U.S. patent application number 15/124333 was filed with the patent office on 2017-03-16 for diagnostic for sepsis.
The applicant listed for this patent is John Boyd, David G. Hancock, Robert E. W. Hancock, Olga M. Pena Serrato. Invention is credited to John Boyd, David G. Hancock, Robert E. W. Hancock, Olga M. Pena Serrato.
Application Number | 20170073734 15/124333 |
Document ID | / |
Family ID | 54070730 |
Filed Date | 2017-03-16 |
United States Patent
Application |
20170073734 |
Kind Code |
A1 |
Hancock; Robert E. W. ; et
al. |
March 16, 2017 |
Diagnostic for Sepsis
Abstract
A method of diagnosing severe sepsis prior to definitive
clinical diagnosis. A pattern of gene expression that correlates
strongly with a future diagnosis of severe sepsis and organ failure
was identified in patients who had their blood drawn at first
clinical presentation. The methods comprise identifying a pattern
of two or more polynucleotides, whereby the altered expression of
these polynucleotides correlates with prospective and actual
sepsis. Also methods of identifying agents for treating sepsis
based on the characteristics of this gene expression pattern are
provided.
Inventors: |
Hancock; Robert E. W.;
(Vancouver, CA) ; Pena Serrato; Olga M.;
(Coquitlam, CA) ; Hancock; David G.; (Vancouver,
CA) ; Boyd; John; (Vancouver, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Hancock; Robert E. W.
Pena Serrato; Olga M.
Hancock; David G.
Boyd; John |
Vancouver
Coquitlam
Vancouver
Vancouver |
|
CA
CA
CA
CA |
|
|
Family ID: |
54070730 |
Appl. No.: |
15/124333 |
Filed: |
March 13, 2015 |
PCT Filed: |
March 13, 2015 |
PCT NO: |
PCT/CA2015/000160 |
371 Date: |
September 7, 2016 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61953458 |
Mar 14, 2014 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
C12Q 1/689 20130101;
C12Q 2600/16 20130101; C12Q 2600/118 20130101; A61P 31/04 20180101;
C12Q 2600/136 20130101; C12Q 1/6883 20130101; C12N 15/1068
20130101; C12Q 2600/158 20130101; C12Q 2600/172 20130101; A61K
35/15 20130101 |
International
Class: |
C12Q 1/68 20060101
C12Q001/68; A61K 35/15 20060101 A61K035/15; C12N 15/10 20060101
C12N015/10 |
Claims
1. A method for diagnosing sepsis in a subject, comprising
determining in a biological sample obtained from the subject a
level of expression for each of a plurality of Endotoxin Tolerance
Signature genes to provide a sample gene signature, and comparing
the sample gene signature with a reference gene signature, wherein
the reference gene signature represents a standard level of
expression of each of the plurality of genes; wherein a difference
between the sample gene signature and the reference gene signature
indicates that the subject has sepsis.
2. The method according to claim 1, wherein the sepsis is severe
sepsis.
3. A method for identifying a subject at risk of developing severe
sepsis, comprising determining in a biological sample obtained from
the subject a level of expression for each of a plurality of
Endotoxin Tolerance Signature genes to provide a sample gene
signature, and comparing the sample gene signature with a reference
gene signature, wherein the reference gene signature represents a
standard level of expression of each of the plurality of genes;
wherein a difference between the sample gene signature and the
reference gene signature indicates that the subject is at risk of
developing severe sepsis.
4. A method for identifying a subject at risk of organ failure,
comprising determining in a biological sample obtained from the
subject a level of expression for each of a plurality of Endotoxin
Tolerance Signature genes to provide a sample gene signature, and
comparing the sample gene signature with a reference gene
signature, wherein the reference gene signature represents a
standard level of expression of each of the plurality of genes;
wherein a difference between the sample gene signature and the
reference gene signature indicates that the subject is at risk of
organ failure
5. The method according to any one of claims 1 to 4, wherein the
subject is suspected of having sepsis.
6. The method according to any one of claims 1 to 4, wherein the
subject has been diagnosed as having sepsis by standard
procedures.
7. The method according to any one of claims 1 to 6, wherein the
plurality of genes is selected from ADAM15, ADAMDEC1, ALCAM,
ALDH1A1, ANKRD1, C19orf59, CA12, CAMP, CCL1, CCL19, CCL22, CCL24,
CCL7, CD14, CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK,
CXCL10, CYP1B1, CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3,
FBP1, FCER1G, FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF,
HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1,
IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO,
MGST1, MMP7, MT1F, MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1,
NRIP3, OLIG2, PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR,
PSTPIP2, PTGES, PTGR1, RAB13, RARRES1, RETN, RHBDD2, RNASE1,
S100A12, S100A4, S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10,
SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4, UPP1 and VCAN.
8. A method for diagnosing endotoxin tolerance in a subject, the
method comprising: a) determining in a biological sample obtained
from the subject a level of expression for each of a plurality of
genes selected from ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1,
C19orf59, CA12, CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14,
CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1,
CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G,
FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3,
HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8,
KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F,
MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2,
PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES,
PTGR1, RAB13, RARRES1, RETN, RHBDD2, RNASE1, S100A12, S100A4,
S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7,
TMEM158, TREM1, TSPAN4, UPP1 and VCAN to provide a sample gene
signature, and b) comparing the sample gene signature with a
reference gene signature, wherein the reference gene signature
represents a standard level of expression of each of the plurality
of genes; wherein a difference between the sample gene signature
and the reference gene signature indicates that the subject has
endotoxin tolerance.
9. The method according to claim 8, wherein the subject has or is
suspected of having sepsis.
10. The method according to claim 8 or 9, further comprising
identifying the subject as being at risk of severe sepsis and/or
organ failure if there is a difference between the sample gene
signature and the reference gene signature.
11. The method according to any one of claims 7 to 10, wherein the
difference between the sample gene signature and the reference gene
signature is defined by a difference in expression of at least two
of the plurality of genes in an expression change direction.
12. The method according to claim 11, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 5 of the
plurality of genes in an expression change direction.
13. The method according to claim 11, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 10 of the
plurality of genes in an expression change direction.
14. The method according to claim 11, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 15 of the
plurality of genes in an expression change direction.
15. The method according to claim 11, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 20 of the
plurality of genes in an expression change direction.
16. The method according to claim 11, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 25 of the
plurality of genes in an expression change direction.
17. The method according to claim 11, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 30 of the
plurality of genes in an expression change direction.
18. The method according to claim 11, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 31 of the
plurality of genes in an expression change direction.
19. The method according to any one of claims 11 to 18, wherein the
expression change direction is upregulation if the gene is
ADAMDEC1, ANKRD1, C19orf59, CA12, CCL1, CCL19, CCL22, CCL24, CCL7,
CD14, CD300LF, CD93, CDK5RAP2, CYP1B1, CYP27B1, DDIT4, DPYSL3,
EGR2, EMR1, EMR3, FBP1, FCER1G, FCER2, FPR1, FPR2, GK, GPR137B,
HBEGF, HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2, HK3, HPSE, HSD11B1,
IL3RA, ITGB8, KIAA1199, LILRA3, LILRA5, MARCO, MGST1, MMP7, MT1F,
MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NRIP3, OLIG2, PANX2,
PAPLN, PDLIM7, PLAUR, PPBP, PROCR, PTGES, PTGR1, RAB13, REIN,
RHBDD2, S100A12, S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10,
SLC7A11, TGM2, TMEM158, TREM1, UPP1 or VCAN, and downregulation if
the gene is ADAM15, ALCAM, ALDH1A1, CAMP, CPVL, CST3, CST6, CTSK,
CXCL10, DHRS9, GPNMB, HTRA1, IL18BP, LIPA, LY86, NQO1, PLD3,
PSTPIP2, RARRES1, RNASE1, S100A4, TLR7 or TSPAN4.
20. The method according to any one of claims 7 to 19, wherein the
plurality of genes are selected from C19orf59, CCL22, CD14,
CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2,
HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN,
RHBDD2, S100A4, S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86
and PROCR.
21. The method according to any one of claims 7 to 19, wherein the
plurality of genes comprises C19orf59, CCL22, CD14, CD300LF,
CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE,
LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4,
S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
22. The method according to any one of claims 1 to 21, wherein
determining the level of expression comprises detecting nucleic
acids encoded by each of the plurality of genes.
23. The method according to claim 22, wherein determining the level
of expression comprises one or more of a polymerase chain reaction
(PCR) amplification method, a non-PCR based amplification method,
reverse transcriptase-(RT) PCR, Q-beta replicase amplification,
ligase chain reaction, signal amplification (Ampliprobe), light
cycling, differential display, Northern analysis, hybridization,
microarray analysis, DNA sequencing, Ref-Seq, MassArray analysis
and MALDI-TOF mass spectrometry.
24. The method according to claim 22, wherein detecting the nucleic
acids comprises contacting the biological sample with a microarray
comprising a plurality of polynucleotide probes capable of
hybridizing to the nucleic acids encoded by each of the plurality
of genes.
25. The method according to claim 22, wherein determining the level
of expression comprises isolating mRNA from the biological sample,
reverse transcribing the mRNA to generate cDNA products and
contacting the cDNA products with a microarray comprising a
plurality of polynucleotide probes capable of hybridizing to a
plurality of cDNAs that are complementary to a plurality of mRNAs
expressed from the plurality of genes.
26. The method according to any one of claims 1 to 25, further
comprising a step of obtaining the biological sample from the
subject.
27. The method according to any one of claims 1 to 26, wherein the
biological sample comprises blood, plasma, serum, tissue, amniotic
fluid, saliva, urine, stool, bronchoalveolar lavage fluid,
cerebrospinal fluid or skin cells.
28. The method according to any one of claims 1 to 26, wherein the
biological sample comprises blood.
29. A method for treating sepsis comprising administering an
effective amount of one or more antibiotics to a subject who has
been diagnosed as having sepsis by the method according to claim
1.
30. A method for treating sepsis in a subject, the method
comprising: a) determining whether the subject has sepsis or is at
risk of developing sepsis by: (i) determining in a biological
sample obtained from the subject a level of expression for each of
a plurality of genes selected from ADAM15, ADAMDEC1, ALCAM,
ALDH1A1, ANKRD1, C19orf59, CA12, CAMP, CCL1, CCL19, CCL22, CCL24,
CCL7, CD14, CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK,
CXCL10, CYP1B1, CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3,
FBP1, FCER1G, FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF,
HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1,
IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO,
MGST1, MMP7, MT1F, MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1,
NRIP3, OLIG2, PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR,
PSTPIP2, PTGES, PTGR1, RAB13, RARRES1, RETN, RHBDD2, RNASE1,
S100A12, S100A4, S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10,
SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4, UPP1 and VCAN to
provide a sample gene signature, and (ii) comparing the sample gene
signature with a reference gene signature, wherein the reference
gene signature represents a standard level of expression of each of
the plurality of genes, and wherein a difference between the sample
gene signature and the reference gene signature indicates that the
subject has sepsis or is at risk of developing sepsis, and b) if
the subject has sepsis or is at risk of developing sepsis,
administering to the subject an effective amount of one or more
antibiotics.
31. The method according to claim 30, wherein the sepsis is severe
sepsis.
32. The method according to any one of claims 29 to 31, wherein the
one or more antibiotics is one or a combination of a glycopeptide,
a ceflasporin, a beta-lactam, a beta-lactamase inhibitor, a
carbapenem, a quinolone, a fluoroquinolone, an aminoglycoside, a
macrolide and a monobactam.
33. A method for decreasing the risk of organ failure in a subject
comprising administering an effective amount of one or more
antibiotics to a subject who has been diagnosed as having sepsis or
being at risk of developing severe sepsis by the method according
to any one of claims 1 to 3.
34. A method for decreasing the risk of organ failure in a subject,
the method comprising: a) determining whether the subject is at
risk of organ failure by: (i) determining in a biological sample
obtained from the subject a level of expression for each of a
plurality of genes selected from ADAM15, ADAMDEC1, ALCAM, ALDH1A1,
ANKRD1, C19orf59, CA12, CAMP, CCL1, CCL19, CCL22, CCL24, CCL7,
CD14, CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10,
CYP1B1, CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1,
FCER1G, FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF, HIST1H1C,
HIST2H2AA3, HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1, IL18BP,
IL3RA, ITGB8, KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO, MGST1,
MMP7, MT1F, MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3,
OLIG2, PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR, PSTPIP2,
PTGES, PTGR1, RAB13, RARRES1, RETN, RHBDD2, RNASE1, S100A12,
S100A4, S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10, SLC7A11,
TGM2, TLR7, TMEM158, TREM1, TSPAN4, UPP1 and VCAN to provide a
sample gene signature, and (ii) comparing the sample gene signature
with a reference gene signature, wherein the reference gene
signature represents a standard level of expression of each of the
plurality of genes, and wherein a difference between the sample
gene signature and the reference gene signature indicates that the
subject is at risk of organ failure, and b) if the subject is at
risk of organ failure, administering to the subject an effective
amount of one or more antibiotics.
