U.S. patent application number 13/916154 was filed with the patent office on 2014-01-16 for method for determining hepatocellular carcinoma subtype and detecting hepatic cancer stem cells.
This patent application is currently assigned to The Government of the United States of America, as represented by the Secretary of the Department of. The applicant listed for this patent is The Government of the United States of America, as represented by the Secretary of the Department of, The Ohio State University Research Foundation, The Government of the United States of America, as represented by the Secretary of the Department of. Invention is credited to Carlo M. Croce, Junfang Ji, Xin Wei Wang, Taro Yamashita.
Application Number | 20140018409 13/916154 |
Document ID | / |
Family ID | 40130411 |
Filed Date | 2014-01-16 |
United States Patent
Application |
20140018409 |
Kind Code |
A1 |
Wang; Xin Wei ; et
al. |
January 16, 2014 |
Method for Determining Hepatocellular Carcinoma Subtype and
Detecting Hepatic Cancer Stem Cells
Abstract
Described herein are methods of determining an HCC subtype in a
subject which includes a) obtaining a sample from the subject, b)
assaying the sample to detect the expression of 1 or more
biomarkers, and c) correlating the expression of the biomarkers
with an HCC subtype in a subject. Also described are methods of
detecting HCC stem cells in a sample, and methods and compositions
for treating subjects with HCC that take advantage of the
biomarkers associated with HCC stem cells.
Inventors: |
Wang; Xin Wei; (Rockville,
MD) ; Ji; Junfang; (Clarksburg, MD) ;
Yamashita; Taro; (Ishikawa, JP) ; Croce; Carlo
M.; (Columbus, OH) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
The Government of the United States of America, as represented by
the Secretary of the Department of
The Ohio State University Research Foundation |
Rockville
Columbus |
MD
OH |
US
US |
|
|
Assignee: |
The Government of the United States
of America, as represented by the Secretary of the Department
of
Rockville
MD
The Ohio State University Research Foundation
Columbus
OH
|
Family ID: |
40130411 |
Appl. No.: |
13/916154 |
Filed: |
June 12, 2013 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
12663586 |
Apr 21, 2010 |
8465917 |
|
|
PCT/US08/07196 |
Jun 9, 2008 |
|
|
|
13916154 |
|
|
|
|
60942833 |
Jun 8, 2007 |
|
|
|
Current U.S.
Class: |
514/44A ;
435/6.11; 435/6.12; 435/7.1; 506/9 |
Current CPC
Class: |
C12Q 1/6886 20130101;
C12Q 2600/158 20130101; C12Q 2600/106 20130101; C12Q 2600/178
20130101; C12Q 2600/112 20130101; A61P 35/00 20180101; G01N 33/6893
20130101 |
Class at
Publication: |
514/44.A ;
435/7.1; 506/9; 435/6.12; 435/6.11 |
International
Class: |
C12Q 1/68 20060101
C12Q001/68; G01N 33/68 20060101 G01N033/68 |
Goverment Interests
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH
[0002] This invention was made with government support under NCI
Grant No. RO1 CA 128609 awarded by the Intramural Research Program
of the U.S. National Cancer Institute. The government has certain
rights in this invention.
Claims
1. A method of determining a hepatocellular carcinoma (HCC) subtype
in a subject comprising; a) analyzing a sample from the subject, by
laboratory assay, for a change in the level of expression of one or
more biomarkers relative to the level of expression of a
corresponding biomarker in at least one control sample, wherein the
biomarker consists of at least one of the biomarkers identified by
SEQ ID NOs: 1-39; b) correlating the change in the level of
expression of the biomarkers, relative to the level of expression
of the corresponding biomarker in the control sample, with the
presence of the subtype of HCC in the subject; and c) determining a
hepatocellular carcinoma (HCC) subtype as the subtype if one or
more of the biomarkers in the sample are high or low relative to
the level of expression of the corresponding biomarker in normal
liver as the at least one control sample, and determining a
hepatocellular subtype as not the HCC subtype if biomarkers in the
sample are not high or low relative to the level of expression of
the corresponding biomarker in normal liver as the at least one
control sample.
2. A method of determining a hepatocellular carcinoma (HCC) subtype
in a subject comprising a) analyzing a sample from the subject, by
laboratory assay, for a change in the level of expression of one or
more biomarkers relative to the level of expression of a
corresponding biomarker in at least one control sample, wherein the
biomarker consists of at least one of the biomarkers identified by
SEQ ID NOs:1-39; and b) correlating the change in the level of
expression of the biomarkers, relative to the level of expression
of the corresponding biomarker in the control sample, with the
presence of the subtype of HCC in the subject, c) determining a
hepatocellular carcinoma (HCC) subtype as: i) hepatic stem
cell-like hepatocellular carcinoma (HSC-HCC) subtype if one or more
of the biomarkers identified by SEQ ID NOs: 1-19 in the sample are
high or low relative to the level of expression of the
corresponding biomarker in normal liver as the at least one control
sample, and determining a hepatocellular carcinoma (HCC) subtype as
not HSC-HCC subtype if one or more of the biomarkers identified by
SEQ ID NOs:1-19 in the sample are not high or low relative to the
level of expression of the corresponding biomarker in normal liver
as the at least one control sample; or, ii) bile duct
epithelium-like hepatocellular carcinoma (BDE-HCC) subtype if one
or more of the biomarkers identified by SEQ ID NOs: 2, 9-12, 14-17
and 19-25 in the sample are high or low relative to the level of
expression of the corresponding biomarker in normal liver as the at
least one control sample, and determining a hepatocellular
carcinoma (HCC) subtype as not BDE-HCC subtype if one or more of
the biomarkers identified by SEQ ID NOs: 2, 9-12, 14-17 and 19-35
in the sample are not high or low relative to the level of
expression of the corresponding biomarker in normal liver as the at
least one control sample; or, iii) hepatocytic progenitor-like
hepatocellular carcinoma (HP-HCC) subtype if one or more of the
biomarkers identified by SEQ ID NOs: 1-8, 11-13, 17-18, 23, 28-29
and 33-39 in the sample are high or low relative to the level of
expression of the corresponding biomarker in normal liver as the at
least one control sample, and determining a hepatocellular
carcinoma (HCC) subtype as not HP-HCC subtype if one or more of the
biomarkers identified by SEQ ID NOs: 1-8, 11-13, 17-18, 23, 28-29
and 33-39 in the sample are not high or low relative to the level
of expression of the corresponding biomarker in normal liver as the
at least one control sample; or iv) mature hepatocyte-like
hepatocellular carcinoma (MH-HCC) subtype if one or more of the
biomarkers identified by SEQ ID NOs: 1, 8-12, 14-17, 19-24 and
26-39 in the sample are high or low relative to the level of
expression of the corresponding biomarker in normal liver as the at
least one control sample, and determining a hepatocellular
carcinoma (HCC) subtype as not MH-HCC subtype if one or more of the
biomarkers identified by SEQ ID NOs: 1, 8-12, 14-17, 19-24 and
26-39 in the sample are not high or low relative to the level of
expression of the corresponding biomarker in normal liver as the at
least one control sample
3. The method of claim 1, wherein the sample is selected from the
group consisting of liver tumor tissue, liver normal tissue, frozen
biopsy tissue, paraffin-embedded biopsy tissue, serum, plasma, and
combinations thereof.
4. The method of claim 1, wherein the sample is analyzed by one or
more methods selected from the group consisting of micro array
techniques, PCR amplification, RNA hybridization, in situ
hybridization, gel electrophoresis, and combinations thereof.
5. The method of claim 1, further including a step (d) of further
discriminating among subtypes: hepatic stem cell-like
hepatocellular carcinoma (HSC-HCC) subtype, bile duct epithelial
(BDE-HCC) subtype, hepatic stem cell (HSC-HCC) subtype, and
hepatocytic progenitor subtype (HP-HCC) subtype, by correlating an
alteration in the level of expression of one or more of the
biomarkers, relative to the level of expression of the
corresponding biomarker in the control sample.
6. The method of claim 1, wherein step (a) further comprises
determining an increased level of expression of at least 2, 3, 4,
5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22,
23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38 or
39 biomarkers.
7. The method of claim 1, wherein step (a) further includes
analyzing the sample for a change in the level of expression of at
least one or more biomarkers identified by SEQ ID NOs:1-15; and,
wherein step (b) further includes correlating an increase in the
level of expression of at least one or more biomarkers identified
by SEQ ID NOs: 1-15, relative to the level of expression of the
corresponding additional biomarker in normal liver as the at least
one control sample, with the presence of HSC-HCC subtype in the
subject.
8. The method of claim 1, wherein step (a) further includes
analyzing the sample for a change in the level of expression of at
least one or biomarkers identified by SEQ ID NOs: 16-19; and
wherein step (b) further includes correlating a decrease in the
level of expression of at least one or more biomarkers identified
by SEQ ID NOs: 16-19, relative to the level of expression of the
corresponding additional biomarker in normal live as the at least
one control sample, with the presence of HSC-HCC subtype in the
subject.
9. The method of claim 1, wherein step (a) further includes
analyzing the sample for a change in the level of expression of at
least one or more biomarkers identified by SEQ ID NOs: 9, 11-12,
14-17 and 19-30; and, wherein step (b) further includes correlating
an increase in the level of expression of at least one or more
biomarkers identified by SEQ ID NOs: 9, 11-12, 14-17and 19-30,
relative to the level of expression of the corresponding additional
biomarker in normal liver as the at least one control sample, with
the presence of BDE-HCC subtype in the subject.
10. The method of claim 1, wherein step (a) further includes
analyzing the sample for a change in the level of expression of at
least one or biomarkers identified by SEQ ID NOs: 2, 10 and 31-35;
and wherein step (b) further includes correlating a decrease in the
level of expression of at least one or more biomarkers identified
by SEQ ID NOs: 2, 10 and 31-35, relative to the level of expression
of the corresponding additional biomarker in normal live as the at
least one control sample, with the presence of BDE-HCC subtype in
the subject.
11. The method of claim 1, wherein step (a) further includes
analyzing the sample for a change in the level of expression of at
least one or more biomarkers identified by SEQ ID NOs: 18, 28-29
and 36-37; and, wherein step (b) further includes correlating an
increase in the level of expression of at least one or more
biomarkers identified by SEQ ID NOs: 18, 28-29 and 36-37, relative
to the level of expression of the corresponding additional
biomarker in normal liver as the at least one control sample, with
the presence of HP-HCC subtype in the subject.
12. The method of claim 1, wherein step (a) further includes
analyzing the sample for a change in the level of expression of at
least one or biomarkers identified by SEQ ID NOs: 1-8, 11-13, 17,
23 and 33-35; and wherein step (b) further includes correlating a
decrease in the level of expression of at least one or more
biomarkers identified by SEQ ID NOs: 1-8, 11-13, 17, 23 and 33-35,
relative to the level of expression of the corresponding additional
biomarker in normal live as the at least one control sample, with
the presence of HP-HCC subtype in the subject.
13. The method of claim 1, wherein step (a) further includes
analyzing the sample for a change in the level of expression of at
least one or more biomarkers identified by SEQ ID NOs: 1, 10, 31-35
and 38-39; and, wherein step (b) further includes correlating an
increase in the level of expression of at least one or more
biomarkers identified by SEQ ID NOs: 1, 10, 31-35 and 38-39,
relative to the level of expression of the corresponding additional
biomarker in normal liver as the at least one control sample, with
the presence of HP-HCC subtype in the subject.
14. The method of claim 1, wherein step (a) further includes
analyzing the sample for a change in the level of expression of at
least one or biomarkers identified by SEQ ID NOs :8-9, 11-12,
14-17, 19-24, 26-30 and 36-37; and wherein step (b) further
includes correlating a decrease in the level of expression of at
least one or more biomarkers identified by SEQ ID NOs: 8-9, 11-12,
14-17, 19-24, 26-30 and 36-37, relative to the level of expression
of the corresponding additional biomarker in normal live as the at
least one control sample, with the presence of HP-HCC subtype in
the subject.
15. The method of claim 1, wherein the sample is selected from the
group consisting of liver tumor tissue, liver normal tissue, frozen
biopsy tissue, paraffin-embedded biopsy tissue, serum, plasma, and
combinations thereof.
16. The method of claim 1, wherein the sample is analyzed by one or
more methods selected from the group consisting of micro array
techniques, PCR amplification, RNA hybridization, in situ
hybridization, gel electrophoresis, and combinations thereof.
17. The method of claim 1, wherein the sample is analyzed for 5 or
more of the biomarkers; 10 or more of the biomarkers; 15 or more of
the biomarkers; 20 or more of the biomarkers; 25 or more of the
biomarkers; or for 30 or more of the biomarkers.
