEQ ID
NO:3 in the sample (iii) and providing diagnostic, prognostic, or
predictive information based on the detecting step. The invention
further includes a method of testing a subject comprising the steps
of (i) providing a sample isolated from the subject, (ii) detecting
expression or activity of at least two genes selected from the
group consisting of: a gene encoding the polypeptide of SEQ ID
NO:1, SEQ ID NO:2, and SEQ ID NO:3 in the sample, and (iii)
providing diagnostic, prognostic, or predictive information based
on the detecting step. In any of these methods the detecting step
may comprise detecting the polypeptide or polypeptides. Detection
may be performed using any appropriate technique including, but not
limited to, immunohistochemistry, ELISA assay, protein array, or
detecting modification of a substrate by the polypeptide.
[0018] The sample may comprise mRNA, in which case the detecting
step may comprise hybridizing the mRNA or cDNA or RNA synthesized
from the mRNA to a microarray or detecting mRNA transcribed from
the gene or detecting cDNA or RNA synthesized from mRNA transcribed
from the gene. In any of the above methods, the sample may be a
blood sample, a urine sample, a serum sample, an ascites sample, a
saliva sample, a cell, and a portion of tissue.
[0019] In another aspect, the invention provides a kit for
diagnosis of a tumor which may include (i) primers for amplifying
an mRNA transcribed from a gene that encodes the polypeptide of any
of SEQ ID NO:1, SEQ ID NO:2; and SEQ ID NO:3 (ii) instructions for
use of the kit; and/or (iii) control samples for testing the
primers, wherein the control samples comprise nucleic acids that
hybridize to the primers.
[0020] In another aspect, the invention provides an antibody that
specifically binds to an epitope found in a polypeptide whose amino
acid sequence comprises the amino acid sequence of SEQ ID NO:1, and
wherein the antibody recognizes basal cells in normal mammary
lactation glands. According to certain embodiments of the invention
the antibody distinguishes basal cells from luminal cells in normal
mammary lactation gland. According to certain embodiments of the
invention the antibody recognizes an epitope found in a peptide
having an amino acid sequence selected from the group consisting of
SEQ ID NO:4, SEQ ID NO:5, and SEQ ID NO:6.
[0021] In another aspect, the invention provides an antibody that
specifically binds to an epitope found in a polypeptide whose amino
acid sequence comprises the amino acid sequence of SEQ ID NO:2, and
wherein the antibody recognizes basal cells in normal mammary
lactation glands. According to certain embodiments of the invention
the antibody distinguishes basal cells from luminal cells in normal
mammary lactation gland. According to certain embodiments of the
invention the antibody recognizes an epitope found in a peptide
having an amino acid sequence selected from the group consisting of
SEQ ID NO:7, SEQ ID NO:8, and SEQ ID NO:9.
[0022] In another aspect, the invention provides an antibody that
specifically binds to an epitope found in a polypeptide whose amino
acid sequence the amino acid sequence of SEQ ID NO:3, and wherein
the antibody recognizes basal cells in normal mammary lactation
glands. According to certain embodiments of the invention the
antibody distinguishes basal cells from luminal cells in normal
mammary lactation gland. According to certain embodiments of the
invention the antibody recognizes an epitope found in a peptide
having an amino acid sequence selected from the group consisting of
SEQ ID NO:10, SEQ ID NO:11, and SEQ ID NO:12.
[0023] The invention further provides a kit for tumor diagnosis
comprising one or more of the foregoing antibodies. The kit may
further include instructions for use of the kit and/or a control
slide comprising breast tissue samples for testing reagents in the
kit or such samples themselves.
[0024] According to another aspect, the invention provides a method
of testing a compound or a combination of compounds for activity
against tumors comprising steps of (i) obtaining or providing tumor
samples taken from subjects who have been treated with the compound
or combination of compounds, wherein the tumors fall within a tumor
subclass, (ii) comparing the response rate of tumors that fall
within the tumor subclass and have been treated with the compound
with the overall response rate of tumors that have been treated
with the compound or combination of compounds or with the response
rate of tumors that do not fall within the subclass and have been
treated with the compound or combination of compounds and (iii)
identifying the compound or combination of compounds as having
selective activity against tumors in the tumor subclass if the
response rate of tumors in the subclass is greater than the overall
response rate or the response rate of tumors that do not fall
within the subclass. In certain embodiments of the invention the
tumors are breast tumors. In certain embodiments of the invention
the tumor subclass is a basal tumor subclass. The tumors may be
classified according to any of the inventive classification methods
described above. In certain embodiments of the invention the
classification is based on expression of the polypeptide of SEQ ID
NO:1, 2, 3, or a combination of these.
[0025] The invention further provides a method of testing a
compound or a combination of compounds for activity against tumors
comprising steps of (i) treating subjects in need of treatment for
tumors with the compound or combination of compounds, (ii)
comparing the response rate of tumors that fall within a tumor
subclass with the overall response rate of tumors or with the
response rate of tumors that do not fall within the subclass, and
(iii) identifying the compound or combination of compounds as
having selective activity against tumors in the tumor subclass if
the response rate of tumors in the subclass is greater than the
overall response rate or the response rate of tumors that do not
fall within the subclass. The method may further comprise various
additional steps. For example, the method may comprise steps of (i)
providing tumor samples from subjects in need of treatment for
tumors, (ii) determining whether the tumors fall within a tumor
subclass, and (iii) stratifying the subjects based on the results
of the determining step prior to performing the treating step. The
method may further comprise the steps of (i) providing tumor
samples from subjects in need of treatment for tumors, (ii)
detecting expression or activity of a gene encoding the polypeptide
of SEQ ID NO:1 in the samples, and (iii) stratifying the subjects
based on the results of the detecting step prior to performing the
treating step. The method may further comprise the steps of (i)
providing tumor samples from subjects in need of treatment for
tumors, (ii) detecting expression or activity of a gene encoding
the polypeptide of SEQ ID NO:2 in the samples, and (iii)
stratifying the subjects based on the results of the detecting step
prior to performing the treating step. The method may further
comprise the steps of (i) providing tumor samples from subjects in
need of treatment for tumors, (ii) detecting expression or activity
of a gene encoding the polypeptide of SEQ ID NO:3 in the samples,
and (iii) stratifying the subjects based on the results of the
detecting step prior to performing the treating step. The method
may further comprise the steps of (i) providing tumor samples from
subjects in need of treatment for tumors, (ii) detecting expression
or activity of a gene encoding a polypeptide whose sequence
comprises a sequence selected from the group consisting of SEQ ID
NO:1, SEQ ID NO:2, and SEQ ID NO:3 in the samples, and (iii)
stratifying the subjects based on the results of the detecting step
prior to performing the treating step.
[0026] In addition, the invention includes a method of testing a
compound or a combination of compounds for activity against tumors
comprising steps of (i) treating subjects in need of treatment for
tumors with the compound or combination of compounds or with an
alternate compound, wherein the tumors fall within a tumor
subclass, (ii) comparing the response rate of tumors treated with
the compound or combination of compounds with the response rate of
tumors treated with the alternate compound; and (iii) identifying
the compound or combination of compounds as having superior
activity against tumors in the tumor subclass, as compared with the
alternate compound, if the response rate of tumors treated with the
compound or combination of compounds is greater than the response
rate of tumors treated with the alternate compound. The method may
further comprise various additional steps. For example, the method
may comprise steps of (i) providing tumor samples from subjects in
need of treatment for tumors, (ii) determining whether the tumors
fall within a tumor subclass, and (iii) stratifying the subjects
based on the results of the determining step prior to performing
the treating step. The method may further comprise the steps of (i)
providing tumor samples from subjects in need of treatment for
tumors, (ii) detecting expression or activity of a gene encoding
the polypeptide of SEQ ID NO:1 in the samples, and (iii)
stratifying the subjects based on the results of the detecting step
prior to performing the treating step. The method may further
comprise the steps of (i) providing tumor samples from subjects in
need of treatment for tumors, (ii) detecting expression or activity
of a gene encoding the polypeptide of SEQ ID NO:2 in the samples,
and (iii) stratifying the subjects based on the results of the
detecting step prior to performing the treating step. The method
may further comprise the steps of (i) providing tumor samples from
subjects in need of treatment for tumors, (ii) detecting expression
or activity of a gene encoding the polypeptide of SEQ ID NO:3 in
the samples, and (iii) stratifying the subjects based on the
results of the detecting step prior to performing the treating
step. The method may further comprise the steps of (i) providing
tumor samples from subjects in need of treatment for tumors, (ii)
detecting expression or activity of a gene encoding a polypeptide
whose sequence comprises a sequence selected from the group
consisting of SEQ ID NO:1, SEQ ID NO:2, and SEQ ID NO:3 in the
samples, and (iii) stratifying the subjects based on the results of
the detecting step prior to performing the treating step.
[0027] In certain embodiments of the invention the alternate
compound is a compound approved by the U.S. Food and Drug
administration for treatment of tumors. The invention also provides
a method of treating a subject comprising steps of (i) identifying
a subject as having a tumor in a basal tumor subclass, and (ii)
administering to the subject a compound identified according to any
of the inventive methods for identifying a subject.
[0028] #In another aspect, the invention provides a method of
treating a subject comprising steps of (i) providing a subject in
need of treatment for cancer, (ii) administering to the subject an
antibody that specifically binds to a polypeptide having an amino
acid sequence comprising the sequence of SEQ ID NO:1, SEQ ID NO:2,
or SEQ ID NO:3 or administering a combination of such antibodies.
In certain embodiments of the invention the tumor is a breast
tumor. In certain embodiments of the invention the antibody is
conjugated with a toxic molecule.
[0029] The invention further provides a method of treating a
subject comprising steps of (i) providing a subject in need of
treatment for cancer, (ii) administering to the subject a compound
that activates or inhibits a gene that encodes an amino acid having
a sequence comprising the sequence of SEQ ID NO:1, SEQ ID NO:2, or
SEQ ID NO:3, or that activates or inhibits an expression product of
the gene.
[0030] In another aspect, the invention provides a composition
comprising two or more compounds identified according to any of the
methods described above for identifying compounds. The invention
also provides a pharmaceutical composition comprising such a
composition and a pharmaceutically acceptable carrier. The
invention also provides a composition comprising (i) a compound
identified according to any of the methods described above for
identifying compounds and (ii) a second compound, wherein the
second compound is approved by the U.S. Food and Drug
administration for the treatment of cancer or has shown potential
efficacy against cancer in pre-clinical studies. The invention also
provides a pharmaceutical composition comprising such a composition
and a pharmaceutically acceptable carrier.
[0031] The present application refers to various patents,
publications, books, articles, and other references. The contents
of all of these items are hereby incorporated by reference in their
entirety. The present application also incorporates by reference
six U.S. patent applications filed by inventors on Jul. 26, 2001.
These applications are entitled "REAGENTS AND METHODS FOR USE IN
MANAGING BREAST CANCER", "BSTP-RAS/RERG PROTEIN AND RELATED
REAGENTS AND METHODS OF USE THEREOF", "BSTP-ECG1 PROTEIN AND
RELATED REAGENTS AND METHODS OF USE THEREOF", "BSTP-CAD PROTEIN AND
RELATED REAGENTS AND METHODS OF USE THEREOF", "BSTP-TRANS PROTEIN
AND RELATED REAGENTS AND METHODS OF USE THEREOF", "BSTP-5 PROTEINS
AND RELATED REAGENTS AND METHODS OF USE THEREOF".
BRIEF DESCRIPTION OF THE DRAWING
[0032] FIG. 1A presents the amino acid sequence of the polypeptide
encoded by the basal marker gene known as cadherin 3 or P-cadherin
(SEQ ID NO:1).
[0033] FIG. 1B presents the amino acid sequence of the polypeptide
encoded by the basal marker gene known as matrix metalloproteinase
14 (SEQ ID NO:2).
[0034] FIG. 1C presents the amino acid sequence of the polypeptide
encoded by the basal marker gene known as cadherin EGF LAG
seven-pass G-type receptor 2 or EGF-Like Domain, Multiple 2 (SEQ ID
NO:3).
[0035] FIG. 1D presents the amino acid sequences of peptides used
to raise antibodies that recognize the cadherin 3, matrix
metalloproteinase 14, cadherin EGF LAG seven-pass G-type receptor
2, and cytokeratin 17 proteins.
[0036] FIG. 2 shows a comparison of dendrograms representing the
results of hierarchical clustering of experimental samples using
the intrinsic gene set and the epithelial-enriched gene set.
[0037] FIG. 3 shows breast tissue immunohistochemistry results
obtained using various antibodies.
[0038] FIG. 3A shows tumor Stanford 2-P stained for immunoglobulin
light chain.
[0039] FIG. 3B shows tumor Stanford 16 stained for the T-lymphocyte
cell surface antigen CD3.
[0040] FIG. 3C shows normal mammary duct stained for the basal
epithelial cell keratins 5/6.
[0041] FIG. 3D shows normal mammary duct stained for the luminal
cell keratins 8/18.
[0042] FIG. 3E shows tumor New York 3 stained for keratin 5/6.
[0043] FIG. 3F shows tumor Stanford 16 stained for keratins
8/18.
[0044] FIG. 4A shows a Western blot demonstrating expression of the
cadherin3 polypeptide in various cell lines.
[0045] FIG. 4B shows a Western blot demonstrating expression of the
matrix metalloproteinase 14 polypeptide in various cell lines.
[0046] FIG. 4C shows a Western blot demonstrating expression of the
cadherin EGF LAG seven-pass G-type receptor 2 polypeptide in
various cell lines.
[0047] FIG. 5A shows a Kaplan-Meier survival curve demonstrating
poor outcome in cytokeratin 17 and/or cytokeratin 5/6 positive
tumors (p=0.012).
[0048] FIG. 5B shows a Kaplan-Meier survival curve demonstrating
poor outcome in cytokeratin 17 and/or cytokeratin 5/6 positive
tumors in lymph node negative patients (p=0.006).
[0049] FIG. 6 shows antibody staining of normal breast tissue cores
in a breast tissue array.
[0050] FIG. 6A shows staining with anti-cytokeratin 5/6 monoclonal
antibody.
[0051] FIG. 6B shows staining with anti-cadherin 3 polyclonal
antibody.
[0052] FIG. 6C shows staining with anti-EGF LAG seven-pass G-type
receptor 2 polyclonal antibody.
[0053] FIG. 6D shows staining with anti-metallproteinase 14
polyclonal antibody.
[0054] FIG. 7 shows antibody staining of breast cancer tissue cores
in a breast cancer tissue array.
[0055] FIG. 7A shows antibody staining with anti-cytokeratin 5/6
monoclonal antibody.
[0056] FIG. 7B shows antibody staining with anti-EGF LAG seven-pass
G-type receptor 2 polyclonal antibody.
[0057] FIG. 7C shows antibody staining with anti-cadherin 3
polyclonal antibody.
BRIEF DESCRIPTION OF APPENDICES A-G (ON CD-ROM)
[0058] Appendix A presents the variation in expression of the 1753
genes listed in Appendix H, Table 1 in 84 experimental samples,
representative of array data from which BST-RAS/RERG was
identified.
[0059] Part a of Appendix A shows a dendrogram representing
similarities in expression patterns between the experimental
samples.
[0060] Part b of Appendix A shows a scaled down version of the
complete 1753 gene cluster diagram.
[0061] Part c of Appendix A indicates the endothelial cell gene
expression subset.
[0062] Part d of Appendix A indicates the stromal/fibroblast gene
subset.
[0063] Part e of Appendix A indicates the basal epithelial gene
subset.
[0064] Part f of Appendix A indicates the B-cell gene subset.
[0065] Part g of Appendix A indicates the adipose-enriched/normal
breast gene subset.
[0066] Part h of Appendix A indicates the macrophage gene
subset.
[0067] Part i of Appendix A indicates the T-cell gene subset.
[0068] Part j of Appendix A indicates the luminal epithelial cell
gene subset.
[0069] Appendix B shows a close-up of the "proliferation" subset of
genes taken from Part a of Appendix A.
[0070] Appendix C shows cluster analysis using the intrinsic gene
set.
[0071] Part a of Appendix C shows the tumor dendrogram obtained by
hierarchical clustering of the experimental samples based on
similarities in expression of the intrinsic gene set.
[0072] Part b of Appendix C shows a scaled down version of the
complete intrinsic gene color matrix diagram with particular gene
subsets indicated by colored bars along the side.
[0073] Part c of Appendix C shows an expanded view of the luminal
gene subset from part b of Appendix A.
[0074] Part d of Appendix C shows an expanded view of the ErbB2
gene subset from part b of Appendix A.
[0075] Part e of Appendix C shows an expanded view of a basal gene
subset from part b of Appendix A.
[0076] Part f of Appendix C shows an expanded view of a second
basal gene subset from part b of Appendix A.
[0077] Part g of Appendix C shows an expanded view of the
lymphocyte/B-cell gene subset from part b of Appendix A.
[0078] Appendix D shows the complete gene cluster diagram of 84
experimental samples versus 1753 genes.
[0079] Appendix E shows the complete 496 gene cluster diagram
formed when using the intrinsic gene set.
[0080] Appendix F shows the complete 374 gene cluster diagram
formed when using the epithelial enriched gene set.
[0081] Appendix G presents the variation in expression of the 1495
genes in 84 experimental samples, representative of array data from
which BST-RAS/RERG was identified. Note that the tumor names in
this image are the alternate names provided in Appendix H, Table 4,
but primarily the same samples as in the other images were used for
the experiment.
Brief Description of the Tables in Appendix H (on CD-ROM)
[0082] Appendix H includes 16 data tables. Some of the tables
contain the numerical data corresponding to the array images in
Appendices A through F. Other tables list the individual genes in
the various gene subsets.
[0083] Table 1 is a master data table for the 65 microarray
experiments performed on individual tumor samples, in which rows
represent I.M.A.G.E. clones that identify approximately 1753 genes
whose expression varied by at least a factor of 4 and columns
represent individual microarray experiments. The first 50 pages of
the table consist of a reference list in which a descriptive name
for each clone (where such a name exists) appears in the column
entitled Name, followed by the Genbank accession number for the
clone. Each row in the reference list contains a number in the
first column that numerically identifies the column. In the
subsequent data portion of the table (pages 1-392), each row is
similarly identified by a number in the first column so that the
name and Genbank accession number for the clone for which data
appears in that row may be determined by consulting the reference
list. In the data portion of the table, the column headings in the
first row identify the tumor samples. Each data cell in the table
represents the measured Cy5/Cy3 fluorescence ratio at the
corresponding target element on the appropriate array. Empty cells
indicate insufficient or missing data. All ratio values are log
transformed (base 2) to treat inductions or repressions of
identical magnitude as numerically equal but with opposite
sign.
[0084] Table 2 is a master data table for the 19 microarray
experiments performed on cell line samples, in which rows represent
I.M.A.G.E. clones that identify approximately 1753 genes whose
expression varied by at least a factor of 4 and columns represent
individual microarray experiments. This table contains only a data
portion, in which the column headings in the first row identify the
cell lines. Each row in the table is identified by a number which
appears in the first column. The same reference list that forms
part of Table 1 may be consulted to determine the name and Genbank
accession number for the clone for which data appears in that row.
Each data cell in the table represents the measured Cy5/Cy3
fluorescence ratio at the corresponding target element on the
appropriate array. Empty cells indicate insufficient or missing
data. All ratio values are log transformed (base 2) to treat
inductions or repressions of identical magnitude as numerically
equal but with opposite sign.
[0085] Table 3 presents a listing and description of the 11 cell
lines used to create the common reference sample.
[0086] Table 4 presents a complete listing of the 84 experimental
samples that were assayed versus the common reference sample. The
table includes a list of alternate names (in the column entitled
Sample ID/old name) for the same tumors. The alternate names are
used to identify the tumor samples in certain contexts, and the
table allows conversion between the two sets of names.
[0087] Table 5 lists the tumors used in the experiments described
herein, along with clinical and pathological information about each
tumor/patient.
[0088] Table 6 is a master data table for the 84 microarray
experiments performed on individual tumor, tissue, and cell line
samples, in which rows represent I.M.A.G.E. clones that identify
the 496 genes in the intrinsic gene set, and columns represent
individual microarray experiments. The first 15 pages of the table
consist of a reference list in which a descriptive name for each
clone (where such a name exists) appears in the column entitled
Name, followed by the Genbank accession number for the clone. Each
row in the reference list contains a number in the first column
that numerically identifies the column. In the subsequent data
portion of the table (pages 1-91), each row is similarly identified
by a number in the first column so that the name and Genbank
accession number for the clone for which data appears in that row
may be determined by consulting the reference list. In the data
portion of the table, the column headings in the first row identify
the tumor samples. Each data cell in the table represents the
measured Cy5/Cy3 fluorescence ratio at the corresponding target
element on the appropriate array. Empty cells indicate insufficient
or missing data. All ratio values are log transformed (base 2) to
treat inductions or repressions of identical magnitude as
numerically equal but with opposite sign.
[0089] Table 7 is a listing of the 374 clones that identify genes
selected for the epithelial enriched gene set including Genbank
accession numbers.
[0090] Table 8 is a listing of the clones that identify genes that
comprise the luminal subset including Genbank accession
numbers.
[0091] Tables 9-1 and 9-2 are listings of the two groups of clones
that identify genes that comprise the basal subset including
Genbank accession numbers.
[0092] Table 10 is a listing of the clones that identify genes that
comprise the ErbB2 subset including Genbank accession numbers.
[0093] Table 11 is a listing of the clones that identify genes that
comprise the endothelial gene subset including Genbank accession
numbers.
[0094] Table 12 is a listing of the clones that identify genes that
comprise the stromal/fibroblast gene subset including Genbank
accession numbers.
[0095] Table 13 is a listing of the clones that identify genes that
comprise the B-cell gene subset including Genbank accession
numbers.
[0096] Table 14 is a listing of the clones that identify genes that
comprise the adipose-enriched/normal breast gene subset including
Genbank accession numbers.
[0097] Table 15 is a listing of the clones that identify genes that
comprise the macrophage gene subset including Genbank accession
numbers.
[0098] Table 16 is a listing of the clones that identify genes that
comprise the T-cell gene subset including Genbank accession
numbers.
[0099] In Table 1, the Genbank accession number for each clone
appears in the column entitled "Name", following a brief
descriptive name for the gene identified by the clone, where
available. In some cases the descriptive name is a number
corresponding to an I.M.A.G.E. clone ID number. As is well known
and accepted in the art, the Genbank accession number represents a
means of definitively identifying a particular clone, since Genbank
accession numbers will be maintained permanently or, if changed,
the change will be accomplished in such a manner as to allow
unambiguous correlation between any new numbering system and the
numbering system currently in use.
[0100] Note that Tables 1, 2, and 6 are provided for purposes of
presenting the clone identifications and the data that was used to
perform hierarchical clustering analysis, and that the format of
the tables may not correspond exactly with the format required by
software developed for the analysis of the data. Appropriate format
will, in general, depend upon the particular computer program. See,
for example, the Web site
genome-www.stanford.edu/.about.sherlock/tutorial.html for
discussion of the appropriate format for one particular analysis
program.
[0101] In Tables 7-16, each entry identifies a clone. The first
portion of each entry is a brief descriptive name for the gene
identified by the clone. The Genbank accession number for the clone
appears on the last line of the entry for that clone.
Detailed Description of Certain Embodiments Definitions
[0102] To facilitate understanding of the invention, the following
definitions are provided. It is to be understood that, in general,
terms not otherwise defined are to be given their meaning or
meanings as generally accepted in the art.
[0103] Agonist: As used herein, the term "agonist" refers to a
molecule that increases or prolongs the duration of the effect of a
polypeptide or a nucleic acid. Agonists may include proteins,
nucleic acids, carbohydrates, lipids, small molecules, ions, or any
other molecules that modulate the effect of the polypeptide or
nucleic acid. An agonist may be a direct agonist, in which case it
is a molecule that exerts its effect by binding to the polypeptide
or nucleic acid, or an indirect agonist, in which case it exerts
its effect via a mechanism other than binding to the polypeptide or
nucleic acid (e.g., by altering expression or stability of the
polypeptide or nucleic acid, by altering the expression or activity
of a target of the polypeptide or nucleic acid, by interacting with
an intermediate in a pathway involving the polypeptide or nucleic
acid, etc.)
[0104] Antagonist: As used herein, the term "antagonist" refers to
a molecule that decreases or reduces the duration of the effect of
a polypeptide or a nucleic acid. Antagonists may include proteins,
nucleic acids, carbohydrates, or any other molecules that modulate
the effect of the polypeptide or nucleic acid. An antagonist may be
a direct antagonist, in which case it is a molecule that exerts its
effect by binding to the polypeptide or nucleic acid, or an
indirect antagonist, in which case it exerts its effect via a
mechanism other than binding to the polypeptide or nucleic acid
(e.g., by altering expression or stability of the polypeptide or
nucleic acid, by altering the expression or activity of a target of
the polypeptide or nucleic acid, by interacting with an
intermediate in a pathway involving the polypeptide or nucleic
acid, etc.)
[0105] Basal cell: The term "basal cell" is a general term applied
to any stratified or pseudostratified epithelium. It refers to
cells which are juxtaposed to the basement membrane and under one
or more additional epithelial layers. Mammary tissue can have both
a two cell layer epithelium (basal and luminal cells) or in the
duct system, a single layered epithelium. In the two cell layer,
the cells adjacent to the basement membrane are termed "basal
cells" and express basal cell markers (e.g., cytokeratin 17 and
cytokeratin 5/6). In pseudostratified epitheum "non-basal" cells
can also contact the basement membrane but since normal breast
epithelium is not, in general, pseudostratified, breast basal cells
are cells located adjacent to basement membrane and under one or
more additional layers of epithelial cells. As used herein, the
term "basal cell" is distinct from "myoepithelial cell" in that
myoepithelial cell refers to cells that have the contractual
apparatus for milk excretion by the ducts (i.e., they express
contractile proteins).
[0106] Breast basal cell marker: A gene whose expression is
characteristic of basal cells of normal breast lactation ducts, or
an expression product of such a gene (e.g., an mRNA or
polypeptide). The marker may be used to distinguish basal cells
from other cells in the breast, e.g., luminal cells. In the case of
a marker that is a polypeptide, antibodies to the polypeptide stain
cells in the basal layer of normal breast lactation ducts when used
to perform immunohistochemistry on breast tissue samples. Since the
present invention is concerned primarily with breast cancer, the
term "basal cell marker" is used interchangeably with "breast basal
cell marker" herein unless otherwise indicated. Examples of basal
cell markers include the cytokeratin 5 and cytokeratin 17 genes,
mRNAs, and proteins, in addition to the newly identified basal cell
markers described herein.
[0107] Breast basal tumor marker: A gene whose expression is
characteristic of basal cells in the normal breast lactation duct
and which is also expressed in a subset of breast tumors, or an
expression product of such a gene. These genes include cytokeratin
5 and cytokeratin 17, which are known from the prior art to
distinguish breast basal cells from other breast tissue cells, and
the genes identified herein. Antibodies to the proteins encoded by
these genes identify basal breast cells when used to perform
immunohistochemical staining of normal breast tissue, i.e., they
stain cells in the basal epithelial layer. The term "basal tumor
marker" is used interchangeably with "breast basal tumor marker"
herein unless otherwise indicated.
[0108] Breast basal tumor subclass: The breast basal tumor
subclass, as used herein, refers to breast tumors that display
characteristics of basal cells of normal breast lactation ducts.
Such characteristics include expression of genes whose expression
has been shown to discriminate between normal basal cells of breast
lactation ducts and other cells in the breast, including luminal
cells of breast lactation ducts. These genes include cytokeratin 5
and cytokeratin 17, which are known from the prior art to
distinguish breast basal cells from other breast tissue cells, and
the genes identified herein. Antibodies to the proteins encoded by
these genes identify basal breast cells when used to perform
immunohistochemical staining of normal breast tissue, i.e., they
stain cells in the basal epithelial layer. The term "breast basal
tumor subclass" is used interchangeably with "basal tumor subclass"
herein unless otherwise indicated.
[0109] Diagnostic information: As used herein, diagnostic
information or information for use in diagnosis is any information
that is useful in determining whether a patient has a disease or
condition and/or in classifying the disease or condition into a
phenotypic category or any category having significance with
regards to the prognosis of or likely response to treatment (either
treatment in general or any particular treatment) of the disease or
condition. Similarly, diagnosis refers to providing any type of
diagnostic information, including, but not limited to, whether a
subject is likely to have a condition (such as a tumor),
information related to the nature or classification of a tumor,
information related to prognosis and/or information useful in
selecting an appropriate treatment. Selection of treatment may
include the choice of a particular chemotherapeutic agent or other
treatment modality such as surgery, radiation, etc., a choice about
whether to withhold or deliver therapy, etc.
[0110] Differential expression: A gene exhibits differential
expression at the RNA level if its RNA transcript varies in
abundance between different samples in a sample set. A gene
exhibits differential expression at the protein level, if a
polypeptide encoded by the gene varies in abundance between
different samples in a sample set. In the context of a microarray
experiment, differential expression generally refers to
differential expression at the RNA level.
[0111] Gene: For the purposes of the present invention, the term
"gene" has its meaning as understood in the art. However, it will
be appreciated by those of ordinary skill in the art that the term
"gene" has a variety of meanings in the art, some of which include
gene regulatory sequences (e.g., promoters, enhancers, etc.) and/or
intron sequences, and others of which are limited to coding
sequences. It will further be appreciated that definitions of
"gene" include references to nucleic acids that do not encode
proteins but rather encode functional RNA molecules such as tRNAs.
For the purpose of clarity we note that, as used in the present
application, the term "gene" generally refers to a portion of a
nucleic acid that encodes a protein; the term may optionally
encompass regulatory sequences. This definition is not intended to
exclude application of the term "gene" to non-protein coding
expression units but rather to clarify that, in most cases, the
term as used in this document refers to a protein coding nucleic
acid.
[0112] Gene product or expression product: A gene product or
expression product is, in general, an RNA transcribed from the gene
or a polypeptide encoded by an RNA transcribed from the gene.