35. The method according to any one of claims 29 to 34, wherein the
difference between the sample gene signature and the reference gene
signature is defined by a difference in expression of at least two
of the plurality of genes in an expression change direction.
36. The method according to claim 35, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 5 of the
plurality of genes in an expression change direction.
37. The method according to claim 35, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 10 of the
plurality of genes in an expression change direction.
38. The method according to claim 35, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 15 of the
plurality of genes in an expression change direction.
39. The method according to claim 35, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 20 of the
plurality of genes in an expression change direction.
40. The method according to claim 35, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 25 of the
plurality of genes in an expression change direction.
41. The method according to claim 35, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 30 of the
plurality of genes in an expression change direction.
42. The method according to claim 35, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 31 of the
plurality of genes in an expression change direction.
43. The method according to any one of claims 35 to 42, wherein the
expression change direction is upregulation if the gene is
ADAMDEC1, ANKRD1, C19orf59, CA12, CCL1, CCL19, CCL22, CCL24, CCL7,
CD14, CD300LF, CD93, CDK5RAP2, CYP1B1, CYP27B1, DDIT4, DPYSL3,
EGR2, EMR1, EMR3, FBP1, FCER1G, FCER2, FPR1, FPR2, GK, GPR137B,
HBEGF, HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2, HK3, HPSE, HSD11B1,
IL3RA, ITGB8, KIAA1199, LILRA3, LILRA5, MARCO, MGST1, MMP7, MT1F,
MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NRIP3, OLIG2, PANX2,
PAPLN, PDLIM7, PLAUR, PPBP, PROCR, PTGES, PTGR1, RAB13, REIN,
RHBDD2, S100A12, S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10,
SLC7A11, TGM2, TMEM158, TREM1, UPP1 or VCAN, and downregulation if
the gene is ADAM15, ALCAM, ALDH1A1, CAMP, CPVL, CST3, CST6, CTSK,
CXCL10, DHRS9, GPNMB, HTRA1, IL18BP, LIPA, LY86, NQO1, PLD3,
PSTPIP2, RARRES1, RNASE1, S100A4, TLR7 or TSPAN4.
44. The method according to any one of claims 29 to 43, wherein the
plurality of genes are selected from C19orf59, CCL22, CD14,
CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2,
HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN,
RHBDD2, S100A4, S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86
and PROCR.
45. The method according to any one of claims 29 to 43, wherein the
plurality of genes comprises C19orf59, CCL22, CD14, CD300LF,
CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE,
LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4,
S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
46. A method for decreasing the risk of a subject developing severe
sepsis comprising administering an effective amount of an agent
that counteracts endotoxin tolerance to a subject who has been
diagnosed as being at risk of developing severe sepsis by the
method according to claim 3.
47. A method for decreasing the risk of organ failure in a subject
comprising administering an effective amount of an agent that
counteracts endotoxin tolerance to a subject who has been diagnosed
as being at risk of organ failure by the method according to claim
4.
48. A method for decreasing the risk of a subject developing severe
sepsis or organ failure comprising administering to the subject an
effective amount of an agent that counteracts endotoxin
tolerance.
49. The method according to claim 48, further comprising
determining that the subject is at risk of developing severe sepsis
or organ failure by: (a) determining in a biological sample
obtained from the subject the level of expression of a plurality of
genes selected from ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1,
C19orf59, CA12, CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14,
CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1,
CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G,
FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3,
HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8,
KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F,
MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2,
PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES,
PTGR1, RAB13, RARRES1, RETN, RHBDD2, RNASE1, S100A12, S100A4,
S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7,
TMEM158, TREM1, TSPAN4, UPP1 and VCAN to provide a sample gene
signature, and (b) comparing the sample gene signature with a
reference gene signature, wherein the reference gene signature
represents a standard level of expression of each of the plurality
of genes, wherein a difference between the sample gene signature
and the reference gene signature indicates that the subject is at
risk of developing severe sepsis or organ failure.
50. The method according to any one of claim 46, 47 or 49, further
comprising monitoring the expression of the plurality genes in
samples obtained from the subject at one or more time points during
treatment.
51. The method according to any one of claim 46, 47, 49 or 50,
wherein the difference between the sample gene signature and the
reference gene signature is defined by a difference in expression
of at least two of the plurality of genes in an expression change
direction.
52. The method according to claim 51, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 5 of the
plurality of genes in an expression change direction.
53. The method according to claim 51, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 10 of the
plurality of genes in an expression change direction.
54. The method according to claim 51, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 15 of the
plurality of genes in an expression change direction.
55. The method according to claim 51, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 20 of the
plurality of genes in an expression change direction.
56. The method according to claim 51, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 25 of the
plurality of genes in an expression change direction.
57. The method according to claim 51, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 30 of the
plurality of genes in an expression change direction.
58. The method according to claim 51, wherein the difference
between the sample gene signature and the reference gene signature
is defined by a difference in expression of at least 31 of the
plurality of genes in an expression change direction.
59. The method according to any one of claims 51 to 58, wherein the
expression change direction is upregulation if the gene is
ADAMDEC1, ANKRD1, C19orf59, CA12, CCL1, CCL19, CCL22, CCL24, CCL7,
CD14, CD300LF, CD93, CDK5RAP2, CYP1B1, CYP27B1, DDIT4, DPYSL3,
EGR2, EMR1, EMR3, FBP1, FCER1G, FCER2, FPR1, FPR2, GK, GPR137B,
HBEGF, HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2, HK3, HPSE, HSD11B1,
IL3RA, ITGB8, KIAA1199, LILRA3, LILRA5, MARCO, MGST1, MMP7, MT1F,
MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NRIP3, OLIG2, PANX2,
PAPLN, PDLIM7, PLAUR, PPBP, PROCR, PTGES, PTGR1, RAB13, RETN,
RHBDD2, S100A12, S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10,
SLC7A11, TGM2, TMEM158, TREM1, UPP1 or VCAN, and downregulation if
the gene is ADAM15, ALCAM, ALDH1A1, CAMP, CPVL, CST3, CST6, CTSK,
CXCL10, DHRS9, GPNMB, HTRA1, IL18BP, LIPA, LY86, NQO1, PLD3,
PSTPIP2, RARRES1, RNASE1, S100A4, TLR7 or TSPAN4.
60. The method according to any one of claims 46, 47 and 49 to 59,
wherein the plurality of genes are selected from C19orf59, CCL22,
CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3,
HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, REIN,
RHBDD2, S100A4, S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86
and PROCR.
61. The method according to any one of claims 46, 47 and 49 to 59,
wherein the plurality of genes comprises C19orf59, CCL22, CD14,
CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2,
HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN,
RHBDD2, S100A4, S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86
and PROCR.
62. The method according to any one of claims 46 to 61, wherein the
agent that counteracts endotoxin tolerance is an immunotherapy.
63. The method according to claim 62, wherein the agent comprises
immune cells.
64. The method according to any one of claims 46 to 61, wherein the
agent is interferon gamma, a CpG-oligonucleotide (ODN), a
combination of a CpG ODN with IL-10, an anti-CD40 antibody, an
inhibitor of STAT3, an inhibitor of STAT6, an inhibitor of p50, an
inhibitor of NF.kappa.B, an inhibitor of IKK.beta., an
imidazoquinolone or zoledronic acid.
65. A method for identifying a candidate agent for the treatment of
sepsis, the method comprising: a) contacting an endotoxin tolerant
cell with a test agent, b) determining the level of expression for
each of a plurality of Endotoxin Tolerance Signature genes in the
endotoxin tolerant cell to provide an expression signature, c)
comparing the expression signature with a reference expression
signature, wherein the reference signature represents the levels of
expression of the plurality of genes in a normal cell, and d)
selecting the test agent as a candidate agent for treatment of
sepsis when the expression signature substantially corresponds with
the reference signature.
66. The method according to claim 65, wherein the plurality of
genes is selected from ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1,
C19orf59, CA12, CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14,
CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1,
CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G,
FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3,
HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8,
KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F,
MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2,
PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES,
PTGR1, RAB13, RARRES1, RETN, RHBDD2, RNASE1, S100A12, S100A4,
S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7,
TMEM158, TREM1, TSPAN4, UPP1 and VCAN.
67. The method according to claim 65 or 66, wherein the plurality
of genes comprises at least 5 genes.
68. The method according to claim 65 or 66, wherein the plurality
of genes comprises at least 10 genes.
69. The method according to claim 65 or 66, wherein the plurality
of genes comprises at least 15 genes.
70. The method according to claim 65 or 66, wherein the plurality
of genes comprises at least 20 genes.
71. The method according to claim 65 or 66, wherein the plurality
of genes comprises at least 25 genes.
72. The method according to claim 65 or 66, wherein the plurality
of genes comprises at least 30 genes.
73. The method according to claim 65 or 66, wherein the plurality
of genes comprises at least 31 genes.
74. The method according to any one of claims 65 to 73, wherein the
plurality of genes are selected from C19orf59, CCL22, CD14,
CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2,
HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN,
RHBDD2, S100A4, S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86
and PROCR.
75. The method according to any one of claims 65 to 73, wherein the
plurality of genes comprises C19orf59, CCL22, CD14, CD300LF,
CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE,
LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4,
S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
76. A kit for determining a level of expression for each of a
plurality of genes selected from ADAM15, ADAMDEC1, ALCAM, ALDH1A1,
ANKRD1, C19orf59, CA12, CAMP, CCL1, CCL19, CCL22, CCL24, CCL7,
CD14, CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10,
CYP1B1, CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1,
FCER1G, FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF, HIST1H1C,
HIST2H2AA3, HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1, IL18BP,
IL3RA, ITGB8, KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO, MGST1,
MMP7, MT1F, MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3,
OLIG2, PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR, PSTPIP2,
PTGES, PTGR1, RAB13, RARRES1, RETN, RHBDD2, RNASE1, S100A12,
S100A4, S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10, SLC7A11,
TGM2, TLR7, TMEM158, TREM1, TSPAN4, UPP1 and VCAN in a sample, the
kit comprising gene specific reagents, each of the gene specific
reagents capable of detecting an expression product of a respective
one of the plurality of genes or complement thereof, and
instructions for use.
77. The kit according to claim 76, wherein the plurality of genes
comprises at least 5 genes.
78. The kit according to claim 76, wherein the plurality of genes
comprises at least 10 genes.
79. The kit according to claim 76, wherein the plurality of genes
comprises at least 15 genes.
80. The kit according to claim 76, wherein the plurality of genes
comprises at least 20 genes.
81. The kit according to claim 76, wherein the plurality of genes
comprises at least 25 genes.
82. The kit according to claim 76, wherein the plurality of genes
comprises at least 30 genes.
83. The kit according to claim 76, wherein the plurality of genes
comprises at least 31 genes.
84. The kit according to any one of claims 76 to 83, wherein the
plurality of genes are selected from C19orf59, CCL22, CD14,
CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2,
HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN,
RHBDD2, S100A4, S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86
and PROCR.
85. The kit according to any one of claims 76 to 83, wherein the
plurality of genes comprises C19orf59, CCL22, CD14, CD300LF,
CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE,
LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4,
S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
86. The kit according to any one of claims 76 to 85, wherein the
expression product or complement thereof is RNA, cDNA or a
protein.
87. The kit according to claim 86, wherein each expression product
is a nucleic acid and each gene specific reagent comprises a
polynucleotide probe capable of specifically binding to at least
one of said nucleic acid expression products or the complement
thereof.
88. The kit according to claim 87, wherein the kit further
comprises polynucleotide primers for amplification of at least a
portion of the nucleic acid expression product.
89. The kit according to claim 87 or 88, wherein the polynucleotide
probes are provided as a microarray.
90. The kit according to any one of claims 76 to 89, further
comprising one or more controls.
91. The kit according to any one of claims 76 to 90, wherein the
kit is for use to diagnose sepsis in a subject, determine the risk
of a subject developing severe sepsis or determine the risk of
organ failure in a subject.
92. A microarray for detecting expression of a plurality of
Endotoxin Tolerance Signature genes in a sample, the microarray
comprising a plurality of polynucleotide probes attached to a solid
support, each of the polynucleotide probes capable of specifically
hybridizing to an expression product of a respective one of the
plurality of genes or the complement thereof.
93. The microarray according to claim 92, wherein the plurality of
genes are selected from ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1,
C19orf59, CA12, CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14,
CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1,
CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G,
FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3,
HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8,
KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F,
MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2,
PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES,
PTGR1, RAB13, RARRES1, REIN, RHBDD2, RNASE1, S100A12, S100A4,
S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7,
TMEM158, TREM1, TSPAN4, UPP1 and VCAN.
94. The microarray according to claim 92 or 93, wherein the
plurality of genes comprises at least 5 genes.
95. The microarray according to claim 92 or 93, wherein the
plurality of genes comprises at least 10 genes.
96. The microarray according to claim 92 or 93, wherein the
plurality of genes comprises at least 15 genes.