18. A method of detecting a hepatocellular carcinoma (HCC) stem
cell in a biological sample comprising: a) analyzing a sample from
the subject, by laboratory assay, for a change in the level of
expression of one or more biomarkers relative to the level of
expression of a corresponding biomarker in at least one control
sample, wherein the biomarker consists of at least one miR-181
biomarker; b) correlating the change in the level of expression of
the miR-181 biomarkers, relative to the level of expression of the
corresponding biomarker in the control sample, with the presence of
the HCC stem cell; and c) determining the presence of the HCC stem
cell if one or more of the miR-181 biomarkers in the sample are
high or low relative to the level of expression of the
corresponding biomarker in normal liver as the at least one control
sample, and determining the absence of the HCC stem cell if
biomarkers in the sample are not high or low relative to the level
of expression of the corresponding biomarker in normal liver as the
at least one control sample.
19. The method of claim 18, wherein the miR-181 biomarker is
selected from the group consisting of miR-181a-1, miR-181a-2,
miR-181b-1, miR-181b-2, and miR-181c.
20. The method of claim 19, wherein the presence of: 2, 3, 4 and/or
5 miR-181 biomarkers are detected.
21. The method of claim 18, wherein the sample is selected from the
group consisting of liver tumor tissue, liver normal tissue, frozen
biopsy tissue, paraffin-embedded biopsy tissue, serum, plasma, and
combinations thereof.
22. The method of claim 18, further comprising: d) correlating the
presence of the HCC stem cell with the presence of a hepatocellular
carcinoma cell in the sample.
23. The method of claim 22, wherein the presence or absence of the
miR-181 biomarker in the sample is analyzed by one or more of the
techniques selected from the group consisting of micro array
techniques, PCR amplification, RNA hybridization, in situ
hybridization, gel electrophoresis, and combinations thereof.
24. The method of claim 18, further comprising determining the
prognosis of the subject.
25. The method of claim 24, which further comprises treating the
subject for the HCC subtype.
26. The method of claim 25, wherein the treatment comprises at
least one procedure selected from the group consisting of: hepatic
resection, transplantation, percutaneous ethanol injection,
radiofrequency ablation, chemoembolisation, chemotherapy, gene
therapy, beta-catenin inhibition, and combinations thereof.
27. The method of claim 25, wherein the treatment comprises
administering to the subject a beta-catenin inhibitor.
28. The method of claim 25, wherein the treatment comprises
administering an effective amount of a nucleic acid complementary
to a miR-181 selected from the group consisting of miR-181a-1,
miR-181a-2, miR-181b-1, miR-181b-2, miR-181c, and combinations
thereof.
29. A method of detecting the HSC-HCC subtype in a biological
sample from a subject, comprising: a) analyzing a sample from the
subject, by laboratory analysis, for the presence of an
EpCAM+AFP+stem cells, and b) correlating the presence of EpCAM+
AFP+ stem cells with the presence of the HSC-HCC subtype in the
sample.
30. The method of claim 29, wherein the stem cells are detected by
assaying the sample for a miR-181 biomarker.
31. The method of claim 30, wherein the miR-181 biomarkers are
selected from the group consisting of miR-181a-1, miR-181a-2,
miR-181b-1, miR-181b-2, miR-181c, and combinations thereof.
32. The method of claim 29, wherein the stem cells are detected by
methods selected from the group consisting of immunofluorescence,
in situ hybridization, immunohistochemical analysis, frozen
activator cell sorting, side population analysis, cell surface
marker detection methods, and combinations thereof.
33. The method of claim 1, further including a step (d) of:
treating a subject with HSC HCC subtype by administering a
therapeutically effective amount of an agent selected from the
group consisting of a beta-catenin inhibitor, at least one miR-181
biomarker inhibitor, and combinations thereof.
34. The method of claim 33, wherein the miR-181 biomarker inhibitor
comprises a reagent comprising a nucleic acid complementary to at
least one biomarker selected from the group consisting of
miR-181a-1, miR-181a-2, miR-181b-1, miR-181b-2, miR-181c, and
combinations thereof.
35. The method of claim 1, further including a step (d) of: i)
treating a subject with HSC-HCC subtype by administering an
effective amount of a reagent comprising nucleic acids
complementary to at least 5 biomarkers selected from the group
consisting of biomarkers identified by SEQ ID NOs: 1-19; or ii)
treating a subject with BDE-HCC subtype by administering an
effective amount of a reagent comprising nucleic acids
complementary to at least 5 biomarkers selected from the group
consisting of biomarkers identified by SEQ ID NOs: 2, 9-12, 14-17,
19-24, and 26-35; or, iii) treating a subject with HP-HCC subtype
by administering an effective amount of a reagent comprising
nucleic acids complementary to at least 5 biomarkers selected from
the group consisting of biomarkers identified by SEQ ID NOs: 1-8,
11-13, 17-18, 23, 28-29 and 33-39; or, iv) treating a subject with
MH-HCC subtype comprising administering an effective amount of a
reagent comprising nucleic acids complementary to at least 5
biomarkers selected from the group consisting of biomarkers
identified by SEQ ID NOs: 1, 8-12, 14-17, 19-24 and 26-39.
36. The method of claim 35, wherein the treatment further comprises
at least one procedure selected from the group consisting of
hepatic resection, hepatic transplantation, percutaneous ethanol
injection, radiofrequency ablation, chemoembolisation,
chemotherapy, gene therapy, beta-catenin inhibition, and
combinations thereof.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is filed under 35 U.S.C. .sctn.111(a) as a
divisional application which claims priority under 35 U.S.C.
.sctn.119, 35 U.S.C. .sctn.120, and the Patent Cooperation Treaty
to parent application U.S. Ser. No. 12/663,586 filed under 35
U.S.C. .sctn.371 on Apr. 21, 2010, now U.S. Pat. No. 8,465,916
issued Jun. 18, 2013; which claims priority to PCT/US08/07196 filed
under the authority of the Patent Cooperation Treat on Jun. 9,
2008, published; which claims priority to U.S. Provisional
Application Ser. No. 60/942,833 filed Jun. 8, 2007.
SEQUENCE LISTING
[0003] The instant application contains a Sequence Listing which
has been submitted in ASCII format via EFS-Web and is hereby
incorporated by reference in its entirety. Said ASCII copy, created
on Sep. 20, 2012, is named
604.sub.--50243_SEQ_LIST_OSU-2006-027-2.txt and is 6,868 bytes in
size.
BACKGROUND OF THE INVENTION
[0004] Hepatocellular carcinoma (HCC) is the third leading cause of
cancer death world-wide. HCC is very heterogeneous in terms of its
clinical presentation and genomic and transcriptomic patterns. The
heterogeneity in HCC and lack of appropriate biomarkers for its
detection and subtype identification has hampered patient prognosis
and treatment stratification.
[0005] Accordingly, there is a desire for one or more biomarkers
that can identify the subtype of HCC in a mammal, as well as
methods of providing appropriate treatment based on the subtype of
HCC.
BRIEF SUMMARY OF THE INVENTION
[0006] The invention provides a method of determining the subtype
of HCC in a subject, the method comprising a) obtaining a sample
from the subject, b) assaying the sample to detect at least 1
biomarkers, and c) correlating the biomarkers detected with an HCC
subtype in the subject. In this regard, the biomarkers are selected
from the group consisting of the biomarkers identified by SEQ ID
NOs: 1-39.
[0007] The invention also provides a method of detecting a HCC stem
cell in a sample. In one embodiment the inventive method comprises
a) obtaining a sample, b) assaying the sample to detect the
presence of a miR-181 biomarker, and c) correlating the presence or
absence of the miR-181 biomarker with the presence or absence of
the HCC stem cell in the sample.
[0008] The invention also provides methods and compositions for
treating subjects with HCC that take advantage of the biomarkers
associated with HCC stem cells.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS
[0009] FIG. 1A shows the expression of miR-181a-1 in log(2) ratio
(of tumor to nontumor tissue) in HSC-HCC cells based on microRNA
analysis.
[0010] FIG. 1B shows the expression of miR-181a-2 in log(2) ratio
(of tumor to nontumor tissue) in HSC, DBE, HP, and MH-HCC cells
based on microRNA analysis.
[0011] FIG. 1C shows the expression of miR-181b-1 in log(2) ratio
(of tumor to nontumor tissue) in HSC, DBE, HP, and MH-HCC cells
based on microRNA analysis.
[0012] FIG. 1D shows the expression of miR-181b-2 in log(2) ratio
(of tumor to nontumor tissue) in HSC, DBE, HP, and MH-HCC cells
based on microRNA analysis.
[0013] FIG. 1E shows the expression of miR-181c in log(2) ratio (of
tumor to nontumor tissue) in HSC, DBE, HP, and MH-HCC cells based
on microRNA analysis.
[0014] FIG. 1F shows the expression of miR-181-a in log(2) ratio
(of tumor to nontumor tissue) in HSC, DBE, HP, and MH-HCC cells as
determined by RT-PCR.
[0015] FIG. 1G shows the expression of miR-181-b in log(2) ratio
(of tumor to nontumor tissue) in HSC, DBE, HP, and MH-HCC cells as
determined by RT-PCR.
[0016] FIG. 1H shows the expression of miR-181c in log(2) ratio (of
tumor to nontumor tissue) in HSC, DBE, HP, and MH-HCC cells as
determined by RT-PCR.
[0017] FIG. 1I shows the expression of miR-181d in log(2) ratio (of
tumor to nontumor tissue) in HSC, DBE, HP, and MH-HCC cells as
determined by RT-PCR.
[0018] FIG. 1J shows the expression of miR-213 in log(2) ratio (of
tumor to nontumor tissue) in HSC, DBE, HP, and MH-HCC cells as
determined by RT-PCR.
[0019] FIG. 2A shows a scatter plot of miR-181a-1.
[0020] FIG. 2B shows a scatter plot of miR-181a-2.
[0021] FIG. 2C shows a scatter plot of miR-181b-1.
[0022] FIG. 2D shows a scatter plot of miR-181b-2.
[0023] FIG. 2E shows a scatter plot of miR-181c.
[0024] FIG. 3A a graph showing the fold production of the
miR-181-a, miR-181b, miR-181c, and miR-181d at 0, 2, and 8 days in
ESC media versus regular culture.
[0025] FIG. 3B is a graph showing the fold of the CAR and UGT2B7 at
0, 2, and 8 days in ESC media versus regular culture.
[0026] FIG. 3C a graph showing the fold production of CCND1 and
TACSTD1 at 0, 2, and 8 days in ESC media versus regular
culture.
[0027] FIG. 3D a graph showing the fold production of the
miR-181-a, miR-181b, miR-181c, and miR-181d at 0, 1, 2, and 8 days
following withdrawal of ESC media.
[0028] FIG. 3E a graph showing the fold production of CAR and
UGT2B7 at 0, 1, 2, and 8 days following withdrawal of ESC
media.
[0029] FIG. 3F a graph showing the fold production of CCND1 and
TCSTD1 at 0, 1, 2, and 8 days following withdrawal of ESC
media.
[0030] FIG. 4 is a graph of the relative expression of miR-181-b in
pMSCV-hTR and pMSCV-miR-181b-1 treated HuH1 cells.
[0031] FIG. 5 is a graph of the relative expression of miR-181s in
HuH7 cells transfected with 2'-O-methyl antisense versus
control.
[0032] FIG. 6A is a graph of the relative expression of CCND1 in
pMSCV-hTR and p-MSCV-miR-181b-1 treated HuH1 cells.
[0033] FIG. 6B is a graph of the relative expression of TACTD1 in
pMSCV-hTR and p-MSCV-miR-181b-1 treated HuH1 cells.
[0034] FIG. 6C is a graph of the relative expression of DKK1 in
pMSCV-hTR and p-MSCV-miR-181b-1 treated HuH1 cells.
[0035] FIG. 6D is a graph of the relative expression of CCND1 in
control and antisense treated HuH7 cells.
[0036] FIG. 6E is a graph of the relative expression of TACSTD1 in
control and antisense treated HuH7 cells.
[0037] FIG. 6F is a graph of the relative expression of DKK1 in
control and antisense treated HuH7 cells.
[0038] FIG. 7A shows the predicted binding site of miR-181-a (SEQ
ID NO: 41), miR-181-b (SEQ ID NO: 42), miR-181c (SEQ ID NO: 43),
and miR-181d (SEQ ID NO: 44) at the 611-632 3'-UTR of DKK1 (SEQ ID
NO: 40).
[0039] FIG. 7B shows predicted binding sites of miR-181-a (SEQ ID
NO: 41), miR-181-b (SEQ ID NO: 42), miR-181c (SEQ ID NO: 43), and
miR-181d (SEQ ID NO: 44) at the 771-799 3'-UTR of DKK1 (SEQ ID NO:
45).