[0113] Marker: A marker, as used herein, refers to a gene whose
expression is characteristic of a particular cell type. The term
may also refer to a product of gene expression, e.g., an RNA
transcribed from the gene or a translation product of such an RNA,
the production of which is characteristic of a particular cell
type. The cell type may be defined based on any phenotypic
criterion. For example, a normal breast basal cell is defined based
on its position within an epithelial layer. In some cases
expression of a marker gene may be the sole criterion used to
define the cell type. The statistical significance of the presence
or absence of a marker gene expression product may vary depending
upon the particular marker. In some cases the detection of a marker
is highly specific in that it reflects a high probability that the
cell is of a particular type. This specificity may come at the cost
of sensitivity, i.e., a negative result may occur even if the cell
is a cell that would be expected to express the marker. Conversely,
markers with a high degree of sensitivity may be less specific than
those with lower sensitivity. Thus it will be appreciated that a
useful marker need not distinguish cells of a particular type with
100% accuracy. Furthermore, it will be appreciated that the use of
multiple markers may improve the specificity and/or sensitivity
with which a cell can be identified as being of a particular cell
type. The concept of a marker may be applied not only to individual
cells, but also to tumors or to other disease states. In the case
of tumors, a marker for a particular tumor class is a gene whose
expression is characteristic of a particular tumor type, i.e., a
gene whose expression is characteristic of some or all of the cells
in the tumor. The term may also refer to a product of gene
expression, e.g., an RNA transcribed from the gene or a translation
product of such an RNA, the production of which is characteristic
of a particular tumor type, i.e., of some or all of the cells in
the tumor.
[0114] Prognostic information and predictive information: As used
herein the terms prognostic information and predictive information
are used interchangeably to refer to any information that may be
used to foretell any aspect of the course of a disease or condition
either in the absence or presence of treatment. Such information
may include, but is not limited to, the average life expectancy of
a patient, the likelihood that a patient will survive for a given
amount of time (e.g., 6 months, 1 year, 5 years, etc.), the
likelihood that a patient will be cured of a disease, the
likelihood that a patient's disease will respond to a particular
therapy (wherein response may be defined in any of a variety of
ways). Prognostic and predictive information are included within
the broad category of diagnostic information.
[0115] Response: As used herein a response to treatment may refer
to any beneficial alteration in a subject's condition that occurs
as a result of treatment. Such alteration may include stabilization
of the condition (e.g., prevention of deterioration that would have
taken place in the absence of the treatment), amelioration of
symptoms of the condition, improvement in the prospects for cure of
the condition, etc. One may refer to a subject's response or to a
tumor's response. In general these concepts are used
interchangeably herein. Tumor or subject response may be measured
according to a wide variety of criteria, including clinical
criteria and objective criteria. Techniques for assessing response
include, but are not limited to, clinical examination, chest X-ray,
CT scan, MRI, ultrasound, endoscopy, laparoscopy, presence or level
of tumor markers in a sample obtained from a subject, cytology,
histology. Many of these techniques attempt to determine the size
of a tumor or otherwise determine the total tumor burden. Methods
and guidelines for assessing response to treatment are discussed in
Therasse P., et al., "New guidelines to evaluate the response to
treatment in solid tumors", European Organization for Research and
Treatment of Cancer, National Cancer Institute of the United
States, National Cancer Institute of Canada. J Natl Cancer Inst,
February 2; 92 (3):205-16, 2000. The exact response criterion can
be selected in any appropriate manner, provided that when comparing
groups of tumors and/or patients, the groups to be compared are
assessed based on the same or comparable criteria for determining
response rate. One of ordinary skill in the art will be able to
select appropriate criteria.
[0116] Sample: As used herein, a sample obtained from a subject may
include, but is not limited to, any or all of the following: a cell
or cells, a portion of tissue, blood, serum, ascites, urine,
saliva, and other body fluids, secretions, or excretions. The term
"sample" also includes any material derived by processing such a
sample. Derived samples may include nucleic acids or proteins
extracted from the sample or obtained by subjecting the sample to
techniques such as amplification or reverse transcription of mRNA,
etc.
[0117] Specific binding: As used herein, the term refers to an
interaction between a target polypeptide (or, more generally, a
target molecule) and a binding molecule such as an antibody,
agonist, or antagonist. The interaction is typically dependent upon
the presence of a particular structural feature of the target
polypeptide such as an antigenic determinant or epitope recognized
by the binding molecule. For example, if an antibody is specific
for epitope A, the presence of a polypeptide containing epitope A
or the presence of free unlabeled A in a reaction containing both
free labeled A and the antibody thereto, will reduce the amount of
labeled A that binds to the antibody. It is to be understood that
specificity need not be absolute. For example, it is well known in
the art that numerous antibodies cross-react with other epitopes in
addition to those present in the target molecule. Such
cross-reactivity may be acceptable depending upon the application
for which the antibody is to be used. One of ordinary skill in the
art will be able to select antibodies having a sufficient degree of
specificity to perform appropriately in any given application
(e.g., for detection of a target molecule, for therapeutic
purposes, etc). It is also to be understood that specificity may be
evaluated in the context of additional factors such as the affinity
of the binding molecule for the target polypeptide versus the
affinity of the binding molecule for other targets, e.g.,
competitors. If a binding molecule exhibits a high affinity for a
target molecule that it is desired to detect and low affinity for
nontarget molecules, the antibody will likely be an acceptable
reagent for immunodiagnostic purposes. Once the specificity of a
binding molecule is established in one or more contexts, it may be
employed in other, preferably similar, contexts without necessarily
re-evaluating its specificity.
[0118] Treating a tumor: As used herein, treating a tumor is taken
to mean treating a subject who has the tumor.
[0119] Tumor sample: The term "tumor sample" as used herein is
taken broadly to include cell or tissue samples removed from a
tumor, cells (or their progeny) derived from a tumor that may be
located elsewhere in the body (e.g., cells in the bloodstream or at
a site of metastasis), or any material derived by processing such a
sample. Derived tumor samples may include nucleic acids or proteins
extracted from the sample or obtained by subjecting the sample to
techniques such as amplification or reverse transcription of mRNA,
etc.
[0120] Tumor subclass: A tumor subclass, also referred to herein as
a tumor subset or tumor class, is the group of tumors that display
one or more phenotypic or genotypic characteristics that
distinguish members of the group from other tumors.
I. Overview and Description of the Basal Marker Genes,
Polynucleotides, and Polypeptides
[0121] The present invention provides new reagents and methods for
the management (e.g., detection, classification, provision of
diagnostic and prognostic information, treatment, etc.) of breast
cancer. Significant progress has been made in understanding risk
factors, including genetic factors, that may contribute to breast
cancer (See, for example, Vogelstein, B. and Kinzler, eds., "Breast
Cancer", by Couch, F. and Weber, B. in The Genetic Basis of Human
Cancer, McGraw Hill, 1998), but the relevance of these factors to
clinical outcome remains unclear. The most powerful prognosticators
are clinical features such as lymph node status, tumor size, and
tumor grade. In addition, the expression level and antibody
staining pattern of several proteins are predictive of outcome and
of the likelihood of response to therapy. However, the clinical
outcome of individual patients remains uncertain. In addition, the
ability to predict which patients are likely to benefit from a
particular type of therapy (e.g., a certain drug or class of drug)
remains elusive.
[0122] The invention encompasses the realization that high
throughput analysis techniques, e.g., those involving the use of
cDNA microarrays, can be used to provide new insights into the
biology of breast cancer. By analyzing the transcriptional profiles
of a large number of breast tumor samples and by undertaking
comparisons, e.g., between tumors associated with varying
prognoses, between primary tumors and metastases, between tumors
before and after treatment, and between tumors with differing
responses to therapy, the present invention provides new tools and
methods for classifying tumors and defines new classes of tumors
based on these methods. The invention identifies genes and gene
subsets that are useful in classifying breast tumors. In addition,
the methods described herein identify genes that are likely to play
a role in breast cancer development, progression, and/or response
to therapy. Classification based on expression of particular genes
may be used to predict clinical course or to predict sensitivity to
chemotherapeutic agents. Ultimately such classification may be used
to guide selection of appropriate therapy. As described herein,
detection of mRNA and protein corresponding to differentially
expressed genes provides new methods of use in cancer prognosis,
diagnosis, and treatment selection. In addition, differentially
expressed genes and their encoded proteins provide targets for the
identification of new therapies for breast cancer.
[0123] As described in further detail below, the invention employs
methods for clustering genes into groups by determining their
expression patterns across a set of samples obtained from breast
tumors and from normal breast tissue. The invention also clusters
the breast tumor and normal breast tissue samples into groups based
on similarities in their expression of a set of genes. This
two-dimensional clustering approach permits the association of
particular classes of tumors with particular subsets of genes that,
for example, show relatively high levels of expression in the
tumors. Correlation with clinical information indicates that the
tumor classes have clinical significance in terms of prognosis or
response to chemotherapy.
[0124] Genes that are relatively overexpressed in tumors may be
particularly appropriate targets for the development of new
therapeutic agents. Any gene (or combination of genes) that is
overexpressed in some tumors forms a basis by which tumors can be
divided into different groups. As demonstrated herein, when
particular sets of genes are used such groups have clinical
significance in that, for example, they display differences in
prognosis. However, regardless of whether the resulting division
has significance in terms of known clinical parameters, therapeutic
agents directed towards such genes or towards their encoded
proteins would be expected to be specific for the tumors that
overexpress the genes. Thus the invention offers an opportunity for
the development and selection of therapeutic agents based on
specific properties of a tumor. In other words, any gene that is
overexpressed in a subset of tumors can be used to define that
subclass and is a potential target for the development of a
therapeutic agent that is specific for that tumor subclass.
[0125] In particular, tumors that display characteristics of basal
cells of the normal breast lactation gland (also referred to herein
as breast basal cells) form a distinct subclass (referred to herein
as the basal subclass). It is known in the art that two distinct
types of epithelial cells are found in the adult human mammary
gland: basal cells and luminal epithelial cells. Expression of
cytokeratin 5 and/or cytokeratin 17 is a characteristic of basal
cells of the normal mammary lactation gland, while cytokeratins 8
and 18 are expressed in luminal cells. Cytokeratins are a family of
intermediate filament proteins, members of which are found in most
or all epithelial cell types (Moll, R., et al., "The catalog of
human cytokeratins: patterns of expression in normal epithelia,
tumors, and cultured cells", Cell, 31 (1), 11-24, 1982.
Intermediate-sized filaments are morphologically similar but
biochemically and immunologically distinguishable cytoplasmic
proteins of which five major filament types have been identified
(cytokeratin, vimentin, desmin, neurofilament protein, glia
filament protein), and antibodies to these proteins have been used
for distinguishing different cell types and tumors derived
therefrom. Epithelial and carcinoma cells are characterized by the
presence of cytokeratin filaments that can be identified by
antibodies. These antibodies can be used to distinguish between
different cell and tumor types (Dobus, E., et al.,
"Immunohistochemical distinction of human carcinomas by cytokeratin
typing with monoclonal antibodies", Am J. Pathol., 114 (1): 121-30,
1984). In particular, antibodies against cytokeratins 5/6, 17, 8,
and 18 may be used to distinguish between breast basal and luminal
cell types in normal breast and in tumors (See, e.g., Purkis, P.,
et al., "Antibody markers of basal cells in complex epithelia", J.
Clin. Pathol., 48:26-32, 1990; Taylor,-Papadimitriou and Lane, E.,
"Keratin expression in the mammary gland" in Neville, M and Daniel
C, eds. The Mammary Gland: Development, Regulation, and Function.
New York: Plenum, pp. 181-215, 1987; Dairkee, S., et al.,
"Immunolocalization of a human basal epithelium-specific keratin in
benign and malignant breast disease. Breast Cancer Res. Treat.,
10:11-20, 1987.)
[0126] Several previous studies suggested that expression of basal
cell keratins is associated with a poor clinical outcome (Dairkee,
S. H., et al., "Monoclonal antibody that predicts early recurrence
of breast cancer", Lancet, 1:514, 1987; Malzahn, K., et al.,
"Biological and prognostic significance of stratified epithelial
cytokeratins in infiltrating ductal breast carcinomas", Virchows
Archiv, 433:119-29, 1998). Inventors have confirmed, in a
large-scale study, that patients with breast tumors whose cells
display characteristics of breast basal cells, e.g., expression of
cytokeratin 5 and/or cytokeratin 17, have a poor clinical outcome
relative to patients with breast tumors that do not express these
markers. However, antibodies to these cytokeratins have been found
(by the inventors and by other investigators) to give spotty, focal
staining patterns when used to perform immunohistochemistry on
breast tumor samples. Thus the utility of cytokeratins 5 and 17 as
markers and the utility of antibodies that bind to cytokeratin 5 or
17 for determining whether a tumor is a member of the basal
subclass has been limited. The inventors have therefore identified
genes whose mRNA expression profiles across a large set of tumor
samples correlate with, i.e., are similar to, the expression
profiles of the known basal cell markers cytokeratins 5 and 17.
These genes include the basal marker genes of the present
invention, i.e., genes that encode cadherin3 or P-cadherin (SEQ ID
NO:1; GenBank protein accession number NP.sub.--001784; GenBank
cDNA accession number NM.sub.--001793), matrix metalloproteinase 14
(SEQ ID NO:2; GenBank protein accession number NP.sub.--004986;
GenBank cDNA accession number NM.sub.--004995); and cadherin EGF
LAG seven-pass G-type receptor 2 or EGF-Like Domain, Multiple 2
(SEQ ID NO:3; GenBank protein accession number NP.sub.--001399;
GenBank cDNA accession number NM.sub.--001408). A portion of the
cadherin3 gene was present as I.M.A.G.E. clone 777301 on the cDNA
microarray described below. This clone is entry #421 in Appendix H,
Table 1. A portion of the matrix metalloproteinase 14 gene was
present as I.M.A.G.E. clone 270505 on the cDNA microarray described
below. This clone is entry #424 in Appendix H, Table 1. A portion
of the cadherin EGF LAG seven-pass G-type receptor 2 gene was
present as I.M.A.G.E. clone 175103 on the cDNA microarray described
below. This clone is entry # 1443 in Appendix H, Table 1.
Information about these genes may be found at NCBI's LocusLink
(www.ncbi.nlm.nih.gov/LocusLink), among other sources. As described
in Examples 10 and 13, the inventors have generated antibodies to
the proteins expressed by these genes and shown that the antibodies
stain basal cells of normal mammary lactation glands. Thus
detection of one or more expression products of these genes may be
used to identify tumors that fall within the basal tumor
subclass.
[0127] As is well known in the art, breast carcinomas lose the
typical histology and architecture of normal breast glands.
Generally, carcinoma cells overgrow the normal cells and lose their
ability to differentiate into glandular like structures. The degree
of loss of differentiation in general is related to the
aggressiveness of the tumor. For example, "in situ" carcinoma by
definition retains the basement membrane intact, whereas as it
progresses to "invasive", the tumor shows breakout of basement
membranes. Thus one would not expect to see, within breast
carcinomas, staining of a discrete layer of basal cells as seen in
normal breast tissue. For a discussion of the physiology and
histology of normal breast and breast carcinoma, see Ronnov-Jessen,
L., Petersen, O. W. & Bissell, M. J. Cellular changes involved
in conversion of normal to malignant breast: importance of the
stromal reaction. Physiol Rev 76, 69-125 (1996).
[0128] The basal marker genes provided herein are expressed in the
best model of basal cells (HMECs, Human Mammary Epithelial Cells)
and based on antibody staining, in normal breast basal cells.
Therefore describing them as basal markers is appropriate. However,
in addition to their specific staining properties, a major
characteristic that makes these genes and their expression products
useful is their variation in expression across cohorts of breast
carcinoma patients, which portends their utility in stratification
of breast carcinoma patients. While not wanting to be limited by
the implications of having chosen a particular descriptor (i.e.
"basal") inventors refer to the set of genes, proteins, and
antibody reactivity patterns as "basal" as it serves as a reminder
of their utility in recognizing breast tumor cells that have
characteristics reminiscent of normal breast basal cells. Breast
tumors containing such cells are likewise referred to as "basal"
without intending any limitations thereby.
[0129] Two of the basal marker genes, cadherin3 and cadherin EGF
LAG seven-pass G-type receptor 2 encode members of the cadherin
superfamily. The cadherin EGF LAG seven-pass G-type receptor 2 or
EGF-Like Domain, Multiple 2 protein is a member of the flamingo
subfamily, part of the cadherin superfamily. The cadherins are a
large family of proteins with critical roles in the regulation of
cell-cell adhesion. Generally expressed in development- or
tissue-specific manners, these factors have been shown to have
important roles in development, cellular proliferation, and
differentiation. The cadherin superfamily include classic
cadherins, desmogleins, desmocollins, protocadherins, CNRs, Fats,
and seven-pass transmembrane cadherins (for review see Nollet et
al. 2000). Typically transmembrane proteins, the cadherins are
characterized by the unique cadherin, or EC, domain. These cadherin
domains, which are involved in Ca.sup.++ binding (Takeichi 1990),
are repeated in the extracellular region of all of the family
members. The amino acid sequences of other regions shows
significant divergence among members, suggesting functional
diversity amongst the various cadherin proteins. However, amid the
members of each subfamily, the cytoplasmic domains are conserved.
In the classic cadherins, which are components of adherens
junctions and desmoplakin plaques, this region interacts with
catenin p120.sup.ctm, and plakoglobin or .beta.-catenin. The latter
binds to .alpha.-catenin, and this molecular complex further
associates with .alpha.-actinin, F-actin and other cytoskeletal
proteins. Consistent with their roles in regulating cell-cell
adhesion events, altered expression of cadherin genes has been
associated with human cancer. Alteration of cadherin function may
lead to subsequent metastasis by disaggregation of tumor cells, and
one proposed role of many cadherins studied to date is as tumor-
and invasion-suppressors. Further discussion of some of the many
members of the cadherin superfamily and their possible role in
cancer is found in references 53-61.
[0130] The flamingo subfamily consists of nonclassic-type
cadherins; a subpopulation that does not interact with catenins.
The flamingo cadherins are located at the plasma membrane and have
nine cadherin domains, seven epidermal growth factor-like repeats
and two laminin A G-type repeats in their ectodomain. They also
have seven transmembrane domains, a characteristic unique to this
subfamily. While not wishing to be bound by any theory, it is
postulated that these proteins are receptors involved in
contact-mediated communication, with cadherin domains acting as
homophilic binding regions and the EGF-like domains involved in
cell adhesion and receptor-ligand interactions. The cadherin EGF
LAG seven-pass G-type receptor 2 gene (also known as CELSR2) has
not been as extensively studied as the classic cadherins, but is
implicated in cell signaling. The Drosophila homolog of this gene
has been studied in more detail, and is clearly important in
regulating different cellular events (Usui T, Shima Y, Shimada Y,
Hirano S, Burgess R W, Schwarz T L, Takeichi M, Uemura T,
"Flamingo, a seven-pass transmembrane cadherin, regulates planar
cell polarity under the control of Frizzled", Cell 1999 September
98:585-95. While not wishing to be bound by any theory, it is
postulated that this protein is a receptor involved in
contact-mediated communication, with the cadherin domains acting as
homophilic binding regions and the EGF-like domains involved in
cell adhesion and receptor-ligand interactions.
[0131] Proteins of the matrix metalloproteinase (MMP) family are
involved in the breakdown of extracellular matrix in normal
physiological processes, such as embryonic development,
reproduction, and tissue remodeling, as well as in disease
processes, such as arthritis and metastasis. Most MMP's are
secreted as inactive proproteins which are activated when cleaved
by extracellular proteinases. However, matrix metalloproteinase 14
protein is a member of the membrane-type MMP (MT-MMP) subfamily;
each member of this subfamily contains a potential transmembrane
domain suggesting that these proteins are expressed at the cell
surface rather than secreted. This protein activates MMP2 protein,
and this activity may be involved in tumor invasion.
[0132] Cadherin3 is predicted to be membrane-bound, with an
extracellular portion. As indicated by the presence of seven
putative transmembrane domains, cadherin EGF LAG seven-pass G-type
receptor 2 is also likely to be a membrane bound protein. The
presence of a predicted transmembrane domain indicates that matrix
metalloproteinase 14 is also membrane bound. The likelihood that
the proteins encoded by the basal marker genes are membrane bound
makes them attractive candidate for the application of serological
assays for diagnostic purposes. In addition, the likelihood that
cadherin3, cadherin EGF LAG seven-pass G-type receptor 2, and
matrix metalloproteinase 14 are membrane bound makes them
attractive candidates for antibody therapeutics.
[0133] The invention provides antibodies that specifically bind to
the polypeptide expression products of the basal marker genes,
i.e., the polypeptides of SEQ ID NO:1, 2, and 3. The antibodies
stain basal cells of the normal mammary lactation gland. In certain
embodiments of the invention the antibodies distinguish basal cells
from luminal cells in normal mammary lactation glands.
[0134] The antibodies are potentially useful as therapeutic
reagents for cancer, particularly breast cancer, either by
themselves or when conjugated to or delivered with another molecule
such as a toxic compound. The invention further provides
pharmaceutical compositions comprising agonists or antagonists of
the polynucleotides and their encoded polypeptides, and methods of
use thereof for the treatment of cancer. The invention includes a
variety of methods for providing information of use in the
prognosis, classification, diagnosis, etc. of cancer, particularly
breast cancer.
[0135] In order that the manner in which the basal cell marker
genes of the present invention were identified may be better
understood, a description of cDNA microarray technology is provided
below. Following this description the specific experimental
approach employed herein is described. Certain aspects of the
invention are then described in further detail.
II. cDNA Microarray Technology
[0136] cDNA microarrays consist of multiple (usually thousands) of
different cDNAs spotted (usually using a robotic spotting device)
onto known locations on a solid support, such as a glass microscope
slide. The cDNAs are typically obtained by PCR amplification of
plasmid library inserts using primers complementary to the vector
backbone portion of the plasmid or to the gene itself for genes
where sequence is known. PCR products suitable for production of
microarrays are typically between 0.5 and 2.5 kB in length. Full
length cDNAs, expressed sequence tags (ESTs), or randomly chosen
cDNAs from any library of interest can be chosen. ESTs are
partially sequenced cDNAs as described, for example, in L. Hillier,
et al., Generation and analysis of 280,000 human expressed sequence
tags, Genome Research, 6, 807-828, 1996. The afore-mentioned
article is herein incorporated by reference, as are the entire
teachings of all other patents and journal articles mentioned
herein, for all purposes and not just those related to the
particular context in which they are mentioned. Although some ESTs
correspond to known genes, frequently very little or no information
regarding any particular EST is available except for a small amount
of 3' and/or 5' sequence and, possibly, the tissue of origin of the
mRNA from which the EST was derived. As will be appreciated by one
of ordinary skill in the art, in general the cDNAs contain
sufficient sequence information to uniquely identify a gene within
the human genome. Furthermore, in general the cDNAs are of
sufficient length to hybridize, preferably specifically and yet
more preferably uniquely, to cDNA obtained from mRNA derived from a
single gene under the hybridization conditions of the
experiment.
[0137] In a typical microarray experiment, a microarray is
hybridized with differentially labeled RNA or DNA populations
derived from two different samples. Most commonly RNA (either total
RNA or poly A.sup.+ RNA) is isolated from cells or tissues of
interest and is reverse transcribed to yield cDNA. Labeling is
usually performed during reverse transcription by incorporating a
labeled nucleotide in the reaction mixture. Although various labels
can be used, most commonly the nucleotide is conjugated with the
fluorescent dyes Cy3 or Cy5. For example, Cy5-dUTP and Cy3-dUTP can
be used. cDNA derived from one sample (representing, for example, a
particular cell type, tissue type or growth condition) is labeled
with one fluor while cDNA derived from a second sample
(representing, for example, a different cell type, tissue type, or
growth condition) is labeled with the second fluor. Similar amounts
of labeled material from the two samples are cohybridized to the
microarray. In the case of a microarray experiment in which the
samples are labeled with Cy5 (which fluoresces red) and Cy3 (which
fluoresces green), the primary data (obtained by scanning the
microarray using a detector capable of quantitatively detecting
fluorescence intensity) are ratios of fluorescence intensity
(red/green, R/G). These ratios represent the relative
concentrations of cDNA molecules that hybridized to the cDNAs
represented on the microarray and thus reflect the relative
expression levels of the mRNA corresponding to each cDNA/gene
represented on the microarray.
[0138] Each microarray experiment can provide tens of thousands of
data points, each representing the relative expression of a
particular gene in the two samples. Appropriate organization and
analysis of the data is of key importance. Various computer
programs that incorporate standard statistical tools have been
developed to facilitate data analysis. One basis for organizing
gene expression data is to group genes with similar expression
patterns together into clusters. A method for performing
hierarchical cluster analysis and display of data derived from
microarray experiments is described in Eisen, M., Spellman, P.,
Brown, P., and Botstein, D., Cluster analysis and display of
genome-wide expression patterns, Proc. Natl. Acad. Sci. USA, 95:
14863-14868, 1998. As described therein, clustering can be combined
with a graphical representation of the primary data in which each
data point is represented with a color that quantitatively and
qualitatively represents that data point. By converting the data
from a large table of numbers into a visual format, this process
facilitates an intuitive analysis of the data. Additional
information and details regarding the mathematical tools and/or the
clustering approach itself may be found, for example, in Sokal, R.
R. & Sneath, P. H. A. Principles of numerical taxonomy, xvi,
359, W.H. Freeman, San Francisco, 1963; Hartigan, J. A. Clustering
algorithms, xiii, 351, Wiley, New York, 1975; Paull, K. D. et al.
Display and analysis of patterns of differential activity of drugs
against human tumor cell lines: development of mean graph and
COMPARE algorithm. J Natl Cancer Inst 81, 1088-92, 1989; Weinstein,
J. N. et al. Neural computing in cancer drug development:
predicting mechanism of action. Science 258, 447-51, 1992; van
Osdol, W. W., Myers, T. G., Paull, K. D., Kohn, K. W. &
Weinstein, J. N. Use of the Kohonen self-organizing map to study
the mechanisms of action of chemotherapeutic agents. J Natl Cancer
Inst 86, 1853-9, 1994; and Weinstein, J. N. et al. An
information-intensive approach to the molecular pharmacology of
cancer. Science, 275, 343-9, 1997.
[0139] Further details of the experimental methods used in the
present invention are found in the Examples. Additional information
describing methods for fabricating and using microarrays is found
in U.S. Pat. No. 5,807,522, which is herein incorporated by
reference. Instructions for constructing microarray hardware (e.g.,
arrayers and scanners) using commercially available parts can be
found at cmgm.stanford.edu/pbrown/ and in Cheung, V., Morley, M.,
Aguilar, F., Massimi, A., Kucherlapati, R., and Childs, G., Making
and reading microarrays, Nature Genetics Supplement, 21:15-19,
1999, which are herein incorporated by reference. Additional
discussions of microarray technology and protocols for preparing
samples and performing microrarray experiments are found in, for
example, DNA arrays for analysis of gene expression, Methods
Enzymol, 303:179-205, 1999; Fluorescence-based expression
monitoring using microarrays, Methods Enzymol, 306: 3-18, 1999; and
M. Schena (ed.), DNA Microarrays: A Practical Approach, Oxford
University Press, Oxford, UK, 1999. Descriptions of how to use an
arrayer and the associated software are found at
cmgm.stanford.edu/pbrown/mguide/arrayerHTML/ArrayerDocs.html, which
is herein incorporated by reference.
III. Experimental Approach of the Invention
[0140] The present invention encompasses the realization that genes
that are differentially expressed are of use in classifying tumors.
Differentially expressed genes are likely to be responsible for the
different phenotypic characteristics of tumors. The present
invention identifies such genes. In general, a differentially
expressed gene is a gene whose transcript abundance varies between
different samples, e.g., between different tumor samples, between
normal versus tumor samples, etc. In the case of the experiment
described herein, the transcript level of a differentially
expressed gene varies by at least 4-fold from its average abundance
in a given sample set in at least 3 of the samples. However, genes
that display smaller variations in expression are also within the
scope of the invention. In general, the amount by which the
expression varies and the number of samples in which the expression
varies by that amount will depend upon the number of samples and
the particular characteristics of the samples. One skilled in the
art will be able to determine, based on knowledge of the samples,
what constitutes a significant degree of differential
expression.
[0141] While analysis of multiple genes is of use in developing a
robust classification of tumors, each of the differentially
expressed genes and their encoded proteins is a target for the
development of diagnostic and therapeutic agents. Investigation of
variation in individual genes in breast tumors reveals that
molecular variation can be related to important features of
clinical variation. For example, expression of the estrogen
receptor alpha gene (ESR1), the Erb-B2/HER2/neu oncogene, and the
mutational status at the TP53, BRCA1 and BRCA2 loci have shown that
molecular variation can be related to important features of
clinical variation. (Discussed, for example, in Osborne, C. K., et
al., The value of estrogen and progesterone receptors in the
treatment of breast cancer, Cancer 46, 2884-2888, 1980; Ingvarsson,
S., Molecular genetics of breast cancer progression, Seminars in
Cancer Biology, 9, 277-288, 1999; Breast Cancer Linkage Consortium,
Pathology of familial breast cancer: differences between breast
cancers in carriers of BRCA1 and BRCA2 mutations and sporadic
cases, Lancet, 349, 1505-1510, 1997; Anderson, T. I., et al.,
Prognostic significance of TP53 alterations in breast carcinoma. Br
J Cancer, 68, 540-548, 1993 and references cited in these
articles). In particular, approximately 60% to 70% of breast tumors
express the estrogen receptor, and this expression has been shown
to be a favorable prognostic factor (reviewed in Allred, D. C., et
al. Prognostic and Predictive Factors in Breast Cancer by
Immunohistochemical Analysis, Modern Pathology, 11 (2), 155-168,
1998).
[0142] As described in more detail in Examples 1, 2, and 4, cDNA
microarrays each representing the same set of approximately 8100
different human genes were produced. The human cDNA clones used to
produce the microarrays contained approximately 4000 named genes,
2000 genes with homology to named genes in other species, and
approximately 2000 ESTs of unknown function. An mRNA sample was
obtained from each of a set of 84 tissue samples or cell lines. The
expression levels of the approximately 8100 genes were measured in
each mRNA sample by hybridization to an individual microarray,
yielding an expression profile for each gene across the
experimental samples. Although more details will be found in the
Examples, an overview of the experimental procedure is presented
here so that the invention may be better understood.
[0143] Variation in patterns of gene expression were characterized
in 62 breast tumor samples from 40 different patients, 3 normal
breast tissue samples, and 19 samples from 17 cultured human cell
lines (one of which was sampled 3 times under different
conditions). Twenty of the tumors had been sampled twice, before
and after a 16 week course of doxorubicin chemotherapy, and two
tumors were paired with a lymph node metastasis from the same
patient. The other 18 tumor samples were single samples from
individual tumors. A detailed listing of the tumor samples and
various characteristics including clinical estrogen receptor and
Erb-B2 status as assessed using antibody staining, estrogen
receptor and Erb-B2 status as assessed by microarray result, tumor
grade, differentiation, survival status and time, age at diagnosis,
doxorubicin response, and p53 status is presented in Table 5. A
listing of the cell lines including description and ATCC (American
Tissue Culture Collection) number or reference is presented in
Table 3. The cell lines provided a framework for interpreting the
variation in gene expression patterns seen in the tumor samples and
included gene expression models for many of the cell types
encountered in tumors.