97. The microarray according to claim 92 or 93, wherein the
plurality of genes comprises at least 20 genes.
98. The microarray according to claim 92 or 93, wherein the
plurality of genes comprises at least 25 genes.
99. The microarray according to claim 92 or 93, wherein the
plurality of genes comprises at least 30 genes.
100. The microarray according to claim 92 or 93, wherein the
plurality of genes comprises at least 31 genes.
101. The microarray according to any one of claims 92 to 100,
wherein the plurality of genes are selected from C19orf59, CCL22,
CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3,
HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN,
RHBDD2, S100A4, S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86
and PROCR.
102. The microarray according to any one of claims 92 to 100,
wherein the plurality of genes comprises C19orf59, CCL22, CD14,
CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2,
HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN,
RHBDD2, S100A4, S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86
and PROCR.
103. The microarray according to any one of claims 92 to 102
further comprising one or more control polynucleotide probes.
104. The microarray according to claim 103, wherein the microarray
consists essentially of (i) the polynucleotide probes capable of
specifically hybridizing to an expression product of a respective
one of the plurality of genes or complement thereof, and (ii) the
one or more control polynucleotide probes.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application claims priority to U.S. provisional patent
application No. 61/953,458 filed on Mar. 14, 2014. The entire
contents of U.S. provisional patent application No. 61/953,458 are
incorporated by reference herein.
FIELD OF THE INVENTION
[0002] The present invention relates to the field of diagnostics
and, in particular, to a unique set of DNA sequences that in
combination enable the early diagnosis of sepsis, and the
prediction of severe sepsis and/or organ failure.
BACKGROUND OF THE INVENTION
[0003] Sepsis continues to be the major infection-related cause of
death globally, leading to an estimated 8.5% of deaths (5 million)
annually [Angus D, et al. Critical Care Medicine 2001; 29(7):
1303-10; Kumar G, Kumar N, Taneja A, et al. Chest 2011;
140:1223-31]. Despite advances in modern medicine including new
antibiotics and vaccines, early recognition and best practice
treatments, and efficient well-equipped intensive care units [Angus
D et al], the high rate of mortality, .about.30%, has remained
little changed for decades [Daniels R. J Antimicrobial Chemotherapy
2011; 66(Suppl 2): ii11-ii23].
[0004] Bacterial endotoxins (including LPS) are potent inducers of
inflammation and have been suggested as triggers for sepsis, as the
cause of an early life-threatening cytokine storm and septic shock
[Opal S M. Contributions to Nephrology 2010; 167: 14-24; Salomao R,
et al. Shock 2012; 38:227-42]. In contrast, LPS can also generate
an opposite effect known as endotoxin tolerance, defined as the
severely reduced capacity of the cell to respond to LPS and other
bacterial products during a second exposure to the stimulus [Otto G
P, et al. Critical Care 2011; 15:R183]. It is important to note
that endotoxin tolerance, also termed cellular reprogramming since
it can be induced by other microbial molecules, is not an
anti-inflammatory state of cells but rather a reprogramming of
cells so they are no longer able of responding to multiple
microbial signatures, including endotoxin.
[0005] It has been proposed that endotoxin tolerance may be
associated with the immunosuppressive state that has been primarily
observed during late-stage severe sepsis [Otto G P, et al. 2011;
Cavaillon J, et al. J Endotoxin Res 2005; 11(5): 311-20; Cavaillon
J, Adib-Conquy M. Critical Care Medicine 2006; 10:233]. However,
this relationship remains poorly characterized, in part due to the
limitations of the ex vivo cytokine assays employed to date.
Despite these observations, the clinical dogma is to identify and
treat sepsis, especially in its early stages, as an excessive
inflammatory response. However, the unique immunosuppressive state
characteristic of sepsis is inherently linked to the prognosis of
this disease. Indeed, understanding the relative balance between
excessive inflammation and immunosuppression, and especially at
what time each develops in the clinical course of disease, is an
important step towards improving sepsis outcomes.
[0006] Biomarkers for the diagnosis of sepsis have been proposed in
U.S. Pat. No. 7,767,395; U.S. Patent Application Publication No.
2011/0312521; U.S. Patent Application Publication No. 2011/0076685;
International Patent Application Publication No. WO 2014/209238,
and International Patent Application Publication No. WO
2013/152047.
[0007] This background information is provided for the purpose of
making known information believed by the applicant to be of
possible relevance to the present invention. No admission is
necessarily intended, nor should be construed, that any of the
preceding information constitutes prior art against the present
invention.
SUMMARY OF THE INVENTION
[0008] The present invention relates generally to a diagnostic for
early severe sepsis. In one aspect, the invention relates to a
method for diagnosing sepsis in a subject, comprising determining
in a biological sample obtained from the subject a level of
expression for each of a plurality of Endotoxin Tolerance Signature
genes to provide a sample gene signature, and comparing the sample
gene signature with a reference gene signature, wherein the
reference gene signature represents a standard level of expression
of each of the plurality of genes; wherein a difference between the
sample gene signature and the reference gene signature indicates
that the subject has sepsis.
[0009] In another aspect, the invention relates to a method for
identifying a subject at risk of developing severe sepsis,
comprising determining in a biological sample obtained from the
subject a level of expression for each of a plurality of Endotoxin
Tolerance Signature genes to provide a sample gene signature, and
comparing the sample gene signature with a reference gene
signature, wherein the reference gene signature represents a
standard level of expression of each of the plurality of genes;
wherein a difference between the sample gene signature and the
reference gene signature indicates that the subject is at risk of
developing severe sepsis.
[0010] In another aspect, the invention relates to a method for
identifying a subject at risk of organ failure, comprising
determining in a biological sample obtained from the subject a
level of expression for each of a plurality of Endotoxin Tolerance
Signature genes to provide a sample gene signature, and comparing
the sample gene signature with a reference gene signature, wherein
the reference gene signature represents a standard level of
expression of each of the plurality of genes; wherein a difference
between the sample gene signature and the reference gene signature
indicates that the subject is at risk of organ failure.
[0011] In certain embodiments, the plurality of genes is selected
from ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1, C19orf59, CA12,
CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14, CD300LF, CD93,
CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1, CYP27B1, DDIT4,
DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G, FCER2, FPR1, FPR2,
GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2,
HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3,
LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F, MT1G, MT1H, MT1M,
MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2, PANX2, PAPLN, PDLIM7,
PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES, PTGR1, RAB13, RARRES1,
RETN, RHBDD2, RNASE1, S100A12, S100A4, S100A8, S100A9, SERPINA1,
SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4,
UPP1 and VCAN.
[0012] In certain embodiments, the plurality of genes is selected
from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0013] In certain embodiments, the plurality of genes comprises
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0014] In certain embodiments, the plurality of genes consists of
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0015] In another aspect, the invention relates to a method for
diagnosing endotoxin tolerance in a subject, the method comprising:
a) determining in a biological sample obtained from the subject a
level of expression for each of a plurality of genes selected from
ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1, C19orf59, CA12, CAMP,
CCL1, CCL19, CCL22, CCL24, CCL7, CD14, CD300LF, CD93, CDK5RAP2,
CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1, CYP27B1, DDIT4, DHRS9,
DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G, FCER2, FPR1, FPR2, GK,
GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2, HK3,
HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3,
LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F, MT1G, MT1H, MT1M,
MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2, PANX2, PAPLN, PDLIM7,
PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES, PTGR1, RAB13, RARRES1,
RETN, RHBDD2, RNASE1, S100A12, S100A4, S100A8, S100A9, SERPINA1,
SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4,
UPP1 and VCAN to provide a sample gene signature, and b) comparing
the sample gene signature with a reference gene signature, wherein
the reference gene signature represents a standard level of
expression of each of the plurality of genes; wherein a difference
between the sample gene signature and the reference gene signature
indicates that the subject has endotoxin tolerance.
[0016] In certain embodiments, the plurality of genes is selected
from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0017] In certain embodiments, the plurality of genes comprises
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0018] In certain embodiments, the plurality of genes consists of
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0019] In another aspect, the invention relates to a method for
treating sepsis comprising administering an effective amount of one
or more antibiotics to a subject who has been diagnosed as having
sepsis by the method described above.
[0020] In another aspect, the invention relates to a method for
treating sepsis in a subject, the method comprising: a) determining
whether the subject has sepsis or is at risk of developing sepsis
by: (i) determining in a biological sample obtained from the
subject a level of expression for each of a plurality of genes
selected from ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1, C19orf59,
CA12, CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14, CD300LF, CD93,
CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1, CYP27B1, DDIT4,
DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G, FCER2, FPR1, FPR2,
GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2,
HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3,
LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F, MT1G, MT1H, MT1M,
MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2, PANX2, PAPLN, PDLIM7,
PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES, PTGR1, RAB13, RARRES1,
RETN, RHBDD2, RNASE1, S100A12, S100A4, S100A8, S100A9, SERPINA1,
SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4,
UPP1 and VCAN to provide a sample gene signature, and (ii)
comparing the sample gene signature with a reference gene
signature, wherein the reference gene signature represents a
standard level of expression of each of the plurality of genes, and
wherein a difference between the sample gene signature and the
reference gene signature indicates that the subject has sepsis or
is at risk of developing sepsis, and b) if the subject has sepsis
or is at risk of developing sepsis, administering to the subject an
effective amount of one or more antibiotics.
[0021] In certain embodiments, the plurality of genes is selected
from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, REIN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0022] In certain embodiments, the plurality of genes comprises
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, REIN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0023] In certain embodiments, the plurality of genes consists of
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, REIN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0024] In another aspect, the invention relates to a method for
decreasing the risk of organ failure in a subject comprising
administering an effective amount of one or more antibiotics to a
subject who has been diagnosed as having sepsis or being at risk of
developing sepsis by the method described above.
[0025] In another aspect, the invention relates to a method for
decreasing the risk of organ failure in a subject, the method
comprising: a) determining whether the subject is at risk of organ
failure by: (i) determining in a biological sample obtained from
the subject a level of expression for each of a plurality of genes
selected from ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1, C19orf59,
CA12, CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14, CD300LF, CD93,
CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1, CYP27B1, DDIT4,
DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G, FCER2, FPR1, FPR2,
GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2,
HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3,
LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F, MT1G, MT1H, MT1M,
MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2, PANX2, PAPLN, PDLIM7,
PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES, PTGR1, RAB13, RARRES1,
RETN, RHBDD2, RNASE1, S100A12, S100A4, S100A8, S100A9, SERPINA1,
SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4,
UPP1 and VCAN to provide a sample gene signature, and (ii)
comparing the sample gene signature with a reference gene
signature, wherein the reference gene signature represents a
standard level of expression of each of the plurality of genes, and
wherein a difference between the sample gene signature and the
reference gene signature indicates that the subject is at risk of
organ failure, and b) if the subject is at risk of organ failure,
administering to the subject an effective amount of one or more
antibiotics.
[0026] In certain embodiments, the plurality of genes is selected
from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0027] In certain embodiments, the plurality of genes comprises
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0028] In certain embodiments, the plurality of genes consists of
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0029] In another aspect, the invention relates to a method for
decreasing the risk of a subject developing severe sepsis
comprising administering an effective amount of an agent that
counteracts endotoxin tolerance to a subject who has been diagnosed
as being at risk of developing severe sepsis by the method
described above.
[0030] In another aspect, the invention relates to a method for
decreasing the risk of organ failure in a subject comprising
administering an effective amount of an agent that counteracts
endotoxin tolerance to a subject who has been diagnosed as being at
risk of organ failure by the method described above.
[0031] In another aspect, the invention relates to a method for
decreasing the risk of a subject developing severe sepsis or organ
failure comprising administering to the subject an effective amount
of an agent that counteracts endotoxin tolerance. In certain
embodiments, the method may further comprise determining that the
subject is at risk of developing severe sepsis or organ failure by:
(a) determining in a biological sample obtained from the subject
the level of expression of a plurality of genes selected from
ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1, C19orf59, CA12, CAMP,
CCL1, CCL19, CCL22, CCL24, CCL7, CD14, CD300LF, CD93, CDK5RAP2,
CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1, CYP27B1, DDIT4, DHRS9,
DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G, FCER2, FPR1, FPR2, GK,
GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2, HK3,
HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3,
LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F, MT1G, MT1H, MT1M,
MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2, PANX2, PAPLN, PDLIM7,
PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES, PTGR1, RAB13, RARRES1,
RETN, RHBDD2, RNASE1, S100A12, S100A4, S100A8, S100A9, SERPINA1,
SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4,
UPP1 and VCAN to provide a sample gene signature, and (b) comparing
the sample gene signature with a reference gene signature, wherein
the reference gene signature represents a standard level of
expression of each of the plurality of genes, wherein a difference
between the sample gene signature and the reference gene signature
indicates that the subject is at risk of developing severe sepsis
or organ failure.