[0040] FIG. 8A is a predicted TCF-4 binding site for miR-181a-1 and
miR-181b-1.
[0041] FIG. 8B is a predicted TCF-4 binding site for miR-181a-2 and
miR-181b-2.
[0042] FIG. 8C is a predicted TCF-4 binding site for miR-181c and
miR-181d.
[0043] FIG. 8D is another predicted TCF-4 binding site for miR-181c
and miR-181d.
[0044] FIG. 9 is a graph of the fold of miR-181-a, miR-181b,
miR-181c, and miR-181d in each cell line (Hep3b type B (HSC-HCC),
MHCC97 type C (HP-HCC), Smmc7721 type D (MH-HCC)) versus primary
hepatocytes.
[0045] FIG. 10 is a graph of the number of miRNAs with increased
and decreased expression in HSC-HCC, BDE-HCC, HP-HCC, and MH-HCC
subtypes.
DETAILED DESCRIPTION OF THE INVENTION
[0046] Micro RNAs (or miRNAs) are small non-coding RNA gene
products (e.g., .about.22 nt) that exist in many organisms and play
key regulatory roles in mRNA translation and degradation by base
pairing to partially complementary sites of the mRNA, predominantly
in the 3' untranslated region. Lee, Science, 294(5543):862-864
(2001); Lau, Science, 294(5543):858-862 (2001); Lagos, Science,
294(5543):853-858 (2001). miRNAs are expressed as long precursor
RNAs that are processed by Drosha, a cellular nuclease, and
subsequently transported to the cytoplasm by an
Exportin-5-dependent mechanism. Yi, Genes Dev, 17(24):3011-3016
(2003); Gregory, Cancer Res., 65(9):3509-3512 (2005). miRNAs are
then cleaved by the DICER enzyme, resulting in approximately 17-24
nt miRNAs that associate with a RNA-induced silencing-like complex.
Lee, EMBO J, 21(17):4663-4670 (2002); Hutvagner, Science,
297(5589):2056-2060 (2002).
[0047] The invention is predicated on the finding miRNA biomarkers
are associated with HCC subtypes. For purposes of the invention,
the HCC subtypes refer to hepatic stem cell-like HCC (HSC-HCC),
which is epithelial cell adhesion molecule (EpCAM)+
alpha-fetoprotein (AFP)+; bile duct epithelium-like HCC (BDE-HCC),
which is EpCAM+ AFP-; hepatocytic progenitor-like HCC (HP-HCC),
which is EpCAM- AFP+; and mature hepatocyte-like HCC (MH-HCC),
which is EpCAM-AFP-. The invention provides a set of biomarkers
useful in identifying each HCC subtype.
[0048] In one embodiment, the invention provides a method of
determining an HCC subtype in a subject comprising a) obtaining a
sample from the subject, b) analyzing the sample for the expression
of 1 or more biomarkers, and c) correlating the expression of the 1
or more biomarkers with the subtype of HCC in the subject. The
expression of the biomarkers may be decreased or increased relative
to normal control. The biomarkers are identified by SEQ ID NOs:
1-39 (see Table 1). In the inventive method, it is preferred that 2
or more, 5 or more, 10 or more, 15 or more, 20 or more, 25 or more,
30 or more, or 35 or more biomarkers are analyzed. More preferably,
all 39 biomarkers are analyzed. For the determination of the
HSC-HCC subtype, preferably at least the biomarkers identified by
SEQ ID NOs: 1-19 are analyzed. For the determination of the BDE-HCC
subtype, preferably at least the biomarkers identified by SEQ ID
NOs: 2, 9-17, and 19-35 are analyzed. For the determination of the
HP-HCC subtype, preferably at least the biomarkers identified by
SEQ ID NOs: 1-8, 11-13, 17-18, 23, 28-29, and 33-39 are analyzed.
For the determination of the MH-HCC subtype, preferably at least
the biomarkers identified by SEQ ID NOs: 1, 8-12, 14-17, and 19-39
are analyzed.
[0049] In addition, it has been discovered that in contrast to
mature liver cells, HCC stem cells are associated with (i.e., they
express) the miR-181 family of miRNA biomarkers, particularly, miR-
181a-1, miR-181a-2, miR-181b-1, miR-181b-2, and miR-181c, and that
presence of HCC stem cells in a sample are indicative of the
HSC-HCC subtype, which is associated with poor prognosis.
Accordingly, in one embodiment, the invention provides a method of
detecting the presence of HCC stem cells in a sample comprising a)
obtaining a sample, b) assaying the sample to detect the presence
of a miR-181 biomarker, and c) correlating the presence or absence
of the miR-181 biomarker with the presence or absence of the HCC
stem cell in the sample. For example, alternatively, EpCAM+AFP+HCC
stem cells may be detected by any suitable methods, e.g.,
immunofluorescence, immunohistochemistry, frozen activator cell
sorting, side population methods, cell surface marker detection
methods or in situ hybridization. For instance, in the side
population technique, the cell-permeable DNA-binding dye Hoechst
33342 is loaded into the cell population of interest; stem cells
and early progenitors subsequently pump this dye out via an
ATP-binding cassette membrane pump-dependent mechanism, resulting
in a low-fluorescence "tail" when the cells are analyzed by flow
cytometry. In one embodiment, the method further comprises
correlating the presence of the HCC stem cell in the sample with
presence of HSC-HCC subtype in the sample. Advantageously, the
detection of HCC stem cells in a sample may allow for earlier
detection of the HSC-HCC subtype in a subject and thus lead to a
greater likelihood of successful treatment and survival.
[0050] As used here, the term "biomarkers" is used interchangeably
with "miRNA" and refers to those biomarkers associated with HCC,
which include at least the 39 biomarkers in Table 1. In the
inventive method, some (i.e., 1, 2, 3, 4, 5, 7, 7, 8, 9, 10, 15,
20, 25, 30, or 35) or all 39 of the biomarkers may be detected.
Preferably, at least 2 or more, more preferably at least 5 or more
biomarkers are detected. In embodiments where a miR-181 biomarker
is detected, the biomarker may be one or more of miR-181a-1,
miR-181a-2, miR-181b-1, miR-181b-2, and miR-181c, preferably. In
this regard, some (i.e., 1, 2, 3, or 4) or all 5 of the miR-181
biomarkers are detected.
[0051] Suitable techniques for determining the presence and level
of expression of the biomarkers in samples are within the skill in
the art. According to one such method, total cellular RNA can be
purified from cells by homogenization in the presence of nucleic
acid extraction buffer, followed by centrifugation. Nucleic acids
are precipitated, and DNA is removed by treatment with DNase and
precipitation. The RNA molecules are then separated by gel
electrophoresis on agarose gels according to standard techniques,
and transferred to nitrocellulose filters by, e.g., the so-called
"Northern" blotting technique. The RNA is then immobilized on the
filters by heating. Detection and quantification of specific RNA is
accomplished using appropriately labeled DNA or RNA probes
complementary to the RNA in question. See, for example, Molecular
Cloning: A Laboratory Manual, J. Sambrook et al., eds., 2nd
edition, Cold Spring Harbor Laboratory Press, 1989, Chapter 7, the
entire disclosure of which is incorporated by reference.
[0052] Methods for preparation of labeled DNA and RNA probes, and
the conditions for hybridization thereof to target nucleotide
sequences, are described in Molecular Cloning: A Laboratory Manual,
J. Sambrook et al., eds., 2nd edition, Cold Spring Harbor
Laboratory Press, 1989, Chapters 10 and 11, the disclosures of
which are herein incorporated by reference. For example, the
nucleic acid probe can be labeled with, e.g., a radionuclide such
as .sup.3H, .sup.32P, .sup.33P, .sup.14C, or .sup.35S; a heavy
metal; or a ligand capable of functioning as a specific binding
pair member for a labeled ligand (e.g., biotin, avidin or an
antibody), a fluorescent molecule, a chemiluminescent molecule, an
enzyme or the like.
[0053] Probes can be labeled to high specific activity by either
the nick translation method of Rigby et al, J. Mol. Biol.,
113:237-251(1977) or by the random priming method of Fienberg,
Anal. Biochem., 132:6-13 (1983), the entire disclosures of which
are herein incorporated by reference. The latter can be a method
for synthesizing .sup.32P-labeled probes of high specific activity
from RNA templates. For example, by replacing preexisting
nucleotides with highly radioactive nucleotides according to the
nick translation method, it is possible to prepare .sup.32P-labeled
nucleic acid probes with a specific activity well in excess of
10.sup.8 cpm/microgram. Autoradiographic detection of hybridization
can then be performed by exposing hybridized filters to
photographic film. Densitometric scanning of the photographic films
exposed by the hybridized filters provides an accurate measurement
of biomarker levels. Using another approach, biomarker levels can
be quantified by computerized imaging systems, such the Molecular
Dynamics 400-B 2D Phosphorimager (Amersham Biosciences, Piscataway,
N.J.).
[0054] Where radionuclide labeling of DNA or RNA probes is not
practical, the random-primer method can be used to incorporate an
analogue, for example, the dTTP analogue 5-(N-(N-biotinyl-
epsilon-aminocaproyl)-3-aminoally)deoxyuridine triphosphate, into
the probe molecule. The biotinylated probe oligonucleotide can be
detected by reaction with biotin-binding proteins, such as avidin,
streptavidin, and antibodies (e.g., anti-biotin antibodies) coupled
to fluorescent dyes or enzymes that produce color reactions.
[0055] In addition to Northern and other RNA blotting hybridization
techniques, determining the levels of RNA expression can be
accomplished using the technique of in situ hybridization. This
technique requires fewer cells than the Northern blotting
technique, and involves depositing whole cells onto a microscope
cover slip and probing the nucleic acid content of the cell with a
solution containing radioactive or otherwise labeled nucleic acid
(e.g., cDNA or RNA) probes. This technique is particularly
well-suited for analyzing tissue biopsy samples from subjects. The
practice of the in situ hybridization technique is described in
more detail in U.S. Pat. No. 5,427,916, the entire disclosure of
which is incorporated herein by reference.
[0056] The relative number of mi-RNAs in a sample can also be
determined by reverse transcription, followed by amplification of
the reverse-transcribed transcripts by polymerase chain reaction
(RT-PCR). The levels of RNA transcripts can be quantified in
comparison with an internal standard, for example, the level of
mRNA from a standard gene present in the same sample. A suitable
gene for use as an internal standard includes, e.g., myosin or
glyceraldehyde-3-phosphate dehydrogenase (G3PDH). The methods for
quantitative RT-PCR and variations thereof are within the skill in
the art.
[0057] In some instances, it may be desirable to simultaneously
determine the expression level of a plurality of different
biomarker genes in a sample. In certain instances, it may be
desirable to determine the expression level of the transcripts of
all known biomarker genes correlated with HCC. Assessing
cancer-specific expression levels for hundreds of biomarker genes
is time consuming and requires a large amount of total RNA (at
least 20 .mu.g for each Northern blot) and autoradiographic
techniques that require radioactive isotopes. To overcome these
limitations, an oligolibrary in microchip format may be constructed
containing a set of probe oligonucleotides specific for a set of
biomarker genes. For example, the oligolibrary may contain probes
corresponding to all known biomarkers from the human genome. The
microchip oligolibrary may be expanded to include additional miRNAs
as they are discovered.
[0058] The microchip is prepared from gene-specific oligonucleotide
probes generated from known miRNAs. For example, the array may
contain two different oligonucleotide probes for each miRNA, one
containing the active sequence and the other being specific for the
precursor of the miRNA. The array may also contain controls such as
one or more mouse sequences differing from human orthologs by only
a few bases, which can serve as controls for hybridization
stringency conditions. tRNAs from both species may also be printed
on the microchip, providing an internal, relatively stable positive
control for specific hybridization. One or more appropriate
controls for non-specific hybridization may also be included on the
microchip. For this purpose, sequences are selected based upon the
absence of any homology with any known miRNAs.