[0144] As described in more detail in Example 2, mRNA was isolated
from each sample. cDNA labeled with the fluorescent dye Cy5 was
prepared from each experimental sample separately. Fluorescently
labeled cDNA, labeled using a second distinguishable dye (Cy3), was
prepared from a pool of mRNAs isolated from 11 different cultured
cell lines. The pooled mRNA sample served as a reference to provide
a common internal standard against which each gene's expression in
each experimental sample was measured.
[0145] Comparative expression measurements were made by separately
mixing Cy5-labeled experimental cDNA derived from each of the 84
samples with a portion of the Cy3-labeled reference cDNA, and
hybridizing each mixture to an individual cDNA microarray. The
ratio of Cy5 fluorescence to Cy3 fluorescence measured at each cDNA
element on the microarray was then quantitatively measured. The use
of a common reference standard in each hybridization allowed the
fluorescence ratios to be treated as comparative measurements of
the expression level of each gene across all the experimental
samples.
[0146] A hierarchical clustering method (Eisen, et al., 1998) was
used to group genes based on similarity in the pattern with which
their expression varied over all experimental samples. The same
clustering method was used to group the experimental samples
(tissue and cell lines separately) based on the similarity in their
patterns of expression. Interpretation of the data obtained from
the clustering algorithm was facilitated by displaying the data in
the form of tumor and gene dendrograms. In the tumor dendrograms,
the pattern and length of the branches reflects the relatedness of
the tumor samples with respect to their expression of genes
represented on the microarray. For example, Appendix A, part a
shows a representative tumor dendrogram obtained by clustering the
tumor samples based on their expression profiles with respect to
1753 of the genes represented on the cDNA microarrays. In general,
the similarity of the gene expression profiles of individual tumor
samples or groups of tumor samples to one another is inversely
related to the length of the branches that connect them. Thus, for
example, adjacent tumor samples connected to one another by short
vertical branches descending from a common horizontal branch (e.g.,
tumor samples Norway 48-BE and Norway 48-AF close to the right of
the tumor dendrogram) are more closely related to one another in
terms of their gene expression profiles than adjacent tumor samples
connected to one another by longer vertical branches descending
from a common horizontal branch (e.g., tumor samples Norway 100-BE
and Norway 100-AF at the left side of the tumor dendrogram). To the
extent that the gene expression programs dictate the biological
properties and behavior of the tumors and reflect their
physiological state and environment, it is expected that the
clustering of the tumors reflects phenotypic relationships among
them, e.g., tumor samples connected by short horizontal branches
(i.e., located in close proximity to one another) are expected to
exhibit similar phenotypic features. In the gene dendrograms, the
pattern and length of the branches reflects the relatedness of the
genes with respect to their expression profiles across the tumor
samples. Appendix D shows a representative gene dendrogram.
Similarly to the tumor samples, genes connected by short vertical
branches are more similar to one another in terms of expression
profile than genes connected by longer vertical branches.
[0147] The expression patterns of the genes were also displayed
using a matrix format, with each row representing all of the
hybridization results for a single cDNA element on the array and
each column representing the measured expression levels for all
genes in a single sample. A representative matrix is shown in
Appendix A, in which a set of 1753 differentially expressed genes
was analyzed. Appendix A, part a shows a dendrogram representing
similarities in the expression patterns between experimental
samples. Appendix A, part b shows a scaled down version of the
complete 1753 gene set. In this format, tumor samples with similar
patterns of expression across the gene set are close to each other
along the horizontal dimension. Similarly, genes with similar
expression patterns across the set of samples are close to each
other along the vertical dimension. To allow the patterns of
expression to be visualized, the normalized expression value of
each gene was represented by a colored box, using red to represent
expression levels greater than the median and green to represent
expression levels less than the median. In all images the brightest
red color represents transcript levels at least 16-fold greater
than the median, and the brightest green color represents
transcript levels at least 16-fold below the median. This display
format facilitates comparisons between genes and the recognition of
significant patterns.
[0148] As described herein, systematic investigation of gene
expression patterns in human breast tumors and their correlation to
specific features of phenotypic variation offers a basis for an
improved molecular taxonomy of breast cancers. Such a taxonomy has
significant clinical utility. For example, correlation of gene
expression patterns with outcome in the absence of treatment is of
use in deciding whether a patient should receive adjuvant
chemotherapy after surgery. As another example, genes whose
expression level varies between tumors that are sensitive to
chemotherapy and tumors that are resistant to chemotherapy are of
use in predicting likelihood of response and in selection of
appropriate treatment. Genes whose expression level varies between
tumor samples taken before and after therapy are of use in
understanding the response of tumors to treatment.
IV. Further Aspects of the Invention
A. Basal Tumor Subclasses and Corresponding Gene Subsets
[0149] Gene and tumor dendrograms were derived from data obtained
by performing a microarray analysis on the set of breast tumor and
breast tissue samples described above, using a set of genes (the
"intrinsic" gene set) described further below and in Example 8.
Appendices A and C present the resulting tumor dendrograms and
color matrix displays of the gene expression profiles obtained.
Although technically the dendrograms identify groups of tumor
samples, since each sample is obtained from a specific tumor the
dendrograms also identify groups of tumors. Thus, in general, a
group of tumor samples corresponds to a group of tumors. Therefore,
throughout most of the discussion herein reference will be made to
tumor groups, classes, etc., rather than tumor sample groups,
classes, etc. The clustering method permits the identification of
subsets of genes with related expression profiles across a set of
tumors and the identification of groups or classes of tumors with
similar expression profiles across a set of genes. Although the
existence of gene subsets is revealed by the display of the data in
dendrogram format, understanding the significance of the gene
subsets obtained in experiments such as those described above
requires interpretation in light of knowledge about the genes and
tumor samples. Groups of tumors identified based on their
expression patterns of sets of genes (e.g., groups of tumors that
overexpress genes in particular gene subsets) can be designated as
tumor classes when deemed significantly distinct to warrant a
distinct classification.
[0150] Table 5 includes information regarding the clinical outcome
of the tumors from which the samples were obtained. In particular,
the table includes survival time of the patients and, for some of
the tumors, whether or not the tumor responded to chemotherapy
(doxorubicin). Such information was used to demonstrate that the
basal tumor class is characterized by a poor clinical outcome
relative to the other tumors. Differences in survival between
groups of patients was demonstrated using the Kaplan-Meier
technique for survival analysis, which is implemented in computer
software such as the SAS package (SAS Institute, Inc, Cary, N.C.)
and described in the accompanying manual. Of course various other
statistical techniques can be used to detect differences in
survival or any other clinical parameters between groups of tumors.
Various appropriate statistical techniques useful for analyzing
survival are discussed, for example, in Lawless, J. F., Statistical
Models and Methods for Lifetime Data. New York: John Wiley &
Sons, 1982. Lee, Elisa T. Statistical Methods for Survival Data
Analysis. 2nd ed. New York: John Wiley & Sons, 1992. Marubini,
Ettore, and Valsecchi, Maria Grazia, Analysing Survival Data from
Clinical Trials and Observational Studies. New York: John Wiley
& Sons, 1995. Miller, Rupert G. Jr. Survival Analysis. New
York: John Wiley & Sons, 1981. Rosner, Bernard, Fundamentals of
Biostatistics. 4th ed. Belmont, Calif.: Duxbury Press, 1995.) Other
clinical parameters of importance include response to therapy, time
to recurrence, etc.
[0151] As will be appreciated by one of ordinary skill in the art,
the correlation of particular tumor groups with survival or other
parameters of clinical importance can be strengthened by the
inclusion of data obtained from additional tumor samples.
[0152] The invention identifies genes and gene subsets that are
associated with the basal tumor subclass. The genes and gene
subsets are identified in part by the overexpression of certain
members of each subset in a particular tumor group and are also
defined in part based on the proximity of genes within each subset
to one another in a gene dendrogram. As used herein unless
otherwise stated, a gene is overexpressed in a tissue sample at the
RNA level if a mRNA corresponding to (i.e., transcribed from) the
gene is present in excess relative to the median abundance of that
mRNA across the set of analyzed specimens. A gene is overexpressed
in a tissue sample at the protein level if a polypeptide
corresponding to (i.e., translated from a mRNA that was transcribed
from) the gene is present in excess relative to the abundance of
that polypeptide across the set of analyzed specimens. The
measurement of relative abundance using cDNA microarrays relies
upon the comparison of all samples relative to a common reference
sample that provides cognate mRNA for as many genes as possible
with the goal of providing a common denominator for the measured
ratios across all samples. Each tested sample can be compared to
all other tested samples in ratio units relative to the reference.
This allows reproducible determination of gene expression in each
tested sample relative to the median gene expression across any
given sample set (Ross, D T, et al., Systematic variation in gene
expression patterns in human cancer cell lines, Nat Genet. 2000
March; 24 (3):227-35, 2000). In general, an appropriate reference
sample comprises a renewable source of diverse cell samples such as
a mixture of cells obtained from the panel of 11 cell lines listed
in Table 3. A particularly preferred reference sample is one in
which all relevant genes are represented in significant abundance
above measured background. This provides for a reproducible
measurement of reference signal for all relevant genes. As is well
known in the art, there is generally a correlation between
overexpression or underexpression at the RNA level and
overexpression or underexpression at the protein level. In other
words, if a mRNA is overexpressed then it is highly likely that the
corresponding polypeptide is also overexpressed, and if a mRNA is
underexpressed then it is highly likely that the corresponding
polypeptide is underexpressed. Therefore, detection of either mRNA
or a corresponding polypeptide is generally sufficient to determine
whether a particular gene is over or underexpressed. However, as is
well known in the art, in certain situations it may be more
convenient and/or practical to detect mRNA while in other
situations it may be more convenient and/or practical to detect
polypeptides.
[0153] As mentioned above, genes that are overexpressed in one or
more samples may be identified by examining the microarray data
displayed in matrix format, wherein red squares indicate
overexpression. The basal gene subset includes a number of genes
known to be expressed in basal epithelial cells (e.g., cytokeratins
5 and 17) and is characterized in that certain of the genes in the
subset are overexpressed at the RNA level in samples obtained from
a subset of tumors that had a poor prognosis relative to the entire
group of tumors (the basal group). Referring to Appendix C, the
basal gene subset comprises two subsets identified with a blue bar
and a green bar along the side of the color matrix in part b and
shown in expanded form in parts e and f. The clones that identify
the genes in these two basal subsets are listed by their Genbank
accession numbers in Table 9. As is evident from examination of
Appendix C, parts e and f, genes in the basal gene subset are, in
general, overexpressed in tumors in the basal tumor group
(identified with orange dendrogram branches). Of course it will be
appreciated that additional genes, not necessarily falling into
either of the two basal gene subsets, also have an expression
pattern similar to that of cytokeratin 5 and/or cytokeratin 17.
[0154] It will be appreciated that not all of the genes are
overexpressed to a similar extent within a particular group of
tumors and that expression of any given gene will likely vary
between different tumors in a group. For example, as shown in
Appendix C, part c, genes identified as "Cytochrome P450, subfamily
IIA" and "Lymphoid nuclear protein related to AF4" are
significantly overexpressed in tumors at the far right of the
luminal tumor group (Stanford 24, Norway 27, 28, 26, and 56) while
they are expressed at lesser levels in other members of the luminal
tumor group. Conversely, genes identified as "417081" and "Homo
Sapiens PWD gene mRNA, 3' end" are, in general, relatively
underexpressed in these tumors. However, the overall expression
patterns of genes in each subset over all tissue samples, are
sufficiently similar to cause them to cluster in close proximity on
the gene dendrogram. Thus whether a gene is a member of one of the
inventive gene subsets is not determined solely on the basis of the
overexpression of that gene within a tumor subset but also on the
relationship of the overall expression pattern of the gene to the
expression pattern of other genes within the subset. It will
further be appreciated that a gene may be overexpressed in more
than one tumor group. For example, certain of the genes in the
basal subset are expressed in a group identified with green
dendrogram branches, which includes both tumor and normal tissue
samples, in addition to being overexpressed in the basal tumor
group.
B. Diagnostics and Methods of Use Thereof
[0155] The invention provides reagents for detecting expression
products of the basal marker genes described herein, i.e.,
cadherin3, matrix metalloproteinase 14, and cadherin EGF LAG
seven-pass G-type receptor 2. Detection of these expression
products identifies tumors in the basal tumor subclass. While not
wishing to be bound by any theory, inventors suggest that breast
carcinoma with basal cell like features has distinguishing biology
that could be targeted in therapeutic development. Once
therapeutics targeted at such tumors are identified (as described
elsewhere herein), detection of these expression products allows
identification of subjects likely to benefit from these
therapeutics. In addition, since the invention has established a
correlation between the expression of the three basal marker genes
and the expression of cytokeratin17 and also established that
cytokeratin 5/6 and/or cytokeratin 17 expression in breast tumors
correlates with a poor outcome, detection of expression of the
basal marker genes is useful in guiding therapeutic decisions in
general. If it is known that a patient has a tumor that falls into
the basal tumor subclass and thus has a poor prognosis, a more
aggressive approach to therapy may be warranted than in tumors not
falling within the basal subclass. For example, in patients where
there is no evidence of disease in lymph nodes (node-negative
patients), a decision must be made regarding whether to administer
chemotherapy (adjuvant therapy) following surgical removal of the
tumor. While some patients are likely to benefit from such
treatment, it has significant side effects. Presently it is
difficult or impossible to predict which patients would benefit.
Knowing that a patient falls into a poor prognosis category may
help in this decision. Of note, inventors showed that in
node-negative patients cytokeratin 5/6 and/or 17 expression was a
prognostic factor independent of tumor size and tumor grade. See
Example 13 for further discussion of these issues and inventor's
findings. Detecting expression of the basal marker genes of the
present invention may provide information related to tumor
progression. It is well known that as tumors progress, their
phenotypic characteristics may change. The invention contemplates
the possibility that breast tumors may evolve from luminal-like to
basal-like (or vice versa), and that detection of expression
products of the basal marker genes can be used to detect such
progression.
[0156] It is well known in the art that some tumors respond to
certain therapies while others do not. In general there is very
little information that may be used to determine, prior to
treatment, the likelihood that a specific tumor will respond to a
given therapeutic agent. Many compounds have been tested for
anti-tumor activity and appear to be effective in only a small
percentage of tumors. Due to the current inability to predict which
tumors will respond to a given agent, these compounds have not been
developed into marketed therapeutics. This problem reflects the
fact that current methods of classifying tumors are limited.
However, the present invention offers the possibility of
identifying tumor subgroups characterized by a significant
likelihood of response to a given agent. Tumor sample archives
containing tissue samples obtained from patients that have
undergone therapy with various agents are available along with
information regarding the results of such therapy. In general such
archives consist of tumor samples embedded in paraffin blocks.
These tumor samples can be analyzed for their expression of
polypeptides encoded by the basal marker genes of the present
invention. For example, immunohistochemistry can be performed using
antibodies that bind to the polypeptides. Tumors belonging to the
basal tumor subclass may then be identified on the basis of this
information. It is then possible to correlate the expression of the
basal marker genes with the response of the tumor to therapy,
thereby identifying particular compounds that show a superior
efficacy in tumors in this class as compared with their efficacy in
tumors overall or in tumors not falling within the basal tumor
subclass. Once such compounds are identified it will be possible to
select patients whose tumors fall into the basal tumor subclass for
additional clinical trials using these compounds. Such clinical
trials, performed on a selected group of patients, are more likely
to demonstrate efficacy. The reagents provided herein, therefore,
are valuable both for retrospective and prospective trials.
[0157] In the case of prospective trials, detection of expression
products of one or more of the marker genes may be used to stratify
patients prior to their entry into the trial or while they are
enrolled in the trial. In clinical research, stratification is the
process or result of describing or separating a patient population
into more homogeneous subpopulations according to specified
criteria. Stratifying patients initially rather than after the
trial is frequently preferred, e.g., by regulatory agencies such as
the U.S. Food and Drug Administration that may be involved in the
approval process for a medication. In some cases stratification may
be required by the study design. Various stratification criteria
may be employed in conjunction with detection of expression of one
or more basal marker genes. Commonly used criteria include age,
family history, lymph node status, tumor size, tumor grade, etc.
Other criteria including, but not limited to, tumor aggressiveness,
prior therapy received by the patient, ER and/or PR positivity,
Her2neu status, p53 status, various other biomarkers, etc., may
also be used. Stratification is frequently useful in performing
statistical analysis of the results of a trial. Ultimately, once
compounds that exhibit superior efficacy against breast basal
tumors are identified, reagents for detecting expression of the
basal marker genes may be used to guide the selection of
appropriate chemotherapeutic agent(s).
[0158] In summary, by providing reagents and methods for
classifying tumors based on their expression of the basal marker
genes, the present invention offers a means to individualize
therapy. The invention further provides a means to identify a
patient population that may benefit from potentially promising
therapies that have been abandoned due to inability to identify the
patients who would benefit from their use.
[0159] Information regarding the expression of the basal marker
genes is useful even in the absence of specific information
regarding their biological function or role in tumor development,
progression, maintenance, or response to therapy. Although the
reagents disclosed herein find particular application with respect
to breast cancer, the invention also contemplates their use to
provide diagnostic and/or prognostic information for other cancer
types. As is well known in the art, mutations in a single gene
(e.g., the p53 gene) may play a role in the development of multiple
cancer types. Thus it is contemplated that some or all of the basal
marker genes described herein will be important both in breast
cancer and in one or more other tumor types, particularly since
basal cells are a feature of epithelia throughout the body.
[0160] In one aspect, the invention provides a method of
classifying tumors by detecting the presence of one or more of the
inventive gene products encoded by the cadherin3, matrix
metalloproteinase 14, and cadherin EGF LAG seven-pass G-type
receptor 2 genes. As is well known in the art, a polypeptide may be
detected using a variety of techniques that employ an antibody that
binds to the polypeptide. As described further below, these
techniques include enzyme-linked immunosorbent assay (ELISA),
immunoblot, and immunohistochemistry. The invention encompasses the
use of protein arrays, including antibody arrays, for detection of
the polypeptide. The use of antibody arrays is described, for
example, in Haab, B., et al., "Protein microarrays for highly
parallel detection and quantitation of specific proteins and
antibodies in complex solutions", Genome Biol. 2001; 2 (2), 2001.
Other types of protein arrays are known in the art.
[0161] In addition, in certain embodiments of the invention the
polypeptides are detected using other modalities known in the art
for the detection of polypeptides, such as aptamers (Aptamers,
Molecular Diagnosis, Vol. 4, No. 4, 1999), reagents derived from
combinatorial libraries for specific detection of proteins in
complex mixtures, random peptide affinity reagents, etc. In
general, any appropriate method for detecting a polypeptide may be
used in conjunction with the present invention, although antibodies
may represent a particularly appropriate modality.
[0162] The invention provides antibodies to the polypeptides
encoded by the encoded by the cadherin3, matrix metalloproteinase
14, and cadherin EGF LAG seven-pass G-type receptor 2 genes.
Example 10 describes the generation of polyclonal antibodies to
these polypeptides. In general, antibodies (either monoclonal or
polyclonal) may be generated by methods well known in the art and
described, for example, in Harlow, E., Lane, E., and Harlow, E.,
(eds.) Using Antibodies: A Laboratory Manual, Cold Spring Harbor
Laboratory Press, Cold Spring Harbor, 1998. Details and references
for the production of antibodies based on an inventive polypeptide
may also be found in U.S. Pat. No. 6,008,337. Antibodies may
include, but are not limited to, polyclonal, monoclonal, chimeric
(e.g., "humanized"), and single chain antibodies, and Fab
fragments, antibodies generated using phage display technology,
etc. The invention encompasses "fully human" antibodies produced
using the XenoMouse.TM. technology (AbGenix Corp., Fremont, Calif.)
according to the techniques described in U.S. Pat. No.
6,075,181.
[0163] The invention encompasses a number of uses for these
antibodies. Detection of the basal marker polypeptides may be used
to provide diagnostic information. As used herein the term
"diagnostic information" includes, but is not limited to, any type
of information that is useful in determining whether a patient has,
or is at increased risk for developing, a disease or disorder; for
providing a prognosis for a patient having a disease or disorder;
for classifying a disease or disorder; for monitoring a patient for
recurrence of a disease or disorder; for selecting a preferred
therapy; for predicting the likelihood of response to a therapy,
etc. In certain embodiments of the invention, the antibodies are
used for providing diagnostic information for cancer, particularly
for breast cancer, but they may also be of use for providing
diagnostic information for other diseases, e.g., other types of
cancer.
[0164] In general, diagnostic assays in which the antibodies may be
employed include methods that use the antibody to detect the
polypeptide in a tissue sample, cell sample, body fluid sample
(e.g., serum), cell extract, etc. Such methods typically involve
the use of a labeled secondary antibody that recognizes the primary
antibody (i.e., the antibody that binds to the polypeptide being
detected). Depending upon the nature of the sample, appropriate
methods include, but are not limited to, immunohistochemistry,
radioimmunoassay, ELISA, immunoblotting, and FACS analysis. In the
case where the polypeptide is to be detected in a tissue sample,
e.g., a biopsy sample, immunohistochemistry is a particularly
appropriate detection method. Techniques for obtaining tissue and
cell samples and performing immunohistochemistry and FACS are well
known in the art. Such techniques are routinely used, for example,
to detect the ER in breast tumor tissue or cell samples. In
general, such tests will include a negative control, which can
involve applying the test to normal tissue so that the signal
obtained thereby can be compared with the signal obtained from the
sample being tested. In tests in which a secondary antibody is used
to detect the antibody that binds to the polypeptide of interest,
an appropriate negative control can involve performing the test on
a portion of the sample with the omission of the antibody that
binds to the polypeptide to be detected, i.e., with the omission of
the primary antibody. Antibodies suitable for use as diagnostics
generally exhibit high specificity for the target polypeptide and
low background. In general, monoclonal antibodies are preferred for
diagnostic purposes.
[0165] In general, the results of such a test can be presented in
any of a variety of formats. The results can be presented in a
qualitative fashion. For example, the test report may indicate only
whether or not a particular polypeptide was detected, perhaps also
with an indication of the limits of detection. The results may be
presented in a semi-quantitative fashion. For example, various
ranges may be defined, and the ranges may be assigned a score
(e.g., 1+ to 4+) that provides a certain degree of quantitative
information. Such a score may reflect various factors, e.g., the
number of cells in which the polypeptide is detected, the intensity
of the signal (which may indicate the level of expression of the
polypeptide), etc. The results may be presented in a quantitative
fashion, e.g., as a percentage of cells in which the polypeptide is
detected, as a protein concentration, etc. As will be appreciated
by one of ordinary skill in the art, the type of output provided by
a test will vary depending upon the technical limitations of the
test and the biological significance associated with detection of
the polypeptide. For example, in the case of certain polypeptides a
purely qualitative output (e.g., whether or not the polypeptide is
detected at a certain detection level) provides significant
information. In other cases a more quantitative output (e.g., a
ratio of the level of expression of the polypeptide in the sample
being tested versus the normal level) is necessary.
[0166] Sequence analysis of two of the basal marker proteins,
matrix metalloproteinase 14 and cadherin EGF LAG seven-pass G-type
receptor 2 indicates that they possess one or more transmembrane
domains and an extracellular portion. Sequence analysis of the
third basal marker protein, cadherin3, indicates that it also has
an extracellular portion. The invention encompasses the recognition
that since these proteins have an extracellular domain, the
likelihood exists that a portion of these proteins may therefore be
present in serum (e.g., the portion may be cleaved by endogenous
proteases and released into the bloodstream), enabling their
detection through a blood test rather than requiring a biopsy
specimen. Regardless of whether the proteins are present in serum,
the likelihood that cadherin3, cadherin EGF LAG seven-pass G-type
receptor 2, and matrix metalloproteinase 14 are membrane bound
makes them attractive candidates for antibody diagnostics. The
proteins may be detected on cells that enter the bloodstream or in
samples obtained from a tumor site (e.g., cell or tissue
samples).
[0167] Measurement of prostate specific antigen (PSA) in serum
using an immunoassay technique is widely used as a method for early
detection of prostate cancer and for monitoring recurrence or
progression after therapy, etc. Methods and considerations in the
use of this clinical marker are described, for example, in Chen D
W, et al. Prostate-specific antigen as a marker for prostate
cancer: A monoclonal and polyclonal immunoassay compared. Clin
Chem, 33:1916-1920, 1987; Oesterling J E, et al. Free, complexed
and total serum prostate specific antigen: The establishment of
appropriate reference ranges for their concentrations and ratios. J
Urol 154:1090-1095, 1995; Hybritech Tandem.RTM.-MP Free PSA.
Package insert. March 1998 and Hybritech Tandem.RTM. Total PSA.
Package insert., Hybritech, Inc., San Diego, Calif. One of ordinary
skill in the art will readily be able to develop appropriate assays
for polypeptides encoded by the basal marker genes described herein
and to apply them to the detection of such polypeptides in serum.
Such assays may be used as screening tests for cancer, to detect
recurrence or progression of cancer, to monitor the response of
cancer to therapy, to classify and/or provide prognostic
information regarding a tumor, etc.
[0168] In certain embodiments of the inventive methods a single
antibody is used whereas in other embodiments of the invention
multiple antibodies, directed either against the same or against
different polypeptides can be used to increase the sensitivity or
specificity of the test or to provide more detailed information
than that provided by a single antibody. Thus the invention
encompasses the use of a battery of antibodies that bind to
polypeptides encoded by the basal marker genes identified herein.
Of course these antibodies can also be used in conjunction with
antibodies against other polypeptides, including antibodies that
bind to cytokeratin 5/6 or 17.
[0169] Various other techniques for detecting the basal marker
polypeptides identified herein are within the scope of the
invention. For example, a basal marker polypeptide may be detected
using an assay for a biochemical activity of the polypeptide, e.g.,
an enzymatic activity. This type of assay may be especially
convenient for tests on samples such as blood or other body fluids.
Such an approach may be particularly attractive in the case of
matrix metalloproteinase 14. As described above, matrix
metalloproteinases are involved in cleavage of various proteins in
the extracellular matrix. The cleavage specificity of this protein
may readily be determined, and an appropriate substrate prepared.
(See, e.g., Turk, B., et al., "Determination of protease cleavage
site motifs using mixture-based oriented peptide libraries", Nature
Biotechnology, 19 (7): 661-667, 2001, which discusses cleavage site
motifs for various metalloproteases including MMP14, referred to as
MT1-MMP therein.) Cleavage of this substrate may then be detected.
In certain embodiments of the invention the substrate includes a
fluorescent moiety for convenient detection. The invention
contemplates use of fluorescent resonance energy transfer (FRET)
assays to detect matrix metalloproteinase 14 (see
www.aurorabio.com).
[0170] Although in many cases detection of polypeptides using
antibodies represents the most convenient means of determining
whether a gene is expressed (or overexpressed) in a particular
sample, the invention also encompasses the use of polynucleotides
for this purpose. Microarray analysis is but one means by which
polynucleotides can be used to detect or measure gene expression.
Expression of a gene can also be measured by a variety of
techniques that make use of a polynucleotide corresponding to part
or all of the gene rather than an antibody that binds to a
polypeptide encoded by the gene. Appropriate techniques include,
but are not limited to, in situ hybridization, Northern blot, and
various nucleic acid amplification techniques such as PCR,
quantitative PCR, and the ligase chain reaction.
[0171] One detection method involves performing quantitative PCR on
a diagnostic sample using a set of oligonucleotide primers designed
to amplify the genes in one or more of the inventive gene sets of
gene subsets. (Considerations for primer design are well known in
the art and are described, for example, in Newton, et al. (eds.)
PCR: Essential data Series, John Wiley & Sons; PCR Primer: A
Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring
Harbor, N.Y., 1995; White, et al. (eds.) PCR Protocols: Current
methods and Applications, Methods in Molecular Biology, The Humana
Press, Totowa, N.J., 1993. In addition, a variety of computer
programs known in the art may be used to select appropriate
primers.)
[0172] According to one embodiment of this method the diagnostic
sample is distributed into multiple vessels, e.g., multiple wells
of a 396 well microtiter plate. A pair of primers designed to
amplify a portion of a gene in one of the inventive gene sets or
subsets is added to each well, and PCR amplification is performed.
The resulting product can then be detected using any of a number of
methods known in the art depending upon the particular method of
performing quantitative PCR that is employed. Primers sufficient
for amplification of genes that allow quantitation of different
cell types within the sample may also be included in the set of
primers.
[0173] The invention also encompasses the detection of mutations
within any of the basal marker genes or within a regulatory region
of a basal marker gene. Such mutations may include, but are not
limited to, deletions, additions, substitutions, and amplification
of regions of genomic DNA that include all or part of a gene.
Methods for detecting such mutations are well known in the art.
Such mutations may result in overexpression or inappropriate
expression of the gene. Detection of mutations can be used, for
example, to predict the likelihood that an individual will develop
a condition associated with the mutation.
[0174] Another aspect of the invention comprises a kit to test for
the presence of any of the inventive polynucleotides or
polypeptides, e.g., in a tissue sample or in a body fluid. The kit
can comprise, for example, an antibody for detection of a
polypeptide or a probe for detection of a polynucleotide. In
addition, the kit can comprise a reference or control sample,
instructions for processing samples, performing the test and
interpreting the results, buffers and other reagents necessary for
performing the test. In certain embodiments of the invention the
kit comprises a panel of antibodies. In certain embodiments of the
invention the kit comprises pairs of primers for detecting
expression of one or more of the basal marker genes. In certain
embodiments of the invention the kit comprises a cDNA or
oligonucleotide array for detecting expression of one or more of
the basal marker genes.
D. Therapeutics
[0175] The invention encompasses the use of the basal marker genes
and their expression products as targets for the development of
therapeutics. The invention specifically encompasses antagonists to
the basal marker genes and their expression products. Such
antagonists (which include, but are not limited to, antibodies,
small molecules, antisense nucleic acids) may be produced or
identified using any of a variety of methods known in the art. For
example, a purified polypeptide or fragment thereof may be used to
raise antibodies or to screen libraries of compounds to identify
those that specifically bind to the polypeptide. The likelihood
that cadherin3, cadherin EGF LAG seven-pass G-type receptor 2, and
matrix metalloproteinase 14 are membrane bound makes them
attractive candidates for antibody therapeutics.