[0032] In certain embodiments, the plurality of genes is selected
from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0033] In certain embodiments, the plurality of genes comprises
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0034] In certain embodiments, the plurality of genes consists of
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0035] In another aspect, the invention relates to a method for
identifying a candidate agent for the treatment of sepsis, the
method comprising: a) contacting an endotoxin tolerant cell with a
test agent, b) determining the level of expression for each of a
plurality of Endotoxin Tolerance Signature genes in the endotoxin
tolerant cell to provide an expression signature, c) comparing the
expression signature with a reference expression signature, wherein
the reference signature represents the levels of expression of the
plurality of genes in a normal cell, and d) selecting the test
agent as a candidate agent for treatment of sepsis when the
expression signature substantially corresponds with the reference
signature.
[0036] In certain embodiments, the plurality of genes is selected
from ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1, C19orf59, CA12,
CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14, CD300LF, CD93,
CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1, CYP27B1, DDIT4,
DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G, FCER2, FPR1, FPR2,
GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2,
HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3,
LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F, MT1G, MT1H, MT1M,
MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2, PANX2, PAPLN, PDLIM7,
PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES, PTGR1, RAB13, RARRES1,
RETN, RHBDD2, RNASE1, S100A12, S100A4, S100A8, S100A9, SERPINA1,
SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4,
UPP1 and VCAN.
[0037] In certain embodiments, the plurality of genes is selected
from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0038] In certain embodiments, the plurality of genes comprises
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0039] In certain embodiments, the plurality of genes consists of
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0040] In another aspect, the invention relates to a kit for
determining a level of expression for each of a plurality of genes
selected from ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1, C19orf59,
CA12, CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14, CD300LF, CD93,
CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1, CYP27B1, DDIT4,
DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G, FCER2, FPR1, FPR2,
GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2,
HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3,
LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F, MT1G, MT1H, MT1M,
MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2, PANX2, PAPLN, PDLIM7,
PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES, PTGR1, RAB13, RARRES1,
RETN, RHBDD2, RNASE1, S100A12, S100A4, S100A8, S100A9, SERPINA1,
SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4,
UPP1 and VCAN in a sample, the kit comprising gene specific
reagents, each of the gene specific reagents capable of detecting
an expression product of a respective one of the plurality of genes
or complement thereof, and instructions for use.
[0041] In certain embodiments, the plurality of genes is selected
from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0042] In certain embodiments, the plurality of genes comprises
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0043] In certain embodiments, the plurality of genes consists of
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0044] In another aspect, the invention relates to a microarray for
detecting expression of a plurality of Endotoxin Tolerance
Signature genes in a sample, the microarray comprising a plurality
of polynucleotide probes attached to a solid support, each of the
polynucleotide probes capable of specifically hybridizing to an
expression product of a respective one of the plurality of genes or
complement thereof.
[0045] In certain embodiments, the plurality of genes are selected
from ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1, C19orf59, CA12,
CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14, CD300LF, CD93,
CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1, CYP27B1, DDIT4,
DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G, FCER2, FPR1, FPR2,
GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2,
HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3,
LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F, MT1G, MT1H, MT1M,
MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2, PANX2, PAPLN, PDLIM7,
PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES, PTGR1, RAB13, RARRES1,
RETN, RHBDD2, RNASE1, S100A12, S100A4, S100A8, S100A9, SERPINA1,
SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4,
UPP1 and VCAN.
[0046] In certain embodiments, the plurality of genes is selected
from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0047] In certain embodiments, the plurality of genes comprises
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0048] In certain embodiments, the plurality of genes consists of
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
BRIEF DESCRIPTION OF THE FIGURES
[0049] These and other features of the invention will become more
apparent in the following detailed description in which reference
is made to the appended drawings.
[0050] FIG. 1 shows a schematic representation of the method used
to define the Endotoxin Tolerance Signature and the Inflammatory
Signature. The Endotoxin Tolerance Signature was defined as 99
genes uniquely differentially expressed in endotoxin-tolerant
PBMCs, but not inflammatory PBMCs, as compared to controls (fold
change>2, p-value<0.05). The Inflammatory Signature was
defined as a 93 gene signature by selecting genes that were
consistently differentially expressed in an in vivo endotoxaemia
dataset.
[0051] FIG. 2 demonstrates that reanalysis of differential gene
expression from sepsis patients from published datasets showed a
strong association with the Endotoxin Tolerance Signature. A
gene-set test approach, ROAST, was used to characterize the
enrichment of "Endotoxin Tolerance" in sepsis patients versus
controls from 9 previously published datasets. All datasets
contained sepsis patients recruited at day 1 or 3 post-ICU
admission and were compared to "healthy" controls. The ROAST
gene-set test was run with 99999 rotations so the most significant
p-value resulting from this test is 0.00001. P-values from the
ROAST gene-set test were graphed as log (1/p-value), but the
untransformed p-values are shown for ease of visualization.
[0052] FIG. 3 shows that sepsis patients based on published
datasets generally showed a less significant association with the
Inflammatory Signature. A gene-set test approach, ROAST, was used
to characterize the enrichment of Inflammatory signature (white)
relative to the Endotoxin Tolerance Signature (grey) in sepsis
patients cf. controls in 9 previously published datasets. All
datasets contained sepsis patients recruited at days 1 and/or 3
post-ICU admission and were compared to `healthy` controls. The
ROAST gene-set test was run with 99999 rotations so the most
significant p-value resulting from this test is 0.00001. P-values
from the ROAST gene-set test were graphed as log (1/p-value), but
the untransformed p-values are shown for ease of visualization.
[0053] FIG. 4 reveals that the association between endotoxin
tolerance and sepsis is independent of the specific method used to
define the Endotoxin Tolerance Signature. Different endotoxin
tolerance related-signatures were identified based on genes
uniquely differentially expressed in endotoxin-tolerant PBMCs, but
not inflammatory PBMCs, as compared to controls at various
fold-change (FC) and P-value cut-offs. Datasets were as described
in the legend to FIG. 3 except the Day 0 RNA-Seq dataset is the one
described here. The final Endotoxin Tolerance Signature was defined
at fold-change (FC) and P-value cut-offs of 2 and 0.05,
respectively.
[0054] FIG. 5 shows that the Endotoxin Tolerance Signature is
strongly associated with sepsis patients at first clinical
presentation. A gene-set test approach was used to characterize the
enrichment, cf. controls, of the Endotoxin Tolerance and
Inflammatory signatures in prospective sepsis patients from a
unique in-house cohort recruited on first clinical suspicion of
sepsis (i.e. generally in the emergency ward prior to ICU
admission). Patients groups were subsequently defined based on
retrospective clinical characteristics as `Sepsis` or `No Sepsis`
consistent with the current sepsis criteria (Table 3). Analyses
were performed comparing `sepsis` and `no sepsis` group vs.
controls (a) and `sepsis` vs. `no sepsis` group (b). Additionally,
enrichment of the signature was also analyzed based on microbial
culture results within the `Sepsis` group (c) and the `No Sepsis`
(d) group (c).
[0055] FIG. 6 shows that the Endotoxin Tolerance Signature is
strongly associated with sepsis patients at first clinical
presentation and is associated with the severity of the disease and
organ failure. A gene-set test approach was used to characterize
the enrichment, cf. surgical controls, of the Endotoxin Tolerance
and Inflammatory signatures in prospective sepsis patients as
described for FIG. 5. (a) Patients were grouped into individual-,
combined-(3+), individual type of organ failure and no-organ
failure groups. (b) Patients were grouped into those requiring and
those not-requiring transfer to the ICU.
[0056] FIG. 7 shows a core set of endotoxin tolerance genes
characteristic of sepsis patients. A core set of 31 of the 99 genes
from the Endotoxin Tolerance Signature was determined based on the
most frequently differentially expressed genes observed in all
sepsis patient studies (literature and in-house datasets). For
better visual comparison across different studies, each individual
dataset was further transformed by dividing gene expression values
into six equal bins. Data is presented as a heatmap with lightest
and darkest shading representing relatively large and relatively
small changes in expression, respectively. The differentiation was
more obvious as a color heatmap.
[0057] FIG. 8 demonstrates a sub-network of genes from the
Endotoxin Tolerance Signature identified using the j-Activemodules
plug-in of Cytoscape. First a network was created by including
first level interactors of the genes listed in Table 1 and then
subjected to analysis using j-Activemodules which identifies
particularly dense (i.e. highly interconnected) subnetworks. Dark
nodes (genes) are highly dysregulated, and light nodes are direct
interactors of the dysregulated genes, lines represent "edges" and
indicate experimentally proven interactions. The fact that 60 of
the 99 genes in the signature were tightly interconnected in the
human cell implicates a biologically meaningful relationship
between these genes; i.e. that these genes are co-regulated or are
involved in a common purpose in the cell. Evident within the
network are hub proteins (central highly interconnected proteins
involved in cellular signalling and trafficking) including Serpin
A1, transcription factors CEBP.alpha.,.beta., EGR2, HNF4A, CXCL10,
and FCER2, as well as the prominent innate immune transcription
factors NFKB1, IRF1, STATE, JUN, and FOS, and receptor TLR4 (not
dysregulated themselves), suggesting their potential involvement in
endotoxin tolerance.
DETAILED DESCRIPTION OF THE INVENTION
[0058] A unique gene signature characteristic of endotoxin
tolerance (an "Endotoxin Tolerance Signature") is identified herein
that may be used in the diagnosis of sepsis. The Endotoxin
Tolerance Signature is able to differentiate between suspected
sepsis patients who either did or did not go on to develop sepsis,
and also to predict organ failure.
[0059] Certain embodiments of the invention thus relate to methods
of diagnosing endotoxin tolerance in a subject, for example a
patient known or suspected of having sepsis, using the Endotoxin
Tolerance Signature described herein. The presence of endotoxin
tolerance is shown to be an indication that a patient has sepsis,
and is furthermore an indication that the patient is at risk of
developing severe sepsis and/or organ failure. Certain embodiments
of the invention relate to methods of diagnosing sepsis in a
subject using the Endotoxin Tolerance Signature described herein.
In certain embodiments, the sepsis is severe sepsis. Certain
embodiments relate to methods of confirming sepsis in a subject
suspected of having sepsis a subject using the Endotoxin Tolerance
Signature described herein. Some embodiments relate to methods of
predicting whether a subject is at risk of developing severe sepsis
and/or organ failure using the Endotoxin Tolerance Signature
described herein.
[0060] As described herein, endotoxin tolerance-mediated immune
dysfunction has been determined to be present in a predominant
manner upon first presentation and throughout the clinical course
of disease. The data provided herein re-defines sepsis as a disease
characterized by endotoxin tolerance-mediated immune dysfunction at
all stages of clinical disease, and thus identifies endotoxin
tolerance as a potential therapeutic target in early and late
sepsis.
[0061] Certain embodiments of the invention thus relate to methods
of treating patients identified as having endotoxin tolerance, for
example by using the diagnostic methods described herein, in order
to reduce the risk that they will develop sepsis, severe sepsis
and/or organ failure. Certain embodiments relate to methods of
treating patients having sepsis, including severe sepsis, with an
agent that counteracts endotoxin tolerance.
[0062] Certain embodiments of the invention relate to methods of
identifying candidate agents for treatment of sepsis using the
Endotoxin Tolerance Signature described herein.
[0063] Certain embodiments relate to a method for diagnosing sepsis
in a subject, comprising determining in a biological sample
obtained from the subject a level of expression for each of a
plurality of Endotoxin Tolerance Signature genes to provide a
sample gene signature, and comparing the sample gene signature with
a reference gene signature, wherein the reference gene signature
represents a standard level of expression of each of the plurality
of genes; wherein a difference between the sample gene signature
and the reference gene signature indicates that the subject has
sepsis.
[0064] Certain embodiments relate to a method for identifying a
subject at risk of developing severe sepsis, comprising determining
in a biological sample obtained from the subject a level of
expression for each of a plurality of Endotoxin Tolerance Signature
genes to provide a sample gene signature, and comparing the sample
gene signature with a reference gene signature, wherein the
reference gene signature represents a standard level of expression
of each of the plurality of genes; wherein a difference between the
sample gene signature and the reference gene signature indicates
that the subject is at risk of developing severe sepsis.
[0065] Certain embodiments relate to a method for identifying a
subject at risk of organ failure, comprising determining in a
biological sample obtained from the subject a level of expression
for each of a plurality of Endotoxin Tolerance Signature genes to
provide a sample gene signature, and comparing the sample gene
signature with a reference gene signature, wherein the reference
gene signature represents a standard level of expression of each of
the plurality of genes; wherein a difference between the sample
gene signature and the reference gene signature indicates that the
subject is at risk of organ failure.
DEFINITIONS
[0066] For convenience, the meaning of certain terms and phrases
employed in the specification, examples, and appended claims are
provided below. The definitions are not meant to be limiting in
nature and serve only to facilitate understanding of certain
aspects of the invention. Unless defined otherwise, all technical
and scientific terms used herein have the same meaning as commonly
understood by one of ordinary skill in the art to which this
invention belongs.