[0059] The microchip may be fabricated by techniques known in the
art. For example, probe oligonucleotides of an appropriate length,
e.g., 20 nucleotides, are 5'-amine modified at position C6 and
printed using suitable available microarray systems, e.g., the
GENEMACHINE OmniGrid 100 Microarrayer and Amersham CODELINK
activated slides. Labeled cDNA oligomer corresponding to the target
RNAs is prepared by reverse transcribing the target RNA with
labeled primer. Following first strand synthesis, the RNA/DNA
hybrids are denatured to degrade the RNA templates. The labeled
target cDNAs thus prepared are then hybridized to the microarray
chip under hybridizing conditions, e.g. 6 times SSPE/30% formamide
at 25 degrees C. for 18 hours, followed by washing in 0.75 times
TNT at 37 degrees C., for 40 minutes. At positions on the array
where the immobilized probe DNA recognizes a complementary target
cDNA in the sample, hybridization occurs. The labeled target cDNA
marks the exact position on the array where binding occurs,
allowing automatic detection and quantification. The output
consists of a list of hybridization events, indicating the relative
abundance of specific cDNA sequences, and therefore the relative
abundance of the corresponding complementary biomarker, in the
subject sample. In an example, the labeled cDNA oligomer is a
biotin-labeled cDNA, prepared from a biotin-labeled primer. The
microarray is then processed by direct detection of the
biotin-containing transcripts using, e.g., Streptavidin-Alexa647
conjugate, and scanned utilizing conventional scanning methods.
Image intensities of each spot on the array are proportional to the
abundance of the corresponding biomarker in the subject sample.
[0060] The use of the array has one or more advantages for miRNA
expression detection. First, the global expression of several
hundred genes can be identified in a same sample at one time point.
Second, through careful design of the oligonucleotide probes,
expression of both mature and precursor molecules can be
identified. Third, in comparison with Northern blot analysis, the
chip requires a small amount of RNA, and provides reproducible
results using as low as 2.5 .mu.g of total RNA. The relatively
limited number of miRNAs (a few hundred per species) allows the
construction of a common microarray for several species, with
distinct oligonucleotide probes for each. Such a tool would allow
for analysis of trans-species expression for each known biomarker
under various conditions.
[0061] The subject may be a human or animal presenting with
symptoms of HCC. Preferably, the subject is a human. The subject
may or may not also have hepatitis B virus or cirrhosis (such as
alcohol induced, primary biliary cirrhosis, genetic
haemchromatosis, autoimmune hepatitis, primary sclerosing
cholangitis). The HCC may be a solitary tumor, multinodular tumor,
and/or a metastatic lesion.
[0062] The sample obtained from the subject may be liver tissue,
which can be tumor tissue or normal tissue. Alternatively, the
sample may be from the subject's serum or plasma, frozen biopsy
tissue, paraffin embedded biopsy tissue, and combinations
thereof.
[0063] The invention further provides a method for determining the
prognosis of a subject by determining whether the subject has the
HSC HCC, BDE-HCC, HP-HCC, or MH-HCC subtype. The inventive method
of prognosis may be utilized in lieu of current methods of
prognosis. Alternatively, the inventive method may be utilized in
conjunction with conventional methods of prognosis. When a combined
approach is utilized, the traditional prognostic approaches may
include spiral computed tomography (CT) of the liver and thorax,
magnetic resonance imaging (MRI) with contrast enhancement or
angiography with lipiodol injection, and biopsy, as well as current
staging systems.
[0064] The method further provides a treatment regimen that may be
devised for the subject on the basis of the HCC subtype in the
subject. In this regard, the inventive method allows for a more
personalized approach to medicine as the aggressiveness of
treatment may be tailored to the subtype of HCC in the subject.
[0065] In one embodiment, the invention takes advantage of the
association between the biomarkers and the HCC subtypes.
Accordingly, the invention provides methods of treatment comprising
administering a therapeutically effective amount of a composition
comprising a reagent comprising nucleic acid complementary to at
least one of the biomarkers associated with HSC-HCC, BDE-HCC,
HP-HCC, or MH-HCC.
[0066] In another embodiment, the invention takes advantage of the
association between the miR-181 biomarkers and HCC stem cells in
order to determine the HCC subtype in a subject and, optionally,
correlate the HCC-subtype in the patient with a prognosis. The
miR-181 biomarkers are associated with the hepatic stem cell-like
(HSC) HCC subtype, which is EpCAM and AFP positive. EpCAM is a
transmembrane protein containing three extracellular domains and
one cytoplasmic domain. The function of EpCAM and the regulatory
mechanism of its expression are largely unknown but are thought to
involve cell-cell adhesion (Winter, Exp. Cell. Res., 285(1): 50-58
(2003)). EpCAM and AFP are not expressed in mature liver tissue.
The HSC HCC subtype typically has a poor prognosis and survival
outcome (Lee, Hepatology, 40(3): 667-676 (2004); Lee, Nat. Med.,
12(4): 410-416 (2006)). Accordingly, the invention provides a
method of determining whether the HCC detected is the HSC HCC
subtype. The determination of the HCC subtype is particularly
useful in determining the appropriate treatment for the subject,
particularly because the EPCAM+AFP+HCC is associated with
Wnt-.beta.-catenin signaling. Wnt-.beta.-catenin signaling is
critical for maintaining the function of stem cells and abnormal
activation has been linked to many human cancers, including HCC.
The miR-181s can contribute Wnt-.beta.-catenin signaling
activation, possibly through Dickkoph-1 (i.e., DKK1) and nemo-like
kinase (i.e., NLK), which are inhibitors of the Wnt-.beta.-catenin
pathway. The invention takes advantage of the regulatory link
between miR-181s and HCC stem cells, and provides methods of
prognosis, and treatment based thereon.
[0067] Treatment options may include traditional treatments as well
as gene therapy approaches that specifically target the miRNAs
described herein. Traditional treatment of HCC includes, for
example, percutaneous ethanol injection (PEI), radiofrequency
ablation, chemoembolisation, and chemotherapy. Treatment is
determined based on the status of the subject and guidelines are
known in the art. (See for example, Ryder, Gut, 52:1-8 (2003)).
[0068] The invention further provides pharmaceutical compositions
for use in the inventive treatment methods. In this regard, the
invention provides a composition comprising a therapeutically
effective amount of a reagent comprising a nucleic acid or nucleic
acids complementary to at least one, preferably at least two of the
biomarkers selected from those identified by SEQ ID NOs: 1-39 and a
pharmaceutically acceptable carrier. Alternatively, the reagent may
comprise nucleic acids complementary to at least 5 or more, 10 or
more, 15 or more, 20 or more, 25 or more, 30 or more, or 35 or more
of the biomarkers. The reagent may comprise only the nucleic acids
or the nucleic acids in combination with delivery reagents such as
recombinant plasmids, viral vectors, liposomes, etc. Preferably,
for the treatment of HSC-HCC, the composition comprises nucleic
acids complementary to the biomarkers identified by SEQ ID NOs:
1-19, even more preferably, the composition comprises nucleic acids
complementary to miR-181a-1, miR-181a-2, miR-181b-1, miR-181b-2,
and miR-181c, and a pharmaceutically acceptable carrier.
Preferably, for the treatment of BDE-HCC, the composition comprises
nucleic acids complementary to at least one, preferably at least 2
biomarkers identified by SEQ ID NOs: 2, 9-17, and 19-35, and a
pharmaceutically acceptable carrier. Preferably, for the treatment
of HP-HCC, the composition comprises nucleic acids complementary to
at least one, preferably at least two biomarkers identified by SEQ
ID NOs: 1-8, 11-13, 17-18, 23, 28, 29, and 33-39, and a
pharmaceutically acceptable carrier. Preferably, for the treatment
of MH-HCC, the composition comprises nucleic acids complementary to
at least one, preferably to at least two biomarkers identified by
SEQ ID NOs: 1, 8-12, 14-17, and 19-39, and a pharmaceutically
acceptable carrier. The composition may bind and/or render
ineffective (i.e., inhibit) the biomarkers, or alternatively, alter
the expression of the gene coding for the biomarkers, thereby
altering the amounts or levels of biomarkers produced, the
technology for which are well known within the art.
[0069] In the practice of the present treatment methods, an
effective amount of at least one composition which inhibits at
least one of the biomarkers can also be administered to the
subject. As used herein, "inhibiting" means that the biomarker
levels and/or production of biomarker gene product from the
corresponding gene in the cancer cell after treatment is less than
the amount produced prior to treatment. In another embodiment, a
composition that increases the expression of one or more of the
biomarkers may be administered. One skilled in the art can readily
determine whether biomarker levels or gene expression has been
inhibited or increased in a cancer cell, using for example the
techniques for determining biomarker transcript level discussed
above.
[0070] As used herein, an "effective amount" of a composition that
inhibits the biomarkers or biomarker gene expression is an amount
sufficient to inhibit proliferation of a cancer cell in a subject
suffering from HCC. One skilled in the art can readily determine an
effective amount of an inhibiting composition to be administered to
a given subject, by taking into account factors such as the size
and weight of the subject; the extent of disease penetration; the
age, health and sex of the subject; the route of administration;
and whether the administration is regional or systemic.
[0071] For example, an effective amount of the expression-altering
composition can be based on the approximate weight of a tumor mass
to be treated. The approximate weight of a tumor mass can be
determined by calculating the approximate volume of the mass,
wherein one cubic centimeter of volume is roughly equivalent to one
gram. Therefore, in one embodiment, an effective amount based on
the weight of a tumor mass can utilized. Alternatively, an
effective amount of the composition can be based on the approximate
or estimated body weight of a subject to be treated. Preferably,
such effective amounts are administered parenterally or
enterally.
[0072] One skilled in the art can also readily determine an
appropriate dosage regimen for administering a composition that
alters biomarker levels or gene expression to a given subject. For
example, the composition can be administered to the subject once
(e.g. as a single injection or deposition). Alternatively, the
composition can be administered once or twice daily to a subject
for a period of from about three to about twenty-eight days, more
preferably from about seven to about ten days. Alternatively, the
composition may be administered once a day for seven days. Where a
dosage regimen comprises multiple administrations, it is understood
that the effective amount of the composition administered to the
subject can comprise the total amount of composition administered
over the entire dosage regimen.
[0073] Suitable compositions for inhibiting biomarker gene
expression include double-stranded RNA (such as short- or
small-interfering RNA or "siRNA"), antisense nucleic acids, and
enzymatic RNA molecules such as ribozymes. Each of these
compositions can be targeted to a given biomarker gene product and
destroy or induce the destruction of the target biomarker gene
product.
[0074] For example, expression of a given biomarker gene can be
inhibited by inducing RNA interference of the biomarker gene with
an isolated double-stranded RNA ("dsRNA") molecule which has at
least 90%, for example 95%, 98%, 99% or 100%, sequence homology
with at least a portion of the biomarker gene product. In a
preferred embodiment, the dsRNA molecule is a "short or small
interfering RNA" or "siRNA."
[0075] siRNA useful in the present methods comprise short
double-stranded RNA from about 17 nucleotides to about 29
nucleotides in length, preferably from about 19 to about 25
nucleotides in length. The siRNA comprise a sense RNA strand and a
complementary antisense RNA strand annealed together by standard
Watson-Crick base-pairing interactions (hereinafter "base-paired").
The sense strand comprises a nucleic acid sequence which is
substantially identical to a nucleic acid sequence contained within
the target biomarker gene product.
[0076] As used herein, the siRNA is "substantially identical" to a
target sequence contained within the target nucleic sequence, is a
nucleic acid sequence that is identical to the target sequence, or
that differs from the target sequence by one or two nucleotides.
The sense and antisense strands of the siRNA can comprise two
complementary, single-stranded RNA molecules, or can comprise a
single molecule in which two complementary portions are base-paired
and are covalently linked by a single-stranded "hairpin" area.
[0077] The siRNA can also be an altered RNA that differs from
naturally-occurring RNA by the addition, deletion, substitution
and/or alteration of one or more nucleotides. Such alterations can
include addition of non-nucleotide material, such as to the end(s)
of the siRNA or to one or more internal nucleotides of the siRNA,
or modifications that make the siRNA resistant to nuclease
digestion, or the substitution of one or more nucleotides in the
siRNA with deoxyribonucleotides.
[0078] One or both strands of the siRNA can also comprise a 3'
overhang. As used herein, a "3' overhang" refers to at least one
unpaired nucleotide extending from the 3'-end of a duplexed RNA
strand. Thus, in one embodiment, the siRNA comprises at least one
3' overhang of from 1 to about 6 nucleotides (which includes
ribonucleotides or deoxyribonucleotides) in length, preferably from
1 to about 5 nucleotides in length, more preferably from 1 to about
4 nucleotides in length, and particularly preferably from about 2
to about 4 nucleotides in length. In a preferred embodiment, the 3'
overhang is present on both strands of the siRNA, and is 2
nucleotides in length. For example, each strand of the siRNA can
comprise 3' overhangs of dithymidylic acid ("TT") or diuridylic
acid ("uu").
[0079] The siRNA can be produced chemically or biologically, or can
be expressed from a recombinant plasmid or viral vector for the
isolated biomarker gene products. Exemplary methods for producing
and testing dsRNA or siRNA molecules are described in U.S.
Published Patent Application No. 2002/0173478 and U.S. Pat. No.