[0176] Preferably antibodies suitable for use as therapeutics
exhibit high specificity for the target polypeptide and low
background binding to other polypeptides. In general, monoclonal
antibodies are preferred for therapeutic purposes. In the case of
breast cancer, antibodies against the HER2/neu/ErbB2 polypeptide (a
polypeptide homologous to the epidermal growth factor receptor)
represent a paradigm in terms of the development of therapeutic
antibodies. The HER2/neu/ErbB2 gene is overexpressed in
approximately 25 to 30 percent of metastatic breast tumors, and an
antibody against the HER2/neu/ErbB2 polypeptide, Herceptin.RTM.
(Trastuzumab) is approved for the treatment of certain patients
with metastatic breast cancer, confirming the utility of
therapeutic antibodies directed against polypeptides that are
specifically overexpressed in particular tumors subsets. Proteins
that are expressed on the cell surface, such as the basal marker
proteins described herein, represent preferred targets for the
development of therapeutic agents, particularly therapeutic
antibodies. The presence of these proteins on the cell surface can
be confirmed using immunohistochemisty.
[0177] Antibodies directed against a polypeptide expressed by a
cell may have a number of mechanisms of action. In certain
instances, e.g., in the case of a polypeptide that exerts a growth
stimulatory effect on a cell, antibodies may directly antagonize
the effect of the polypeptide and thereby arrest tumor progression,
trigger apoptosis, etc. While not wishing to be bound by any
theory, it may be particularly likely that certain genes that are
overexpressed in tumors having a poor prognosis (e.g., genes in the
basal gene subsets) encode polypeptides that have a growth
stimulatory effect on tumor cells or facilitate the growth of such
cells in some other way, e.g., by enhancing angiogenesis, by
allowing cells to overcome normal growth regulatory mechanisms, or
by blocking mechanisms that would normally lead to elimination of
mutated or otherwise abnormal cells.
[0178] In certain embodiments of the invention the antibody may
serve to target a toxic moiety to the cell. Thus the invention
encompasses the use of antibodies that have been conjugated with a
cytotoxic agent, e.g., a toxin such as ricin or diphtheria toxin, a
radioactive moiety, etc. Such antibodies can be used to direct the
cytotoxic agent specifically to cells that express the inventive
polypeptide, particularly in the case of a polypeptide that is
expressed on the cell surface.
[0179] Although certain antagonists may function through direct
interaction with a polypeptide, e.g., by inhibiting its activity,
others may function by affecting expression of the polypeptide.
Reduction in expression of an endogenously produced polypeptide may
be achieved by the administration of antisense nucleic acids (e.g.,
oligonucleotides, RNA, DNA, most typically oligonucleotides that
have been modified to improve stability or targeting) or peptide
nucleic acids comprising sequences complementary to those of the
mRNA that encodes the polypeptide. Antisense technology and its
applications are described in Phillips, M. I. (ed.) Antisense
Technology, Methods Enzymol., Volumes 313 and 314, Academic Press,
San Diego, 2000, and references mentioned therein. Ribozymes
(catalytic RNA molecules that are capable of cleaving other RNA
molecules) represent another approach to reducing gene expression.
Such ribozymes can be designed to cleave specific mRNAs
corresponding to a gene of interest. Their use is described in U.S.
Pat. No. 5,972,621, and references therein. The invention
encompasses the delivery of antisense and/or ribozyme molecules via
a gene therapy approach in which vectors or cells expressing the
antisense molecules are administered to an individual.
[0180] It may also be desirable to increase the expression of a
gene in an inventive gene subset or to increase the activity of the
corresponding polypeptide. For example, in the case of genes that
are overexpressed in tumors having a good prognosis, e.g., certain
genes in the luminal subset, it may be desirable to increase the
expression of such genes or the activity of the corresponding
polypeptides in tumors that fail to express these genes.
[0181] Small molecule modulators (e.g., inhibitors or activators)
of gene expression are also within the scope of the invention and
may be detected by screening libraries of compounds using, for
example, cell lines that express the polypeptide or a version of
the polypeptide that has been modified to include a readily
detectable moiety. Methods for identifying compounds capable of
modulating gene expression are described, for example, in U.S. Pat.
No. 5,976,793. The screening methods described therein are
particularly appropriate for identifying compounds that do not
naturally occur within cells and that modulate the expression of
genes of interest whose expression is associated with a defined
physiological or pathological effect within a multicellular
organism.
[0182] More generally, the invention encompasses compounds that
modulate the activity of a basal marker gene of the present
invention. Methods of screening for such interacting compounds are
well known in the art and depend, to a certain degree, on the
particular properties and activities of the polypeptide encoded by
the gene. Representative examples of such screening methods may be
found, for example, in U.S. Pat. No. 5,985,829, U.S. Pat. No.
5,726,025, U.S. Pat. No. 5,972,621, and U.S. Pat. No. 6,015,692.
The skilled practitioner will readily be able to modify and adapt
these methods as appropriate for a given polypeptide. Thus the
invention encompasses methods of screening for molecules that
modulate the activity of a polypeptide encoded by a basal marker
gene.
[0183] The invention also encompasses the use of polynucleotide
sequences corresponding to basal marker genes, or portions thereof,
as DNA vaccines. Such vaccines comprise polynucleotide sequences,
typically inserted into vectors, that direct the expression of an
antigenic polypeptide within the body of the individual being
immunized. Details regarding the development of vaccines, including
DNA vaccines for various forms of cancer may be found, for example,
in Brinckerhoff L. H., Thompson L. W., Slingluff C. L., Jr.,
Melanoma Vaccines, Curr Opin Oncol, 12 (2):163-73, 2000 and in
Stevenson, F. K., DNA vaccines against cancer: from genes to
therapy, Ann. Oncol., 10 (12): 1413-8, 1999 and references therein.
The polypeptides, or fragments thereof, that are encoded by genes
in the inventive gene subsets may also find use as cancer vaccines.
Such vaccines may be used for the prevention and/or treatment of
cancer.
[0184] The invention includes pharmaceutical compositions
comprising the inventive antibodies, or small molecule inhibitors,
agonists, or antagonists described above. In general, a
pharmaceutical composition will include an active agent in addition
to one or more inactive agents such as a sterile, biocompatible
carrier including, but not limited to, sterile water, saline,
buffered saline, or dextrose solution. The pharmaceutical
compositions may be administered either alone or in combination
with other therapeutic agents including other chemotherapeutic
agents, hormones, vaccines, and/or radiation therapy. By "in
combination with", it is not intended to imply that the agents must
be administered at the same time or formulated for delivery
together, although these methods of delivery are within the scope
of the invention. In general, each agent will be administered at a
dose and on a time schedule determined for that agent.
Additionally, the invention encompasses the delivery of the
inventive pharmaceutical compositions in combination with agents
that may improve their bioavailability, reduce or modify their
metabolism, inhibit their excretion, or modify their distribution
within the body. The invention encompasses treating cancer,
particularly breast cancer, by administering the pharmaceutical
compositions of the invention. Although the pharmaceutical
compositions of the present invention can be used for treatment of
any subject (e.g., any animal) in need thereof, they are most
preferably used in the treatment of humans.
[0185] The pharmaceutical compositions of this invention can be
administered to humans and other animals by a variety of routes
including oral, intravenous, intramuscular, intraarterial,
subcutaneous, intraventricular, transdermal, rectal intravaginal,
intraperitoneal, topical (as by powders, ointments, or drops),
bucal, or as an oral or nasal spray or aerosol. In general the most
appropriate route of administration will depend upon a variety of
factors including the nature of the compound (e.g., its stability
in the environment of the gastrointestinal tract), the condition of
the patient (e.g., whether the patient is able to tolerate oral
administration), etc. At present the intravenous route is most
commonly used to deliver therapeutic antibodies and nucleic acids.
However, the invention encompasses the delivery of the inventive
pharmaceutical composition by any appropriate route taking into
consideration likely advances in the sciences of drug delivery.
[0186] General considerations in the formulation and manufacture of
pharmaceutical agents may be found, for example, in Remington's
Pharmaceutical Sciences, 19.sup.th ed., Mack Publishing Co.,
Easton, Pa., 1995. It will be appreciated that certain of the
compounds of the present invention can exist in free form for
treatment, or, where appropriate, in salt form, as discussed in
more detail below. Compounds to be utilized in the pharmaceutical
compositions include compounds existing in free form or
pharmaceutically acceptable derivatives thereof, as defined herein,
such as pharmaceutically acceptable salts, esters, salts of such
esters, or any other adduct or derivative, which upon
administration to a patient in need, is capable of providing,
directly or indirectly, a compound as otherwise described herein,
or a metabolite or residue thereof, e.g., a prodrug. Thus, as used
herein, the term "pharmaceutically acceptable salt" refers to those
salts which are, within the scope of sound medical judgment,
suitable for use in contact with the tissues of humans and lower
animals without undue toxicity, irritation, allergic response and
the like, and are commensurate with a reasonable benefit/risk
ratio. Pharmaceutically acceptable salts are well known in the art.
For example, S. M. Berge, et al. describe pharmaceutically
acceptable salts in detail in J. Pharmaceutical Sciences, 66: 1-19
(1977), incorporated herein by reference. The salts can be prepared
in situ during the final isolation and purification of the
compounds of the invention, or separately by reacting the free base
function with a suitable organic acid. Examples of pharmaceutically
acceptable, nontoxic acid addition salts are salts of an amino
group formed with inorganic acids such as hydrochloric acid,
hydrobromic acid, phosphoric acid, sulfuric acid and perchloric
acid or with organic acids such as acetic acid, oxalic acid, maleic
acid, tartaric acid, citric acid, succinic acid, or malonic acid or
by using other methods used in the art such as ion exchange. Other
pharmaceutically acceptable salts include adipate, alginate,
ascorbate, aspartate, benzenesulfonate, benzoate, bisulfate,
borate, butyrate, camphorate, camphorsulfonate, citrate,
cyclopentanepropionate, digluconate, dodecylsulfate,
ethanesulfonate, formate, fumarate, glucoheptonate,
glycerophosphate, gluconate, hemisulfate, heptanoate, hexanoate,
hydroiodide, 2-hydroxy-ethanesulfonate, lactobionate, lactate,
laurate, lauryl sulfate, malate, maleate, malonate,
methanesulfonate, 2-naphthalenesulfonate, nicotinate, nitrate,
oleate, oxalate, palmitate, pamoate, pectinate, persulfate,
3-phenylpropionate, phosphate, picrate, pivalate, propionate,
stearate, succinate, sulfate, tartrate, thiocyanate,
p-toluenesulfonate, undecanoate, valerate salts, and the like.
Representative alkali or alkaline earth metal salts include sodium,
lithium, potassium, calcium, magnesium, and the like. Further
pharmaceutically acceptable salts include, when appropriate,
nontoxic ammonium, quaternary ammonium, and amine cations formed
using counterions such as halide, hydroxide, carboxylate, sulfate,
phosphate, nitrate, lower alkyl sulfonate and aryl sulfonate.
[0187] Additionally, as used herein, the term "pharmaceutically
acceptable ester" refers to esters that hydrolyze in vivo and
include those that break down readily in the human body to leave
the parent compound or a salt thereof. Suitable ester groups
include, for example, those derived from pharmaceutically
acceptable aliphatic carboxylic acids, particularly alkanoic,
alkenoic, cycloalkanoic and alkanedioic acids, in which each alkyl
or alkenyl moiety advantageously has not more than 6 carbon atoms.
Examples of particular suitable esters includes formates, acetates,
propionates, butyrates, acrylates and ethylsuccinates.
[0188] Furthermore, the term "pharmaceutically acceptable prodrugs"
as used herein refers to those prodrugs of the compounds of the
present invention that are, within the scope of sound medical
judgment, suitable for use in contact with the tissues of humans
and lower animals without undue toxicity, irritation, allergic
response, and the like, commensurate with a reasonable benefit/risk
ratio, and effective for their intended use, as well as the
zwitterionic forms, where possible, of the compounds of the
invention. The term "prodrug" refers to compounds that are rapidly
transformed in vivo to yield a particular active compound, for
example by hydrolysis in blood. A thorough discussion is provided
in T. Higuchi and V. Stella, "Pro-drugs as Novel Delivery Systems",
Vol. 14 of the A.C.S. Symposium Series, and in Edward B. Roche,
ed., Bioreversible Carriers in Drug Design, American Pharmaceutical
Association and Pergamon Press, 1987, both of which are
incorporated herein by reference.
[0189] As mentioned above, the pharmaceutical compositions of the
present invention additionally comprise a pharmaceutically
acceptable carrier, which, as used herein, means a non-toxic, inert
solid, semi-solid or liquid filler, diluent, encapsulating
material, or formulation auxiliary of any type. Some examples of
materials which can serve as pharmaceutically acceptable carriers
are sugars such as lactose, glucose and sucrose; starches such as
corn starch and potato starch; cellulose and its derivatives such
as sodium carboxymethyl cellulose, ethyl cellulose and cellulose
acetate; powdered tragacanth; malt; gelatin; talc; excipients such
as cocoa butter and suppository waxes; oils such as peanut oil,
cottonseed oil; safflower oil; sesame oil; olive oil; corn oil and
soybean oil; glycols; such a propylene glycol; esters such as ethyl
oleate and ethyl laurate; agar; buffering agents such as magnesium
hydroxide and aluminum hydroxide; alginic acid; water; isotonic
saline; Ringer's solution; ethyl alcohol, and phosphate buffer
solutions, dextrose solutions, as well as other non-toxic
compatible lubricants such as sodium lauryl sulfate and magnesium
stearate, as well as coloring agents, releasing agents, coating
agents, sweetening, flavoring and perfuming agents, preservatives
and antioxidants can also be present in the composition, according
to the judgment of the formulator.
[0190] Liquid dosage forms for oral administration include
pharmaceutically acceptable emulsions, microemulsions, solutions,
suspensions, syrups and elixirs. In addition to the active
compounds, the liquid dosage forms may contain inert diluents
commonly used in the art such as, for example, water or other
solvents, solubilizing agents and emulsifiers such as ethyl
alcohol, isopropyl alcohol, ethyl carbonate, ethyl acetate, benzyl
alcohol, benzyl benzoate, propylene glycol, 1,3-butylene glycol,
dimethylformamide, oils (in particular, cottonseed, groundnut,
corn, germ, olive, castor, and sesame oils), glycerol,
tetrahydrofurfuryl alcohol, polyethylene glycols and fatty acid
esters of sorbitan, and mixtures thereof. Besides inert diluents,
the oral compositions can also include adjuvants such as wetting
agents, emulsifying and suspending agents, sweetening, flavoring,
and perfuming agents.
[0191] Injectable preparations, for example, sterile injectable
aqueous or oleaginous suspensions may be formulated according to
the known art using suitable dispersing or wetting agents and
suspending agents. The sterile injectable preparation may also be a
sterile injectable solution, suspension or emulsion in a nontoxic
parenterally acceptable diluent or solvent, for example, as a
solution in 1,3-butanediol. Among the acceptable vehicles and
solvents that may be employed are water, Ringer's solution, U.S.P.
and isotonic sodium chloride solution. In addition, sterile, fixed
oils are conventionally employed as a solvent or suspending medium.
For this purpose any bland fixed oil can be employed including
synthetic mono- or diglycerides. In addition, fatty acids such as
oleic acid are used in the preparation of injectables.
[0192] The injectable formulations can be sterilized, for example,
by filtration through a bacterial-retaining filter, or by
incorporating sterilizing agents in the form of sterile solid
compositions which can be dissolved or dispersed in sterile water
or other sterile injectable medium prior to use.
[0193] In order to prolong the effect of a drug, it is often
desirable to slow the absorption of the drug from subcutaneous or
intramuscular injection. This may be accomplished by the use of a
liquid suspension of crystalline or amorphous material with poor
water solubility. The rate of absorption of the drug then depends
upon its rate of dissolution which, in turn, may depend upon
crystal size and crystalline form. Alternatively, delayed
absorption of a parenterally administered drug form is accomplished
by dissolving or suspending the drug in an oil vehicle. Injectable
depot forms are made by forming microencapsulated matrices of the
drug in biodegradable polymers such as polylactide-polyglycolide.
Depending upon the ratio of drug to polymer and the nature of the
particular polymer employed, the rate of drug release can be
controlled. Examples of other biodegradable polymers include
poly(orthoesters) and poly(anhydrides). Depot injectable
formulations are also prepared by entrapping the drug in liposomes
or microemulsions which are compatible with body tissues.
[0194] Compositions for rectal or vaginal administration are
preferably suppositories which can be prepared by mixing the
compounds of this invention with suitable non-irritating excipients
or carriers such as cocoa butter, polyethylene glycol or a
suppository wax which are solid at ambient temperature but liquid
at body temperature and therefore melt in the rectum or vaginal
cavity and release the active compound.
[0195] Solid dosage forms for oral administration include capsules,
tablets, pills, powders, and granules. In such solid dosage forms,
the active compound is mixed with at least one inert,
pharmaceutically acceptable excipient or carrier such as sodium
citrate or dicalcium phosphate and/or a) fillers or extenders such
as starches, lactose, sucrose, glucose, mannitol, and silicic acid,
b) binders such as, for example, carboxymethylcellulose, alginates,
gelatin, polyvinylpyrrolidinone, sucrose, and acacia, c) humectants
such as glycerol, d) disintegrating agents such as agar--agar,
calcium carbonate, potato or tapioca starch, alginic acid, certain
silicates, and sodium carbonate, e) solution retarding agents such
as paraffin, f) absorption accelerators such as quaternary ammonium
compounds, g) wetting agents such as, for example, cetyl alcohol
and glycerol monostearate, h) absorbents such as kaolin and
bentonite clay, and i) lubricants such as talc, calcium stearate,
magnesium stearate, solid polyethylene glycols, sodium lauryl
sulfate, and mixtures thereof. In the case of capsules, tablets and
pills, the dosage form may also comprise buffering agents.
[0196] Solid compositions of a similar type may also be employed as
fillers in soft and hard-filled gelatin capsules using such
excipients as lactose or milk sugar as well as high molecular
weight polyethylene glycols and the like. The solid dosage forms of
tablets, dragees, capsules, pills, and granules can be prepared
with coatings and shells such as enteric coatings and other
coatings well known in the pharmaceutical formulating art. They may
optionally contain opacifying agents and can also be of a
composition that they release the active ingredient(s) only, or
preferentially, in a certain part of the intestinal tract,
optionally, in a delayed manner. Examples of embedding compositions
that can be used include polymeric substances and waxes. Solid
compositions of a similar type may also be employed as fillers in
soft and hard-filled gelatin capsules using such excipients as
lactose or milk sugar as well as high molecular weight polethylene
glycols and the like.
[0197] The active compounds can also be in micro-encapsulated form
with one or more excipients as noted above. The solid dosage forms
of tablets, dragees, capsules, pills, and granules can be prepared
with coatings and shells such as enteric coatings, release
controlling coatings, and other coatings well known in the
pharmaceutical formulating art. In such solid dosage forms the
active compound may be admixed with at least one inert diluent such
as sucrose, lactose or starch. Such dosage forms may also comprise,
as is normal practice, additional substances other than inert
diluents, e.g., tableting lubricants and other tableting aids such
a magnesium stearate and microcrystalline cellulose. In the case of
capsules, tablets and pills, the dosage forms may also comprise
buffering agents. They may optionally contain opacifying agents and
can also be of a composition that they release the active
ingredient(s) only, or preferentially, in a certain part of the
intestinal tract, optionally, in a delayed manner. Examples of
embedding compositions that can be used include polymeric
substances and waxes.
[0198] Dosage forms for topical or transdermal administration of a
compound of this invention include ointments, pastes, creams,
lotions, gels, powders, solutions, sprays, inhalants or patches.
The active component is admixed under sterile conditions with a
pharmaceutically acceptable carrier and any needed preservatives or
buffers as may be required. Ophthalmic formulation and ear drops
are also contemplated as being within the scope of this invention.
The ointments, pastes, creams and gels may contain, in addition to
an active compound of this invention, excipients such as animal and
vegetable fats, oils, waxes, paraffins, starch, tragacanth,
cellulose derivatives, polyethylene glycols, silicones, bentonites,
silicic acid, talc and zinc oxide, or mixtures thereof. Powders and
sprays can contain, in addition to the compounds of this invention,
excipients such as lactose, talc, silicic acid, aluminum hydroxide,
calcium silicates and polyamide powder, or mixtures of these
substances. Sprays can additionally contain propellants known in
the art such as chlorofluorohydrocarbons.
[0199] Transdermal patches have the added advantage of providing
controlled delivery of a compound to the body. Such dosage forms
can be made by dissolving or dispensing the compound in the proper
medium. Absorption enhancers can also be used to increase the flux
of the compound across the skin. The rate can be controlled by
either providing a rate controlling membrane or by dispersing the
compound in a polymer matrix or gel.
[0200] In yet another aspect, the present invention also provides a
pharmaceutical pack or kit comprising one or more containers filled
with one or more of the ingredients of the pharmaceutical
compositions of the invention, and in certain embodiments, includes
an additional approved therapeutic agent for use as a combination
therapy. Optionally associated with such container(s) can be a
notice in the form prescribed by a governmental agency regulating
the manufacture, use or sale of pharmaceutical products, which
notice reflects approval by the agency of manufacture, use or sale
for human administration. Instructions for use of the compound(s)
may also be included.
[0201] According to the methods of treatment of the present
invention, cancer, particularly breast cancer, is treated or
prevented in a patient such as a human or other mammal by
administering to the patient a therapeutically effective amount of
a compound of the invention, in such amounts and for such time as
is necessary to achieve the desired result. By a "therapeutically
effective amount" of a compound of the invention is meant a
sufficient amount of the compound to treat (e.g. to ameliorate the
symptoms of, delay progression of, prevent recurrence of, cure,
etc.) cancer, particularly breast cancer, at a reasonable
benefit/risk ratio, which involves a balancing of the efficacy and
toxicity of the compound. In general, therapeutic efficacy and
toxicity may be determined by standard pharmacological procedures
in cell cultures or with experimental animals, e.g., by calculating
the ED.sub.50 (the dose that is therapeutically effective in 50% of
the treated subjects) and the LD.sub.50 (the dose that is lethal to
50% of treated subjects). The ED.sub.50/LD.sub.50 represents the
therapeutic index of the compound. Although in general drugs having
a large therapeutic index are preferred, as is well known in the
art, a smaller therapeutic index may be acceptable in the case of a
serious disease, particularly in the absence of alternative
therapeutic options. Ultimate selection of an appropriate range of
doses for administration to humans is determined in the course of
clinical trials.
[0202] It will be understood that the total daily usage of the
compounds and compositions of the present invention for any given
patient will be decided by the attending physician within the scope
of sound medical judgment. The specific therapeutically effective
dose level for any particular patient will depend upon a variety of
factors including the disorder being treated and the severity of
the disorder; the activity of the specific compound employed; the
specific composition employed; the age, body weight, general
health, sex and diet of the patient; the time of administration,
route of administration, and rate of excretion of the specific
compound employed; the duration of the treatment; drugs used in
combination or coincidental with the specific compound employed;
and like factors well known in the medical arts.
[0203] The total daily dose of the compounds of this invention
administered to a human or other mammal in single or in divided
doses can be in amounts, for example, from 0.01 to 50 mg/kg body
weight or more usually from 0.1 to 25 mg/kg body weight. Single
dose compositions may contain such amounts or submultiples thereof
to make up the daily dose. In general, treatment regimens according
to the present invention comprise administration to a patient in
need of such treatment from about 0.1 .mu.g to about 2000 mg of the
compound(s) of the invention per day in single or multiple
doses.
EXAMPLES
[0204] Note: A numbered list of references appears following the
Examples, all of which are incorporated herein by reference.
Example 1
Preparation of Microarrays Containing 8498 Human cDNAs
[0205] The human cDNA clones used in this study were obtained from
Research Genetics (Huntsville Ala., USA) as bacterial colonies in
96-well microtiter plates. The clones were chosen from a set of
15,000 cDNA clones that corresponded to the Research Genetics Human
Gene Filters sets GF200-202 (www.resgen.com/). These clones form
part of a set of clones assembled by the I.M.A.G.E. consortium
(Lennon, G. G., Auffray, C., Polymeropoulos, M., Soares, M. B. The
I.M.A.G.E. Consortium: An Integrated Molecular Analysis of Genomes
and their Expression. Genomics 33:151-152, 1996) and are identified
by I.M.A.G.E. clone ID numbers. All clones printed on these arrays
were sequence validated as part of a product offered at Research
Genetics, Inc. We estimate that greater than 97% of the clones on
the array are correctly identified.
[0206] A detailed protocol for the production of the cDNA
microarrays used in this study is available at
cmgm.stanford.edu/pbrown/protocols.html and is reproduced below
with insubstantial changes. As described below, the protocol
includes steps of (1) cleaning the glass slides onto which the DNAs
(e.g., products of PCR reactions) are to be spotted; (2) spotting
the DNAs onto the glass slides with an arrayer; (3) Post processing
to prepare arrays containing spotted DNAs for hybridization. All
procedures are done at room temperature and with double distilled
water unless otherwise stated. Unless otherwise stated, in this
Example and the following Examples, reagents are prepared according
to protocols available in Maniatis, T., Sambrook, J. and Fritsch,
E., Molecular Cloning: A Laboratory Manual (3 Volume Set), Cold
Spring Harbor Laboratory Press, Cold Spring Harbor, 1989.
Cleaning Slides
[0207] Use 30 slide racks in 350 mL glass dishes [0208] 1. Dissolve
50 g of NaOH pellets into 150 ml ddH2O [0209] 2. Add 200 ml of 95%
EtOH, stir until completely mixed [0210] 3. If solution remains
cloudy, add ddH2O until clear [0211] 4. Pour solution into glass
slide box. [0212] 5. Drop in 30 slides in a metal rack. (Gold Seal
slides, Cat. 3010) [0213] 6. Let soak on an orbital shaker for at
least two hours [0214] 7. Rinse slides by transferring rack to
slide dish filled with ddH2O [0215] 8. Repeat ddH2O rinses
.times.3. It's important to remove all traces of the NaOH-ethanol.
[0216] 9. Prepare Poly-1-lysine solution: Use Sigma Poly-1-lysine
solution. Cat. No. 8920 [0217] 10. Add 70 mL poly-1-lysine to 280
ml of water [0218] 11. Transfer slides to poly-1-lysine solution
and let soak for 1 hour. [0219] 12. Remove excess liquid from
slides by spinning the rack of slides on microtiter plate carriers
at 500 rpm. [0220] 13. Dry slides at 40 degrees C. for 5 minutes in
a vacuum oven. [0221] 14. Store slides in a closed box for at least
two weeks prior to use. [0222] 15. Before printing arrays, check a
sample slide to make sure it's hydrophobic (water should bead off
it) but the lysine coating is not turning opaque. Arraying [0223]
1. Transfer PCR reactions to 96-well V-bottom tissue culture plates
(Costar). Add 1/10 vol. 3M sodium acetate (pH 5.2) and equal volume
isopropanol. Store at -20 C for a few hours. [0224] 2. Centrifuge
in Sorvall at 3500 RPM for 45 min. Rinse with 70% EtOH, centrifuge
again and dry. [0225] 2. Resuspend DNA in 12 ul 3.times.SSC for a
few hours and transfer to flexible U-bottom printing plates. [0226]
4. Spot DNA onto poly-1-lysine slides with an arrayer. Post
Processing [0227] 1. Rehydrate arrays by suspending slides over a
dish of warm ddH2O. (.about.1 minute) [0228] 2. Snap-dry each array
(DNA side up) on a 100C hot plate for 3 seconds. [0229] 3. UV
cross-link DNA to the glass by using a Stratalinker set for 60
millijoules [0230] 4. Dissolve 5 g of succinic anhydride (Aldrich)
in 315 mL of n-methyl-pyrrolidinone. [0231] 5. To this, add 35 mL
of 0.2M NaBorate pH 8.0 (made by dissolving boric acid in water and
adjusting the pH with NaOH), and stir until dissolved. [0232] 6.
Soak arrays in this solution for 15 minutes with shaking. [0233] 7.
Transfer arrays to 95C water bath for 2 minutes [0234] 8. Quickly
transfer arrays to 95% EtOH for 1 minute. [0235] 9. Remove excess
liquid from slides by spinning the rack of slides on microtiter
plate carriers at 500 rpm. [0236] 10. Arrays can be used
immediately. Reagent Suppliers [0237] Microscope slides Goldseal
brand. (Cat. 3010) [0238] Poly-1-lysine solution Sigma product
number P8920 [0239] Succinic Anhydride Aldrich product number
23,969-0 [0240] N-Methyl-Pyrrolidinone Aldrich product number
32,863-4
[0241] Microarrays were prepared according to the above protocol
using the 8498 cDNA clones described above. All microarrays used in
the experiments described herein were from a single print run batch
of microarrays.
Example 2
Cell Lines, Breast Tissue, and Breast Tumor Samples for Microarray
Analysis and Preparation of mRNA Samples
Common Reference Sample
[0242] Each of the 84 experimental samples tested here was analyzed
by a comparative hybridization, using a common reference RNA pool
as a standard; this reference sample was composed of equal mixtures
of mRNA isolated from 11 established cell lines derived from human
tissue (MCF7, Hs578T, OVCAR3, HepG2, NTERA2, MOLT4, RPMI-8226,
NB4+ATRA, UACC-62, SW872, and Colo205: also see Table 3 for more
details). The 11 cell lines were all grown to 70-90% confluence in
RPMI medium, containing 10% Fetal Calf Serum and
Penicillin/Streptomycin. The cells were harvested either by
scraping or centrifugation, quickly resuspended in RNA lysis buffer
and mRNA prepared using the FastTrack.TM. 2.0 mRNA Isolation Kit
(Invitrogen, Carlsbad, Calif.) according to the manufacturer's
instructions. In each case, multiple individual mRNA preparations
were collected for each cell line, which were then pooled together
and analyzed via Northern analysis before final mixing to ensure
the quality of the input mRNAs (e.g., to confirm that the mRNA
exhibited a size distribution indicating that it was substantially
nondegraded). The 11 mRNA samples were then mixed together in equal
amounts, aliquoted in 10 mM Tris (7.4), and stored at -80 C until
use (2 micrograms of common reference sample was used per
microarray hybridization and was always labeled using Cy3).
Normal Breast Tissue
[0243] Three samples of normal breast tissue were analyzed. Two of
the samples were obtained from Clontech (Palo Alto, Calif.) and
were pools of six (Normal1) or two (Normal2) whole normal breasts.
The third sample (Normal3) was obtained from a single
individual.