[0067] The term "plurality" as used herein means more than one, for
example, two or more, three or more, four or more, and the
like.
[0068] The term "gene" refers to a nucleic acid sequence that
comprises coding sequences necessary for producing a polypeptide or
precursor. Control sequences that direct and/or control expression
of the coding sequences may also be encompassed by the term "gene"
in some instances. The polypeptide or precursor may be encoded by a
full length coding sequence or by a portion of the coding sequence.
A gene may contain one or more modifications in either the coding
or the untranslated regions that could affect the biological
activity or the chemical structure of the polypeptide or precursor,
the rate of expression, or the manner of expression control. Such
modifications include, but are not limited to, mutations,
insertions, deletions, and substitutions of one or more
nucleotides, including single nucleotide polymorphisms that occur
naturally in the population. The gene may constitute an
uninterrupted coding sequence or it may include one or more
subsequences. The term "gene" as used herein includes variants of
the genes identified in Table 1.
[0069] The terms "gene expression profile" or "gene signature"
refer to a group of genes expressed by a particular cell or tissue
type wherein expression of the genes taken together, or the
differential expression of such genes, is indicative and/or
predictive of a certain condition, such as sepsis.
[0070] The term "nucleic acid" as used herein, refers to a molecule
comprised of one or more nucleotides, for example, ribonucleotides,
deoxyribonucleotides, or both. The term includes monomers and
polymers of nucleotides, with the nucleotides being bound together,
in the case of the polymers, in sequence, typically via 5' to 3'
linkages, although alternative linkages are also contemplated in
some embodiments. The nucleotide polymers may be single or
double-stranded. The nucleotides may be naturally occurring or may
be synthetically produced analogs that are capable of forming
base-pair relationships with naturally occurring base pairs.
Examples of non-naturally occurring bases that are capable of
forming base-pairing relationships include, but are not limited to,
aza and deaza pyrimidine analogs, aza and deaza purine analogs, and
other heterocyclic base analogs, wherein one or more of the carbon
and nitrogen atoms of the pyrimidine rings have been substituted by
heteroatoms, e.g., oxygen, sulphur, selenium, phosphorus, and the
like.
[0071] The term "corresponding to" and grammatical variations
thereof as used herein with respect to a nucleic acid sequence
indicates that the nucleic acid sequence is identical to all or a
portion of a reference nucleic acid sequence. In contradistinction,
the term "complementary to" is used herein to indicate that the
nucleic acid sequence is identical to all or a portion of the
complementary strand of the reference nucleic acid sequence. For
illustration, the nucleic acid sequence "TATAC" corresponds to a
reference sequence "TATAC" and is complementary to a reference
sequence "GTATA." As used herein, "complement thereof" means a
nucleic acid that is complementary in nucleotide sequence to a
referenced nucleic acid. The complement of an mRNA may be an RNA
polynucleotide sequence or a DNA polynucleotide sequence. The
complement of a DNA polynucleotide may be an RNA polynucleotide or
a DNA polynucleotide.
[0072] The term "differential expression" refers to quantitative
and/or qualitative differences in the expression of a gene or a
protein in diseased tissue or cells versus normal tissue or cells.
For example, a differentially expressed gene may have its
expression activated or completely inactivated in normal versus
disease conditions, or may be up-regulated (over-expressed) or
down-regulated (under-expressed) in a disease condition versus a
normal condition. Stated another way, a gene or protein is
differentially expressed when expression of the gene or protein
occurs at a higher or lower level in the diseased tissues or cells
of a patient relative to the level of its expression in the normal
(disease-free) tissues or cells of the patient and/or control
tissues or cells.
[0073] The term "biological sample" refers to a sample obtained
from an organism (e.g., a human patient) or from components (e.g.,
cells) of an organism. The sample may be of any relevant biological
tissue or fluid. The sample may be a "clinical sample" which is a
sample derived from a patient. Such samples include, but are not
limited to, sputum, blood, blood cells (e.g., white cells),
amniotic fluid, plasma, semen, bone marrow, and tissue or fine
needle biopsy samples, urine, peritoneal fluid, and pleural fluid,
or cells therefrom. Biological samples may also include sections of
tissues such as frozen sections taken for histological purposes. A
biological sample may also be referred to as a "patient
sample."
[0074] As used herein, the terms "comprising," "having,"
"including" and "containing," and grammatical variations thereof,
are inclusive or open-ended and do not exclude additional,
unrecited elements and/or method steps. The term "consisting
essentially of" when used herein in connection with a composition,
use or method, denotes that additional elements and/or method steps
may be present, but that these additions do not materially affect
the manner in which the recited composition, method or use
functions. The term "consisting of" when used herein in connection
with a composition, use or method, excludes the presence of
additional elements and/or method steps. A composition, use or
method described herein as comprising certain elements and/or steps
may also, in certain embodiments consist essentially of those
elements and/or steps, and in other embodiments consist of those
elements and/or steps, whether or not these embodiments are
specifically referred to.
[0075] It is contemplated that any embodiment discussed herein can
be implemented with respect to any of the disclosed methods, uses
or compositions of the invention, and vice versa.
Sepsis
[0076] "Sepsis" generally refers to a clinical response to a
suspected or proven infection. Sepsis may be defined, for example,
as including two or more of the following symptoms: tachypnea or
tachycardia; leukocytosis or leukopenia; and hyperthermia or
hypothermia, and may manifest as a complex infectious and
immunological disorder. Many other symptoms may or may not occur
and have been defined by consensus meetings of physicians (see Bone
R C, Balk R A, Cerra F B, et al. Chest 2009; 136(5 Suppl):e28),
however none of these symptoms are specific for sepsis. Sepsis may
be complicated by organ failure and may require admission to an
intensive care ward in which case it is termed "severe sepsis."
When a patient, often in the emergency ward, acquires some of the
early symptoms associated with sepsis, they are frequently
considered to be suspected sepsis patients, which triggers a
special hospital protocol for treatment. However, only
retrospectively after 24-48 hours when infection is confirmed by
microbiological tests or the patient acquires more severe symptoms
including failure of one of more organs, are they confirmed to have
been "early stage sepsis" patients (see review in Lyle N H, et al.,
Annals of the New York Academy of Sciences 2014, 1323:101-14).
Endotoxin Tolerance Signature
[0077] In one aspect, the invention relates to a plurality of genes
regulated during sepsis, the expression profile of which serves to
define endotoxin tolerance in a subject. Differences in expression
of these genes, either up- or down-regulation depending on the gene
in question, when compared to a control defines a gene signature
that is indicative of endotoxin tolerance (an "Endotoxin Tolerance
Signature"). Non-limiting examples of endotoxin tolerance signature
genes (ETSGs) that may be comprised by an Endotoxin Tolerance
Signature in accordance with certain embodiments of the invention
are provided in Table 1.
[0078] The sequences of these genes can readily be obtained by one
of skill in the art from publicly available databases, such as the
GenBank database maintained by the National Center for
Biotechnology (NCBI), for example, by searching using the provided
gene symbols. These gene symbols are universally recognized by all
databases including HGNC, Entrez Gene, UniProtKB/Swiss-Prot, OMIM,
GeneLoc, and Ensembl; all aliases are defined by the Gene Cards
database. Non-limiting examples of representative gene sequences
available from GenBank are provided in Table 1.
TABLE-US-00001 TABLE 1 Representative Endotoxin Tolerance Signature
genes (ETSGs) Up (+) or GenBank Down (-) Gene Symbol Description
RefSeq # Regulation ADAM15 ADAM metallopeptidase domain 15
NP_001248393.1 - ADAMDEC1 ADAM-like, decysin 1 NP_001138743.1 +
ALCAM Activated leukocyte cell adhesion molecule NP_001230209.1 -
ALDH1A1 Aldehyde dehydrogenase 1 family, member A1 NP_000680.2 -
ANKRD1 Ankyrin repeat domain 1 (cardiac muscle) NP_055206.2 +
C19orf59 Chromosome 19 open reading frame 59 NP_777578.2 + CA12
Carbonic anhydrase XII NP_001209.1 + CAMP Cathelicidin
antimicrobial peptide NP_004336.3 - CCL1 Chemokine (C-C motif)
ligand 1; SCYA1 NP_002972.1 + CCL19 Chemokine (C-C motif) ligand
19; MIP3.beta. NP_006265.1 + CCL22 Chemokine (C-C motif) ligand 22;
MDC NP_002981.2 + CCL24 Chemokine (C-C motif) ligand 24; Eotaxin-2
NP_002982.2 + CCL7 Chemokine (C-C motif) ligand 7 NP_006264.2 +
CD14 CD14 molecule NP_000582.1 + CD300LF CD300 molecule-like family
member F NP_001276011.1 + CD93 CD93 molecule NP_036204.2 + CDK5RAP2
CDK5 regulatory subunit associated protein 2 NP_001011649.1 + CPVL
Carboxypeptidase, Vitellogenic-like NP_061902.2 - CST3 Cystatin C
NP_000090.1 - CST6 Cystatin E/M NP_001314.1 - CTSK Cathepsin K
NP_000387.1 - CXCL10 Chemokine (C-X-C motif) ligand 10 NP_001556.2
- CYP1B1 Cytochrome P450, family 1, subfamily B, NP_000095.2 +
polypeptide 1 CYP27B1 Cytochrome P450, family 27, subfamily B,
NP_000776.1 + polypeptide 1 DDIT4 DNA-damage-inducible transcript 4
NP_061931.1 + DHRS9 Dehydrogenase/reductase (SDR family) member
NP_001135742.1 - 9 DPYSL3 Dihydropyrimidinase-like 3 NP_001184223.1
+ EGR2 Early growth response 2 NP_000390.2 + EMR1 EGF-like module
containing, mucin-like, NP_001243181.1 + hormone receptor-like 1
EMR3 EGF-like module containing, mucin-like, NP_001276087.1 +
hormone receptor-like 3 FBP1 Fructose-1,6-bisphosphatase 1
NP_000498.2 + FCER1G Fc fragment of IgE, high affinity I, receptor
for; NP_004097.1 + gamma polypeptide FCER2 Fc fragment of Ige, low
affinity II, receptor for NP_001193948.2 + (CD23) FPR1 Formyl
peptide receptor 1 NP_001180235.1 + FPR2 Formyl peptide receptor 2
NP_001005738.1 + GK Glycerol kinase NP_000158.1 + GPNMB
Glycoprotein (transmembrane) NMB NP_001005340.1 - GPR137B G
protein-coupled receptor 137B NP_003263.1 + HBEGF Heparin-binding
EGF-like growth factor NP_001936.1 + HIST1H1C Histone cluster 1,
H1C NP_005310.1 + HIST2H2AA3 Histone cluster 2, H2AA3
NP_001035807.1 + HIST2H2AC Histone cluster 2, H2AC NP_003508.1 +
HK2 Hexokinase 2 NP_000180.2 + HK3 Hexokinase 3 (white cell)
NP_002106.2 + HPSE Heparanase NP_001092010.1 + HSD11B1
Hydroxysteroid (11-beta) dehydrogenase 1 NP_001193670.1 + HTRA1
HTRA serine peptidase 1 NP_002766.1 - IL18BP Interleukin 18 binding
protein NP_001034748.1 - IL3RA Interleukin 3 receptor, alpha (low
affinity) NP_001254642.1 + ITGB8 Integrin, beta 8 NP_002205.1 +
KIAA1199 KIAA1199 NP_001280227.1 + LILRA3 Leukocyte
immunoglobulin-like receptor, NP_001166125.1 + subfamily A (without
TM domain), member 3 LILRA5 Leukocyte immunoglobulin-like receptor,
NP_067073.1 + subfamily A (with TM domain), member 5 LIPA Lipase A,
lysosomal acid, cholesterol esterase NP_000226.2 - LY86 Lymphocyte
antigen 86 NP_004262.1 - MARCO Macrophage receptor with collagenous
structure NP_006761.1 + MGST1 Microsomal glutathione S-transferase
1 NP_001247440.1 + MMP7 Matrix metallopeptidase 7 (matrilysin,
uterine) NP_002414.1 + MT1F Metallothionein 1F NP_001288201.1 +
MT1G Metallothionein 1G NP_001288196.1 + MT1H Metallothionein 1H
NP_005942.1 + MT1M Metallothionein 1M NP_789846.1 + MT1X
Metallothionein 1X NP_005943.1 + MXD1 MAX dimerization protein 1
NP_001189442.1 + MYADM Myeloid-associated differentiation marker
NP_001018654.1 + NEFH Neurofilament, heavy polypeptide NP_066554.2
+ NQO1 NAD(P)H dehydrogenase, Quinone 1 NP_000894.1 - NRIP3 Nuclear
receptor interacting protein 3 NP_065696.1 + OLIG2 Oligodendrocyte
lineage transcription factor 2 NP_005797.1 + PANX2 Pannexin 2
NP_001153772.1 + PAPLN Papilin, proteoglycan-like sulfated
glycoprotein NP_775733.3 + PDLIM7 PDZ and LIM domain 7 (enigma)
NP_005442.2 + PLAUR Plasminogen activator, Urokinase receptor
NP_001005376.1 + PLD3 Phospholipase D family, member 3
NP_001026866.1 - PPBP Pro-platelet basic protein (chemokine (C-X-C
NP_002695.1 + motif) ligand 7) PROCR Protein C receptor,
endothelial NP_006395.2 + PSTPIP2 Proline-serine-threonine
phosphatase interacting NP_077748.3 - protein 2 PTGES Prostaglandin
E synthase NP_004869.1 + PTGR1 Prostaglandin reductase 1
NP_001139580.1 + RAB13 RAB13, member RAS oncogene family
NP_001258967.1 + RARRES1 Retinoic acid receptor responder
(Tazarotene NP_002879.2 - induced) 1 RETN Resistin NP_001180303.1 +
RHBDD2 Rhomboid domain containing 2 NP_001035546.1 + RNASE1
Ribonuclease, RNAse A family, 1 (pancreatic) NP_002924.1 - S100A12
S100 calcium binding protein A12 NP_005612.1 + S100A4 S100 calcium
binding protein A4 NP_002952.1 - S100A8 S100 calcium binding
protein A8 NP_002955.2 + S100A9 S100 calcium binding protein A9
NP_002956.1 + SERPINA1 Serpin peptidase inhibitor, Clade A
(.alpha.-1 anti- NP_000286.3 + proteinase, anti-trypsin), member 1
SERPINB7 Serpin peptidase inhibitor, Clade B (ovalbumin),
NP_001035237.1 + member 7 SLC16A10 Solute carrier family 16, member
10 (aromatic NP_061063.2 + amino acid transporter) SLC7A11 Solute
carrier family 7 (anionic amino acid NP_055146.1 + transporter
light chain, xc- system), member 11 TGM2 Transglutaminase 2
NP_004604.2 + TLR7 Toll-like receptor 7 NP_057646.1 - TMEM158
Transmembrane protein 158 (gene/pseudogene) NP_056259.2 + TREM1
Triggering receptor expressed on myeloid cells 1 NP_001229518.1 +
TSPAN4 Tetraspanin 4 NP_001020405.1 - UPP1 Uridine phosphorylase 1
NP_001274355.1 + VCAN Versican NP_001119808.1 +
[0079] An Endotoxin Tolerance Signature may comprise all endotoxin
tolerance signature genes (ETSGs) shown in Table 1, or it may
comprise a subset of these genes. In certain embodiments, the
Endotoxin Tolerance Signature may comprise as few as two ETSGs and
up to 99 of the ETSGs shown in Table 1. In some embodiments, the
Endotoxin Tolerance Signature comprises at least three, at least
four, at least five, at least six, at least seven, at least eight,
or least nine, at least ten, at least eleven, at least twelve, at
least thirteen, at least fourteen, or at least fifteen of the ETSGs
of Table 1. In some embodiments, the Endotoxin Tolerance Signature
comprises 15 or more ETSGs, for example, 20 or more, 25 or more or
30 or more ETSGs. In some embodiments, the Endotoxin Tolerance
Signature comprises about 31 ETSGs of Table 1. In some embodiments,
the Endotoxin Tolerance Signature comprises about 35, 40, 45, 50,
55, 60, 65, 70, 75, 80, 85, 90, 95, or 99 ETSGs.