7,148,342, the entire disclosures of which are herein incorporated
by reference.
[0080] Expression of a given biomarker gene can also be inhibited
by an antisense nucleic acid. As used herein, an "antisense nucleic
acid" refers to a nucleic acid molecule that binds to target RNA by
means of RNA-RNA or RNA-DNA or RNA-peptide nucleic acid
interactions, which alters the activity of the target RNA.
Antisense nucleic acids suitable for use in the present methods are
single-stranded nucleic acids (e.g., RNA, DNA, RNA-DNA chimeras,
PNA) that generally comprise a nucleic acid sequence complementary
to a contiguous nucleic acid sequence in a biomarker gene product.
Preferably, the antisense nucleic acid comprises a nucleic acid
sequence that is 50-100% complementary, more preferably 75-100%
complementary, and most preferably 95-100% complementary to a
contiguous nucleic acid sequence in an biomarker gene product.
[0081] Antisense nucleic acids can also contain modifications to
the nucleic acid backbone or to the sugar and base moieties (or
their equivalent) to enhance target specificity, nuclease
resistance, delivery or other properties related to efficacy of the
molecule. Such modifications include cholesterol moieties, duplex
intercalators such as acridine or the inclusion of one or more
nuclease-resistant groups.
[0082] Antisense nucleic acids can be produced chemically or
biologically, or can be expressed from a recombinant plasmid or
viral vector, as described above for the isolated biomarker gene
products. Exemplary methods for producing and testing are within
the skill in the art; see, e.g., Stein, Science, 261:1004 (1993)
and U.S. Pat. No. 5,849,902 to Woolf et al., the entire disclosures
of which are herein incorporated by reference.
[0083] Expression of a given biomarker gene can also be inhibited
by an enzymatic nucleic acid. As used herein, an "enzymatic nucleic
acid" refers to a nucleic acid comprising a substrate binding
region that has complementarity to a contiguous nucleic acid
sequence of a biomarker gene product, and which is able to
specifically cleave the biomarker gene product. Preferably, the
enzymatic nucleic acid substrate binding region is 50-100%
complementary, more preferably 75-100% complementary, and most
preferably 95-100% complementary to a contiguous nucleic acid
sequence in a biomarker gene product. The enzymatic nucleic acids
can also comprise modifications at the base, sugar, and/or
phosphate groups. An exemplary enzymatic nucleic acid for use in
the present methods is a ribozyme.
[0084] The enzymatic nucleic acids can be produced chemically or
biologically, or can be expressed from a recombinant plasmid or
viral vector, as described above for the isolated biomarker gene
products. Exemplary methods for producing and testing dsRNA or
siRNA molecules are described in Werner, Nucl. Acids Res.,
23:2092-96 (1995); Hammann, Antisense and Nucleic Acid Drug Dev.,
9:25-31 (1999); and U.S. Pat. No. 4,987,071, the entire disclosures
of which are herein incorporated by reference.
[0085] Administration of at least one composition for inhibiting at
least one biomarker or expression of a biomarker gene will inhibit
the proliferation of cancer cells in a subject who has HCC. As used
herein, to "inhibit the proliferation of a cancer cell" means to
kill the cell, or permanently or temporarily arrest or slow the
growth of the cell Inhibition of cancer cell proliferation can be
inferred if the number of such cells in the subject remains
constant or decreases after administration of the inventive
composition. An inhibition of cancer cell proliferation can also be
inferred if the absolute number of such cells increases, but the
rate of tumor growth decreases.
[0086] The number of cancer cells in a subject's body can be
determined by direct measurement, or by estimation from the size of
primary or metastatic tumor masses. For example, the number of
cancer cells in a subject can be measured by immunohistological
methods, flow cytometry, or other techniques designed to detect
characteristic surface markers of cancer cells.
[0087] The size of a tumor mass can be ascertained by direct visual
observation, or by diagnostic imaging methods, such as X-ray,
magnetic resonance imaging, ultrasound, and scintigraphy.
Diagnostic imaging methods used to ascertain size of the tumor mass
can be employed with or without contrast agents, as is known in the
art. The size of a tumor mass can also be ascertained by physical
means, such as palpation of the tissue mass or measurement of the
tissue mass with a measuring instrument, such as a caliper.
[0088] The inventive compositions can be administered to a subject
by any method suitable for delivering these compositions to the
cancer cells of the subject. For example, the compositions can be
administered by methods suitable to transfect cells of the subject
with these compositions. Preferably, the cells are transfected with
a plasmid or viral vector comprising sequences encoding at least
one biomarker gene product or biomarker gene expression inhibiting
composition.
[0089] Transfection methods for eukaryotic cells are well known in
the art, and include, e.g., direct injection of the nucleic acid
into the nucleus or pronucleus of a cell; electroporation; liposome
transfer or transfer mediated by lipophilic materials; receptor
mediated nucleic acid delivery, bioballistic or particle
acceleration; calcium phosphate precipitation, and transfection
mediated by viral vectors.
[0090] For example, cells can be transfected with a liposomal
transfer composition, e.g., DOTAP
(N-[1-(2,3-dioleoyloxy)propyl]-N,N,N-trimethyl-ammonium
methylsulfate, Boehringer-Mannheim) or an equivalent, such as
LIPOFECTIN. The amount of nucleic acid used is not critical to the
practice of the invention; acceptable results may be achieved with
0.1-100 micrograms of nucleic acid/10.sup.5 cells. For example, a
ratio of about 0.5 micrograms of plasmid vector in 3 micrograms of
DOTAP per 10.sup.5 cells can be used.
[0091] The composition can also be administered to a subject by any
suitable enteral or parenteral administration route. Suitable
enteral administration routes for the present methods include,
e.g., oral, rectal, or intranasal delivery. Suitable parenteral
administration routes include, e.g., intravascular administration
(e.g., intravenous bolus injection, intravenous infusion,
intra-arterial bolus injection, intra-arterial infusion and
catheter instillation into the vasculature); peri- and intra-tissue
injection (e.g., peri-tumoral and intra-tumoral injection,
intra-retinal injection, or subretinal injection); subcutaneous
injection or deposition, including subcutaneous infusion (such as
by osmotic pumps); direct application to the tissue of interest,
for example by a catheter or other placement device (e.g., a
retinal pellet or a suppository or an implant comprising a porous,
non-porous, or gelatinous material); and inhalation. Preferred
administration routes are injection, infusion and direct injection
into the tumor.
[0092] In the present methods, the composition can be administered
to the subject either as naked RNA, in combination with a delivery
reagent, or as a nucleic acid (e.g., a recombinant plasmid or viral
vector) comprising sequences that express the biomarker gene
product or expression inhibiting composition. Suitable delivery
reagents include, e.g., the Mirus Transit TKO lipophilic reagent;
lipofectin; lipofectamine; cellfectin; polycations (e.g.,
polylysine), and liposomes.
[0093] Recombinant plasmids and viral vectors comprising sequences
that express the biomarker or biomarker gene expression inhibiting
compositions, and techniques for delivering such plasmids and
vectors to cancer cells, are discussed above.
[0094] In a preferred embodiment, liposomes are used to deliver a
biomarker or biomarker gene expression-inhibiting composition (or
nucleic acids comprising sequences encoding them) to a subject.
Liposomes can also increase the blood half-life of the gene
products or nucleic acids.
[0095] Liposomes suitable for use in the invention can be formed
from standard vesicle-forming lipids, which generally include
neutral or negatively charged phospholipids and a sterol, such as
cholesterol. The selection of lipids is generally guided by
consideration of factors such as the desired liposome size and
half-life of the liposomes in the blood stream. A variety of
methods are known for preparing liposomes, for example, as
described in Szoka, Ann. Rev. Biophys. Bioeng., 9:467 (1980); and
U.S. Pat. Nos. 4,235,871, 4,501,728, 4,837,028, and 5,019,369, the
entire disclosures of which are herein incorporated by
reference.
[0096] The liposomes for use in the present methods can comprise a
ligand molecule that targets the liposome to cancer cells. Ligands
which bind to receptors prevalent in cancer cells, such as
monoclonal antibodies that bind to tumor cell antigens, are
preferred.
[0097] The compositions of the present invention may include a
pharmaceutically acceptable carrier. The term
"pharmaceutically-acceptable carrier" as used herein means one or
more compatible solid or liquid fillers, diluents, other
excipients, or encapsulating substances which are suitable for
administration into a human or veterinary patient. The term
"carrier" denotes an organic or inorganic ingredient, natural or
synthetic, with which the active ingredient is combined to
facilitate the application. The components of the pharmaceutical
compositions also are capable of being co-mingled with the
molecules of the present invention, and with each other, in a
manner so as not to substantially impair the desired pharmaceutical
efficacy. "Pharmaceutically acceptable" materials are capable of
administration to a patient without the production of undesirable
physiological effects such as nausea, dizziness, rash, or gastric
upset. It is, for example, desirable for a therapeutic composition
comprising pharmaceutically acceptable excipients not to be
immunogenic when administered to a human patient for therapeutic
purposes.
[0098] The pharmaceutical compositions may contain suitable
buffering agents, including: acetic acid in a salt; citric acid in
a salt; boric acid in a salt; and phosphoric acid in a salt. The
pharmaceutical compositions also may contain, optionally, suitable
preservatives, such as: benzalkonium chloride, chlorobutanol,
parabens and thimerosal.
[0099] The pharmaceutical compositions may conveniently be
presented in unit dosage form and may be prepared by any of the
methods well known in the art of pharmacy. All methods include the
step of bringing the active agent into association with a carrier
that constitutes one or more accessory ingredients. In general, the
compositions are prepared by uniformly and intimately bringing the
active composition into association with a liquid carrier, a finely
divided solid carrier, or both, and then, if necessary, shaping the
product.
[0100] Compositions suitable for parenteral administration
conveniently comprise a sterile aqueous preparation of the
inventive composition, which is preferably isotonic with the blood
of the recipient. This aqueous preparation may be formulated
according to known methods using suitable dispersing or wetting
agents and suspending agents. The sterile injectable preparation
also may be a sterile injectable solution or suspension in a
non-toxic parenterally-acceptable diluent or solvent, for example,
as a solution in 1, 3-butane diol. Among the acceptable vehicles
and solvents that may be employed are water, Ringer's solution, 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 may be employed including
synthetic mono-or di-glycerides. In addition, fatty acids such as
oleic acid may be used in the preparation of injectables. Carrier
formulation suitable for oral, subcutaneous, intravenous,
intramuscular, etc administrations can be found in Remington's
Pharmaceutical Sciences, Mack Publishing Co., Easton, Pa. which is
incorporated herein in its entirety by reference thereto.
[0101] The delivery systems of the invention are designed to
include time-released, delayed release or sustained release
delivery systems such that the delivering of the inventive
composition occurs prior to, and with sufficient time, to cause
sensitization of the site to be treated. The inventive composition
may be used in conjunction with other therapeutic agents or
therapies. Such systems can avoid repeated administrations of the
inventive composition, increasing convenience to the subject and
the physician, and may be particularly suitable for certain
compositions of the present invention.
[0102] Many types of release delivery systems are available and
known to those of ordinary skill in the art. They include polymer
base systems such as poly(lactide-glycolide), copolyoxalates,
polycaprolactones, polyesteramides, polyorthoesters,
polyhydroxybutyric acid, and polyanhydrides. Microcapsules of the
foregoing polymers containing drags are described in, for example,
U.S. Pat. No. 5,075,109. Delivery systems also include non-polymer
systems that are: lipids including sterols such as cholesterol,
cholesterol esters and fatty acids or neutral fats such as
mono-di-and tri-glycerides; hydrogel release systems; sylastic
systems; peptide based systems; wax coatings; compressed tablets
using conventional binders and excipients; partially fused
implants; and the like. Specific examples include, but are not
limited to: (a) erosional systems in which the active composition
is contained in a form within a matrix such as those described in
U.S. Pat. Nos. 4,452,775, 4,667,014, 4,748,034 and 5,239,660 and
(b) diffusional systems in which an active component permeates at a
controlled rate from a polymer such as described in U.S. Pat. Nos.
3,832,253, and 3,854,480. In addition, pump-based hardware delivery
systems can be used, some of which are adapted for
implantation.
[0103] The invention further provides a method of assessing the
efficacy of treatment of HCC in a subject by determining whether
there are any remaining HCC stem cells remaining in the liver of
the subject following a course of treatment. In this regard, a
sample is obtained from the subject and assayed to detect the
presence or absence of a miR-181 biomarker. The presence or absence
of a miR-181 biomarker is then correlated with the presence or
absence, respectively, of EpCAM+ AFP+ HCC in a subject. This
information is used to determine whether treatment of the HCC in
the subject has or has not been effective.