Breast Tumor Samples
[0244] The 40 individual breast tumor samples were collected at
either Stanford University in Stanford Calif., USA, or in the
Haukeland University Hospital in Bergen, Norway. Twenty of the
forty breast tumors were sampled twice as part of a larger
Norwegian study on locally advanced breast cancers (T3/T4 and/or N2
tumors) and have been described previously (Aas, T., et al., Nat.
Med., 2, 811-814, 1996, the contents of which are incorporated
herein by reference); these patients underwent an open surgical
biopsy before treatment with doxorubicin monotherapy (range 12-23
weeks), followed by the definitive surgical resection of the
remaining tumor after therapy, and were evaluated for clinical
responses according to UICC criteria (Hayward, J., et al., Br. J.
Cancer, 35, 292-298, 1977). In addition to the 20 pairs, there were
8 additional "before" specimens from Norway and 10 tumor specimens
from Stanford (all Stanford tumors tested had a diameter of 3 cm or
larger). Finally, 2 of the 10 Stanford tumor specimens assayed were
also paired with a lymph node metastasis from the same patient.
mRNA Isolation from Breast Tumor and Tissue Samples
[0245] Following their excision, breast tumor samples were rapidly
frozen in liquid N2 and then stored at -80 C until use. mRNA was
isolated from breast tumors and normal breast tissue using the
Trizol Reagent (Gibco-BRL) and Invitrogen FastTrack 2.0 Kit (all
Stanford samples, and see genome-www.stanford.edu/sbcmp/web.shtml
for the detailed protocol) or using the Trizol Reagent followed by
Dynal bead separation for the mRNA purification step (all Norway
tissue samples). Briefly, frozen tumor samples were cut into small
pieces and immediately placed into 12 ml of Trizol Reagent. Each
tumor sample in Trizol was homogenized using a PowerGen 125 Tissue
Homogenizer (Fisher Scientific), and total RNA was isolated
according to the Trizol reagent manufacturer's protocol. Tumor mRNA
was isolated according to the manufacturer's protocols using the
FastTrack 2.0 Kit (Invitrogen) or Dynal beads.
Example 3
Characterization of Breast Tissue and Tumor Samples
[0246] For all but two of the tumor specimens (i.e. New York 1 and
New York 2), the mutational status of the TP53 gene was determined
using published methods (Aas, T., et al.).
[0247] A single pathologist (applicant Matt van de Rijn) reviewed
hematoxylin and eosin (H&E) sections of each tumor, including
all before and after pairs, and made a histological evaluation of
each while blinded to the source. Tumors were graded using a
modified version of the Bloom-Richardson method (Robbins, P., et
al., Hum Pathol, 26, 873-879, 1995). These data are displayed in
Appendix H, Table 4. Representative H&E sections of each tumor
are posted on Applicants' website at
genome-www.stanford.edu/molecularportraits/.
[0248] Immunohistochemistry was performed as described previously
(Perou, C., et al., 1999; Bindl, J. and Warnke, R., Am J Clin
Pathol, 85, 490-493, 1986, and Natkunam, Y., et al., Am. J. Path.,
156 (1), 2000). The antibodies used included the commercially
available monoclonal antibodies CAM5.2 (specific for keratins 8/18,
available from Becton Dickinson), anti-keratin 5/6 (available
originally from Boehringer Mannheim, Indianapolis, Ind., cat. no.
1273396 and now from Chemicon International, Temekula, Calif.),
anti-keratin 17 (clone E3, available from Dako, Carpinteria,
Calif., cat. no. M7046), anti-CD3 (available from Dako), and
anti-immunoglobulin light chain (A191, A193, available from Dako).
These immunohistochemical methods were applied for all the
immunohistochemical studies described in the present application
unless otherwise stated. Results are presented in FIG. 3 and are
described in further examples as appropriate.
Example 4
cDNA Synthesis and Labeling and Microarray Hybridization
[0249] mRNA was isolated from breast tissue, breast tumor samples,
and cell lines as described in Example 2. Fluorescently labeled
cDNA was synthesized from the mRNA using a reverse transcriptase
reaction that included dUTP labeled with either Cy3 or Cy5. For
each hybridization experiment differentially labeled cDNA samples
(an experimental sample and a reference sample) were pooled and
hybridized to a cDNA microarray, which was then scanned as
described in Example 4. The protocol below provides details of the
steps performed for cDNA synthesis and labeling and for microarray
hybridization. [0250] 1. To set up for the reverse transcriptase
(RT) reaction, combine the following (e.g., in an Eppendorf tube):
[0251] (a) Anchored Oligo dT primer--2 microliters at 2.5
micrograms/microliter or control--2 microliters. [0252] (b)
mRNA--(whatever volume is needed to reach 1.5-2 micrograms) [0253]
(c) DEPC/H2O--add sufficient volume so that final volume is 16
microliters [0254] 2. Heat at 70.degree. C. for 10 minutes [0255]
3. Chill on ice for 1-2 minutes [0256] 4. Add the following RT
reaction components to each individual tube: [0257] (a) 5.times.RT
Buffer--6 microliters [0258] (b) 50.times. dNTPs--0.7
microliters--(500 mm A,C,G, 200 mm T) [0259] (c) Cy Dyes dUTP--3
microliters--(either Cy3 or Cy5) [0260] (d) DTT Stock--3
microliters--(comes with RT setup) [0261] (e) Superscript II
RT--1.7 microliters--(cat# 18064-014 Gibco-BRL) [0262] 5. Mix well
[0263] 6. Incubate at 42.degree. C. for 1 hour [0264] 7. Add
another 1 microliter of Superscript II RT and mix [0265] 8.
Incubate at 42.degree. C. for 1 more hour [0266] 9. Degrade mRNA
with 1.5 microliters of 1M NaOH/2 mM EDTA [0267] 10. Incubate at
65.degree. C. for 8 minutes (do NOT go TOO long here) [0268] 11.
Add 15 microliters of 0.1M HCL [0269] 12. Add 450 microliters of TE
(pH 7.4) to each sample and place each sample into a microcon-30
filter. [0270] 13. Add 15 microliters of Human COT1 DNA
(Gibco-BRL=1 microgram/microliter) to each sample in the microcon
filter. [0271] 14. Spin in Eppendorf centrifuge until volume equals
about 50 microliters (8-10') [0272] 15. Remove flowthroughs, and
pool Cy3 and Cy5 flowthroughs together for future recovery of Cy
dyes (store at -20.degree. C.). [0273] 16. Invert microcons,
recover labeled samples, and pool Cy3 and Cy5 samples together that
will be used for an individual experiment, in a single microcon
filter that was used in step 15. [0274] 17. Add 500 microliters of
T.E again, and spin until final volume equals 8 microliters or less
(BE VERY CAREFUL TO NOT SPIN THE SAMPLE DRY!!!) [0275] 18. To the 8
microliter combined Cy3+Cy5 sample, add the following: [0276] (a)
Yeast tRNA--1 microliter--(10 micrograms/microliter) [0277] (b)
PolyA DNA--2 microliters--(10 micrograms/microliter) [0278] (c)
20.times.SSC--2 microliters--(FINAL SSC concentration approximately
3.times.) [0279] (d) 10% SDS--0.3 microliters [0280] FINAL
VOLUME=13.3 MICROLITERS [0281] 19. Mix well. [0282] 20. Heat sample
at 100.degree. C. for 2 minutes, spin very briefly. [0283] 21.
Place samples at 42.degree. C. for 20-30 minutes. [0284] 22. During
Step 21, prepare the necessary number of hybridization chambers
(Custom made by Die-Tech, San Jose, Calif. (see "Drawings for
custom parts at cmgm.stanford.edu/pbrown/mguide/HybChamber.pdf") or
purchased at Corning Costar, Acton, Mass. (CTM.TM. Hybridization
Chamber, #2551), get 22 mm.times.22 mm coverslips ready, and get
arrays ready. [0285] 23. Add the 13 microliters of probe (i.e.,
labeled cDNA mixture) onto the center of the array while NOT
actually touching the array face with the pipette tip. [0286] 24.
Quickly and gently place the 22 mm.times.22 mm glass#1 coverslip
onto the array face. [0287] 25. Add about 15-20 microliters of
3.times.SSC in two drops onto the end of the array slide away from
the actual array for hydration purposes. [0288] 26. Assemble the
hybridization chamber with the array slide in it, and place into a
65 C water bath overnight. [0289] 27. Pull out the hybridization
chamber and dry off the excess H.sub.2O. [0290] 28. Disassemble the
hybridization chamber, and quickly place the slides into a slide
washing chamber that contains 2.times.SSC/0.05% SDS. Jiggle the
slide holder up and down until the slide coverslip falls off.
Repeat this individually for each array, one at a time, until all
are done [0291] 29. Wash slides in 1.times.SSC for 3-5 minutes.
[0292] 30. Wash slides in 50 C 0.2.times.SSC for 3-5 minutes,
twice. [0293] 31. Spin slides down in centrifuge at 200 RPM for 2
minutes. [0294] 32. SCAN immediately.
Example 5
Collection, Processing, and Analysis of Data from Microarray
Hybridizations
[0295] The cDNA microarrays were scanned with either a General
Scanning (Watertown, Mass.) ScanArray 3000 at 20 microns
resolution, or with a prototype Axon Instruments (Foster City,
Calif.) GenePix Scanner at 10 micron resolution. The output files,
which were TIFF images, were then analyzed using the program
ScanAlyze (M. Eisen; available at www.microarrays.org/software).
Fluorescent ratios and quantitative data on spot quality (see
ScanAlyze manual) were stored in a prototype of the AMAD database
(M. Eisen; available at www.microarrays.org/software). Areas of the
array with obvious blemishes were manually flagged and excluded
from subsequent analyses. The primary data tables can be downloaded
at genome-www.stanford.edu/molecularportraits/, in text/tab
delimited format after obtaining a password.
[0296] Data were extracted from the database in a single table,
with each row representing an array element, each column a
hybridization, and each cell the observed fluorescent ratio for the
array element in the appropriate hybridization. Previously flagged
spots were excluded, as were spots that did not pass quality
control. This table had 9216 rows and 84 columns. Array elements
were removed if they were not well measured in at least 80% of the
hybridizations. The data table was split into tumors and cell
lines, and the two subtables were separately median polished (the
rows and columns were iteratively adjusted to have median 0) before
being rejoined into a single table. Genes whose expression varied
by at least 4-fold from the median in this sample set in at least
three of the samples tested were selected for the analyses
described in the Detailed Description and in Examples 6 and 7 (1753
genes satisfied these conditions).
[0297] Average-linkage hierarchical clustering, as implemented in
the program Cluster (M. Eisen; www.microarrays.org/software), was
applied separately to both the genes and arrays. The results were
analyzed, and images generated, using TreeView (M. Eisen;
www.microarrays.org/software).
Example 6
Molecular Portraits of Tumors Based on Variation in Expression of
1753 Genes
Methods
[0298] A hierarchical clustering method (Eisen, 1998) was used to
group 1753 differentially expressed genes (i.e., those genes whose
expression varied by at least 4-fold from the median in the sample
set in at least three of the samples tested) based on similarity in
the pattern with which their expression varied over all samples.
The same clustering method was used to group the experimental
samples (tissues and cell lines separately) based on the similarity
in their patterns of expression. The expression patterns of the
1753 genes are displayed in Appendix A. In this illustration, the
data are presented in a matrix format, with each row representing a
single gene, and each column representing an experimental sample.
The ratio of the abundance of transcripts of each gene, in each
sample, to the median abundance of the gene's transcript among all
the cell lines (left panel) or to its median abundance across all
the clinical samples (right panel) is represented by the color of
the corresponding cell in the matrix. Green squares represent
transcript levels below the median; black squares represent
transcript levels equal to the median; red squares represent
transcript levels greater than the median; gray squares indicate
technically inadequate or missing data. The color saturation
reflects the magnitude of the ratio relative to the median for each
set of samples (see scale at bottom left). In all images the
brightest red color represents transcript levels at least 16-fold
greater than the median, and the brightest green color represents
transcript levels at least 16-fold below the median. The full gene
cluster diagram is presented in Appendix D.
Results
(i) Molecular Portraits of Tumors
[0299] Three striking general features of the tumors' gene
expression patterns are evident in Appendices A and D. First, the
breast tumors show remarkable variation in their patterns of gene
expression. Second, this variation is multidimensional, that is,
many different sets of genes show largely independent patterns of
variation. Third, the patterns of gene expression have a pervasive
order reflecting relationships among the genes, relationships among
the tumors, and connections between specific genes and specific
tumors.
[0300] The hierarchical clustering algorithm organized the
experimental samples based only on overall similarity in their gene
expression patterns; relationships among the experimental samples
are summarized in a dendrogram (Appendix A, part a), in which the
pattern and length of the branches reflect the relatedness of the
samples (Eisen, M., et al., 1998). Fifteen of the 20 pairs of
samples taken from the same tumor before and after doxorubicin
chemotherapy (red dendrogram branches), and both pairs of samples
taken from a primary tumor and an associated lymph node metastasis
(blue branches) were clustered together on adjacent terminal
branches in the dendrogram (Appendix A, part a). The three
clustered normal breast samples are highlighted in green. The
branches representing the four breast luminal epithelial cell lines
are displayed in pink; breast basal epithelial cell lines are
displayed in orange, the endothelial cell lines in blue, the
mesynchemal-like cell lines in dark green, and the
lymphocyte-derived cell lines in dark red.
[0301] As is evident from Appendix A, part a, application of the
clustering method to the samples and genes identified the two
members of each primary tumor/metastasis pair as being closely
related to one another based on similarity in gene expression. Thus
this method can provide information useful in determining whether a
tumor sample obtained from a second tumor is a metastasis
originating from a first tumor or is an independent primary tumor.
In addition, despite the potential confounding effects of an
interval of 16 weeks, independent surgical procedures and cytotoxic
chemotherapy, the independent samples taken from the same tumor
before and after chemotherapy were in most cases recognizably more
similar to each other in their overall pattern of gene expression
than either was to any of the other samples.
[0302] Closer examination of the five before and after pairs that
were not matched by the clustering algorithm provided further
insight. In three instances, the after chemotherapy specimens (i.e.
Norway 47, 61, and 101) were clustered into a branch of the
dendrogram that contained the three normal breast samples along
with five additional tumor samples; we know from the clinical data
that these three tumors were all classified as doxorubicin
responders (Table 5 and Aas, T., et al.). Thus, in most cases,
independent tumor biopsies from the same individual could be
recognized as such solely on the basis of gene expression patterns.
This implies that the patterns of gene expression are homogeneous
and stable in each breast tumor, and yet, sufficiently diverse
between tumors, so that they can be viewed as molecular portraits
of each tumor.
(ii) Specific Properties of the Tumors
[0303] The molecular portraits revealed in the patterns of gene
expression not only uncovered similarities and differences among
the tumors but, in many cases, pointed to a biological
interpretation. As discussed below, variation in growth rate, in
the activity of specific signaling pathways, and in the cellular
composition of the tumors were all reflected in corresponding
variations in the expression of specific subsets of genes.
[0304] Growth and Proliferation. The largest distinct subset of
genes among the 1753 genes presented in Appendix A was the
proliferation subset, illustrated in Appendix B, which is a group
of approximately 120 genes whose level of expression correlates
with cellular proliferation rates (See Perou, C., et al., 1999;
Ross, D., et al., Nature Genetics, 24 (3): 227-35, 2000.).
Expression of this subset of genes varied widely among the tumor
samples, and was generally well correlated with a standard
pathological index of tumor cell proliferation, namely the mitotic
index. The mitotic grade of each tumor, as determined by evaluating
mitotic index, is displayed in a color-coded format below the tumor
name, with green indicating mitotic grade 1, black indicating
mitotic grade 2, red indicating mitotic grade 3, and gray
indicating that mitotic grade was not evaluated. The growth and
proliferation cluster also included the genes encoding two widely
used immunohistochemical markers of cell proliferation (Ki-67 and
PCNA, names in blue/purple letters).
[0305] Diverse proliferation-related functions are represented in
the genes comprising this subset, including macromolecular
synthesis, cell-cycle regulation, mitosis and cytokinesis. Many
genes in which alterations in sequence or expression that are
associated with tumorigenesis were also found in this gene subset,
in particular, numerous genes implicated in chromosomal instability
and/or anueploidy (names in pink letters in Appendix B).sup.22.
These genes included the spindle checkpoint gene hBUB1.sup.23, the
human MAD2 homologue.sup.24, the STK15/IPL1 kinase.sup.25, and the
PLK1/HSTPK13 kinase.sup.26.
[0306] The importance of this clustered set of genes in cancer
biology is further highlighted by its inclusion of genes encoding
the molecular targets of widely used anticancer agents (names in
orange letters in Appendix B), including both subunits of
ribonucleotide reductase, topoisomerase II alpha, and dihydrofolate
reductase. The many uncharacterized genes in this subset,
therefore, are candidates for important roles in the regulation and
execution of the cell's program for growth and proliferation, and
potential targets for oncogenic mutations or antiproliferative
drugs. Thus the clustering method, by generating a set of genes
known to be involved in proliferation and/or known to be targets
for antiproliferative drugs and further identifying a set of
unknown genes whose expression patterns cause them to fall within
the subset, identifies potential targets for the development of new
chemotherapeutic agents.
[0307] Variation in signaling pathways. Several groups of
co-expressed genes provided views of the activities of specific
signaling and/or regulatory systems.
[0308] (a) Interferon signaling: A large subset of genes known to
be regulated by the interferon pathway (including STAT1) showed
substantial variation in expression among the tumors.
[0309] (b) Estrogen receptor: Variation in expression of the
estrogen receptor alpha gene (ESR1) correlated well with the direct
clinical measurement of the estrogen receptor protein levels in the
tumors (Table 5, concordance in 36/38 tumors tested), and
paralleled variation in the expression of a larger group of genes
that included three other transcription factors (GATA-binding
protein 3, X-box binding protein 1 and hepatocyte nuclear factor 3
alpha (see also references 27 and 28). In a specific subset of the
estrogen receptor positive tumors, the BCL2 gene and two previously
known estrogen regulated genes (LIV1 and trefoil factor 1.sup.29)
were also highly expressed (See Appendices C and D). The regulatory
program reflected in the expression of this ESR1-containing subset
of genes may play an important role in the clinical course of a
breast tumor, as the loss of expression of the estrogen receptor is
known to be associated with a poor prognosis.sup.17, while high
levels of expression of both BCL2 and ESR1 are associated with a
more favorable prognosis.sup.30,31.
[0310] (c) Erb-B2: HER2/neu, also known as the Erb-B2 oncogene, is
a gene whose aberrant expression is thought to contribute to
tumorigenesis in the breast.sup.16. The Erb-B2 receptor-tyrosine
kinase is known to be overexpressed in 20-30% of all breast tumors,
usually associated with DNA amplification of the chromosomal locus
(17q12-q22) that contains the ERB-B2 gene.sup.32,33. Interestingly,
most of the other genes contained within the Erb-B2 cluster were
also located in this same small region of Chromosome 17 (Appendix
C, part d and Appendix D). These expression data suggested, and the
results of microarray comparative genomic hybridization confirmed,
that these other closely linked genes were also amplified on the
genomic DNA level and, consequently, overexpressed on the mRNA
level in tumors with an amplified Erb-B2 gene.sup.33-35.
[0311] (d) Fos/Jun Signaling: A subset of genes that included
c-Fos, JunB, and other genes involved in the "immediate-early"
response to serum, co-varied in expression among the tumor
specimens (See Appendix D); these genes were most highly expressed
in the three normal breast samples. Applicants have found that this
set of genes is characteristically induced by prolonged handling of
the samples following surgical resection. The observed variation in
the expression of this set of genes may therefore reflect variation
in post surgical handling rather than true in vivo differences.
Example 7
Identification of Cell Type Specific Components Within Tumors Based
on Variation in Expression of 1753 Genes
Methods and Rationale
[0312] Clustering was performed as described in the previous
Example. The resulting dendrogram and matrix were used to identify
gene expression patterns indicative of the presence of certain cell
types within the samples. Human breast tumors are histologically
complex tissues, containing a variety of cell types in addition to
the carcinoma cells.sup.18. In analyzing the gene expression
patterns in tumors and tissues, two lines of reasoning were used to
infer the lineage of the cells that accounted for apparently
cell-type specific expression of particular clustered groups of
genes. First, such gene subsets usually included genes whose
expression patterns have been well characterized by previous
workers, and have consistently pointed to a specific cell type.
Second, these inferences were often corroborated by observing
comparable expression of the same group of genes in one or more of
the cultured cell lines (Appendix A and reference 21). Some of the
prominent patterns of gene expression that appear, on this basis,
to indicate the variable abundance of particular cell types in
these tissue samples are summarized below.
[0313] Immunohistochemistry was performed as described in Example
3.
Results
[0314] At least eight subsets of genes appeared to reflect
variation in specific cell types present within the tumors
(Appendices A and D). Appendix A, part b presents a scaled down
representation of the complete 1753 gene cluster diagram; the
colored bars to the right identify the locations of the inserts
displayed in 1c-j, each of which represents a portion of a gene
subset associated with one of the cell types/populations described
below.
[0315] The notion that developmental lineage has a pervasive
influence on gene expression patterns is highlighted by the
clustering pattern of the cultured cell lines in Appendix A. For
example, the three lymphocyte cell lines comprise one branch, the
two endothelial cell lines constitute another and the mesenchymal
cell lines form a third. Cell lines derived from two distinct types
of breast epithelial cells (basal and luminal) also formed distinct
dendrogram branches. Some of the prominent patterns of gene
expression that appear to indicate the variable abundance of
particular cell types within a tumor sample are summarized in the
remainder of this Example.
[0316] (a) Endothelial cells: A subset of genes characteristically
expressed by endothelial cells, including CD34, CD31 and von
Willebrand Factor.sup.36,37 were also strongly expressed in the two
endothelial cell lines HUVEC and HMVEC (Appendix A, part c).
Variation among the tumor samples in the abundance of transcripts
from this subset of genes may therefore reflect variation in the
vascularity or angiogenic activity within the tumors.
[0317] (b) Stromal cells: A previously characterized subset of
genes that included multiple isoforms of collagen and other genes
encoding extracellular matrix components, many of which are
characteristically expressed by mesenchymal cells, showed
significant variation in expression among the tumor samples
(Appendix A, part d).sup.8,21.
[0318] (c) Adipose-Enriched/Normal Breast: A subset of genes that
included fatty acid binding protein 4 and PPAR.quadrature. may
represent the presence of adipose cells in the tumor
samples.sup.38,39. This subset of genes was most highly expressed
in the three normal breast samples (Appendix A, part g). As we have
no cell line guide for this cluster, the exact nature of the cell
type underlying expression of these genes cannot be unequivocally
determined.
[0319] (d) B-lymphocytes: Variation in expression of a subset of
genes that were highly expressed in RPMI-8226 (a multiple
myeloma-derived cell line), including many immunoglobulin genes,
appears to represent variable B-cell infiltration of the tumors.
This interpretation was corroborated by immunohistochemistry
(Appendix A, part f).sup.8,21.
[0320] (e) T-lymphocytes: One subset of co-expressed genes included
CD3, and two subunits of the T-cell receptor (Appendix A, part i).
Most of the genes in this subset were expressed at their highest
levels in the T-cell leukemia derived cell line, MOLT-4. Variation
in expression of this subset of genes was therefore interpreted as
representing variation in T-lymphocyte populations in the tumors.
Immunohistochemical staining of tumor samples, using anti-CD3
antibodies, confirmed that tumors with the highest levels of
expression of this subset of genes contained numerous CD3-positive
lymphocytes (FIG. 3b).
[0321] (f) Macrophages: A subset of genes that appeared to be
markers of macrophage/monocyte populations included CD68, acid
phosphatase 5, chitinase, and lysozyme (Appendix A, part h).
Interestingly, the transcripts for these genes were the most
abundant in the three after chemotherapy tumor samples that
clustered apart from their before counterparts (i.e. Norway 47, 61,
and 101). These three tumors, all of which had responded to the
chemotherapy, were thus notable not only for an overall gene
expression pattern resembling that of normal breast tissue, but
also, for a particularly large population of macrophages, perhaps
representing a secondary response to tumor necrosis.
[0322] (g) Basal and Luminal Epithelial Cells of the Mammary Duct,
and Their Malignant Counterparts: Two distinct kinds of epithelial
cells are found in the adult human mammary gland, basal (and/or
myoepithelial cells) and luminal epithelial cells.sup.18,40. These
two cell types are conveniently distinguished
immunohistochemically; basal epithelial cells can be stained with
antibodies to keratin 5/6 (FIG. 3c), while luminal epithelial cells
stain with antibodies against keratins 8/18 (FIG. 3c). Many genes
were expressed by one of these two cell lines, but not by the other
(Appendix A, parts e, f, and j and Appendix D). The gene expression
subsets characteristic of basal epithelial cells included several
genes that have previously been shown to play important roles in
this cell type, e.g., keratin 5, keratin 17, integrin-.quadrature.4
and laminin (Appendix A, parts e and f).sup.18. The gene expression
subset characteristic of luminal cells was anchored by the
previously noted subset of transcription factors that included the
estrogen receptor gene (Appendix A, part j).
Example 8
Classification of Breast Tumors Using an Optimized Set of Genes
Showing Differential Expression Between Tumors
Methods and Rationale
[0323] As described in Examples 6 and 7, analysis of genes that are
differentially expressed in breast tumor samples provides an
indication of the relatedness of the samples and allows
identification of samples taken from the same tumor or members of a
tumor/metastasis pair. Such analysis further provides insight into
specific tumor properties such as variation in growth rate,
activity of specific signaling pathways, and the cellular
composition of the tumors. The subset of genes analyzed in Examples
6 and 7 was selected solely based upon the fact that genes in the
subset were differentially expressed among the experimental
samples. Recognizing that the choice of genes whose expression
levels provide the basis for the ordering of the tumor samples
determines which phenotypic relationships among the tumors are
reflected in the clustering patterns, applicants devised methods
for selecting subsets of genes optimized to reflect phenotypic
relationships among the tumors.
(i) Selection of an Intrinsic Gene Subset
[0324] The rationale behind the first optimized gene subset was
Applicants' recognition that specific features of a gene expression
pattern that are to be used as the basis for classifying tumors
should typify that tumor; that is, these features should be similar
in any sample taken from the same tumor, and they should vary among
different tumors. The 22 pairs of independent samples taken from 22
different tumors provided an opportunity for the selection of genes
that fulfill these criteria. To select a set of genes whose
variation in expression optimally represented differences between
tumors rather than just differences between tumor samples, a
"within-between" score was assigned to each gene equal to the mean
effect of the gene on the pairwise correlation coefficients of the
22 matched tumor pairs less the mean effect of the gene on the
remaining 210 tumor-tumor pairwise correlation coefficients. The
"effect" of a gene on a pairwise correlation was defined as the
difference in the correlation coefficient with and without data for
the gene included. Higher "within-between" scores indicated that
the gene had a good tendency to group together paired samples.
[0325] The 496 genes with a score one standard deviation above the
mean score were selected and defined as the "intrinsic" gene
subset. To confirm the existence of an "intrinsic" set of genes and
to verify that the "within-between" score identified these genes,
the predictive quality of the score was examined using a type of
"leave-one-out" cross-validation analysis. The entire analysis was
repeated 22 times, each with one of the 22 matched pairs completely
removed from the analysis. If an "intrinsic" set of genes existed,
and if the "within-between" score successfully identified these
genes, it was expected that the genes with high scores in each
reduced dataset would produce relatively high correlations in the
excluded pair. When the genes were sorted based on their
"within-between" score in each reduced dataset, the correlation
coefficient of the excluded matched pair in sliding windows of 250
genes increased progressively with increasing "within-between"
score for nearly all of the matched pairs, while no such increase
was found when randomly matched pairs were used.
[0326] The clustering method was used as described above to cluster
the experimental samples based on the gene expression patterns of
the 496 genes included in the "intrinsic" gene subset.
(ii) Selection of an "Epithelial-Enriched" Gene Subset
[0327] A second optimized gene subset (called the
"epithelial-enriched" gene subset) was selected consisting of 374
genes that Applicants considered likely to be expressed primarily
by normal or malignant breast epithelial cells. The rationale for
this gene subset is that each of the tumors was ultimately caused
by alterations in breast epithelial cells. The seven individual
subsets of genes that were chosen to form the "epithelial-enriched"
gene subset were selected from the 1753 gene cluster diagram
presented in Appendix B. The actual groups of genes chosen are
listed in Table 7. These seven subsets of genes included: [0328] 1)
A subset that was very highly expressed in the cultured basal cell
lines, along with some of the other breast derived cell lines
including Hs578T and BT-549; [0329] 2) A subset that was expressed
in all of the cultured epithelial cell lines (both basal and
luminal); [0330] 3) A subset of genes centered around the high
level of expression of Erb-B2; [0331] 4) A subset of genes that
contained genes known to be important for tumor biology (e.g., the
urokinase receptor); [0332] 5) A subset that contained genes that
were most highly expressed in the basal-like tumors; [0333] 6) A
subset of genes highly expressed in some of the luminal-like
tumors; [0334] 7) A subset of genes that was primarily expressed in
the four breast carcinoma derived cell lines and/or in many of the
luminal-like tumors.
[0335] The clustering method was used as described above to cluster
the experimental samples based on the gene expression patterns of
the 374 genes included in the "epithelial-enriched" gene set.
[0336] To confirm the results of the clustering analysis described
below, a "weighted voting" method was applied to the data as
described in Golub, T. R., et al., Science, 286, 531-537, 1999.
Results
[0337] The 496 genes included in the "intrinsic" gene set are
identified in Table 6, and Appendix D shows the complete 496 gene
cluster diagram formed using the "intrinsic" gene set. Appendix C
presents details of the results of cluster analysis using the
"intrinsic" gene set. Two large branches were apparent in the tumor
dendrogram, and within each of these two branches, smaller branches
were identified for which common biological themes could be
inferred. The branches are colored accordingly (basal-like=ORANGE,
Erb-B2 positive=PINK, normal breast-like=GREEN, and luminal
epithelial-like=BLUE). Appendix C, part a shows the cluster
dendrogram obtained by hierarchical clustering of the experimental
samples based on similarities in expression of the intrinsic gene
set. As is evident from this dendrogram, 17 of the 20 before and
after doxorubicin pairs (indicated with suffixes BE and AF
following the numerical identifier for each tumor) were matched
together on terminal dendrogram branches (red branches), as were
both of the tumor/lymph node metastasis pairs (blue branches). The
small black bars beneath the dendrogram identify the 17 pairs that
were correctly matched by this hierarchical clustering, while the
larger green bars identify the positions of the three pairs that
were not matched by the clustering. It is noted that the
after-chemotherapy sample in each of these three sample pairs was
clustered in a branch with normal breast tissue samples. Thus as
for the 1753 gene set described in Examples 6 and 7, the intrinsic
gene subset correctly identified independent tumor samples from the
same tumor as related to each other. Despite the potential
confounding effects of an interval of 16 weeks, independent
surgical procedures and cytotoxic chemotherapy, the independent
samples taken from the same tumor were in most cases recognizably
more similar to each other in their overall pattern of gene
expression than either was to any of the other samples. In
addition, samples taken from a primary tumor and a metastasis from
the same tumor could be recognized as closely related to one
another. Thus in most cases independent samples from the same tumor
were recognizable as such solely on the basis of gene expression
patterns. This implies that the patterns of gene expression are
homogeneous and stable in each breast tumor and yet sufficiently
diverse between tumors so that they can be viewed as molecular
portraits of each tumor.