[0080] In certain embodiments, the Endotoxin Tolerance Signature
comprises 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, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49 50, 51,
52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68,
69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85,
86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99 of the
ETSGs in Table 1.
[0081] In certain embodiments, the Endotoxin Tolerance Signature
comprises at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15
ETSGs selected from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9,
FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1,
PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9,
S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0082] In some embodiments, the Endotoxin Tolerance Signature
comprises at least 15, at least 20, at least 25 or at least 30
ETSGs selected from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9,
FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1,
PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9,
S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0083] In certain embodiments, the Endotoxin Tolerance Signature
comprises 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 or 31 ETSGs
selected from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9,
FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1,
PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9,
S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR, and may
optionally comprise one or more other ETSGs from Table 1.
[0084] In some embodiments, the Endotoxin Tolerance Signature
comprises the ETSGs: C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9,
FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1,
PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9,
S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR, and may
optionally comprise one or more other ETSGs from Table 1.
[0085] The change in expression of an ETSG may be defined by an
expression change direction, which indicates whether the gene is
up- or down-regulated in a subject with endotoxin tolerance when
compared to expression of the ETSG in a control (or reference)
sample. With reference to the ETSGs shown in Table 1 for example, a
subject with endotoxin tolerance would show an upregulation of one
or more of ADAMDEC1, ANKRD1, C19orf59, CA12, CCL1, CCL19, CCL22,
CCL24, CCL7, CD14, CD300LF, CD93, CDK5RAP2, CYP1B1, CYP27B1, DDIT4,
DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G, FCER2, FPR1, FPR2, GK,
GPR137B, HBEGF, HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2, HK3, HPSE,
HSD11B1, IL3RA, ITGB8, KIAA1199, LILRA3, LILRA5, MARCO, MGST1,
MMP7, MT1F, MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NRIP3,
OLIG2, PANX2, PAPLN, PDLIM7, PLAUR, PPBP, PROCR, PTGES, PTGR1,
RAB13, RETN, RHBDD2, S100A12, S100A8, S100A9, SERPINA1, SERPINB7,
SLC16A10, SLC7A11, TGM2, TMEM158, TREM1, UPP1 or VCAN, and a
downregulation of one or more of ADAM15, ALCAM, ALDH1A1, CAMP,
CPVL, CST3, CST6, CTSK, CXCL10, DHRS9, GPNMB, HTRA1, IL18BP, LIPA,
LY86, NQO1, PLD3, PSTPIP2, RARRES1, RNASE1, S100A4, TLR7 or
TSPAN4.
[0086] The change in expression of an ETSG may be optionally
further defined by a minimum fold change in expression level over
control. In certain embodiments, up- or down-regulation of a given
ETSG may be defined as an at least 1.5-fold change in the level of
expression of the gene when compared to a control. In some
embodiments, up- or down-regulation of a given ETSG may be defined
as a 2-fold or greater change in the level of expression of the
gene when compared to a control. A control (or standard or
reference) level of expression may be, for example, the level of
expression of the ETSG in a sample from a healthy subject, or the
level of expression of the ETSG in a non-endotoxin tolerant
cell.
Methods
Diagnostic Methods
[0087] Certain embodiments of the invention relate to diagnostic
methods that use the Endotoxin Tolerance Signature to determine
whether a subject having or suspected of having sepsis has
endotoxin tolerance and is, therefore, at risk of developing one or
more of sepsis, severe sepsis and/or organ failure.
[0088] In certain embodiments, the subject is suspected of having
sepsis and the method identifies the patient as having sepsis. In
some embodiments, the subject is suspected of having sepsis and the
method identifies the subject as being at risk of developing severe
sepsis and/or organ failure. In certain embodiments, the subject is
suspected of having sepsis and the method identifies the patient as
having severe sepsis.
[0089] Generally, the diagnostic methods comprise detecting the
expression of the genes comprised by the Endotoxin Tolerance
Signature in a biological sample obtained from a test subject.
Differences in expression of these genes when compared to a control
are determined. A difference in expression of at least two of these
genes in the defined expression change direction is indicative that
the subject has, or is at risk of developing, one or more of
sepsis, severe sepsis and/or organ failure.
[0090] In certain embodiments, a difference in expression of three
or more, four or more, five or more, six or more, seven or more,
eight or more, nine or more, ten or more, eleven or more, twelve or
more, thirteen or more, fourteen or more, or fifteen or more of the
ETSGs in the Endotoxin Tolerance Signature when compared to a
control sample is indicative that the subject has, or is at risk of
developing, one or more of sepsis, severe sepsis and/or organ
failure. In some embodiments, a difference in expression of at
least 15, at least 20, at least 25 or at least 30 of the ETSGs in
the Endotoxin Tolerance Signature when compared to a control sample
is indicative that the subject has, or is at risk of developing,
one or more of sepsis, severe sepsis and/or organ failure. In some
embodiments, a difference in expression of about 31 of the ETSGs in
the Endotoxin Tolerance Signature when compared to a control sample
is indicative that the subject has, or is at risk of developing,
one or more of sepsis, severe sepsis and/or organ failure.
[0091] In alternative embodiments, a difference in expression of at
least 20% of the ETSGs in the Endotoxin Tolerance Signature when
compared to a control sample is indicative that the subject has, or
is at risk of developing, one or more of sepsis, severe sepsis
and/or organ failure. In some embodiments, a difference in
expression of 20% or more, 30% or more, 40% or more, 50% or more,
60% or more, 70% or more, 80% or more, or 90% or more of the ETSGs
in the Endotoxin Tolerance Signature when compared to a control
sample is indicative that the subject has, or is at risk of
developing, one or more of sepsis, severe sepsis and/or organ
failure. In some embodiments, a difference in expression of at
least 35% of the ETSGs in the Endotoxin Tolerance Signature when
compared to a control sample is indicative that the subject has, or
is at risk of developing, one or more of sepsis, severe sepsis
and/or organ failure.
[0092] In some embodiments, a difference in expression of each of
the ETSGs in an Endotoxin Tolerance Signature when compared to a
control sample is indicative that the subject has, or is at risk of
developing, one or more of sepsis, severe sepsis and/or organ
failure, wherein the Endotoxin Tolerance Signature may comprise
between two and about 99 ETSGs, for example, between about 3, 4, 5,
6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 25 or 30 and about 99
ETSGs.
[0093] In certain embodiments, a difference in expression of 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,
39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49 50, 51, 52, 53, 54, 55,
56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,
73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
90, 91, 92, 93, 94, 95, 96, 97, 98, or 99 of the ETSGs in Table 1
when compared to a control sample is indicative that the subject
has, or is at risk of developing, one or more of sepsis, severe
sepsis and/or organ failure.
[0094] In certain embodiments, a difference in expression of 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, or 31 of the following ETSGs
when compared to a control sample is indicative that the subject
has, or is at risk of developing, one or more of sepsis, severe
sepsis and/or organ failure: C19orf59, CCL22, CD14, CD300LF,
CYP1B1, DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE,
LILRA5, MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4,
S100A9, S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0095] The biological sample may comprise, for example, blood,
plasma, serum, tissue, amniotic fluid, saliva, urine, stool,
bronchoalveolar lavage fluid, cerebrospinal fluid, or cells (such
as skin cells) or cellular extracts.
[0096] The expression of the ETSGs comprised by the Endotoxin
Tolerance Signature may be determined by detection of an expression
product of each gene. The expression product may be, for example,
RNA, cDNA prepared from RNA, or protein. When the expression
product is RNA or cDNA, the entire sequence of the gene may be
detected, or any definitive portion of the gene, for example, a
sequence of 10 nucleotides or more, may be detected.
[0097] Methods of detecting and quantifying expression of genes are
well-known in the art (see, for example, Current Protocols in
Molecular Biology, 1987 & updates, Ausubel et al. (ed.), Wiley
& Sons, New York, N.Y.) and include the use of detectably
labelled polynucleotide probes, antibodies, aptamers, and the
like.
[0098] In certain embodiments, one or more of polymerase chain
reaction (PCR), reverse transcriptase-(RT) PCR, Q-beta replicase
amplification, ligase chain reaction, nucleic acid sequence
amplification, signal amplification (Ampliprobe), light cycling,
differential display, Northern analysis, hybridization,
microarrays, RNA-Seq, nucleic acid sequencing, MassArray analysis,
and MALDI-TOF mass spectrometry may be employed in determining
expression of the ETSGs.
[0099] In certain embodiments, the diagnostic methods employ
detectably labelled polynucleotides for detecting expression of the
ETSGs. The methods may further comprise one or more of isolation of
nucleic acids from the sample, purification of the nucleic acids,
reverse transcription of RNA, and/or nucleic acid amplification. In
some embodiments, the polynucleotide probes used to determine
expression of the ETSGs may be immobilized on a solid support, for
example, as an array or microarray allowing for more rapid
processing of the sample. Methods of preparing arrays and
microarrays are well known in the art. In addition, a number of
standard microarrays are available commercially that include probes
for detecting some of the genes identified herein as ETSGs and thus
may be suitable for use in the disclosed diagnostic methods. For
example, Affymetrix U133 GeneChip.TM. arrays (Affymetrix, Inc.,
Santa Clara, Calif.), Agilent Technologies genomic cDNA microarrays
(Santa Clara, Calif.), and arrays available from Illumina, Inc.
(San Diego, Calif.). These arrays have probe sets for the whole
human genome immobilized on a chip, and can be used to determine
up- and down-regulation of genes in test samples. Custom-made
arrays and microarrays for detecting pre-selected genes are also
available commercially from a number of companies. Instruments and
reagents for performing gene expression analysis are commercially
available (for example, the Affymetrix GeneChip.TM. System). The
expression data obtained from the analysis may then be input into
an appropriate database for further analysis if necessary or
desired.