[0104] The following examples further illustrate the invention but,
of course, should not be construed as in any way limiting its
scope.
EXAMPLES
[0105] The following techniques were utilized for the examples set
forth below.
[0106] Clinical specimens. Hepatic tissues were obtained with
informed consent from subjects who underwent radical resection
between 2002 and 2003 at the Liver Cancer Institute and Zhongshan
Hospital (Fudan University, Shanghai, China). The study was
approved by the Institutional Review Board of the Liver Cancer
Institute and National Institutes of Health. The sample enrollment
criteria included those with a history of HBV infection or
HBV-related liver cirrhosis, HCC diagnosed by two independent
pathologists, detailed information on clinical presentation and
pathological characteristics, as well as detailed follow-up data
for at least 3 years, which included intrahepatic recurrence,
intrahepatic venous metastasis, lymph node involvement,
extrahepatic metastasis, disease-free, overall survival, and cause
of death. The updated TNM classification is superior to other
staging systems, including CLIP and OKUDA, for HCC subjects who
undergo resection and was therefore chosen to stratify early stage
subjects (TNM stage I and II) for analysis of miRNA prediction
capacity. Varotti, Eur J. Surg Oncol, 31(7):760-767 (2005); Huang
et al., J. Gastroenterol Hepatol, 20(5):765-771 (2005). A
prospective study revealed that the BCLC system was superior to the
new TNM classification system updated in 2002, therefore, Cox
proportional hazards modeling based on early stage subjects
categorized by BCLC (Stage 0 and A) was also performed. Gene
expression profiles were conducted in primary HCC and corresponding
noncancerous hepatic tissues from 244 Chinese HCC subjects. Among
them, 93% had underlying cirrhosis and 68% had a serum
alpha-fetoprotein (AFP) level >20 ng/mL A total of 134
well-defined cases were used as the training group. Among them, 30
had primary HCC lesions accompanied by tumor emboli found in the
major branches of the portal vein (n=25), inferior vena cava (n=2),
or common bile duct (n=4; one also with tumor thrombi in inferior
vena cava), and 104 had solitary HCC with no metastasis/recurrence
found at follow-up (3yr). In the validation analysis, a testing
group of 110 independent cases was used whose prognosis could not
be accurately determined at the time of resection by several HCC
staging mechanisms. The testing cases included 43 multinodular and
67 solitary HCC. Of the 43 multinodular HCC cases, 18 developed
intrahepatic recurrence and one developed extrahepatic metastasis
in addition to an intrahepatic recurrence. Of the 67 solitary HCC
cases, 4 subjects had a solitary tumor with an appearance of
aggregated nodules, 10 developed intra- and/or extrahepatic
metastasis while 49 developed intrahepatic recurrence confirmed at
follow-up (3 yr). In addition, eight normal liver tissues from
disease-free subjects (described in Budhu, Cancer Cell,
10(2):99-111 (2006)) were included as normal controls.
[0107] RNA isolation and miRNA arrays. The RNA isolation and miRNA
array methodology were carried out as described in Ye, Nat Med,
9(4):416-423 (2003); Calin, N Engl J. Med, 353(17):1793-1802
(2005). In the analysis of the 244 HCC cases, RNA was isolated in a
pairwise fashion from tumor or non-tumor tissue and samples were
selected in random order for miRNA analysis to avoid grouping bias.
A total of 488 microarrays were performed. The microarray platform
(V 2.0) was composed of 250 non-redundant human and 200 mouse
miRNAs. To examine the robustness of the miRNA microarray platform,
miRNA was analyzed to determine whether expression could
differentiate 244 tissues from their paired surrounding
noncancerous hepatic tissues. Using a supervised class comparison
method with univariate paired t-test and a multivariate test with
1000 permutations of the class label with the false discovery rate
set to .ltoreq.1 with a 99% confidence, 209 non-redundant miRNAs
were identified that could significantly discriminate HCC tumor
tissues (T) from their paired nontumor tissue (NT). These
significant miRNAs clearly separated T and NT samples, illustrated
by hierarchical clustering analysis. Multivariate class prediction
algorithm analyses with 10% cross-validation and 100 random
permutations indicated that these miRNAs can provide a
statistically significant prediction of T and NT samples
(p<0.01) with greater than 97% accuracy by the nearest neighbor
predictor. These initial analyses indicated that the miRNA arrays
were robust and could identify a significant difference between
tumor and noncancerous hepatic tissue.
[0108] Statistical analysis. Unsupervised hierarchical clustering
analysis was performed by the GENESIS software version 1.5
developed by Alexander Sturn (IBMT-TUG, Graz, Austria). The BRB
ArrayTools Software V3.3 was used for supervised analysis as
previously described (Ye, Nat Med, 9(4):416-423 (2003); Budhu,
Cancer Cell, 10(2):99-111 (2006)). The Kaplan-Meier survival
analysis was used to compare subject survival based on prediction
results, using Excel-based WinSTAT software. The statistical p
value was generated by the Cox-Mantel log-rank test. Cox
proportional hazards regression was used to analyze the effect of
sixteen clinical variables on subject survival or recurrence using
STATA 9.2 (College Station, Tex.). The statistical significance was
defined as p<0.05. TargetScan analysis was based on a website
tool developed by Ben Lewis (Lewis, Cell, 120(1):15-20 (2005)). Cox
proportional hazards regression was used to analyze the effect of
clinical variables on subject overall and relapse-free survival,
including age, sex, HBV active status, pre-resection AFP,
cirrhosis, alanine transferase (ALT), Child-Pugh score, tumor size,
tumor encapsulation, nodular type, status of microvascular
invasion, Edmondson grade, and several HCC prognosis staging
systems, including BCLC staging (Llovet, Semin Liver Dis,
19(3):329-338 (1999)); CLIP classification ("The Cancer of the
Liver Italian Program", Hepatology, 28(3):751-755 (1998)), Okuda
staging (Okuda, Cancer, 56(4):918-928 (1985)), and TNF
classification (American Joint Committee on Cancer
(AJCC)/International Union Against Cancer (UICC)'s TNM
Classification of Malignant Tumours, 6.sup.th Edition, Hoboken,
N.J., John Wiley & Sons 2002).
[0109] qRT-PCR. Total RNA was extracted using TRIzol (Invitrogen,
Carlsbad, Calif.). TACSTD1, BAMBI, DKK1, CCND1, CTNNB1, and MYC
expression were measured in triplicate using Applied Biosystems
7700 Sequence Detection System (Foster City, CA). Probes used were:
TACSTD1, Hs00158980_ml; CTNNB1, HS00170025_ml; BAMBI, HS00180818,
DKK1, Hs00183740_ml, CCND1, Hs00277039_ml, CTNNB1, MYC,
Hs00153408_ml; 18S, Hs999999901_sl (Applied Biosystems). All
procedures were performed according to manufacturer suggestion.
[0110] Immunohistochemical Analysis Immunohistochemical analysis
was performed using Envision+ kits (DAKO USA, Carpinteria, Calif.)
according to manufacturer instruction. Primary antibodies were used
as follows: anti-.beta.-catenin monoclonal antibody clone 14 (BD
Transduction Laboratories, San Jose, Calif.) and anti-EpCAM
monoclonal antibody clone VU-1D9 (Oncogene Research Products, San
Diego, Calif.).
[0111] Immunofluorescence. Cells were cultured on chamber slides
and treated with indicated chemicals for 48 h. Cells were then
fixed with 4% paraformaldehyde for 10 min, methanol for 20 min and
incubated in phosphate-buffered saline. Samples were blocked with
10% normal donkey serum for 1 h at room temperature and stained
with primary antibodies for 1 h at 37.degree. C., followed by Alexa
568 Texas Red-conjugated anti-mouse antibodies (Molecular Probes,
Eugene, Oreg.).
[0112] EMSA. Recombinant Tcf-4 was expressed in E. coli as GST
fusion protein and extracted. EMSA was performed using LightShift
Chemiluminescent EMSA kit (Pierce, Rockford, Ill.) according to
manufacturer instructions. Double-stranded DNA oligonucleotides
containing the putative Tcf binding sites of EpCAM promoter and 10
adjacent nucleotides upstream and downstream were constructed and
used as probes. Mutant TBE1 and TBE2 probes were also used.
[0113] Cell lines, antisense and plasmids. Known Hep3B type B,
MHCC97 type C, Smmc7721 type D, HUH1 and HUH7 HCC cell lines were
cultured routinely. Cells were transfected with pMSCV-miR-181b-1
for functional assays. HUH7 cells were also treated with
2'-O-methyl miR-181s antisense, an inhibitor of miR-181s.
Example 1
[0114] This example demonstrates that miRNA expression can
differentiate HCC tissue from non-cancerous tissue and can
distinguish among four subtypes of HCC.
[0115] Utilizing paired HCC tissue and surrounding non-HCC tissue
samples from a total of 230 HCC patients, a total of 209
non-redundant miRNAs were found to provide 97% accuracy in
correctly identifying the samples (multivariate p<0.01).
Heterogeneity of the samples was evident and the samples were
clustered based on the four HCC subtypes (HSC, BDE, HP, and
MH).
[0116] Expression of significant miRNAs among the four HCC subtypes
were sought. Hierarchical clustering revealed that 39 pre-miRNA
genes showed significant altered expression in the four HCC
subtypes (p<0.002, FDR<0.05) from overlapping genes based on
both class comparison and class prediction with a 10-fold cross
validation to establish prediction accuracy (Table 1). Of the 39
miRNAs, some were up-regulated and others were down-regulated in
each subtype (FIG. 10).