[0338] Appendix C, part b shows a scaled-down representation of the
entire "intrinsic" cluster diagram (the complete "intrinsic"
cluster diagram, with all gene names is presented in Appendix E).
Appendix C, part c shows the luminal epithelial cell gene subset,
including the estrogen receptor. Appendix C, part d shows the
Erb-B2 overexpression subset. Appendix C, part e shows the basal
epithelial cell-associated gene subset, including keratins 5 and
17, while Appendix C, part f shows a second basal epithelial
cell-associated gene subset. Appendix C, part g shows the
lymphocyte/B-cell-associated gene subset. The 374 genes included in
the "epithelial-enriched" subset are listed in Table 8, and the
complete 374 gene cluster diagram formed when using the
"epithelial-enriched" gene set is shown in Appendix F.
[0339] FIG. 2 presents a comparison of tumor dendrograms
representing the results of hierarchical clustering of experimental
samples using the "intrinsic" gene set (Appendix E) and the
dendrogram obtained by clustering using the "epithelial-enriched"
gene set (Appendix F). The dendrograms are colored according to the
clustering patterns obtained using the "intrinsic" gene set. Only
two tumors (identified by the colored arrows) were placed in
significantly different groups when the clustering was based on
expression of the "epithelial-enriched" gene set instead of the
"intrinsic" gene set.
[0340] The overall architecture of the two dendrograms representing
the clustering of breast tumor samples using these two alternative
gene sets was very similar, with only two tumor pairs (i.e. Norway
14 and 26) materially changing position (FIG. 2). Thus, the
classifications derived from the "intrinsic" gene set are
consistent with the results using the "epithelial-enriched" gene
set, even though the two sets shared only 25% of their genes.
[0341] A consistent division of the tumor samples into two
subgroups was a striking feature of the dendrograms produced by
both gene sets. Application of the "weighted voting" method of
Golub recapitulated the sorting of the tissue samples between these
two subgroups for all but one of the 65 samples, thus confirming
the robustness of the division.
Example 9
Identification of Breast Tumor Subgroups Based on Optimized Gene
Sets
[0342] Several groups of tumors that shared pervasive similarities
in their expression patterns could be identified by cluster
analysis; the dendrograms in FIG. 2 and Appendices A, C, and D are
color-coded to highlight these subgroups. Characteristic features
of the expression patterns, or the membership, of each highlighted
group also suggested biological interpretations. These data confirm
the ability of the clustering method to divide breast tumors into
meaningful subgroups when applied using the "intrinsic" and
"epithelial-enriched" gene subsets. Specific subgroups are
discussed below and are named according to correlations between the
genes expressed at high levels in the tumors and genes known to be
expressed in particular cell types.
[0343] Luminal Epithelial Cell Pattern: As described above, the
major distinction was between a large group of tumors (identified
by blue letters and dendrogram branches) and a second large group
that included all of the other tumor subtypes and the normal breast
samples (highlighted in other colors). The tumors in this "blue"
group were characterized by relatively high levels of expression of
many genes known to be expressed by the luminal epithelial cells of
the normal mammary duct, notably including the estrogen and
prolactin receptors (Appendix C, part c). This connection was
further corroborated using immunohistochemical analysis of breast
tumor sections using antibodies against the luminal cell keratins
8/18, which stained the carcinoma cells in tumor specimens in this
"blue" branch as shown, for example, in FIG. 3f. With one
exception, none of the tumors in this group expressed Erb-B2 at
high levels (Appendix C, part d). An estrogen receptor-positive
phenotype is known to be associated with a relatively favorable
prognosis.sup.30, 31, while Erb-B2 expression is believed to
contribute to tumorogenesis.
[0344] Normal Breast Tissue Pattern: Several tumors, including two
"before and after" pairs and the single fibroadenoma tested
(displayed in green), were clustered in a group of samples that
contained all three of the normal breast specimens (Appendices C
and E). The "normal breast" gene expression pattern was typified by
a relatively high level of expression of genes characteristic of
basal epithelial cells and adipose cells, and relatively low levels
of expression of genes characteristic of luminal epithelial
cells.
[0345] Basal Epithelial Cell Pattern: Many of the genes
characteristic of basal epithelial cells were highly expressed in a
group of six tumors (New York 2 and 3, Stanford 14 and 23, and
Norway 41 and 109, indicated in orange in the dendrogram in
Appendix C, part a), that were clustered based on pervasive
similarities in their gene expression patterns (Appendices C and
E). To corroborate the "basal cell-like" characteristics of these
tumors, immunohistochemistry was performed using antibodies against
keratins 5/6, 8/18, and 17. All six of these tumors showed staining
for either keratins 5/6 and/or 17 (basal cell keratins), and no
staining for keratins 8/18 (See FIG. 3e.) Notably, these six tumors
also failed to express the estrogen receptor and most of the other
genes that were usually co-expressed with it (Appendix C, part c).
Approximately 90% of breast tumors are suggested to have
characteristics of luminal epithelial cells, while the
characteristics of the remaining 10% are less well defined.sup.18.
Breast tumors that stain positive for basal cell keratins may
account for 3-15% of all breast tumors.sup.41-46.
[0346] The incidence among the tumor samples described herein was
15% (6/40). Many of the tumors that stained positive for basal cell
keratins only showed staining in a fraction of the tumor cells, and
neither basal nor luminal keratins could be detected in any of the
other remaining tumor cells (FIG. 3e).
[0347] Erb-B2 Positive: As mentioned above, overexpression of the
Erb-B2 oncogene was associated with a high level of expression of a
specific set of genes, almost all of which map to the Erb-B2 region
of chromosome 17.sup.33. A clustered group of tumors was identified
that was partially characterized by the high level of expression of
this subset of genes (Appendix C, part d: Stanford 2 and Norway 47,
53, 57 and 101, indicated in pink on the dendrogram in Appendix C,
part a). These tumors showed low levels of expression of the
estrogen receptor.sup.48,49 and almost all of the other genes
associated with estrogen receptor expression (Appendix C, part c),
a trait they share with the "basal-like" tumors, and which may
contribute to the poor prognosis associated with these two subtypes
of breast tumors.sup.41,43,49,50; in addition, both the basal-like
and Erb-B2 positive tumors also show many p53 sequence mutations
(see Table 5).
Example 10
Producing Antibodies to Basal Marker Polypeptides and Cytokeratin
17
[0348] This example describes the generation of polyclonal
antibodies that bind to cytokeratin 17 and the generation of
polyclonal antibodies that bind to the polypeptides encoded by the
three basal marker genes described herein, i.e., cadherin3, matrix
metalloproteinase 14, and cadherin EGF LAG seven-pass G-type
receptor 2. The example further describes affinity purification of
the antibodies.
Materials
[0349] Anisole (Cat. No. A4405, Sigma) [0350]
2,2'-azino-di-(3-ethyl-benzthiazoline-sulfonic acid) (ABTS) (Cat.
No. A6499, Molecular Probes Eugene, Oreg.) [0351] Activated
Maleimide Keyhole Limpet Cyanin (Cat. No. 77106, Pierce Chemical
Co. Rockford, Ill.) [0352] Biotin (Cat. No. B2643, Sigma) [0353]
Boric acid (Cat. No. B0252, Sigma) [0354] Sepharose 4b (Cat. No.
17-0120-01, LKB/Pharmacia, Uppsala, Sweden) [0355] Bovine Serum
Albumin (LP) (Cat. No. 100 350, Boehringer Mannheim, Indianapolis,
Ind.) [0356] Cyanogen bromide (Cat. No. C6388 Sigma, St. Louis,
Mo.) [0357] Dialysis tubing Spectra/Por Membrane MWCO: 6-8,000
(Cat. No. 132 665, Spectrum Industries Inc., Laguna Hills, Calif.)
[0358] Dimethyl formamide (DMF) (Cat. No. 22705-6, Aldrich Chemical
Company, Milwaukee, Wis.) [0359] DIC (Cat. No. BP 592-500, Fisher)
[0360] Ethanedithiol (Cat. No. 39,802-0, Aldrich Chemicals,
Milwaukee, Wis.) [0361] Ether (Cat. No. TX 1275-3, EM Sciences)
[0362] Ethylenediaminetetraacetatic acid (EDTA)(Cat No. BP 120-1,
Fisher Scientific, Springfield, N.J.) [0363]
1-ethyl-3-(3'dimethylaminopropyl)-carbodiimide, HCL (EDC) (Cat No.
341-006, Calbiochem, San Diego, Calif.) [0364] Freund's Adjuvant,
complete (Cat. No. M-0638-50B, Lee Laboratories, Grayson, Ga.)
[0365] Freund's Adjuvant, incomplete (Cat. No. M0639-50B, Lee
Laboratories) [0366] Fritted chromatography columns (Column part
No. 12131011; Frit: Part No. 12131029, Varian Sample Preparation
Products, Harbor City, Calif.) [0367] Gelatin from Bovine Skin
(Cat. No. G9382, Sigma) [0368] Glycine (Cat. No. BP381-5, Fisher)
[0369] Goat anti-rabbit IgG, biotinylated (Cat No. A 0418, Sigma)
[0370] HOBt (Cat. No. 01-62-0008, Calbiochem-Novabiochem) [0371]
Horseradish peroxidase (HRP) (Cat. No. 814 393, Boehringer
Mannheim) [0372] HRP-Streptavidin (Cat. No. S 5512, Sigma) [0373]
Hydrochloric Acid (Cat No. 71445-500, Fisher) [0374] Hydrogen
Peroxide 30% w/w (Cat. No. H1009, Sigma) [0375] Methanol (Cat. No.
A412-20, Fisher) [0376] Microtiter plates, 96 well (Cat. No. 2595,
Corning-Costar Pleasanton, Calif.) [0377] N-.quadrature.-Fmoc
protected amino acids available from Calbiochem-Novabiochem, San
Diego, Calif. See 1997-1998 catalog pages 1-45. [0378]
N-.quadrature.-Fmoc protected amino acids attached to Wang Resin
available from Calbiochem-Novabiochem. See 1997-1998 catalog pages
161-164. [0379] NMP (Cat. No. CAS 872-50-4, Burdick and Jackson,
Muskegon, Mich.) [0380] Peptide (Synthesized by Research Genetics,
Inc. Details given below) [0381] Piperidine (Cat. No. 80640, Fluka,
available through Sigma) [0382] Sodium Bicarbonate (Cat. No.
BP328-1, Fisher) [0383] Sodium Borate (Cat. No. B9876, Sigma)
[0384] Sodium Carbonate (Cat. No. BP357-1, Fisher) [0385] Sodium
Chloride (Cat. No. BP 358-10, Fisher) [0386] Sodium Hydroxide (Cat.
No. SS 255-1, Fisher) [0387] Streptavidin (Cat. No. 1 520,
Boehringer Mannheim) [0388] Thioanisole (Cat. No. T-2765, Sigma)
[0389] Trifluoroacetic acid (Cat. No. TX 1275-3, EM Sciences)
[0390] Tween-20 (Cat. No. BP 337-500, Fisher) [0391]
Wetbox-(Rubbermaid Rectangular Servin' Saver.TM. Part No. 3862
Wooster, Ohio) Solutions [0392] BBS--Borate Buffered Saline with
EDTA dissolved in distilled water (pH 8.2 to 8.4 with HCl or NaOH)
[0393] 25 mM Sodium borate (Borax) [0394] 100 mM Boric Acid [0395]
75 mM NaCl [0396] 5 mM EDTA [0397] 0.1 N HCl in saline [0398]
concentrated HCl (8.3 mL/0.917 L distilled water) [0399] 0.154 M
NaCl [0400] Glycine (pH 2.0 and pH 3.0) dissolved in distilled
water and adjusted to the desired pH. [0401] 0.1 M glycine [0402]
0.154 M NaCl [0403] 5.times. Borate 1.times. Sodium Chloride
dissolved in distilled water. [0404] 0.11 M NaCl [0405] 60 mM
Sodium Borate [0406] 250 mM Boric Acid [0407] Substrate Buffer in
distilled water adjusted to pH 4.0 with sodium hydroxide: [0408] 50
to 100 mM Citric Acid Peptide Synthesis Solutions [0409] AA
solution: HOBt is dissolved in NMP (8.8 grams HOBt to 1 liter NMP).
Fmoc-N-a-amino at a concentration at 0.53 M. [0410] DIC solution: 1
part DIC to 3 parts NMP. [0411] Deprotecting solution: 1 part
Piperidine to 3 parts DMF [0412] Reagent R: 2 parts anisole, 3
parts ethanedithiol, 5 parts thioanisole, 90 parts trifluoroacetic
acid. Equipment [0413] MRX Plate Reader (Dynatech Inc., Chantilly,
Va.) [0414] Hamilton Eclipse (Hamilton Instruments, Reno, Nev.)
[0415] Beckman TJ-6 Centrifuge, Refrigerated (Model No. TJ-6,
Beckman Instruments, Fullerton, Calif.) [0416] Chart Recorder
(Recorder 1 Part No. 18-1001-40, Pharmacia LKB Biotechnology)
[0417] UV Monitor (Uvicord SII Part No. 18-1004-50, Pharmacia LKB
Biotechnology) [0418] Amicon Stirred Cell Concentrator (Model 8400,
Amicon Inc., Beverly, Mass.) [0419] 30 kD MW cut-off filter (Cat.
No. YM-30 Membranes Cat. No. 13742, Amicon Inc., Beverly, Mass.)
[0420] Multi-channel Automated Pipettor (Cat. No. 4880, Corning
Costar Inc., Cambridge, Mass.) [0421] pH Meter Corning 240 (Corning
Science Products, Corning Glassworks, Corning, N.Y.) [0422] ACT396
peptide synthesizer (Advanced ChemTech, Louisville, Ky.) [0423]
Vacuum dryer (Box is from Labconco, Kansas City, Mo.; Pump is from
Alcatel, Laurel Md.). [0424] Lyophilizer (Unitop 600sl in tandem
with Freezemobile 12, both from Virtis, Gardiner, N.Y.) Methods
[0425] Peptides were selected using the program Omiga.TM. 1.1
(Oxford Molecular Group, Inc., 2105 So. Bascom Ave., Suite 200,
Campbell, Calif. 95008) using the Hopp/Woods method, which is
described in Hopp T P, Woods K R, Mol Immunol, April; 20 (4):483-9
A computer program for predicting protein antigenic determinants,
1983, and Hopp T P and Woods K R, Proc. Nat. Acad. Sci. U.S.A. 78,
3824-3828, 1981. Preferred peptide sequences displayed minimal
homology with known proteins. Three peptide sequences were selected
for each polypeptide. The sequences were as follows:
[0426] Peptides for antibodies that bind to cadherin3 (GenBank
accession number NP.sub.--001784): TABLE-US-00001
RAVFREAEVTLEAGGAEQE (SEQ ID NO: 4) QEPALFSTDNDDFTVRN (SEQ ID NO: 5)
QKYEAHVPENAVGHE (SEQ ID NO: 6)
[0427] Peptides for antibodies that bind to matrix
metalloproteinase 14 (GenBank accession number NP.sub.--004986):
TABLE-US-00002 AYIREGHEKQADIMIFFAE (SEQ ID NO: 7)
DEASLEPGYPKHIKELGR (SEQ ID NO: 8) RGSFMGSDEVFTYFYK (SEQ ID NO:
9)
[0428] Peptides for antibodies that bind to anti-cadherin EGF LAG
seven-pass G-type receptor 2 (GenBank accession number
NP.sub.--001399): TABLE-US-00003 QASSLRLEPGRANDGDWH (SEQ ID NO: 10)
ELKGFAERLQRNESGLDSGR (SEQ ID NO: 11) RSGKSQPSYIPFLLREE (SEQ ID NO:
12)
[0429] Peptides for antibodies that bind to anti-cytokeratin17:
TABLE-US-00004 KKEPVTTRQVRTIVEE (SEQ ID NO: 13) QDGKVISSREQVHQTTR
(SEQ ID NO: 14) SSSIKGSSGLGGGSS (SEQ ID NO: 15)
Synthesis of Peptides
[0430] Incubate: Resin was immersed in appropriate solution. All
incubation steps occured with mixing.
[0431] Wash: Added 2 mls. DMF, incubated 5 minutes and drained.
[0432] Wash Cycle: Five washes.
Machine Synthesis
[0433] The sequence of the desired peptide was provided to the
peptide synthesizer. The C-terminal residue was determined and the
appropriate Wang Resin was attached to the reaction vessel. The
peptides were synthesized C-terminus to N-terminus by adding one
amino acid at a time using a synthesis cycle. Which amino acid is
added was controlled by the peptide synthesizer, which looks to
sequence of the peptide entered into its database. [0434] Step
1--Resin Swelling: Added 2 mL DMF, incubated 30 minutes, drained
DMF. [0435] Step 2--Synthesis cycle [0436] 2a--Deprotection: 1 mL
deprotecting solution was added to the reaction vessel and
incubated for 20 minutes. [0437] 2b--Wash Cycle [0438]
2c--Coupling: 750 mL of amino acid solution and 250 mL of DIC
solution were added to the reaction vessel. The reaction vessel was
incubated for thirty minutes and washed once. The coupling step was
repeated once. [0439] 2d--Wash Cycle [0440] Step 2 was repeated
over the length of the peptide. The amino acid solution changed as
the sequence listed in peptide synthesizer dictated. [0441] Step
3--Final Deprotection: Steps 2a and 2b were performed one last
time.
[0442] Resins were deswelled in methanol--rinsed twice in 5 mL
methanol, incubated 5 minutes in 5 mL methanol, rinsed in 5 mL
methanol--and then vacuum dried.
[0443] Peptide was removed from the resin by incubating 2 hours in
reagent R and then precipitated into ether. Peptide was washed in
ether and then vacuum dried. Peptide was resolubilized in diH2O,
frozen, and lyophilized overnight.
Conjugation of Peptide with Keyhole Limpet Hemocyanin
[0444] Peptide (6 mg) was dissolved in PBS (6 mL) and mixed with 6
mg of maleiimide activated KLH carrier in 6 mL of PBS for a total
volume of 12 mL. The entire solution was mixed for two hours,
dialyzed in IL PBS, and lyophilized.
Immunization of Rabbits
[0445] Two New Zealand White Rabbits were injected with 250 .mu.g
keyhole limpet hemocyanin (KLH) conjugated peptide in an equal
volume of complete Freund's adjuvant and saline in a total volume
of 1 mL. Antigens (KLH-Peptide, 100 .mu.g each) in an equal volume
of incomplete Freund's Adjuvant and saline were injected into three
to four subcutaneous dorsal sites for a total volume of 1 mL two,
four, and six weeks after the first immunization. The three
peptides were injected together.
[0446] The immunization schedule was as follows: TABLE-US-00005 Day
0 Pre-immune bleed, primary immunization Day 15 1st Boost Day 27
1st Bleed Day 44 2nd Boost Day 57 2nd Bleed and 3rd Boost Day 69
3rd Bleed Day 84 4th boost Day 98 4th bleed
The Collection of Rabbit Serum
[0447] The rabbits were bled (30 to 50 mL) from the auricular
artery. The blood was allowed to clot at room temperature for 15
minutes and the serum was separated from the clot using an IEC
DPR-6000 centrifuge at 5000.times.g. Cell-free serum was decanted
gently into a clean test tube and stored at -20.degree. C. for
affinity purification.
Determination of Antibody Titer
[0448] All solutions with the exception of wash solution were added
by the Hamilton Eclipse, a liquid handling dispenser. The antibody
titer was determined in the rabbits using an ELISA assay with
peptide on the solid phase. Flexible high binding ELISA plates were
passively coated with peptide diluted in BBS (100 .mu.L, 1
.mu.g/well) and the plate was incubated at 4.degree. C. in a wetbox
overnight (air-tight container with moistened cotton balls). The
plates were emptied and then washed three times with BBS containing
0.1% Tween-20 (BBS-TW) by repeated filling and emptying using a
semi-automated plate washer. The plates were blocked by completely
filling each well with BBS-TW containing 1% BSA and 0.1% gelatin
(BBS-TW-BG) and incubating for 2 hours at room temperature. The
plates were emptied and sera of both pre- and post-immune serum
were added to wells. The first well contained sera at 1:50 in BBS.
The sera were then serially titrated eleven more times across the
plate at a ratio of 1:1 for a final (twelfth) dilution of
1:204,800. The plates were incubated overnight at 4.degree. C. The
plates were emptied and washed three times as described.
[0449] Biotinylated goat anti-rabbit IgG (100 .mu.L) was added to
each microtiter plate test well and incubated for four hours at
room temperature. The plates were emptied and washed three times.
Horseradish peroxidase-conjugated Streptavidin (100 .mu.L diluted
1:10,000 in BBS-TW-BG) was added to each well and incubated for two
hours at room temperature. The plates were emptied and washed three
times. The ABTS was prepared fresh from stock by combining 10 mL of
citrate buffer (0.1 M at pH 4.0), 0.2 mL of the stock solution (15
mg/mL in water) and 10 .mu.L of 30% H.sub.2O.sub.2. The ABTS
solution (100 .mu.L) was added to each well and incubated at room
temperature. The plates were read at 414.times., 20 minutes
following the addition of substrate.
Preparation of the Peptide Affinity Purification Column:
[0450] The affinity column was prepared by conjugating 5 mg of
peptide to 10 mL of cyanogen bromide-activated Sepharose 4B, and 5
mg of peptide to hydrazine-Sepharose 4B. Briefly, 100 uL of DMF was
added to peptide (5 mg) and the mixture was vortexed until the
contents were completely wetted. Water was then added (900 .mu.L)
and the contents were vortexed until the peptide dissolved. Half of
the dissolved peptide (500 .mu.L) was added to separate tubes
containing 10 mL of cyanogen-bromide activated sepharose 4B in 0.1
mL of borate buffered saline at pH 8.4 (BBS), and 10 mL of
hydrazine-Sepharose 4B in 0.1 M carbonate buffer adjusted to pH 4.5
using excess EDC in citrate buffer pH 6.0. The conjugation
reactions were allowed to proceed overnight at room temperature.
The conjugated sepharose was pooled and loaded onto fritted
columns, washed with 10 mL of BBS, blocked with 10 mL of 1 M
glycine, and washed with 10 mL 0.1 M glycine adjusted to pH 2.5
with HCl and re-neutralized in BBS. The column was washed with
enough volume for the optical density at 280% to reach
baseline.
The Affinity Purification of Antibodies
[0451] The peptide affinity column was attached to a UV monitor and
chart recorder.
[0452] The titered rabbit antiserum was thawed and pooled. The
serum was diluted with one volume of BBS and allowed to flow
through the columns at 10 mL per minute. The non-peptide
immunoglobulins and other proteins were washed from the column with
excess BBS until the optical density at 280 .lamda. reached
baseline. The columns were disconnected and the affinity purified
column was eluted using a stepwise pH gradient from pH 7.0 to pH
1.0. The elution was monitored at 280 nM, and fractions containing
antibody (pH 3.0 to pH 1.0) were collected directly into excess 0.5
M BBS. Excess buffer (0.5 M BBS) in the collection tubes served to
neutralize the antibodies collected in the acidic fractions of the
pH gradient.
[0453] The entire procedure was repeated with "depleted" serum to
ensure maximal recovery of antibodies. The eluted material was
concentrated using a stirred cell apparatus and a membrane with a
molecular weight cutoff of 30 kD. The concentration of the final
preparation was determined using an optical density reading at 280
nM. The concentration was determined using the following formula:
mg/mL=OD.sub.280/1.4.
Example 11
SDS-PAGE and Immunoblot Analysis of Basal Marker Polypeptides
[0454] To investigate the expression pattern of cadherin3, matrix
metalloproteinase 14, and cadherin EGF LAG seven-pass G-type
receptor 2, extracts were made from a variety of different cell
lines and subjected to SDS-PAGE followed by immunoblotting
according to the protocol below, using affinity purified polyclonal
antibody to BSTP-ECG1 prepared as described in Example 10.
Materials
[0455] Acetic acid, Glacial (Cat. No. A38.sup.c-212, Fisher) [0456]
Acrylamide (Cat. No. A-3553, Sigma) [0457] Anti-Rabbit IgG
(H&L) (Cat. No. 31460ZZ, Pierce) [0458] Bis-acrylamide (Cat.
No. M-7279, Sigma) [0459] Blotting paper (Cat. No. 170-3960,
Bio-Rad, Hercules, Calif.) [0460] Bovine Serum Albumin (LP) (Cat.
No. 100-350, Boehringer Mannheim, Indianapolis, Ind.) [0461]
Brilliant Blue R-250 (Cat. No. BP101-25, Fisher) [0462]
Complete.TM. Mini (Cat. No. 1836153, Boehringer Mannheim) [0463]
ECL Western Blotting Detection Reagents (Cat. No. RPN2109, Amersham
Pharmacia Biotech, Piscataway, N.J.) [0464] Ethyl alcohol (AAPER
Alcohol and Paper Chemical Co., Shelbyville, Ky.) [0465] Gelplate
Clean (Cat. No. 786-140RF, Geno Technology, Inc., St. Louis) [0466]
Gelatin (Cat. No. G-2500, Sigma) [0467] Glycerol (Cat. No. BP229-1,
Fisher) [0468] Glycine (Cat. No. G-8898, Sigma) [0469] Hybond ECL
(Cat. No. RPN303D, Amersham Pharmacia Biotech) [0470] Lauryl
Sulfate (SDS) (Cat. No. L-3771, Sigma) [0471] Methanol (Cat. No.
BP1105-4, Fisher) [0472] M-Per (Cat. No. 78501, Pierce, Rockford,
Ill.) [0473] Nalgene bottle top filters (Cat. No. 09-740-62B,
Fisher) [0474] Nonfat dry milk (Kroger Co., Cincinnati, Ohio)
[0475] Ponceau-S (Cat. No. P-07170, Sigma) [0476] Potassium
phosphate (Cat. No. P-0662, Sigma) [0477] 2.times. SDS gel loading
buffer (Cat. No. 750006, Research Genetics, Huntsville, Ala.)
[0478] Size markers (Cat. No. M-3913, M-4038, M-3788, Sigma) [0479]
Sodium azide (Cat. No. S2271-25, Fish) [0480] Sodium chloride (Cat.
No. S271-3, Fisher) [0481] Sodium phosphate, Dibasic, Anhydrous
(Cat. No. BP332-1, Fisher) [0482] t-amyl alcohol (Cat. No. A-16852,
Sigma) [0483] TEMED (Cat. No. T-9281, Sigma) [0484] Trizma.RTM.
Base (Cat. No. T-6066, Sigma) [0485] Tween-20 (Cat. No. BP337-500,
Fisher) Solutions [0486] PBS--Phosphate Buffered Saline dissolved
in distilled water [0487] 136 mM NaCl [0488] 2.7 mM KCl [0489] 10.1
mM Na.sub.2HPO.sub.4 [0490] 1.8 mM KH.sub.2PO.sub.4 [0491]
Acrylamide/Bis (30% T, 2.67% C) dissolved in distilled water [0492]
4.1 M acrylamide [0493] 51.9 mM N,N'- [0494] 1.5 M Tris-HCl (pH
8.8) dissolved in distilled water [0495] 0.5 M Tris-HCl (pH 6.8)
dissolved in distilled water [0496] 10% SDS--dissolve 10 grams SDS
in 100 mls distilled water [0497] Running Buffer [0498] 24.8 mM
Tris base [0499] 191.9 mM glycine [0500] 3.5 mM SDS [0501] Towbin
transfer buffer (pH 8.3) dissolved in distilled water [0502] 20%
methanol [0503] 25 mM Tris [0504] 192 mM glycine [0505]
Equilibrating buffer for gel drying, mixed in distilled water
[0506] 20% ethanol [0507] 10% glycerol [0508] Gel staining solution
dissolved in distilled water [0509] 0.3 mM Coomassie brilliant blue
R-250- [0510] 40% methanol [0511] 7% glacial acetic acid [0512] Gel
destaining solution mixed in distilled water [0513] 25% methanol
[0514] 7% glacial acetic acid [0515] 10% Tween.RTM.20 in PBS [0516]
5% Nonfat dry milk in PBS [0517] 0.2% BSA Blocking Buffer dissolved
in PBS [0518] 0.2% BSA [0519] 0.1% gelatin [0520] 0.05%
Tween.RTM.20 [0521] Wash Buffer [0522] 0.05% Tween.RTM.20 [0523]
1.times. PBS Equipment [0524] Microcentrifuge (Model 5415,
Eppendorf) [0525] Power Pak 200 (Cat. No. 165-5052, Bio-Rad) [0526]
Power Pak 3000 (Cat. No. 165-5056, Bio-Rad) [0527] Protean II xi
Cell (Cat. No. 165-1813, Bio-Rad) [0528] Recirculating chiller
(Cat. No. CFT33D115V, Neslab Instruments, Inc., Portsmouth, N.H.)
[0529] 20-Well comb (Cat. No. 165-1867, Bio-Rad) [0530] pH Meter
Corning 240 (Corning Science Products, Corning Glasswares, Corning,
N.Y.) [0531] Air Cadet vacuum pump (Cat. No. P-07530-50,
Cole-Palmer Instruments Co., Chicago, Ill.) [0532] Tissue Tearor
tissue homogenizer (Cat. No. 985370-07, BioSpec Products Inc.,
Bartletsville, Okla.) Methods Sample Preparation
[0533] The following cell lines were used: 184B5, MCF7, OVCAR3,
UACC62, HepG2, Colo205, UACC62, JURKAT, N-TERA2, MOLT4, Sw872.