[0100] In some embodiments, the differentially expressed genes can
be detected, after conversion to cDNAs by the use of
Matrix-assisted laser desorption/ionization-time of flight
(MALDI-TOF) mass spectrometry using, for example the Sequenom
MassARRAY.RTM. system (see, for example, Kricka L J. Clin Chem
1999; 45:453-458).
[0101] The expression of certain genes known as "reference genes,"
"control genes" or "housekeeping genes" may also be determined in
the sample as a means of ensuring the veracity of the expression
profile. Reference genes are genes that are consistently expressed
in many tissue types, including cancerous and normal tissues, and
thus are useful to normalize gene expression profiles. Determining
the expression of reference genes in parallel with the genes in the
Endotoxin Tolerance Signature provides further assurance that the
techniques used for determination of the gene expression profile
are working properly. Appropriate reference genes (also referred to
herein as control genes and housekeeping genes) can be readily
selected by the skilled person.
[0102] The expression levels determined for the ETSGs of the
Endotoxin Tolerance Signature are compared to a suitable reference
or control, which may be for example expression levels of the ETSGs
in a biological sample from a healthy individual or expression
levels of the ETSGs in a non-endotoxin tolerant cell. The
comparison may include, for example, a visual inspection and/or an
arithmetic or statistical comparison of measurements and may take
into account expression of any reference genes. Suitable methods of
comparison to determine differences in expression levels of genes
are well known in the art.
[0103] In certain embodiments, the diagnostic methods may be used
as confirmatory diagnostics to standard sepsis diagnostic
procedures. In some embodiments, the diagnostic methods may be used
as a stand-alone diagnostic.
[0104] In certain embodiments, the diagnostic methods may be used
to confirm sepsis in a subject suspected of having sepsis. The
subject may have already undergone one or more assessments to
determine whether they meet the standard diagnostic criteria for
sepsis, for example, microbial culture analysis, measurement of
blood pressure, white blood cell count, measurement of temperature,
measurement of respiratory rate, and/or measurement of heart rate.
In certain embodiments, the diagnostic method may be used to
confirm sepsis in a patient having been diagnosed as having sepsis
by standard diagnostic criteria. In certain embodiments, the
diagnostic method may be used to diagnose a patient with sepsis as
having severe sepsis and/or being at risk of organ failure.
[0105] In certain embodiments, determining the level of expression
of ETSGs in a biological sample comprises detecting the presence in
the biological sample of a plurality of mRNAs encoded by a
plurality of ETSGs. In some embodiments, detecting the presence in
the sample of mRNAs encoded by the ETSGs comprises performing a
reverse transcription reaction using mRNAs obtained from the
biological sample to generate cDNA products, and contacting the
cDNA products with nucleic acid probes that are capable of
hybridizing to cDNAs that comprise nucleotide sequences
complementary to mRNAs encoded by the ETSGs.
[0106] In some embodiments, the methods comprise contacting cDNA
products generated by a reverse transcription reaction using mRNAs
obtained from a biological sample with a microarray comprising
nucleic acid probes capable of hybridizing to cDNAs that comprise
nucleotide sequences complementary to mRNAs encoded by a plurality
of ETSGs.
Methods of Treatment
[0107] In certain embodiments, the invention relates to methods of
treating patients identified as having endotoxin tolerance, for
example by using the diagnostic methods described herein, in order
to reduce the risk that they will develop sepsis, severe sepsis
and/or organ failure. In certain embodiments, early identification
of the immunological state of sepsis patients by the methods
described herein helps to guide selection of an appropriate
therapy.
[0108] In certain embodiments, when a patient is identified as
having endotoxin tolerance and being at risk of developing sepsis,
severe sepsis and/or organ failure, the method of treatment
comprises administering a therapeutically effective dose of at
least one antibiotic that is indicated for the treatment of severe
sepsis to the patient.
[0109] Examples of suitable antibiotics for treating severe sepsis
include, but are not limited to, glycopeptides (such as vancomycin,
oritvancin or televancin) ceflasporins (such as ceftriaxone,
cefotaxime, or cefepime), beta-lactams/beta-lactamase inhibitors
(such as piperacillin-tazobactam, ticarcillin-clavulanate),
carbapenems (such as imipenem or meropenem), quinolones and
fluoroquinolones (such as ciprofloxacin, moxifloxacin or
levofloxacin), aminoglycosides (such as gentamicin, tobramycin or
amikacin), macrolides (such as azithromycin, clarithromycin or
erythromycin) and monobactams (such as aztreonam), and various
combinations thereof. Typically combinations comprise antibiotics
from different classes.
[0110] As demonstrated herein, sepsis may be defined as a disease
characterized by endotoxin tolerance-mediated immune dysfunction.
Thus counteracting endotoxin tolerance in sepsis patients is a
potential therapeutic approach to prevent or decrease the
likelihood of the patient developing severe sepsis and/or organ
failure. Accordingly, in some embodiments, the invention relates to
methods of treating a patient with sepsis that comprise
administering to the patient an agent that counteracts endotoxin
tolerance. In some embodiments, the invention relates to a method
of preventing or decreasing the risk of a patient developing severe
sepsis and/or organ failure comprising administering to the patient
an agent that counteracts endotoxin tolerance. In certain
embodiments, patients are identified as being at risk of developing
sepsis, severe sepsis and/or organ failure by the diagnostic
methods described herein.
[0111] The agent that counteracts endotoxin tolerance may be, for
example, an immunotherapy. In some embodiments, the agent that
counteracts endotoxin tolerance comprises immune cells. Other
examples of agents that counteract endotoxin tolerance include, but
are not limited to, interferon-gamma, CpG oligonucleotides alone or
in combination with IL-10, anti-CD40 antibodies, inhibitors of
STAT3, inhibitors of STATE, inhibitors of p50, inhibitors of
NF.kappa.B, inhibitors of IKK.beta., imidazoquinolines and
zoledronic acid.
[0112] Endotoxin tolerance may result in macrophages being "locked"
into an M2 state. In certain embodiments, the agent that
counteracts endotoxin tolerance is capable of altering macrophage
phenotype from M2 to M1, or M2 to M0 (which represents uncommitted
macrophages).
[0113] In some embodiments, the invention relates to methods of
treating a patient with sepsis that comprise administering to the
patient an agent that alters macrophage phenotype from M2 to M1. In
some embodiments, the invention relates to a method of preventing
or decreasing the risk of a patient developing severe sepsis and/or
organ failure comprising administering to the patient an agent that
alters macrophage phenotype from M2 to M1. In certain embodiments,
patients are identified as being at risk of developing sepsis,
severe sepsis and/or organ failure by the diagnostic methods
described herein.
[0114] In certain embodiments, the agent capable of altering
macrophage phenotype from M2 to M1 is selected from an
immunotherapy, immune cells, interferon-gamma, CpG oligonucleotides
alone or in combination with IL-10, anti-CD40 antibodies,
inhibitors of STAT3, inhibitors of STATE, inhibitors of p50,
inhibitors of NF.kappa.B, inhibitors of IKK.beta.,
imidazoquinolines and zoledronic acid.
[0115] Certain embodiments of the invention relate to a method for
decreasing the risk of a subject developing severe sepsis
comprising administering an effective amount of an agent that
counteracts endotoxin tolerance to a subject in need thereof. In
some embodiments, the subject has been diagnosed as being at risk
for developing severe sepsis by a method disclosed herein.
[0116] Certain embodiments of the invention relate to a method for
decreasing the risk of organ failure in a subject comprising
administering an effective amount of an agent that counteracts
endotoxin tolerance to a subject in need thereof. In some
embodiment, the subject has been diagnosed as being at risk of
organ failure by a method disclosed herein.
[0117] Certain embodiments of the invention relate to a method for
treating sepsis, comprising administering an effective amount of an
agent that counteracts endotoxin tolerance to a subject in need
thereof. In some embodiments, the subject has been diagnosed as
having sepsis by a method disclosed herein.
[0118] In one embodiment, the agent that counteracts endotoxin
tolerance and finds use in methods disclosed herein may be an
immunotherapy. In one embodiment, the agent that counteracts
endotoxin tolerance and finds use in methods disclosed herein
comprises immune cells. In one embodiment, the immune cell is a
syngeneic immune cell, for example, the cell may be from the
subject to whom the immune cell is being administered. In another
embodiment, the immune cell is an allogeneic immune cell, that is,
from an individual other than the subject to whom the immune cell
is being administered.
[0119] In one embodiment, the agent that counteracts endotoxin
tolerance and finds use in methods disclosed herein is interferon
gamma. In one embodiment, the agent that counteracts endotoxin
tolerance and finds use in methods disclosed herein is a
CpG-oligonucleotide (ODN). In one embodiment, the agent that
counteracts endotoxin tolerance and finds use in methods disclosed
herein is a combination of a CpG ODN and interleukin-10 (IL-10). In
one embodiment, the agent that counteracts endotoxin tolerance and
finds use in methods disclosed herein is an anti-CD40 antibody. In
one embodiment, the agent that counteracts endotoxin tolerance and
finds use in methods disclosed herein is an inhibitor of STAT3. In
one embodiment, the agent that counteracts endotoxin tolerance and
finds use in methods disclosed herein is an inhibitor of STAT-6. In
one embodiment, the agent that counteracts endotoxin tolerance and
finds use in methods disclosed herein is an inhibitor of p50. In
one embodiment, the agent that counteracts endotoxin tolerance and
finds use in methods disclosed herein is an inhibitor of
NF.kappa.B. In one embodiment, the agent that counteracts endotoxin
tolerance and finds use in methods disclosed herein is an inhibitor
of I.kappa..kappa..beta.. In one embodiment, the agent that
counteracts endotoxin tolerance and finds use in methods disclosed
herein is an immidazoqinolone. In one embodiment, the agent that
counteracts endotoxin tolerance and finds use in methods disclosed
herein is zoledonic acid.
Methods of Screening
[0120] Certain embodiments of the invention relate to methods for
identifying a candidate agent for the treatment of sepsis by
evaluating the effect of a test agent on the expression of the
ETSGs comprised by an Endotoxin Tolerance Signature. The ability of
the test compound to affect expression of the ETSGs may be assessed
for example by contacting a cell in vitro with the test compound,
determining the expression of the ETSGs in the cell and comparing
the expression of the ETSGs in the cell with the level of
expression of the same ETSGs in a control cell.
[0121] Expression of the ETSGs may be assessed by various methods
known in the art as described herein and elsewhere.
[0122] In certain embodiments, the test cell may be an endotoxin
tolerant cell and the control cell may be a non-endotoxin tolerant
(normal) cell. In accordance with this embodiment, if the pattern
of expression (or gene signature) of the cell treated with the test
agent substantially corresponds to the pattern of expression (or
gene signature) of the control cell, this indicates that the test
agent is a candidate agent for the treatment of sepsis. By
"substantially corresponds" in this context, it is meant that
expression of those ETSG that are upregulated in exotoxin tolerant
cells is decreased and expression of those ETSGs that are
downregulated in exotoxin tolerant cells is increased.
[0123] In some embodiments, the level of expression of at least one
of the ETSGs in the treated cell is within a predetermined margin
of the level of expression of the same ETSG in the control cell.
For example, within about .+-.25%, within about .+-.20%, within
about .+-.15%, or within about .+-.10% of the level of expression
of the same ETSG in the control cell.
[0124] In some embodiments, the method may further comprise
contacting the cell with an endotoxin for a sufficient time to
induce endotoxin tolerance in the cell prior to contacting the cell
with the test agent. The endotoxin may be, for example, a bacterial
lipopolysaccharide (LPS) or lipoteichoic acid or a combination
thereof. The LPS or lipoteichoic acid may be in an isolated form,
or may be provided by contacting the cell with a bacterium that
naturally contains the LPS and/or lipoteichoic acid. The amount of
time required to induce endotoxin tolerance can be readily
determined by the skilled person. More than one treatment with
endotoxin may be required to induce endotoxin tolerance. In
general, a time between about 12 and about 24 hours may be used,
for example, about 14, about 16, about 18 or about 20 hours, and
between one and three treatments with endotoxin. When multiple
treatments are used, the endotoxin used in each treatment may be
the same or different.
[0125] In some embodiments the method of screening may include
assessing the endotoxin tolerant cell for restoration of the
ability to react to endotoxin, thus indicating that the test agent
is capable of breaking tolerance in the cell. In some embodiments,
the method of screening further comprises contacting a second cell
with an agent known to counteract endotoxin tolerance, such as
interferon-gamma, a CpG-oligonucleotide (with or without IL-10), an
anti-CD40 antibody, an inhibitor of STAT3, an inhibitor of STAT6,
an inhibitor of p50, an inhibitor of NF.kappa.B, an inhibitor of
IKK.beta., an imidazoquinolone or zoledronic acid, and determining
the expression of the same ETSGs in the second cell.