TABLE-US-00001 TABLE 1 HCC Group SEQ Para- Permu- ID gene gene
metric tation No. symbol location mature sequence p-value FDR
p-value BDE HSC 1 let-7a- 9q22.32 ugagguaguagguuguauagu 0.0002
0.0089 0.0003 720 1 2 let-7a- 11q24.1 ugagguaguagguuguauaguu 0.0003
0.0101 0.0003 1592 2 3 let-7a- 22q13.31 ugagguaguagguuguaugguu
0.0027 0.0362 0.0018 1406 3 4 let-7b 22q13.31
ugagguaguagguugugugguu 0.0041 0.0455 0.0037 2134 5 let-7c 21q21.1
ugagguaguagguuguaugguu 0.0019 0.0281 0.0013 1614 6 let-7d 9q22.32
agagguaguagguugcauagu 0.0002 0.0087 0.0002 893 7 let-7f- Xp11.22
ugagguaguagauuguauagu 0.0028 0.0362 0.0026 482 2 8 let-7g 3p21.2
ugagguaguaguuuguacagu 0.0006 0.0138 0.0003 1043 9 miR- 7q32.1
cuuuuugcggucugggcuugcu 0.0004 0.0116 0.0003 274 129-1 10 miR-
11p11.2 cuuuuugcggucugggcuugcu 0.0002 0.0085 0.0001 484 129-2 11
miR- 1q31.3 aacauucauugcugucgguggg 0.0000 0.0001 0.0000 1182 181b-1
12 miR 9q33.3 aacauucauugcugucgguggg 0.0000 0.0007 0.0000 12978
181b-2 13 miR- 12q13.13 uagguaguuucauguuguugg 0.0036 0.0410 0.0045
24665 196a-2 14 miR- 14q32.31 uccagcuccuauaugaugccuuu 0.0001 0.0084
0.0001 217 337 15 miR- 7q22.1 aaagugcuguucgugcagguag 0.0025 0.0343
0.0023 1973 93 16 miR- 13q31.3 caaagugcuuacagugcagguagu 0.0001
0.0079 0.0001 1608 17 17 miR- 19p13.12 aacauucaaccugucggugagu
0.0000 0.0011 0.0000 564 181c 18 miR- 17q23.2
cagugcaauaguauugucaaagc 0.0044 0.0473 0.0040 6047 301 19 miR-
Xq26.2 uauugcacuugucccggccug 0.0003 0.0101 0.0002 10397 92-2 BDE 20
miR- Xq26.2 aaaagugcuuacagugcagguagc 0.0002 0.0085 0.0001 1471 106a
21 miR- 7q22.1 uaaagugcugacagugcagau 0.0006 0.0135 0.0006 860 106b
9 miR- 7q32.1 cuuuuugcggucugggcuugcu 0.0004 0.0116 0.0003 274 129-1
16 miR- 13q31.3 caaagugcuuacagugcagguagu 0.0001 0.0079 0.0001 1608
17 22 miR- 1q31.3 aacauucaacgcugucggugagu 0.0004 0.0108 0.0003 1081
181-a-1 23 miR- 9q33.3 aacauucaacgcugucggugagu 0.0000 0.0039 0.0000
639 181-a-2 11 miR- 1q31.3 aacauucauugcugucgguggg 0.0000 0.0001
0.0000 1182 181b-1 12 miR- 9q33.3 aacauucauugcugucgguggg 0.0000
0.0007 0.0000 1298 181b-2 17 miR- 19p13.12 aacauucaaccugucggugagu
0.0000 0.0011 0.0000 564 181c 24 miR- 13q31.3
uaaagugcuuauagugcagguag 0.0005 0.0123 0.0007 1201 20a 25 miR-
Xp11.3 agcuacauugucugcuggguuu 0.0002 0.0085 0.0004 2023 221 26 miR-
Xp11.3 agcuacaucuggcuacugggucuc 0.0006 0.0135 0.0004 1573 222 27
miR- 7q22.1 cauugcacuugucucggucuga 0.0000 0.0039 0.0000 2713 25 28
miR- 9q31.3 uauugcacauuacuaaguugc 0.0000 0.0007 0.0000 1140 32 29
miR- 14q32.31 gcacauuacacggucgaccucu 0.0001 0.0079 0.0001 200 323
14 miR- 14q32.31 uccagcuccuauaugaugccuuu 0.0001 0.0084 0.0001 217
337 30 miR- 13q31.3 uauugcacuugucccggccug 0.0014 0.0218 0.0012
17617 92-1 19 miR- Xq26.2 uauugcacuugucccggccug 0.0003 0.0101
0.0002 10397 92-2 15 miR- 7q22.1 aaagugcuguucgugcagguag 0.0025
0.0343 0.0023 1973 93 2 let-7a- 11q24.1 ugagguaguagguuguauaguu
0.0003 0.0101 0.0003 1592 2 31 miR- 18q21.31
uggagugugacaaugguguuugu 0.0032 0.0391 0.0049 687 122a 32 miR-
11q24.1 ucccugagacccuaacuuguga 0.0007 0.0138 0.0003 1467 125b-1 33
miR- 21q21.1 ucccugagacccuaacuuguga 0.0007 0.0145 0.0009 1696
125b-2 10 miR- 11p11.2 cuuuuugcggucugggcuugcu 0.0002 0.0085 0.0001
484 129-2 34 miR- 7q32.3 uagcaccaucugaaaucgguu 0.0002 0.0085 0.0004
1477 29a 35 miR- 1q32.2 uagcaccauuugaaaucaguguu 0.0004 0.0116
0.0009 1076 29b-2 HP 28 miR- 9q31.3 uauugcacauuacuaaguugc 0.0000
0.0007 0.0000 1140 32 29 miR- 14q32.31 gcacauuacacggucgaccucu
0.0001 0.0079 0.0001 200 323 18 miR- 17q23.2
cagugcaauaguauugucaaagc 0.0044 0.0473 0.0040 6047 301 36 miR-
17p13.1 cgcauccccuagggcauuggugu 0.0038 0.0418 0.0035 413 324 37
miR- 19q13.41 cacccguagaaccgaccuugcg 0.0036 0.0410 0.0034 239 99b 1
let-7a- 9q22.32 ugagguaguagguuguauagu 0.0002 0.0089 0.0003 720 1 2
let-7a- 11q24.1 ugagguaguagguuguauaguu 0.0003 0.0101 0.0003 1592 2
3 let-7a- 22q13.31 ugagguaguagguuguaugguu 0.0027 0.0362 0.0018 1406
3 4 let-7b 22q13.31 ugagguaguagguugugugguu 0.0041 0.0455 0.0037
2134 5 let-7c 21q21.1 ugagguaguagguuguaugguu 0.0019 0.0281 0.0013
1614 6 let-7d 9q22.32 agagguaguagguugcauagu 0.0002 0.0087 0.0002
893 7 let-7f- Xp11.22 ugagguaguagauuguauagu 0.0028 0.0362 0.0026
482 2 8 let-7g 3p21.2 ugagguaguaguuuguacagu 0.0006 0.0138 0.0003
1043 33 miR- 21q21.1 ucccugagacccuaacuuguga 0.0007 0.0145 0.0009
1696 125b-2 23 miR- 9q33.3 aacauucaacgcugucggugagu 0.0000 0.0039
0.0000 639 181-a-2 11 miR- 1q31.3 aacauucauugcugucgguggg 0.0000
0.0001 0.0000 1182 181b-1 12 miR 9q33.3 aacauucauugcugucgguggg
0.0000 0.0007 0.0000 1298 181b-2 17 miR 19q13.12
aacauucaaccugucggugagu 0.0000 0.0011 0.0000 564 181c 13 miR-
12q13.13 uagguaguuucauguuguugg 0.0036 0.0410 0.0045 2465 196a-2 34
miR- 7q32.3 uagcaccaucugaaaucgguu 0.0002 0.0085 0.0004 1477 29a 38
miR- 7q32.3 uagcaccauuugaaaucaguguu 0.0008 0.0166 0.0022 1194 29b-1
35 miR- 1q32.2 uagcaccauuugaaaucaguguu 0.0004 0.0116 0.0009 1076
29b-2 39 miR- 1q32.2 uagcaccauuugaaaucggu 0.0015 0.0232 0.0020 1047
29c MH 1 let-7a- 9q22.32 ugagguaguagguuguauagu 0.0002 0.0089 0.0003
720 1 31 miR- 18q21.31 uggagugugacaaugguguuugu 0.0032 0.0391 0.0049
687 122a 32 miR- 11q24.1 ucccugagacccuaacuuguga 0.0007 0.0138
0.0003 1467 125b-1 33 miR- 21q21.1 ucccugagacccuaacuuguga 0.0007
0.0145 0.0009 1696 125b-2 10 miR- 11p11.2 cuuuuugcggucugggcuugcu
0.0002 0.0085 0.0001 484 129-2 34 miR- 7q32.3 uagcaccaucugaaaucgguu
0.0002 0.0085 0.0004 1477 29a 38 miR- 7q32.3
uagcaccauuugaaaucaguguu 0.0008 0.0166 0.0022 1194 29b-1 35 miR-
1q32.2 uagcaccauuugaaaucaguguu 0.0004 0.0116 0.0009 1076 29b-2 39
miR- 1q32.2 uagcaccauuugaaaucggu 0.0015 0.0232 0.0020 1047 29c
[[9]] let-7g 3p21.2 ugagguaguaguuuguacagu 0.0006 0.0138 0.0003 1043
8 20 miR- Xq26.2 aaaagugcuuacagugcagguagc 0.0002 0.0085 0.0001 1471
106a 21 miR- 7q22.1 uaaagugcugacagugcagau 0.0006 0.0135 0.0006 860
106b 9 miR- 7q32.1 cuuuuugcggucugggcuugcu 0.0004 0.0116 0.0003 274
129-1 16 miR- 13q31.3 caaagugcuuacagugcagguagu 0.0001 0.0079 0.0001
1608 17 22 miR- 1q31.3 aacauucaacgcugucggugagu 0.0004 0.0108 0.0003
1081 181-a-1 23 miR- 9q33.3 aacauucaacgcugucggugagu 0.0000 0.0039
0.0000 639
181-a-2 11 miR- 1q31.3 aacauucauugcugucgguggg 0.0000 0.0001 0.0000
1182 181b-1 12 miR- 9q33.3 aacauucauugcugucgguggg 0.0000 0.0007
0.0000 1298 181b-2 17 miR- 19p13.12 aacauucaaccugucggugagu 0.0000
0.0011 0.0000 564 181c 24 miR- 13q31.3 uaaagugcuuauagugcagguag
0.0005 0.0123 0.0007 1201 20a 25 miR- Xp11.3 agcuacauugucugcuggguuu
0.0002 0.0085 0.0004 2023 221 26 miR- Xp11.3
agcuacaucuggcuacugggucuc 0.0006 0.0135 0.0004 1573 222 27 miR-
7q22.1 cauugcacuugucucggucuga 0.0000 0.0039 0.0000 2713 25 28 miR-
9q31.3 uauugcacauuacuaaguugc 0.0000 0.0007 0.0000 1140 32 29 miR-
14q32.31 gcacauuacacggucgaccucu 0.0001 0.0079 0.0001 200 323 36
miR- 17p13.1 cgcauccccuagggcauuggugu 0.0038 0.0418 0.0035 413 324
14 miR- 14q32.31 uccagcuccuauaugaugccuuu 0.0001 0.0084 0.0001 217
337 30 miR- 13q31.3 uauugcacuugucccggccug 0.0014 0.0218 0.0012
17617 92-1 19 miR- Xq26.2 uauugcacuugucccggccug 0.0003 0.0101
0.0002 10397 92-2 15 miR- 7q22.1 aaagugcuguucgugcagguag 0.0025
0.0343 0.0023 1973 93 37 miR- 19q13.41 cacccguagaaccgaccuugcg
0.0036 0.0410 0.0034 239 99b HCC Group Geom mean SEQ of intensities
ID HCC Normal Non-HCC up/ No. HSC HPC MH Liver BDE HSC HPC MH down
HSC 1 491 442 592 720 4030 2910 2282 2409 up 2 1035 878 1136 1570
191 194 203 192 up 3 996 999 1185 1450 1246 1386 1474 1317 up 4
1675 1529 1826 2202 147 180 119 128 up 5 1226 1048 1353 2017 1048
1055 1159 980 up 6 632 556 670 976 1191 1071 1011 934 up 7 345 326
422 478 733 661 692 661 up 8 766 658 801 962 2050 1419 1441 1363 up
9 265 215 170 178 3002 3067 2779 2859 up 10 338 404 446 608 2199
2007 2127 1989 up 11 1344 926 719 608 615 525 513 509 up 12 1613
1153 988 864 1434 1431 1332 1294 up 13 1585 1226 1533 1791 2477
2742 2470 2432 up 14 204 168 89 215 1080 1029 1023 1013 up 15 1950
1589 1273 901 2303 2082 1983 1947 up 16 2957 1994 1650 1376 1972
2305 2050 2171 down 17 886 561 537 515 584 739 763 741 down 18
11619 14523 13198 25310 13590 16251 15375 14177 down 19 19133 14127
11409 18228 7590 13765 15979 15213 down BDE 20 2316 1733 1318 1239
1848 1767 1727 1699 up 21 1078 860 712 520 up 9 265 215 170 178 191
194 203 192 up 16 2957 1994 1650 1376 1972 2305 2050 2171 up 22
1355 991 921 804 1024 1137 1132 1098 up 23 858 588 526 499 719 767
815 768 up 11 1344 926 719 608 1048 1055 1159 980 up 12 1613 1153
988 864 1246 1386 1474 1317 up 17 886 561 537 515 584 739 763 741
up 24 1842 1376 1042 718 up 25 3332 2103 1956 678 891 1121 1219
1160 up 26 1920 1492 1237 640 761 769 968 846 up 27 3722 2714 2141
3056 up 28 1536 1227 800 1296 1366 1242 1219 1060 up 29 213 203 83
up 14 204 168 89 215 147 180 119 128 up 30 25783 21298 17727 21489
24398 24972 24312 22036 up 19 19133 14127 11409 18228 13590 16251
15375 14177 up 15 1950 1589 1273 901 2050 1419 1441 1363 up 2 1035
878 1136 1570 2303 2082 1983 1947 down 31 529 651 848 1338 1730
1609 1491 1625 down 32 905 923 1510 3329 4016 3551 3319 3336 down
33 1154 1202 1801 3245 3608 3620 3529 3471 down 10 338 404 446 608
615 525 513 509 down 34 1030 964 1630 1150 2289 2304 2036 2166 down
35 984 926 1510 1234 1690 2229 2032 2034 down HP 28 1536 1227 800
1296 1366 1242 1219 1060 up 29 213 203 83 up 18 11619 14523 13198
25310 7590 13765 15979 15213 up 36 432 434 359 415 379 384 405 403
up 37 248 257 200 165 200 179 202 190 up 1 491 442 592 720 1191
1071 1011 934 down 2 1035 878 1136 1570 2303 2082 1983 1947 down 3
996 999 1185 1450 2199 2007 2127 1989 down 4 1675 1529 1826 2202
3002 3067 2779 2859 down 5 1226 1048 1353 2017 2477 2742 2470 2432
down 6 632 556 670 976 1080 1029 1023 1013 down 7 345 326 422 478
733 661 692 661 down 8 766 658 801 962 1434 1431 1332 1294 down 33
1154 1202 1801 3245 3608 3620 3529 3471 down 23 858 588 526 499 719
767 815 768 down 11 1344 926 719 608 1048 1055 1159 980 down 12
1613 1153 988 864 1246 1386 1474 1317 down 17 886 561 537 515 584
739 763 741 down 13 1585 1226 1533 1791 4030 2910 2282 2409 down 34
1030 964 1630 1150 2289 2304 2036 2166 down 38 904 749 1308 918
1866 2062 1751 1813 down 35 984 926 1510 1234 1690 2229 2032 2034
down 39 917 820 1308 1018 1619 2165 1895 1797 down MH 1 491 442 592
720 615 525 513 509 up 31 529 651 848 1338 1191 1071 1011 934 up 32
905 923 1510 3329 1730 1609 1491 1625 up 33 1154 1202 1801 3245
4016 3551 3319 3336 up 10 338 404 446 608 3608 3620 3529 3471 up 34
1030 964 1630 1150 2289 2304 2036 2166 up 38 904 749 1308 918 1866
2062 1751 1813 up 35 984 926 1510 1234 1690 2229 2032 2034 up 39
917 820 1308 1018 1619 2165 1895 1797 up [[9]] 766 658 801 962 1434
1431 1332 1294 down 8 20 2316 1733 1318 1239 719 767 815 768 down
21 1078 860 712 520 1048 1055 1159 980 down 9 265 215 170 178 1246
1386 1474 1317 down 16 2957 1994 1650 1376 1972 2305 2050 2171 down
22 1355 991 921 804 1024 1137 1132 1098 down 23 858 588 526 499 584
739 763 741 down 11 1344 926 719 608 13590 16251 15375 14177 down
12 1613 1153 988 864 191 194 203 192 down 17 886 561 537 515 147
180 119 128 down 24 1842 1376 1042 718 2050 1419 1441 1363 down 25
3332 2103 1956 678 1848 1767 1727 1699 down 26 1920 1492 1237 640
down 27 3722 2714 2141 3056 down 28 1536 1227 800 1296 891 1121
1219 1160 down 29 213 203 83 761 769 968 846 down 36 432 434 359
415 down 14 204 168 89 215 1366 1242 1219 1060 down 30 25783 21298
17727 21489 down 19 19133 14127 11409 18228 24398 24972 24312 22036
down 15 1950 1589 1273 901 379 384 405 403 down 37 248 257 200 165
200 179 202 190 down
Example 2
[0117] This example demonstrates that miR-181s are associated with
HSC-HCC and contribute to the function of liver cancer stem
cells.