These cell lines are well known in the art. Descriptions of these
cell lines are provided in Table 3, in Perou, et al., Molecular
portraits of human breast tumours, Nature, 406 (6797):747-52, 2000,
in Ross, D. T. et al. Systematic Variation in Gene Expression
Patterns in Human Cancer Cell Lines. Nature Genetics, 24
(3):227-35, 2000, and at the American Type Culture Collection Web
site: www.atcc.org. Cell lines were maintained under standard
growth conditions and in standard tissue culture media as
appropriate for the particular cell line. Cells were collected
according to standard techniques (e.g., trypsinization in the case
of adherent cells), and the resulting cell suspension was prepared
as follows: [0534] The cell suspension was pelleted by
centrifugation at 3000 RPM for 10 minutes, and the supernatant was
discarded. [0535] The pellet was washed with 1 ml PBS, centrifuged
at 10000 RPM for 10 minutes, and the supernatant was discarded.
[0536] An appropriate volume of M-Per.TM. Reagent was added to the
cell pellet and mixed gently for 10 minutes in an ice bath. The
mixture was centrifuged at 13200 RPM for 15 minutes, and the
supernatant was saved.
[0537] The protein concentration in the supernatant was measured
according to standard techniques. All samples were mixed at 1:1
with gel loading buffer and boiled for 5 minutes before
loading.
SDS PAGE
[0538] Standard SDS-PAGE stacking and running gels were prepared
and placed in an electrophoresis apparatus. After filling the upper
and lower chambers with running buffers the samples (60
.quadrature.g/lane) were loaded. The inner core was placed in the
lower chamber and the lid placed on top. The apparatus was
connected to the power supply and recirculating system. The
temperature setting was 10.degree. C. The stacking gel was run at
14 mA per gel for 1 hour. The separating gel was run at 0.58 mA per
gel per hour for 16 hours.
Transfer to Nitrocellulose
[0539] After electrophoresis was complete, the gel was equilibrated
in Towbin Buffer for 15-30 minutes. The assembly for transfer was
as follows: [0540] cathode [0541] pre-soaked blotting paper [0542]
gel [0543] pre-wetted nitrocellulose [0544] pre-soaked blotting
paper [0545] anode
[0546] The transfer was performed at 20V for 25 minutes, then 25V
for 20 minutes. After the transfer was complete, the gel was
stained with Coomassie and the blot was stained with Ponceau-S.
Western Blotting
Primary and Secondary Antibodies
[0547] All primary and secondary antibodies were diluted in 0.2%
BSA blocking buffer. All incubation steps were done with gentle
mixing.
[0548] Blots were blocked in 5% milk overnight at room temperature.
The blots were rinsed with wash buffer before adding the primary
antibody and incubating for two hours at room temperature.
[0549] The primary antibodies were used at titers of 1:200, 1:500,
and 1:1000 for anti-matrix metalloproteinase 14 and anti-cadherin
EGF LAG seven-pass G-type receptor 2 and at 1:100 for
anti-cadherin3.
[0550] One wash cycle was performed. One wash cycle consisted of:
[0551] Wash 5 min, rinse [0552] Wash 5 min, rinse [0553] Wash 10
min, rinse [0554] Wash 5 min, rinse [0555] Wash 5 min, rinse
[0556] The secondary antibody was added and incubated for one hour
at room temperature. One wash cycle was then performed.
Peptide Block
[0557] As a control to demonstrate the specificity of the antibody,
in some experiments equal amounts (w/w) of peptide and antibody
were added to 1/10 of the final volume of blocking buffer and
incubated overnight at 4.degree. C. The volume of blocking buffer
was then brought up to the final volume, and the membrane was
incubated for an additional two hours at room temperature.
Developing
[0558] The blots were placed in a Ziploc.RTM. bag. Equal volumes of
ECL western blotting detection reagents were mixed and distributed
evenly over the blots. The blots were placed in an autoradiography
cassette, covered with a piece of film, and exposed.
Results
[0559] FIG. 4A shows a Western blot demonstrating expression of the
cadherin3 polypeptide in various cell lines. The lane order is,
from left to right: MCF-7, Colo205, UACC62, JURKAT, HEPG2, N-TERA2,
MOLT4, Sw872. The primary antibody was used at a dilution of
1:100.
[0560] FIG. 4B shows a Western blot demonstrating expression of the
matrix metalloproteinase 14 polypeptide in various cell lines. The
lane order is, from left to right: 184B5, MCF7, OVCAR3, UACC62,
HepG2. The three images present identical blots in which the
primary antibody was used at dilutions of 1:200 (left), 1:500
(middle), and 1:1000 (right).
[0561] FIG. 4C shows a Western blot demonstrating expression of the
cadherin EGF LAG seven-pass G-type receptor 2 polypeptide in
various cell lines. The lane order is, from left to right: 184B5,
MCF7, OVCAR3, UACC62, HepG2. The three images present identical
blots in which the primary antibody was used at dilutions of 1:200
(left), 1:500 (middle), and 1:1000 (right).
[0562] For all three antibodies, the Western blots demonstrated
that the antibodies bind to a polypeptide of the expected size. All
of the basal marker polypeptides are expressed in a range of
different cell types. While not wishing to be bound by any theory,
inventors postulate that basal cells in tissues other than breast
may express the basal marker genes, which may make them useful for
identification of basal tumor subclasses for tumors other than
breast tumors.
Example 12
Immunohistochemical Staining of Breast Tumor Arrays with Antibodies
to Cytokeratin 17 Demonstrates that Cytokeratin 17 Expression
Correlates with Poor Outcome
Materials and Methods
Tissue Arrays.
[0563] A total of 611 different paraffin embedded breast carcinoma
samples were identified in the files in the Department of Pathology
at the University of Basel, Women's hospital Rheinfelden, and the
Kreiskrankenhaus Lorrach. The specimens were obtained from patients
who underwent surgery in the period between 1985 and 1994. The
histologic parameters for all cases were reviewed by a single
pathologist (JT) and the histologic type and grade was determined
for each case according to Elston and Ellis Elston C W, Ellis I O:
Pathological prognostic factors in breast cancer. I. The value of
histological grade in breast cancer: experience from a large study
with long-term follow-up. Histopathology 1991, 19:403-10.
[0564] Follow-up was obtained for 553 cases and ranged from 1 to
151 months with a mean of 65.9 months. The use of these specimens
and data for research purposes was approved by the Ethics Committee
of the Basel University Hospital. Tissue arrays were constructed by
obtaining 0.6 mm diameter tissue cores from each tumor and placing
these cores in a new paraffin block in rows and columns as
described in Kononen J, Bubendorf L, Kallioniemi A, Barlund M,
Schraml P, Leighton S, Torhorst J, Mihatsch M J, Sauter G,
Kallioniemi O P: Tissue microarrays for high-throughput molecular
profiling of tumor specimens [see comments]. Nat Med 1998, 4:844-7
and in Schraml P, Kononen J, Bubendorf L, Moch H, Bissig H, Nocito
A, Mihatsch M J, Kallioniemi O P, Sauter G: Tissue microarrays for
gene amplification surveys in many different tumor types. Clin
Cancer Res 1999, 5:1966-75.
[0565] Each of the 611 cases was sampled twice, once from the
center of the tumor, and once from the periphery of the mass. Cores
taken from the central area from each case were combined in one
array and cores taken from the periphery of the tumor were combined
in the other array.
Immunohistochemistry and Scoring.
[0566] Double staining of normal breast epithelium in conventional
paraffin sections was performed by first staining lumenal cells
with CAM5.2 using alkaline phosphatase/fast blue staining and
subsequently staining basal cells with CK17 using horse radish
peroxidase/DAB staining.
[0567] Sections of arrays were stained with monoclonal antibodies
specific for cytokeratin 17 (DAKO, clone E3, dilution 1:10) and
cytokeratin 5/6 (Boehringer Mannheim, dilution 1:10) after antigen
retrieval by microwaving in citrate buffer. Note that the
anti-cytokeratin 5/6 antibody used herein detects both cytokeratins
5 and 6. However, cytokeratin 5 is likely to be the major antigen
recognized by this antibody in breast basal cells. Staining results
were scored as follows: 1=invasive tumor cells present in tissue
core and no staining seen; 2=invasive tumor cells present and weak
staining; 3=invasive tumor cells present with strong staining. Only
those cores containing tissue consistent with a diagnosis of
invasive carcinoma were included in the outcome analysis. Cases
that either had no tissue present on the array sections or cases in
which the material sampled consisted of fat, fibrosis, normal
breast glands, or in-situ carcinoma only, were omitted from further
analysis. Cytokeratins often showed only focal staining of tumor
cells within the tissue array cores or conventional paraffin
sections. To account for the focal expression of CK17 and CK5/6,
each of the 612 breast tumors was analyzed 4 times: with anti-CK17
and anti-CK5/6 antibody on the "central sample" array, and with
anti-CK17 and anti-CK5/6 antibody on the "peripheral sample" array.
A breast tumor sample was scored as staining positive for the
keratins if infiltrating carcinoma in one or more of the cores from
that sample reacted with either of the antibodies.
[0568] To aid in recognizing infiltrating carcinoma in the core
samples, sections of each array were also stained with an
anti-cytokeratin antibody mix reacting with cytokeratins 8 and 18
(CAM5.2, Becton & Dickinson, dilution 1:20) after antigen
unmasking by trypsin digestion to highlight invasive carcinoma
cells.
Statistical Analysis
[0569] Univariate survival analysis based upon gene expression
defined subgroups of patients was performed by Kaplan-Meier
statistics using WinSTAT software (www.winstat.com). Subsequent
multivariate analyses were performed using Cox's proportional
hazards model for survival data (Cox: Regression models and life
tables. Journal Royal Statistical Society 1972, 74:187-220).
Results
Basal Keratin Staining in Normal Breast and Breast Carcinoma.
[0570] In normal breast, antibodies that bind to cytokeratin17
(CK17) and cytokeratin 5/6 (CK5/6) stain the basal layer of breast
glandular epithelium while antibodies that bind to cytokeratins 8
and 18 stain lumenal cells (FIGS. 3C and 3D). Whole paraffin
sections of breast carcinoma showed that cytokeratin 17 and 5/6
expression in paraffin embedded tissue when present was focal
(FIGS. 3E and 3F) with often less than 10% of tumor cells reacting.
In an attempt to study further the focal reactivity of the
monoclonal antibodies against the basal type cytokeratins, and to
attempt to improve the reliability of this test, rabbit antisera
against CK17 were raised as described in Example 12. This serum was
tested on a separate tissue array with over 300 hundred breast
samples. The antiserum and the monoclonal antibody against CK17
showed highly similar reactivity with epithelial cells in the
breast cores. Both reagents stained the same fraction of tumor
cells suggesting that neither is a significantly better reagent.
These results suggest that the focal reactivity seen with
monoclonal anti-CK17 was not due to weak reactivity of the
monoclonal antibody but indicates that within a tumor only a subset
of tumor cells express these basal keratins, reinforcing the need
for alternative basal markers.
Basal Keratin Staining on Breast Carcinoma Tissue Arrays.
[0571] Since the size of sample examined in tissue array cores is
significantly smaller than on conventional samples, there was a
concern that the focal reactivity of basal type cytokeratins might
cause positive tumors to be missed. We decided to maximize the
chance of detecting basal keratin expression in the breast tumors
on the arrays by staining them with monoclonal antibodies directed
at CK5/6 and CK17 and by examining arrays made with cores taken
from central and peripheral areas of the tumors. By combining the
results from the "central" array and the "peripheral" array, 532
tumors were available for CK17 analysis, 535 were available for
CK5/6 analysis, and 564 were available for either CK17 or CK5/6.
The remainder of the tumors represented on the arrays were either
lost in transfer during sectioning of the tissue arrays block, or
showed no convincing invasive carcinoma on the core section. Of the
cases available for scoring, 75 and 63 tumors scored positive
(either weak or strongly) for CK17 and CK5/6, respectively. By
combining the results from the stains for CK17 and CK5/6, 90 cases
(16%) out of the 564 tumors examined reacted with either CK17
and/or CK5/6. Follow-up data were available for 505 of the 564
cases on which CK staining data was obtained. The follow-up period
ranged from 1 to 151 months with a mean of 66.1 months.
[0572] Kaplan-Meier survival analysis on all patients with
follow-up showed that the absence of cytokeratin 17 and cytokeratin
5 is associated with a significantly better prognosis than the
presence of either of these cytokeratins (FIG. 5A, p=0.012). In the
group of 229 patients with known lymph node metastases, the
expression of CK17 and CK5/6 had no predictive value. In contrast,
in the group of 245 patients without lymph node metastases, CK17
and/or CK5/6 expression was significantly associated with shorter
survival (FIG. 5B, p=0.006). The percentage of basal keratin
positive tumors was similar in patients with and without lymph node
metastases. Multivariate analysis on all patients taken together
showed that the prognostic association of basal cytokeratin
expression with poor outcome was not independent from tumor size,
LN status and histologic grade. However when analyzed on
LN-negative tumors alone, the expression of basal cytokeratins is
not only a statistically significant prognosticator, but is also
independent of tumor size, tumor grade, her2neu status, ER status,
and GATA3 status. The results clearly demonstrate the utility of
cytokeratin 17 as a marker for a subclass of tumors with a poor
clinical outcome while also highlighting the difficulties
associated with use of anti-cytokeratin17 antibodies.
Her2neu, Estrogen Receptor and GATA-3 Staining on Breast Carcinoma
Arrays
[0573] To further confirm the accuracy of correlations between
immunohistochemistry results and clinical data obtained using
tissue arrays, sections of the arrays made with peripheral cores
were stained for a variety of other proteins known or suspected to
be associated with a good or a poor clinical outcome, for example
estrogen receptor and Her2neu. As expected, expression of estrogen
receptors was associated with a better clinical outcome. This
finding was independent of BRE grade, LN status and size. In
contrast, Her2neu expression was associated with a poor prognosis.
These results are compatible with published data and are similar to
those of two additional studies performed on the same breast tumor
arrays. (Bucher C, Torhorst J, Kononen J, Haas P, Schraml L,
Bubendorf L, Zuber M, Kochli O R, Mross F, Dieterich H, Askaa J,
Godtfredsen S E, Seelig S, Moch H, Mihatsch M, Kallioniemi O,
Sauter G: Prognostic significance of HER-2 amplification and
overexpression in breast cancer: Methodological comparison of
fluorescence in situ hybridization and immunohistochemistry using
tissue microarrays of 611 primary breast cancers. in press, 2001;
Torhorst J, Bucher C, Kononen J, Haas P, Zuber M, Kochli O R, Mross
F, Dieterich H, Moch H, Mihatsch M, Kallioniemi O, Sauter G: Tissue
microarrays for rapid linking of molecular changes to clinical
endpoints. in press. 2001)
[0574] Sections of the arrays were also stained for GATA-binding
protein 3, an antigen thought to be co-expressed with estrogen
receptors on the mRNA and protein level (Hoch R V, Thompson D A,
Baker R J, Weigel R J: GATA-3 is expressed in association with
estrogen receptor in breast cancer. International Journal of Cancer
1999, 84:122-8). The expression for GATA-3 was associated with a
good clinical outcome and had a high correlation (Chi-square=720.3
on 9 degrees of freedom) with estrogen receptor expression. The
staining results for estrogen receptor, GATA-3 and her2neu confirm
findings from prior studies, and also function as an independent
validation of tissue array-based studies.
[0575] Tissue arrays present a number of advantages for tumor
analysis. Analysis of large numbers of tissue sections using
conventional techniques is laborious and expensive. An added
disadvantage is that slides are stained in different batches, which
can introduce variation in staining intensity. In addition, the
analysis of large number of conventional glass slides makes
comparisons between tumor samples difficult. Many of these problems
are circumvented by the new technique of tissue arrays. This
approach allows the efficient analysis of antibody reactivity on
large numbers of tumors that are stained together on the same
slide.
[0576] The tissue array studies reported here allowed separation of
the patients groups into patients with lymph node metastasis and
those without. In patients with metastatic disease to the lymph
nodes, the expression of the basal cytokeratins was not associated
with a significant difference in clinical outcome. However, in
lymph node negative patients the reactivity for these markers was
associated with a poor prognosis independent of tumor size, tumor
grade, or immunostain reactivity for ER, her2neu or GATA3. While
not wishing to be bound by any theory, taken together with the gene
array data, these findings support the idea that anti-cytokeratin
antibodies may identify a different type of tumor rather than just
another prognostic marker and suggest the possibility that these
tumors are derived from basal cells and not from lumenal cells.
[0577] Due to the focal and often weak reactivity of monoclonal
antibodies against basal type keratins, the interpretation of
staining results for these markers can be difficult. The intensity
of staining with these markers is not comparable with other markers
currently used in diagnosis of breast carcinoma, such as estrogen
receptor and her2neu, a feature that prevents their use in clinical
settings. We attempted to generate new reagents in the hope that
they would have more robust IHC staining characteristics. Analysis
of over 300 breast carcinoma samples in a separate array showed
that the number of cells and the pattern of focal reactivity for
the antiserum against CK17 and the intensity of staining were
similar to that seen with the monoclonal antibodies. This indicates
that the basal keratins are indeed only focally expressed and that
the low numbers of cells stained with antibodies is not due to a
weak reactivity of the monoclonal antibodies with the protein.
[0578] The studies presented here show that basal epithelial
cytokeratin positive tumors occur with a significant frequency
(>10%) and are associated with a poor prognosis. Patients with
metastatic breast carcinoma to the axillary lymph nodes are at high
risk for recurrence and most receive adjuvant therapy. The
situation for node negative patients is less clear; depending on
the size and grade of the tumor, the reported recurrence rate
varies between 5-30%. In lymph node negative patients, the clinical
decision whether to give or withhold systemic therapy thus is a
difficult one and hence it is in this group of patients that the
need for new prognostic markers is the greatest. The relative size
of this group of patients is also expected to increase, due to
continuing advances in screening and diagnostic techniques that
identify increasingly smaller breast tumors. Most of these smaller
tumors have not metastasized to the "sentinel" lymph node. This
group of patients, therefore, has to make a difficult choice
between a variety of additional therapies, such as: lumpectomy,
mastectomy, chemotherapy, radiation therapy, or hormonal therapy in
the absence of reliable guidance from pathologic characteristics of
their tumor. The cytokeratins 17 and 5/6 appear to detect a
subcategory of tumors that behave poorly and may help in treatment
decisions for node-negative breast carcinoma patients. These
results suggest that patients that present with basal epithelial
cytokeratin expressing tumors may be candidates for more aggressive
treatment procedures and also for alternate therapies directed
against tumors with this particular biology.
Example 13
Immunohistochemical Staining of Normal Breast and Breast Tumor
Samples in Tissue Arrays with Antibodies to Basal Marker
Polypeptides
Materials and Methods
[0579] Tissue arrays including normal breast and breast tumor
samples were prepared as described in Example 12. Monoclonal
antibody to cytokeratin 5/6 (Boeringer Mannheim, Inc.) and
polyclonal, affinity purified, anti-peptide antibodies to
cadherin3, cadherin EGF LAG seven-pass G-type receptor 2, and
matrix metalloproteinase 14 prepared as described in Example 10
were used to perform immunohistochemical staining using the DAKO
Envision+, Peroxidase IHC kit (DAKO Corp., Carpenteria, Calif.)
with DAB substrate according to the manufacturer's
instructions.
Results
[0580] FIG. 6 shows antibody staining of normal breast tissue
cores. FIG. 6A shows staining with anti-cytokeratin 5/6 monoclonal
antibody (ck5/6). FIGS. 6B, 6C, and 6D show staining with
anti-cadherin 3 polyclonal antibody (s0158), anti-EGF LAG
seven-pass G-type receptor 2 polyclonal antibody (s0137), and
anti-metalloproteinase 14 polyclonal antibody (s0144),
respectively, on sections from a core derived from the same
patient. The brown areas represent prominent staining of the basal
layer in the two-cell layered epithelium lining the mammary gland
lumen. These results confirm that the staining pattern of
antibodies to the basal marker polypeptides identified herein is
comparable to that of antibodies to cytokeratin 17 in terms of the
cell type stained and the ability to distinguish between basal and
luminal cells in the normal mammary gland.
[0581] FIG. 7 shows antibody staining of breast cancer tissue
cores. FIG. 7A shows antibody staining with anti-cytokeratin 5/6
monoclonal antibody (cd5/6). FIGS. 7B and 7C show staining with
anti-EGF LAG seven-pass G-type receptor 2 polyclonal antibody
(s0137) and anti-cadherin 3 polyclonal antibody (s0158),
respectively. The brown areas represent prominent staining of the
epithelial cells within tumor tissue. Note the loss of normal
breast glandular architecture consistent with the diagnosis of
carcinoma.
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Sequence CWU 1
1
15 1 829 PRT Artificial Sequence Description of Artificial
SequenceSequence of Cadherin 3 1 Met Gly Leu Pro Arg Gly Pro Leu
Ala Ser Leu Leu Leu Leu Gln Val 1 5 10 15 Cys Trp Leu Gln Cys Ala
Ala Ser Glu Pro Cys Arg Ala Val Phe Arg 20 25 30 Glu Ala Glu Val
Thr Leu Glu Ala Gly Gly Ala Glu Gln Glu Pro Gly 35 40 45 Gln Ala
Leu Gly Lys Val Phe Met Gly Cys Pro Gly Gln Glu Pro Ala 50 55 60
Leu Phe Ser Thr Asp Asn Asp Asp Phe Thr Val Arg Asn Gly Glu Thr 65
70 75 80 Val Gln Glu Arg Arg Ser Leu Lys Glu Arg Asn Pro Leu Lys
Ile Phe 85 90 95 Pro Ser Lys Arg Ile Leu Arg Arg His Lys Arg Asp
Trp Val Val Ala 100 105 110 Pro Ile Ser Val Pro Glu Asn Gly Lys Gly
Pro Phe Pro Gln Arg Leu 115 120 125 Asn Gln Leu Lys Ser Asn Lys Asp
Arg Asp Thr Lys Ile Phe Tyr Ser 130 135 140 Ile Thr Gly Pro Gly Ala
Asp Ser Pro Pro Glu Gly Val Phe Ala Val 145 150 155 160 Glu Lys Glu
Thr Gly Trp Leu Leu Leu Asn Lys Pro Leu Asp Arg Glu 165 170 175 Glu
Ile Ala Lys Tyr Glu Leu Phe Gly His Ala Val Ser Glu Asn Gly 180 185
190 Ala Ser Val Glu Asp Pro Met Asn Ile Ser Ile Ile Val Thr Asp Gln
195 200 205 Asn Asp His Lys Pro Lys Phe Thr Gln Asp Thr Phe Arg Gly
Ser Val 210 215 220 Leu Glu Gly Val Leu Pro Gly Thr Ser Val Met Gln
Val Thr Ala Thr 225 230 235 240 Asp Glu Asp Asp Ala Ile Tyr Thr Tyr
Asn Gly Val Val Ala Tyr Ser 245 250 255 Ile His Ser Gln Glu Pro Lys
Asp Pro His Asp Leu Met Phe Thr Ile 260 265 270 His Arg Ser Thr Gly
Thr Ile Ser Val Ile Ser Ser Gly Leu Asp Arg 275 280 285 Glu Lys Val
Pro Glu Tyr Thr Leu Thr Ile Gln Ala Thr Asp Met Asp 290 295 300 Gly
Asp Gly Ser Thr Thr Thr Ala Val Ala Val Val Glu Ile Leu Asp 305 310
315 320 Ala Asn Asp Asn Ala Pro Met Phe Asp Pro Gln Lys Tyr Glu Ala
His 325 330 335 Val Pro Glu Asn Ala Val Gly His Glu Val Gln Arg Leu
Thr Val Thr 340 345 350 Asp Leu Asp Ala Pro Asn Ser Pro Ala Trp Arg
Ala Thr Tyr Leu Ile 355 360 365 Met Gly Gly Asp Asp Gly Asp His Phe
Thr Ile Thr Thr His Pro Glu 370 375 380 Ser Asn Gln Gly Ile Leu Thr
Thr Arg Lys Gly Leu Asp Phe Glu Ala 385 390 395 400 Lys Asn Gln His
Thr Leu Tyr Val Glu Val Thr Asn Glu Ala Pro Phe 405 410 415 Val Leu
Lys Leu Pro Thr Ser Thr Ala Thr Ile Val Val His Val Glu 420 425 430
Asp Val Asn Glu Ala Pro Val Phe Val Pro Pro Ser Lys Val Val Glu 435
440 445 Val Gln Glu Gly Ile Pro Thr Gly Glu Pro Val Cys Val Tyr Thr
Ala 450 455 460 Glu Asp Pro Asp Lys Glu Asn Gln Lys Ile Ser Tyr Arg
Ile Leu Arg 465 470 475 480 Asp Pro Ala Gly Trp Leu Ala Met Asp Pro
Asp Ser Gly Gln Val Thr 485 490 495 Ala Val Gly Thr Leu Asp Arg Glu
Asp Glu Gln Phe Val Arg Asn Asn 500 505 510 Ile Tyr Glu Val Met Val
Leu Ala Met Asp Asn Gly Ser Pro Pro Thr 515 520 525 Thr Gly Thr Gly
Thr Leu Leu Leu Thr Leu Ile Asp Val Asn Asp His 530 535 540 Gly Pro
Val Pro Glu Pro Arg Gln Ile Thr Ile Cys Asn Gln Ser Pro 545 550 555
560 Val Arg His Val Leu Asn Ile Thr Asp Lys Asp Leu Ser Pro His Thr
565 570 575 Ser Pro Phe Gln Ala Gln Leu Thr Asp Asp Ser Asp Ile Tyr
Trp Thr 580 585 590 Ala Glu Val Asn Glu Glu Gly Asp Thr Val Val Leu
Ser Leu Lys Lys 595 600 605 Phe Leu Lys Gln Asp Thr Tyr Asp Val His
Leu Ser Leu Ser Asp His 610 615 620 Gly Asn Lys Glu Gln Leu Thr Val
Ile Arg Ala Thr Val Cys Asp Cys 625 630 635 640 His Gly His Val Glu
Thr Cys Pro Gly Pro Trp Lys Gly Gly Phe Ile 645 650 655 Leu Pro Val
Leu Gly Ala Val Leu Ala Leu Leu Phe Leu Leu Leu Val 660 665 670 Leu
Leu Leu Leu Val Arg Lys Lys Arg Lys Ile Lys Glu Pro Leu Leu 675 680
685 Leu Pro Glu Asp Asp Thr Arg Asp Asn Val Phe Tyr Tyr Gly Glu Glu
690 695 700 Gly Gly Gly Glu Glu Asp Gln Asp Tyr Asp Ile Thr Gln Leu
His Arg 705 710 715 720 Gly Leu Glu Ala Arg Pro Glu Val Val Leu Arg
Asn Asp Val Ala Pro 725 730 735 Thr Ile Ile Pro Thr Pro Met Tyr Arg
Pro Arg Pro Ala Asn Pro Asp 740 745 750 Glu Ile Gly Asn Phe Ile Ile
Glu Asn Leu Lys Ala Ala Asn Thr Asp 755 760 765 Pro Thr Ala Pro Pro
Tyr Asp Thr Leu Leu Val Phe Asp Tyr Glu Gly 770 775 780 Ser Gly Ser
Asp Ala Ala Ser Leu Ser Ser Leu Thr Ser Ser Ala Ser 785 790 795 800
Asp Gln Asp Gln Asp Tyr Asp Tyr Leu Asn Glu Trp Gly Ser Arg Phe 805
810 815 Lys Lys Leu Ala Asp Met Tyr Gly Gly Gly Glu Asp Asp 820 825
2 582 PRT Artificial Sequence Description of Artificial
SequenceMatrix Metalloproteinase 2 Met Ser Pro Ala Pro Arg Pro Pro
Arg Cys Leu Leu Leu Pro Leu Leu 1 5 10 15 Thr Leu Gly Thr Ala Leu
Ala Ser Leu Gly Ser Ala Gln Ser Ser Ser 20 25 30 Phe Ser Pro Glu
Ala Trp Leu Gln Gln Tyr Gly Tyr Leu Pro Pro Gly 35 40 45 Asp Leu
Arg Thr His Thr Gln Arg Ser Pro Gln Ser Leu Ser Ala Ala 50 55 60
Ile Ala Ala Met Gln Lys Phe Tyr Gly Leu Gln Val Thr Gly Lys Ala 65
70 75 80 Asp Ala Asp Thr Met Lys Ala Met Arg Arg Pro Arg Cys Gly
Val Pro 85 90 95 Asp Lys Phe Gly Ala Glu Ile Lys Ala Asn Val Arg
Arg Lys Arg Tyr 100 105 110 Ala Ile Gln Gly Leu Lys Trp Gln His Asn
Glu Ile Thr Phe Cys Ile 115 120 125 Gln Asn Tyr Thr Pro Lys Val Gly
Glu Tyr Ala Thr Tyr Glu Ala Ile 130 135 140 Arg Lys Ala Phe Arg Val
Trp Glu Ser Ala Thr Pro Leu Arg Phe Arg 145 150 155 160 Glu Val Pro
Tyr Ala Tyr Ile Arg Glu Gly His Glu Lys Gln Ala Asp 165 170 175 Ile
Met Ile Phe Phe Ala Glu Gly Phe His Gly Asp Ser Thr Pro Phe 180 185
190 Asp Gly Glu Gly Gly Phe Leu Ala His Ala Tyr Phe Pro Gly Pro Asn
195 200 205 Ile Gly Gly Asp Thr His Phe Asp Ser Ala Glu Pro Trp Thr
Val Arg 210 215 220 Asn Glu Asp Leu Asn Gly Asn Asp Ile Phe Leu Val
Ala Val His Glu 225 230 235 240 Leu Gly His Ala Leu Gly Leu Glu His
Ser Ser Asp Pro Ser Ala Ile 245 250 255 Met Ala Pro Phe Tyr Gln Trp
Met Asp Thr Glu Asn Phe Val Leu Pro 260 265 270 Asp Asp Asp Arg Arg
Gly Ile Gln Gln Leu Tyr Gly Gly Glu Ser Gly 275 280 285 Phe Pro Thr
Lys Met Pro Pro Gln Pro Arg Thr Thr Ser Arg Pro Ser 290 295 300 Val
Pro Asp Lys Pro Lys Asn Pro Thr Tyr Gly Pro Asn Ile Cys Asp 305 310
315 320 Gly Asn Phe Asp Thr Val Ala Met Leu Arg Gly Glu Met Phe Val
Phe 325 330 335 Lys Glu Arg Trp Phe Trp Arg Val Arg Asn Asn Gln Val
Met Asp Gly 340 345 350 Tyr Pro Met Pro Ile Gly Gln Phe Trp Arg Gly
Leu Pro Ala Ser Ile 355 360 365 Asn Thr Ala Tyr Glu Arg Lys Asp Gly
Lys Phe Val Phe Phe Lys Gly 370 375 380 Asp Lys His Trp Val Phe Asp
Glu Ala Ser Leu Glu Pro Gly Tyr Pro 385 390 395 400 Lys His Ile Lys
Glu Leu Gly Arg Gly Leu Pro Thr Asp Lys Ile Asp 405 410 415 Ala Ala
Leu Phe Trp Met Pro Asn Gly Lys Thr Tyr Phe Phe Arg Gly 420 425 430
Asn Lys Tyr Tyr Arg Phe Asn Glu Glu Leu Arg Ala Val Asp Ser Glu 435
440 445 Tyr Pro Lys Asn Ile Lys Val Trp Glu Gly Ile Pro Glu Ser Pro
Arg 450 455 460 Gly Ser Phe Met Gly Ser Asp Glu Val Phe Thr Tyr Phe
Tyr Lys Gly 465 470 475 480 Asn Lys Tyr Trp Lys Phe Asn Asn Gln Lys
Leu Lys Val Glu Pro Gly 485 490 495 Tyr Pro Lys Ser Ala Leu Arg Asp
Trp Met Gly Cys Pro Ser Gly Gly 500 505 510 Arg Pro Asp Glu Gly Thr
Glu Glu Glu Thr Glu Val Ile Ile Ile Glu 515 520 525 Val Asp Glu Glu
Gly Gly Gly Ala Val Ser Ala Ala Ala Val Val Leu 530 535 540 Pro Val
Leu Leu Leu Leu Leu Val Leu Ala Val Gly Leu Ala Val Phe 545 550 555
560 Phe Phe Arg Arg His Gly Thr Pro Arg Arg Leu Leu Tyr Cys Gln Arg
565 570 575 Ser Leu Leu Asp Lys Val 580 3 2923 PRT Artificial
Sequence Description of Artificial SequenceCadherin EGF LAG Seven
Pass G-Type Receptor 2 3 Met Arg Ser Pro Ala Thr Gly Val Pro Leu
Pro Thr Pro Pro Pro Pro 1 5 10 15 Leu Leu Leu Leu Leu Leu Leu Leu
Leu Pro Pro Pro Leu Leu Gly Asp 20 25 30 Gln Val Gly Pro Cys Arg
Ser Leu Gly Ser Arg Gly Arg Gly Ser Ser 35 40 45 Gly Ala Cys Ala
Pro Met Gly Trp Leu Cys Pro Ser Ser Ala Ser Asn 50 55 60 Leu Trp
Leu Tyr Thr Ser Arg Cys Arg Asp Ala Gly Thr Glu Leu Thr 65 70 75 80
Gly His Leu Val Pro His His Asp Gly Leu Arg Val Trp Cys Pro Glu 85
90 95 Ser Glu Ala His Ile Pro Leu Pro Pro Ala Pro Glu Gly Cys Pro
Trp 100 105 110 Ser Cys Arg Leu Leu Gly Ile Gly Gly His Leu Ser Pro
Gln Gly Lys 115 120 125 Leu Thr Leu Pro Glu Glu His Pro Cys Leu Lys
Ala Pro Arg Leu Arg 130 135 140 Cys Gln Ser Cys Lys Leu Ala Gln Ala
Pro Gly Leu Arg Ala Gly Glu 145 150 155 160 Arg Ser Pro Glu Glu Ser
Leu Gly Gly Arg Arg Lys Arg Asn Val Asn 165 170 175 Thr Ala Pro Gln
Phe Gln Pro Pro Ser Tyr Gln Ala Thr Val Pro Glu 180 185 190 Asn Gln
Pro Ala Gly Thr Pro Val Ala Ser Leu Arg Ala Ile Asp Pro 195 200 205
Asp Glu Gly Glu Ala Gly Arg Leu Glu Tyr Thr Met Asp Ala Leu Phe 210
215 220 Asp Ser Arg Ser Asn Gln Phe Phe Ser Leu Asp Pro Val Thr Gly
Ala 225 230 235 240 Val Thr Thr Ala Glu Glu Leu Asp Arg Glu Thr Lys
Ser Thr His Val 245 250 255 Phe Arg Val Thr Ala Gln Asp His Gly Met
Pro Arg Arg Ser Ala Leu 260 265 270 Ala Thr Leu Thr Ile Leu Val Thr
Asp Thr Asn Asp His Asp Pro Val 275 280 285 Phe Glu Gln Gln Glu Tyr
Lys Glu Ser Leu Arg Glu Asn Leu Glu Val 290 295 300 Gly Tyr Glu Val
Leu Thr Val Arg Ala Thr Asp Gly Asp Ala Pro Pro 305 310 315 320 Asn
Ala Asn Ile Leu Tyr Arg Leu Leu Glu Gly Ser Gly Gly Ser Pro 325 330
335 Ser Glu Val Phe Glu Ile Asp Pro Arg Ser Gly Val Ile Arg Thr Arg
340 345 350 Gly Pro Val Asp Arg Glu Glu Val Glu Ser Tyr Gln Leu Thr
Val Glu 355 360 365 Ala Ser Asp Gln Gly Arg Asp Pro Gly Pro Arg Ser
Thr Thr Ala Ala 370 375 380 Val Phe Leu Ser Val Glu Asp Asp Asn Asp
Asn Ala Pro Gln Phe Ser 385 390 395 400 Glu Lys Arg Tyr Val Val Gln
Val Arg Glu Asp Val Thr Pro Gly Ala 405 410 415 Pro Val Leu Arg Val
Thr Ala Ser Asp Arg Asp Lys Gly Ser Asn Ala 420 425 430 Val Val His
Tyr Ser Ile Met Ser Gly Asn Ala Arg Gly Gln Phe Tyr 435 440 445 Leu
Asp Ala Gln Thr Gly Ala Leu Asp Val Val Ser Pro Leu Asp Tyr 450 455
460 Glu Thr Thr Lys Glu Tyr Thr Leu Arg Val Arg Ala Gln Asp Gly Gly
465 470 475 480 Arg Pro Pro Leu Ser Asn Val Ser Gly Leu Val Thr Val
Gln Val Leu 485 490 495 Asp Ile Asn Asp Asn Ala Pro Ile Phe Val Ser
Thr Pro Phe Gln Ala 500 505 510 Thr Val Leu Glu Ser Val Pro Leu Gly
Tyr Leu Val Leu His Val Gln 515 520 525 Ala Ile Asp Ala Asp Ala Gly
Asp Asn Ala Arg Leu Glu Tyr Arg Leu 530 535 540 Ala Gly Val Gly His
Asp Phe Pro Phe Thr Ile Asn Asn Gly Thr Gly 545 550 555 560 Trp Ile
Ser Val Ala Ala Glu Leu Asp Arg Glu Glu Val Asp Phe Tyr 565 570 575
Ser Phe Gly Val Glu Ala Arg Asp His Gly Thr Pro Ala Leu Thr Ala 580
585 590 Ser Ala Ser Val Ser Val Thr Val Leu Asp Val Asn Asp Asn Asn
Pro 595 600 605 Thr Phe Thr Gln Pro Glu Tyr Thr Val Arg Leu Asn Glu
Asp Ala Ala 610 615 620 Val Gly Thr Ser Val Val Thr Val Ser Ala Val
Asp Arg Asp Ala His 625 630 635 640 Ser Val Ile Thr Tyr Gln Ile Thr
Ser Gly Asn Thr Arg Asn Arg Phe 645 650 655 Ser Ile Thr Ser Gln Ser
Gly Gly Gly Leu Val Ser Leu Ala Leu Pro 660 665 670 Leu Asp Tyr Lys
Leu Glu Arg Gln Tyr Val Leu Ala Val Thr Ala Ser 675 680 685 Asp Gly
Thr Arg Gln Asp Thr Ala Gln Ile Val Val Asn Val Thr Asp 690 695 700
Ala Asn Thr His Arg Pro Val Phe Gln Ser Ser His Tyr Thr Val Asn 705
710 715 720 Val Asn Glu Asp Arg Pro Ala Gly Thr Thr Val Val Leu Ile
Ser Ala 725 730 735 Thr Asp Glu Asp Thr Gly Glu Asn Ala Arg Ile Thr
Tyr Phe Met Glu 740 745 750 Asp Ser Ile Pro Gln Phe Arg Ile Asp Ala
Asp Thr Gly Ala Val Thr 755 760 765 Thr Gln Ala Glu Leu Asp Tyr Glu
Asp Gln Val Ser Tyr Thr Leu Ala 770 775 780 Ile Thr Ala Arg Asp Asn
Gly Ile Pro Gln Lys Ser Asp Thr Thr Tyr 785 790 795 800 Leu Glu Ile
Leu Val Asn Asp Val Asn Asp Asn Ala Pro Gln Phe Leu 805 810 815 Arg
Asp Ser Tyr Gln Gly Ser Val Tyr Glu Asp Val Pro Pro Phe Thr 820 825
830 Ser Val Leu Gln Ile Ser Ala Thr Asp Arg Asp Ser Gly Leu Asn Gly
835 840 845 Arg Val Phe Tyr Thr Phe Gln Gly Gly Asp Asp Gly Asp Gly
Asp Phe 850 855 860 Ile Val Glu Ser Thr Ser Gly Ile Val Arg Thr Leu
Arg Arg Leu Asp 865 870 875 880 Arg Glu Asn Val Ala Gln Tyr Val Leu
Arg Ala Tyr Ala Val Asp Lys 885 890 895 Gly Met Pro Pro Ala Arg Thr
Pro Met Glu Val Thr Val Thr Val Leu 900 905 910 Asp Val Asn Asp Asn
Pro Pro Val Phe Glu Gln Asp Glu Phe Asp Val 915 920 925 Phe Val Glu
Glu Asn Ser Pro Ile Gly Leu Ala Val Ala Arg Val Thr 930 935 940 Ala
Thr Asp Pro Asp Glu Gly Thr Asn Ala Gln Ile Met Tyr Gln Ile 945 950
955 960 Val Glu Gly Asn Ile Pro Glu Val Phe Gln Leu Asp Ile Phe Ser
Gly 965 970 975 Glu Leu Thr Ala Leu Val Asp Leu Asp Tyr Glu Asp Arg
Pro Glu Tyr 980 985 990 Val Leu Val Ile Gln Ala Thr
Ser Ala Pro Leu Val Ser Arg Ala Thr 995 1000 1005 Val His Val Arg
Leu Leu Asp Arg Asn Asp Asn Pro Pro Val Leu Gly 1010 1015 1020 Asn
Phe Glu Ile Leu Phe Asn Asn Tyr Val Thr Asn Arg Ser Ser Ser 1025
1030 1035 1040 Phe Pro Gly Gly Ala Ile Gly Arg Val Pro Ala His Asp
Pro Asp Ile 1045 1050 1055 Ser Asp Ser Leu Thr Tyr Ser Phe Glu Arg
Gly Asn Glu Leu Ser Leu 1060 1065 1070 Val Leu Leu Asn Ala Ser Thr
Gly Glu Leu Lys Leu Ser Arg Ala Leu 1075 1080 1085 Asp Asn Asn Arg
Pro Leu Glu Ala Ile Met Ser Val Leu Val Ser Asp 1090 1095 1100 Gly
Val His Ser Val Thr Ala Gln Cys Ala Leu Arg Val Thr Ile Ile 1105
1110 1115 1120 Thr Asp Glu Met Leu Thr His Ser Ile Thr Leu Arg Leu
Glu Asp Met 1125 1130 1135 Ser Pro Glu Arg Phe Leu Ser Pro Leu Leu
Gly Leu Phe Ile Gln Ala 1140 1145 1150 Val Ala Ala Thr Leu Ala Thr
Pro Pro Asp His Val Val Val Phe Asn 1155 1160 1165 Val Gln Arg Asp
Thr Asp Ala Pro Gly Gly His Ile Leu Asn Val Ser 1170 1175 1180 Leu
Ser Val Gly Gln Pro Pro Gly Pro Gly Gly Gly Pro Pro Phe Leu 1185
1190 1195 1200 Pro Ser Glu Asp Leu Gln Glu Arg Leu Tyr Leu Asn Arg
Ser Leu Leu 1205 1210 1215 Thr Ala Ile Ser Ala Gln Arg Val Leu Pro
Phe Asp Asp Asn Ile Cys 1220 1225 1230 Leu Arg Glu Pro Cys Glu Asn
Tyr Met Arg Cys Val Ser Val Leu Arg 1235 1240 1245 Phe Asp Ser Ser
Ala Pro Phe Ile Ala Ser Ser Ser Val Leu Phe Arg 1250 1255 1260 Pro
Ile His Pro Val Gly Gly Leu Arg Cys Arg Cys Pro Pro Gly Phe 1265
1270 1275 1280 Thr Gly Asp Tyr Cys Glu Thr Glu Val Asp Leu Cys Tyr
Ser Arg Pro 1285 1290 1295 Cys Gly Pro His Gly Arg Cys Arg Ser Arg
Glu Gly Gly Tyr Thr Cys 1300 1305 1310 Leu Cys Arg Asp Gly Tyr Thr
Gly Glu His Cys Glu Val Ser Ala Arg 1315 1320 1325 Ser Gly Arg Cys
Thr Pro Gly Val Cys Lys Asn Gly Gly Thr Cys Val 1330 1335 1340 Asn
Leu Leu Val Gly Gly Phe Lys Cys Asp Cys Pro Ser Gly Asp Phe 1345
1350 1355 1360 Glu Lys Pro Tyr Cys Gln Val Thr Thr Arg Ser Phe Pro
Ala His Ser 1365 1370 1375 Phe Ile Thr Phe Arg Gly Leu Arg Gln Arg
Phe His Phe Thr Leu Ala 1380 1385 1390 Leu Ser Phe Ala Thr Lys Glu
Arg Asp Gly Leu Leu Leu Tyr Asn Gly 1395 1400 1405 Arg Phe Asn Glu
Lys His Asp Phe Val Ala Leu Glu Val Ile Gln Glu 1410 1415 1420 Gln
Val Gln Leu Thr Phe Ser Ala Gly Glu Ser Thr Thr Thr Val Ser 1425
1430 1435 1440 Pro Phe Val Pro Gly Gly Val Ser Asp Gly Gln Trp His
Thr Val Gln 1445 1450 1455 Leu Lys Tyr Tyr Asn Lys Pro Leu Leu Gly
Gln Thr Gly Leu Pro Gln 1460 1465 1470 Gly Pro Ser Glu Gln Lys Val
Ala Val Val Thr Val Asp Gly Cys Asp 1475 1480 1485 Thr Gly Val Ala
Leu Arg Phe Gly Ser Val Leu Gly Asn Tyr Ser Cys 1490 1495 1500 Ala
Ala Gln Gly Thr Gln Gly Gly Ser Lys Lys Ser Leu Asp Leu Thr 1505
1510 1515 1520 Gly Pro Leu Leu Leu Gly Gly Val Pro Asp Leu Pro Glu
Ser Phe Pro 1525 1530 1535 Val Arg Met Arg Gln Phe Val Gly Cys Met
Arg Asn Leu Gln Val Asp 1540 1545 1550 Ser Arg His Ile Asp Met Ala
Asp Phe Ile Ala Asn Asn Gly Thr Val 1555 1560 1565 Pro Gly Cys Pro
Ala Lys Lys Asn Val Cys Asp Ser Asn Thr Cys His 1570 1575 1580 Asn
Gly Gly Thr Cys Val Asn Gln Trp Asp Ala Phe Ser Cys Glu Cys 1585
1590 1595 1600 Pro Leu Gly Phe Gly Gly Lys Ser Cys Ala Gln Glu Met
Ala Asn Pro 1605 1610 1615 Gln His Phe Leu Gly Ser Ser Leu Val Ala
Trp His Gly Leu Ser Leu 1620 1625 1630 Pro Ile Ser Gln Pro Trp Tyr
Leu Ser Leu Met Phe Arg Thr Arg Gln 1635 1640 1645 Ala Asp Gly Val
Leu Leu Gln Ala Ile Thr Arg Gly Arg Ser Thr Ile 1650 1655 1660 Thr
Leu Gln Leu Arg Glu Gly His Val Met Leu Ser Val Glu Gly Thr 1665
1670 1675 1680 Gly Leu Gln Ala Ser Ser Leu Arg Leu Glu Pro Gly Arg
Ala Asn Asp 1685 1690 1695 Gly Asp Trp His His Ala Gln Leu Ala Leu
Gly Ala Ser Gly Gly Pro 1700 1705 1710 Gly His Ala Ile Leu Ser Phe
Asp Tyr Gly Gln Gln Arg Ala Glu Gly 1715 1720 1725 Asn Leu Gly Pro
Arg Leu His Gly Leu His Leu Ser Asn Ile Thr Val 1730 1735 1740 Gly
Gly Ile Pro Gly Pro Ala Gly Gly Val Ala Arg Gly Phe Arg Gly 1745
1750 1755 1760 Cys Leu Gln Gly Val Arg Val Ser Asp Thr Pro Glu Gly
Val Asn Ser 1765 1770 1775 Leu Asp Pro Ser His Gly Glu Ser Ile Asn
Val Glu Gln Gly Cys Ser 1780 1785 1790 Leu Pro Asp Pro Cys Asp Ser
Asn Pro Cys Pro Ala Asn Ser Tyr Cys 1795 1800 1805 Ser Asn Asp Trp
Asp Ser Tyr Ser Cys Ser Cys Asp Pro Gly Tyr Tyr 1810 1815 1820 Gly
Asp Asn Cys Thr Asn Val Cys Asp Leu Asn Pro Cys Glu His Gln 1825
1830 1835 1840 Ser Val Cys Thr Arg Lys Pro Ser Ala Pro His Gly Tyr
Thr Cys Glu 1845 1850 1855 Cys Pro Pro Asn Tyr Leu Gly Pro Tyr Cys
Glu Thr Arg Ile Asp Gln 1860 1865 1870 Pro Cys Pro Arg Gly Trp Trp
Gly His Pro Thr Cys Gly Pro Cys Asn 1875 1880 1885 Cys Asp Val Ser
Lys Gly Phe Asp Pro Asp Cys Asn Lys Thr Ser Gly 1890 1895 1900 Glu
Cys His Cys Lys Glu Asn His Tyr Arg Pro Pro Gly Ser Pro Thr 1905
1910 1915 1920 Cys Leu Leu Cys Asp Cys Tyr Pro Thr Gly Ser Leu Ser
Arg Val Cys 1925 1930 1935 Asp Pro Glu Asp Gly Gln Cys Pro Cys Lys
Pro Gly Val Ile Gly Arg 1940 1945 1950 Gln Cys Asp Arg Cys Asp Asn
Pro Phe Ala Glu Val Thr Thr Asn Gly 1955 1960 1965 Cys Glu Val Asn
Tyr Asp Ser Cys Pro Arg Ala Ile Glu Ala Gly Ile 1970 1975 1980 Trp
Trp Pro Arg Thr Arg Phe Gly Leu Pro Ala Ala Ala Pro Cys Pro 1985
1990 1995 2000 Lys Gly Ser Phe Gly Thr Ala Val Arg His Cys Asp Glu
His Arg Gly 2005 2010 2015 Trp Leu Pro Pro Asn Leu Phe Asn Cys Thr
Ser Ile Thr Phe Ser Glu 2020 2025 2030 Leu Lys Gly Phe Ala Glu Arg
Leu Gln Arg Asn Glu Ser Gly Leu Asp 2035 2040 2045 Ser Gly Arg Ser
Gln Gln Leu Ala Leu Leu Leu Arg Asn Ala Thr Gln 2050 2055 2060 His
Thr Ala Gly Tyr Phe Gly Ser Asp Val Lys Val Ala Tyr Gln Leu 2065
2070 2075 2080 Ala Thr Arg Leu Leu Ala His Glu Ser Thr Gln Arg Gly
Phe Gly Leu 2085 2090 2095 Ser Ala Thr Gln Asp Val His Phe Thr Glu
Asn Leu Leu Arg Val Gly 2100 2105 2110 Ser Ala Leu Leu Asp Thr Ala
Asn Lys Arg His Trp Glu Leu Ile Gln 2115 2120 2125 Gln Thr Glu Gly
Gly Thr Ala Trp Leu Leu Gln His Tyr Glu Ala Tyr 2130 2135 2140 Ala
Ser Ala Leu Ala Gln Asn Met Arg His Thr Tyr Leu Ser Pro Phe 2145
2150 2155 2160 Thr Ile Val Thr Pro Asn Ile Val Ile Ser Val Val Arg
Leu Asp Lys 2165 2170 2175 Gly Asn Phe Ala Gly Ala Lys Leu Pro Arg
Tyr Glu Ala Leu Arg Gly 2180 2185 2190 Glu Gln Pro Pro Asp Leu Glu
Thr Thr Val Ile Leu Pro Glu Ser Val 2195 2200 2205 Phe Arg Glu Thr
Pro Pro Val Val Arg Pro Ala Gly Pro Gly Glu Ala 2210 2215 2220 Gln
Glu Pro Glu Glu Leu Ala Arg Arg Gln Arg Arg His Pro Glu Leu 2225
2230 2235 2240 Ser Gln Gly Glu Ala Val Ala Ser Val Ile Ile Tyr Arg
Thr Leu Ala 2245 2250 2255 Gly Leu Leu Pro His Asn Tyr Asp Pro Asp
Lys Arg Ser Leu Arg Val 2260 2265 2270 Pro Lys Arg Pro Ile Ile Asn
Thr Pro Val Val Ser Ile Ser Val His 2275 2280 2285 Asp Asp Glu Glu
Leu Leu Pro Arg Ala Leu Asp Lys Pro Val Thr Val 2290 2295 2300 Gln
Phe Arg Leu Leu Glu Thr Glu Glu Arg Thr Lys Pro Ile Cys Val 2305
2310 2315 2320 Phe Trp Asn His Ser Ile Leu Val Ser Gly Thr Gly Gly
Trp Ser Ala 2325 2330 2335 Arg Gly Cys Glu Val Val Phe Arg Asn Glu
Ser His Val Ser Cys Gln 2340 2345 2350 Cys Asn His Met Thr Ser Phe
Ala Val Leu Met Asp Val Ser Arg Arg 2355 2360 2365 Glu Asn Gly Glu
Ile Leu Pro Leu Lys Thr Leu Thr Tyr Val Ala Leu 2370 2375 2380 Gly
Val Thr Leu Ala Ala Leu Leu Leu Thr Phe Phe Phe Leu Thr Leu 2385
2390 2395 2400 Leu Arg Ile Leu Arg Ser Asn Gln His Gly Ile Arg Arg
Asn Leu Thr 2405 2410 2415 Ala Ala Leu Gly Leu Ala Gln Leu Val Phe
Leu Leu Gly Ile Asn Gln 2420 2425 2430 Ala Asp Leu Pro Phe Ala Cys
Thr Val Ile Ala Ile Leu Leu His Phe 2435 2440 2445 Leu Tyr Leu Cys
Thr Phe Ser Trp Ala Leu Leu Glu Ala Leu His Leu 2450 2455 2460 Tyr
Arg Ala Leu Thr Glu Val Arg Asp Val Asn Thr Gly Pro Met Arg 2465
2470 2475 2480 Phe Tyr Tyr Met Leu Gly Trp Gly Val Pro Ala Phe Ile
Thr Gly Leu 2485 2490 2495 Ala Val Gly Leu Asp Pro Glu Gly Tyr Gly
Asn Pro Asp Phe Cys Trp 2500 2505 2510 Leu Ser Ile Tyr Asp Thr Leu
Ile Trp Ser Phe Ala Gly Pro Val Ala 2515 2520 2525 Phe Ala Val Ser
Met Ser Val Phe Leu Tyr Ile Leu Ala Ala Arg Ala 2530 2535 2540 Ser
Cys Ala Ala Gln Arg Gln Gly Phe Glu Lys Lys Gly Pro Val Ser 2545
2550 2555 2560 Gly Leu Gln Pro Ser Phe Ala Val Leu Leu Leu Leu Ser
Ala Thr Trp 2565 2570 2575 Leu Leu Ala Leu Leu Ser Val Asn Ser Asp
Thr Leu Leu Phe His Tyr 2580 2585 2590 Leu Phe Ala Thr Cys Asn Cys
Ile Gln Gly Pro Phe Ile Phe Leu Ser 2595 2600 2605 Tyr Val Val Leu
Ser Lys Glu Val Arg Lys Ala Leu Lys Leu Ala Cys 2610 2615 2620 Ser
Arg Lys Pro Ser Pro Asp Pro Ala Leu Thr Thr Lys Ser Thr Leu 2625
2630 2635 2640 Thr Ser Ser Tyr Asn Cys Pro Ser Pro Tyr Ala Asp Gly
Arg Leu Tyr 2645 2650 2655 Gln Pro Tyr Gly Asp Ser Ala Gly Ser Leu
His Ser Thr Ser Arg Ser 2660 2665 2670 Gly Lys Ser Gln Pro Ser Tyr
Ile Pro Phe Leu Leu Arg Glu Glu Ser 2675 2680 2685 Ala Leu Asn Pro
Gly Gln Gly Pro Pro Gly Leu Gly Asp Pro Gly Ser 2690 2695 2700 Leu
Phe Leu Glu Gly Gln Asp Gln Gln His Asp Pro Asp Thr Asp Ser 2705
2710 2715 2720 Asp Ser Asp Leu Ser Leu Glu Asp Asp Gln Ser Gly Ser
Tyr Ala Ser 2725 2730 2735 Thr His Ser Ser Asp Ser Glu Glu Glu Glu
Glu Glu Glu Glu Glu Glu 2740 2745 2750 Ala Ala Phe Pro Gly Glu Gln
Gly Trp Asp Ser Leu Leu Gly Pro Gly 2755 2760 2765 Ala Glu Arg Leu
Pro Leu His Ser Thr Pro Lys Asp Gly Gly Pro Gly 2770 2775 2780 Pro
Gly Lys Ala Pro Trp Pro Gly Asp Phe Gly Thr Thr Ala Lys Glu 2785
2790 2795 2800 Ser Ser Gly Asn Gly Ala Pro Glu Glu Arg Leu Arg Glu
Asn Gly Asp 2805 2810 2815 Ala Leu Ser Arg Glu Gly Ser Leu Gly Pro
Leu Pro Gly Ser Ser Ala 2820 2825 2830 Gln Pro His Lys Gly Ile Leu
Lys Lys Lys Cys Leu Pro Thr Ile Ser 2835 2840 2845 Glu Lys Ser Ser
Leu Leu Arg Leu Pro Leu Glu Gln Cys Thr Gly Ser 2850 2855 2860 Ser
Arg Gly Ser Ser Ala Ser Glu Gly Ser Arg Gly Gly Pro Pro Pro 2865
2870 2875 2880 Arg Pro Pro Pro Arg Gln Ser Leu Gln Glu Gln Leu Asn
Gly Val Met 2885 2890 2895 Pro Ile Ala Met Ser Ile Lys Ala Gly Thr
Val Asp Glu Asp Ser Ser 2900 2905 2910 Gly Ser Glu Phe Leu Phe Phe
Asn Phe Leu His 2915 2920 4 19 PRT Artificial Sequence Description
of Artificial SequencePeptides for Antibodies that Bind to Cadherin
3 4 Arg Ala Val Phe Arg Glu Ala Glu Val Thr Leu Glu Ala Gly Gly Ala
1 5 10 15 Glu Gln Glu 5 17 PRT Artificial Sequence Description of
Artificial SequencePeptides for Antibodies that Bind to Cadherin 3
5 Gln Glu Pro Ala Leu Phe Ser Thr Asp Asn Asp Asp Phe Thr Val Arg 1
5 10 15 Asn 6 15 PRT Artificial Sequence Description of Artificial
SequencePeptides for Antibodies that Bind to Cadherin 3 6 Gln Lys
Tyr Glu Ala His Val Pro Glu Asn Ala Val Gly His Glu 1 5 10 15 7 19
PRT Artificial Sequence Description of Artificial SequencePeptides
for Antibodies that Bind to Matrix Metalloproteinase 14 7 Ala Tyr
Ile Arg Glu Gly His Glu Lys Gln Ala Asp Ile Met Ile Phe 1 5 10 15
Phe Ala Glu 8 18 PRT Artificial Sequence Description of Artificial
SequencePeptides for Antibodies that Bind to Matrix
Metalloporteinase 8 Asp Glu Ala Ser Leu Glu Pro Gly Tyr Pro Lys His
Ile Lys Glu Leu 1 5 10 15 Gly Arg 9 16 PRT Artificial Sequence
Description of Artificial SequencePeptides for Antibodies that bind
to Matrix Metalloporteinase 9 Arg Gly Ser Phe Met Gly Ser Asp Glu
Val Phe Thr Tyr Phe Tyr Lys 1 5 10 15 10 18 PRT Artificial Sequence
Description of Artificial Sequence Peptides for Antibodies that
Bind to Anti-Cadherin EGF LAG Seven-Pass G-Type Receptor 2 10 Gln
Ala Ser Ser Leu Arg Leu Glu Pro Gly Arg Ala Asn Asp Gly Asp 1 5 10
15 Trp His 11 20 PRT Artificial Sequence Description of Artificial
SequencePeptides for Antibodies that bind to Anti-Cadherin EGF LAG
Seven-Pass G-Type Receptor 2 11 Glu Leu Lys Gly Phe Ala Glu Arg Leu
Gln Arg Asn Glu Ser Gly Leu 1 5 10 15 Asp Ser Gly Arg 20 12 17 PRT
Artificial Sequence Description of Artificial Sequence Peptides for
Antibodies that Bind to Anti-Cadherin EGF LAG Seven-Pass G-Type
Receptor 2 12 Arg Ser Gly Lys Ser Gln Pro Ser Tyr Ile Pro Phe Leu
Leu Arg Glu 1 5 10 15 Glu 13 16 PRT Artificial Sequence Description
of Artificial SequencePeptides for Antibodies that Bind to
Anti-Cytokeratin 17 13 Lys Lys Glu Pro Val Thr Thr Arg Gln Val Arg
Thr Ile Val Glu Glu 1 5 10 15 14 17 PRT Artificial Sequence
Description of Artificial SequencePeptides for Antibodies that Bind
to Anti-Cytokeratin 17 14 Gln Asp Gly Lys Val Ile Ser Ser Arg Glu
Gln Val His Gln Thr Thr 1 5 10 15 Arg 15 15 PRT Artificial Sequence
Description of Artificial Sequence Peptides for Antibodies that
Bind to Anti-Cytokeratin 17 15 Ser Ser Ser Ile Lys Gly Ser Ser Gly
Leu Gly Gly Gly Ser Ser 1 5 10 15
* * * * *
References