[0118] The expression levels of miR-181s in both precursors (A) and
mature miRNAs (B) are significantly increased in HSC-HCCs and
BDE-HCCs but decreased in HP- and MH-HCCs, versus their
corresponding non-HCC tissues. HSC-HCC and BDE-HCC refer to HCCs
with stem cell-like features and bile duct epithelium-like
features, respectively. Mir-181 expression, based on miRNA
microarray analysis of miRNA precursors in each HCC subtype versus
corresponding non-HCC tissues from 230 patients is shown in FIG.
1A-E for miR-181a-1, miR-181a-2, miR-181b-1, miR-181b-2 and
miR-181c, respectively. Gene expression ratios are shown
(mean.+-.95% CI) in log2 scale. FIGS. 1F-J shows RT-PCR analysis of
all mature miR-181s in 40 HCC and non-HCC sample pairs. Scatter
plot analysis of pre-miR-181s and mature miR-181s is shown in FIG.
2, with r-values representing Spearman's correlation
coefficient.
[0119] Next, miR-181 expression was positively correlated with
Wnt-.beta.-catenin signaling activation and negatively correlated
with many mature hepatocyte genes in both clinical specimens and
cultured HCC cell lines. Hierarchical clustering was conducted of 5
pre-miR-181s, 15 hepatocyte-specific genes, and 5 beta-catenin
associated genes whose expression was significantly correlated with
each other (p<0.001) from correlation analysis between
microarray data and mRNA array data. In 3 different types of HCC
cell lines, miR-181 expression was positively correlated with
beta-catenin protein level (FIG. 9).
[0120] After culturing HuH1 cells with ESC culture media, which is
a basal medium optimized for growth of undifferentiated embryonic
stem (ES) cells, the expression of miR-181 and beta-catenin
regulated genes was increased and the expression of
hepatocyte-specific genes was decreased as analyzed by qRT-PCR
(FIGS. 3A-C) as well as immunoblotting using antibodies to
beta-catenin and actin (as a control). Following withdrawal of ESC
media, the expression of the above genes was changed reversely, as
analyzed by qRT-PCR (FIGS. 3D-F). Gene expression was measured in
triplicate and is shown as mean .+-.SD.
Example 3
[0121] This example demonstrates that miR-181 expression is
involved in the activation of wnt-beta-catenin signaling.
[0122] After transfecting pMSCV-miR-181b-1 to HuH1 cells, miR-181-b
was detected by RT-PCR and expression was compared to that of
pMSCV-hTR cells. Gene expression was measured in triplicate and is
shown as mean .+-.SD in FIG. 4. As shown, miR-181 was over
expressed in the HuH1 cells.
[0123] HuH7 cells were treated with 2'-O-methyl miR-181s antisense
and the expression of all miR-181s was subsequently detected. A
significant decrease in gene expression (compared to a control
oligo), which was measured in triplicate, is shown as mean .+-.SD
in FIG. 5.
[0124] Following miR-181 overexpression in HuH1 cells, the
expression of beta-catenin regulated genes (CCND1, TACSTD1, and
DKK1) was detected by RT-PCR and compared to expression by
pMSCV-hTR cells (FIGS. 6A-C). Cell lysates of cell lines were also
analyzed by immunoblots with antibodies to .beta.-catenin and
actin.
[0125] Following miR-181 downregulation in HuH7 cells, the
expression of beta-catenin regulated genes (CCND1, TACSTD1, and
DKK1) was detected by RT-PCR and compared to the expression of
pMSCV-hTR cells (FIGS. 6D-F). Cell lysates of cell lines were also
analyzed by immunoblots with antibodies to .beta.-catenin and
actin.
[0126] Mir-181s affect wnt-beta-catenin expression. It is possible
that this occurs through a functional feedback link. DKK1 is an
inhibitor of beta-catenin. Beta-catenin induces miR-181 as well as
DKK1, which subsequently inhibits beta-catenin. It is thought that
miR-181 acts to inhibit the inhibitory activity of DKK1. Predicted
miR-181s binding sites in DKK1 3'-UTR are shown in FIG. 7A-B. The
BC001539, homo sapien dickkopf homolog 1 cDNA was used. FIG. 7A
shows the binding sites in the position of 611-632 of DKK1 3'-UTR.
FIG. 7B shows the predicted binding sites in the position of
771-799 of DKK1 3'-UTR.
[0127] The predicted transcription factor-4 (TCF-4) binding sites
((A/T)(A/T)CAAAG) OR (CTTTG(A/T)(A/T)) in miR-181s' promoters are
shown in FIGS. 8A-D. 6,060 base pairs were analyzed at the upstream
of transcriptional start site. FIG. 8A shows the promoter of
miR-181a-1 and miR-181b-1 in Chromosome 1, for which the
NW.sub.--926128, homo sapiens chromosome 1 genomic contig was used.
FIG. 8B shows the promoter of miR-181a-2 and miR-181b-2 in
Chromosome 9, for which the NT.sub.--008470 homo sapien chromosome
9 genomic contig was used. In the Sanger Database, both EST genes
are predicted in the region of miR-181c and miR-181d locating,
which have different transcriptional start sites (FIGS. 8C-D). The
promoter of miR-181c and miR-181d in Chromosome 19 in FIG. 8C is
the promoter from ENSESTT00000290819. The promoter of miR-181c and
miR-181d in Chromosome 19 in FIG. 8D is the promoter from
ENSESTT00000290818.
[0128] All references, including publications, patent applications,
and patents, cited herein are hereby incorporated by reference to
the same extent as if each reference were individually and
specifically indicated to be incorporated by reference and were set
forth in its entirety herein.
[0129] The use of the terms "a" and "an" and "the" and similar
referents in the context of describing the invention (especially in
the context of the following claims) are to be construed to cover
both the singular and the plural, unless otherwise indicated herein
or clearly contradicted by context. The terms "comprising,"
"having," "including," and "containing" are to be construed as
open-ended terms (i.e., meaning "including, but not limited to,")
unless otherwise noted. Recitation of ranges of values herein are
merely intended to serve as a shorthand method of referring
individually to each separate value falling within the range,
unless otherwise indicated herein, and each separate value is
incorporated into the specification as if it were individually
recited herein. All methods described herein can be performed in
any suitable order unless otherwise indicated herein or otherwise
clearly contradicted by context. The use of any and all examples,
or exemplary language (e.g., "such as") provided herein, is
intended merely to better illuminate the invention and does not
pose a limitation on the scope of the invention unless otherwise
claimed. No language in the specification should be construed as
indicating any non-claimed element as essential to the practice of
the invention.
[0130] Preferred embodiments of this invention are described
herein, including the best mode known to the inventors for carrying
out the invention. Variations of those preferred embodiments may
become apparent to those of ordinary skill in the art upon reading
the foregoing description. The inventors expect skilled artisans to
employ such variations as appropriate, and the inventors intend for
the invention to be practiced otherwise than as specifically
described herein. Accordingly, this invention includes all
modifications and equivalents of the subject matter recited in the
claims appended hereto as permitted by applicable law. Moreover,
any combination of the above-described elements in all possible
variations thereof is encompassed by the invention unless otherwise
indicated herein or otherwise clearly contradicted by context.
Sequence CWU 1
1
45121RNAHomo sapiens 1ugagguagua gguuguauag u 21222RNAHomo sapiens
2ugagguagua gguuguauag uu 22322RNAHomo sapiens 3ugagguagua
gguuguaugg uu 22422RNAHomo sapiens 4ugagguagua gguugugugg uu
22522RNAHomo sapiens 5ugagguagua gguuguaugg uu 22621RNAHomo sapiens
6agagguagua gguugcauag u 21721RNAHomo sapiens 7ugagguagua
gauuguauag u 21821RNAHomo sapiens 8ugagguagua guuuguacag u
21922RNAHomo sapiens 9cuuuuugcgg ucugggcuug cu 221022RNAHomo
sapiens 10cuuuuugcgg ucugggcuug cu 221122RNAHomo sapiens
11aacauucauu gcugucggug gg 221222RNAHomo sapiens 12aacauucauu
gcugucggug gg 221321RNAHomo sapiens 13uagguaguuu cauguuguug g
211423RNAHomo sapiens 14uccagcuccu auaugaugcc uuu 231522RNAHomo
sapiens 15aaagugcugu ucgugcaggu ag 221624RNAHomo sapiens
16caaagugcuu acagugcagg uagu 241722RNAHomo sapiens 17aacauucaac
cugucgguga gu 221823RNAHomo sapiens 18cagugcaaua guauugucaa agc
231921RNAHomo sapiens 19uauugcacuu gucccggccu g 212024RNAHomo
sapiens 20aaaagugcuu acagugcagg uagc 242121RNAHomo sapiens
21uaaagugcug acagugcaga u 212223RNAHomo sapiens 22aacauucaac
gcugucggug agu 232323RNAHomo sapiens 23aacauucaac gcugucggug agu
232423RNAHomo sapiens 24uaaagugcuu auagugcagg uag 232522RNAHomo
sapiens 25agcuacauug ucugcugggu uu 222624RNAHomo sapiens
26agcuacaucu ggcuacuggg ucuc 242722RNAHomo sapiens 27cauugcacuu
gucucggucu ga 222821RNAHomo sapiens 28uauugcacau uacuaaguug c
212922RNAHomo sapiens 29gcacauuaca cggucgaccu cu 223021RNAHomo
sapiens 30uauugcacuu gucccggccu g 213123RNAHomo sapiens
31uggaguguga caaugguguu ugu 233222RNAHomo sapiens 32ucccugagac
ccuaacuugu ga 223322RNAHomo sapiens 33ucccugagac ccuaacuugu ga
223421RNAHomo sapiens 34uagcaccauc ugaaaucggu u 213523RNAHomo
sapiens 35uagcaccauu ugaaaucagu guu 233623RNAHomo sapiens
36cgcauccccu agggcauugg ugu 233722RNAHomo sapiens 37cacccguaga
accgaccuug cg 223823RNAHomo sapiens 38uagcaccauu ugaaaucagu guu
233920RNAHomo sapiens 39uagcaccauu ugaaaucggu 204022RNAHomo sapiens
40aaugaucaua gcaccuugga ug 224123RNAHomo sapiens 41ugaguggcug
ucgcaacuua caa 234222RNAHomo sapiens 42ggguggcugu cguuacuuac aa
224322RNAHomo sapiens 43ugaguggcug uccaacuuac aa 224424RNAHomo
sapiens 44uuggguggcu guuguuacuu acaa 244529RNAHomo sapiens
45aaccuguccu gaaagaaggu caagugugu 29
* * * * *