[0126] In certain embodiments, the method may further comprise
assaying the test agent for the ability to alter macrophage
phenotype from M2 to M1.
Kits and Microarrays
[0127] Certain embodiments of the invention relate to kits useful
for detecting ETSGs as identified herein. Accordingly, the kit will
comprise one or more reagents for determining expression of a
plurality, for example two or more, ETSGs. Typically, the kit will
comprise a collection of reagents, for example, two or more, that
are used together to perform a diagnostic method, or one or more
steps of a diagnostic method, as described herein, and which are
provided together, usually within a common packaging.
[0128] The one or more reagents for determining expression of an
ETSG may comprise a gene specific probe that is capable of
detecting an expression product of the ETSG (nucleic acid or
protein) or the complement of a nucleic acid expression product.
Polynucleotide primers for reverse transcription of mRNA encoded by
the ETSG, and/or for amplification of a nucleic acid sequence from
the ETSG or from cDNA prepared from the ETSG encoded mRNA may also
be provided in the kit.
[0129] In certain embodiments, the kit comprises gene specific
probes for a plurality of ETSGs are selected from the ETSGs listed
in Table 1. In some embodiments, the plurality of ETSGs comprise
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0130] In certain embodiments, a kit comprises gene specific probes
for 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, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49 50, 51, 52, 53,
54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70,
71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87,
88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99 of the ETSGs in
Table 1.
[0131] In certain embodiments, the gene specific probes of a kit
that are specific for ETSGs comprise probes for ETSGs selected from
Table 1.
[0132] In certain embodiments, the gene specific probes of a kit
that are specific for ETSGs consist of probes for ETSGs selected
from Table 1.
[0133] In certain embodiments, the gene specific probes of a kit
that are specific for ETSGs consists of probes for all the ETSGs in
Table 1.
[0134] In certain embodiments, the gene specific probes of a kit
that are specific for ETSGs comprise probes for ETSGs selected from
C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1, FPR2,
GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7, PLAUR,
PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12, SERPINA1,
UPP1, CPVL, CST3, LY86 and PROCR.
[0135] In certain embodiments, the gene specific probes of a kit
that are specific for ETSGs consist of probes for ETSGs selected
from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0136] In certain embodiments, the gene specific probes of a kit
that are specific for ETSGs consist of probes for each of the
following: C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G,
FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0137] In certain embodiments, a kit comprises gene specific probes
for 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, or 31 of the following
ETSGs: C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0138] In certain embodiments, the kit may comprise or consist of a
microarray that comprises a plurality of ETSG specific
polynucleotide probes immobilized onto a solid support. The
microarray may further comprise control polynucleotide probes
specific for control sequences, such as housekeeping genes.
[0139] The kit may optionally include one or more other reagents
required to conduct a biological procedure, such as buffers, salts,
enzymes, enzyme co-factors, substrates, detection reagents, washing
reagents, and the like. Additional components, such as buffers and
solutions for the isolation and/or treatment of a test sample, may
also be included in the kit. The kit may additionally include one
or more control sequences or samples.
[0140] One or more of the components of the kit may optionally be
lyophilised and the kit may further comprise reagents suitable for
the reconstitution of the lyophilised component(s).
[0141] The various components of the kit are provided in suitable
containers. In some embodiments, the container may itself be a
suitable vessel for carrying out the biological procedure, for
example, a microtitre plate. Where appropriate, the kit may also
optionally contain reaction vessels, mixing vessels and other
components that facilitate the preparation of reagents or a test
sample, or the carrying out of the biological procedure. The kit
may also include one or more instruments for assisting with
obtaining a test sample, such as a syringe, pipette, forceps, or
the like.
[0142] In some embodiments, reagents comprised by the kit or their
containers may be colour-coded to facilitate their use. When
reagents are colour-coded, addition of one reagent to another in a
particular step may for example result in a change in the colour of
the mixture, thus providing an indication that the step was carried
out.
[0143] The kit can optionally include instructions for use, which
may be provided in paper form, in computer-readable form, such as a
CD, DVD, USB stick or the like, or in the form of directions or
instructions for accessing a website. The kit may also comprise
computer readable media comprising software, or directions or
instructions for accessing a website that provides software, to
assist in the interpretation of results obtained from using the
kit.
[0144] Certain embodiments of the invention relate to microarrays
for detection of a plurality of ETSGs. In one embodiment, the
microarrays comprise a plurality of polynucleotide probes attached
to a solid support, each of the polynucleotide probes capable of
specifically hybridizing to an expression product (or complement
thereof) of a respective one of the plurality of ETSGs. The
microarray may optionally include one or more control probes, for
example, probes capable of detecting the expression of housekeeping
genes. In some embodiments, the microarray may further comprise
probes for a plurality of Inflammatory Signature genes, for
example, selected from those identified in Table 4. For
microanalysis, probe sequences are typically between about 15 and
about 100 nucleotides in length, for example, between about 15 and
about 90 nucleotides in length, between about 15 and about 80
nucleotides in length, between about 15 and about 70 nucleotides in
length, between about 15 and about 60 nucleotides in length, or
between about 20 and about 60 nucleotides in length. By way of
example only and not meant to be limiting, generally probe
sequences comprise about 25 nt in Affymetrix arrays, and about 60
nt in Agilent arrays.
[0145] In certain embodiments, the microarray comprises a plurality
of nucleic acid probes capable of hybridizing to cDNAs that
comprise nucleotide sequences complementary to mRNAs encoded by a
plurality of ETSGs.
[0146] In some embodiments, the microarray consists essentially of
nucleic acid probes capable of hybridizing to cDNAs that comprise
nucleotide sequences complementary to mRNAs encoded by a plurality
of ETSGs. In some embodiments, the microarray consists essentially
of (i) nucleic acid probes capable of hybridizing to cDNAs that
comprise nucleotide sequences complementary to mRNAs encoded by a
plurality of ETSGs, and (ii) nucleic acid probes capable of
hybridizing to cDNAs that comprise nucleotide sequences
complementary to mRNAs encoded by a partial set of non-ETSGs. In
some embodiments, the microarray consists essentially of (i)
nucleic acid probes capable of hybridizing to cDNAs that comprise
nucleotide sequences complementary to mRNAs encoded by a plurality
of ETSGs, and (ii) nucleic acid probes capable of hybridizing to
cDNAs that comprise nucleotide sequences complementary to mRNAs
encoded by a partial set of housekeeping genes. In some
embodiments, the microarray consists essentially of (i) nucleic
acid probes capable of hybridizing to cDNAs that comprise
nucleotide sequences complementary to mRNAs encoded by a plurality
of ETSGs, and (ii) nucleic acid probes capable of hybridizing to
cDNAs that comprise nucleotide sequences complementary to mRNAs
encoded by a plurality of Inflammatory Signature genes. In some
embodiments, the microarray consists essentially of (i) nucleic
acid probes capable of hybridizing to cDNAs that comprise
nucleotide sequences complementary to mRNAs encoded by a plurality
of ETSGs, (ii) nucleic acid probes capable of hybridizing to cDNAs
that comprise nucleotide sequences complementary to mRNAs encoded
by a plurality of Inflammatory Signature genes, and (iii) nucleic
acid probes capable of hybridizing to cDNAs that comprise
nucleotide sequences complementary to mRNAs encoded by a partial
set of housekeeping genes. In some embodiments, the microarray
consists essentially of (i) nucleic acid probes capable of
hybridizing to cDNAs that comprise nucleotide sequences
complementary to mRNAs encoded by a plurality of ETSGs, (ii)
nucleic acid probes capable of hybridizing to cDNAs that comprise
nucleotide sequences complementary to mRNAs encoded by a plurality
of Inflammatory Signature genes, and (iii) nucleic acid probes
capable of hybridizing to cDNAs that comprise nucleotide sequences
complementary to mRNAs encoded by a partial set of non-ETSGs.
[0147] In some embodiments, the microarray consists of nucleic acid
probes capable of hybridizing to cDNAs that comprise nucleotide
sequences complementary to mRNAs encoded by a plurality of ETSGs.
In some embodiments, the microarray consists of (i) nucleic acid
probes capable of hybridizing to cDNAs that comprise nucleotide
sequences complementary to mRNAs encoded by a plurality of ETSGs,
and (ii) nucleic acid probes capable of hybridizing to cDNAs that
comprise nucleotide sequences complementary to mRNAs encoded by a
partial set of non-ETSGs. In some embodiments, the microarray
consists of (i) nucleic acid probes capable of hybridizing to cDNAs
that comprise nucleotide sequences complementary to mRNAs encoded
by a plurality of ETSGs, and (ii) nucleic acid probes capable of
hybridizing to cDNAs that comprise nucleotide sequences
complementary to mRNAs encoded by a partial set of housekeeping
genes. In some embodiments, the microarray consists of (i) nucleic
acid probes capable of hybridizing to cDNAs that comprise
nucleotide sequences complementary to mRNAs encoded by a plurality
of ETSGs, and (ii) nucleic acid probes capable of hybridizing to
cDNAs that comprise nucleotide sequences complementary to mRNAs
encoded by a plurality of Inflammatory Signature genes. In some
embodiments, the microarray consists of (i) nucleic acid probes
capable of hybridizing to cDNAs that comprise nucleotide sequences
complementary to mRNAs encoded by a plurality of ETSGs, (ii)
nucleic acid probes capable of hybridizing to cDNAs that comprise
nucleotide sequences complementary to mRNAs encoded by a plurality
of Inflammatory Signature genes, and (iii) nucleic acid probes
capable of hybridizing to cDNAs that comprise nucleotide sequences
complementary to mRNAs encoded by a partial set of housekeeping
genes. In some embodiments, the microarray consists of (i) nucleic
acid probes capable of hybridizing to cDNAs that comprise
nucleotide sequences complementary to mRNAs encoded by a plurality
of ETSGs, (ii) nucleic acid probes capable of hybridizing to cDNAs
that comprise nucleotide sequences complementary to mRNAs encoded
by a plurality of Inflammatory Signature genes, and (iii) nucleic
acid probes capable of hybridizing to cDNAs that comprise
nucleotide sequences complementary to mRNAs encoded by a partial
set of non-ETSGs.
[0148] In some embodiments, the number of nucleic acid probes
capable of hybridizing to cDNAs that comprise nucleotide sequences
complementary to mRNAs encoded by a plurality of ETSGs is greater
than the number of other nucleic acid probes of the microarray. In
some embodiments, the number of nucleic acid probes capable of
hybridizing to cDNAs that comprise nucleotide sequences
complementary to mRNAs encoded by ETSGs plus the number of nucleic
acid probes capable of hybridizing to cDNAs that comprise
nucleotide sequences complementary to mRNAs encoded by Inflammatory
Signature genes is greater than the number of other nucleic acid
probes of the microarray.
[0149] In some embodiments, the plurality of ETSGs are selected
from the ETSGs listed in Table 1. In some embodiments, the
plurality of ETSGs comprise C19orf59, CCL22, CD14, CD300LF, CYP1B1,
DHRS9, FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5,
MGST1, PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9,
S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR. In some
embodiments, the plurality of Inflammatory Signature genes are
selected from the genes listed in Table 4.
[0150] In certain embodiments, a microarray includes probes for 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, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49 50, 51, 52, 53, 54,
55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88,
89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99 of the ETSGs in Table
1.
[0151] In certain embodiments, the plurality of probes of a
microarray that are specific for ETSGs comprise probes for ETSGs
selected from Table 1.
[0152] In certain embodiments, the plurality of probes of a
microarray that are specific for ETSGs consists of probes for ETSGs
selected from Table 1.
[0153] In certain embodiments, the plurality of probes of a
microarray that are specific for ETSGs consists of probes for all
the ETSGs in Table 1.
[0154] In certain embodiments, the plurality of probes of a
microarray that are specific for ETSGs comprises probes for ETSGs
selected from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9,
FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1,
PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9,
S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0155] In certain embodiments, the plurality of probes of a
microarray that are specific for ETSGs consists of probes for ETSGs
selected from C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9,
FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1,
PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9,
S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0156] In certain embodiments, the plurality of probes of a
microarray that are specific for ETSGs consists of probes for each
of the following: C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9,
FCER1G, FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1,
PDLIM7, PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9,
S100A12, SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0157] In certain embodiments, a microarray includes probes for 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, or 31 of the following
ETSGs: C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
Further Aspects and Embodiments
[0158] Also disclosed herein are the following further aspects and
embodiments of the invention:
[0159] In one embodiment, there is provided a method of identifying
a patient who has severe sepsis or is at high risk of developing
severe sepsis comprising obtaining a biological sample from the
individual and determining the level of expression of at least two
or more genes from the endotoxin tolerance signature whereby the
risk of sepsis, severe sepsis or organ failure is indicated by the
altered expression of endotoxin tolerance signature genes relative
to the expression of the same genes in non-sepsis individuals.
[0160] In one aspect, the invention provides a method of
identifying a patient who has severe sepsis or is at high risk of
developing severe sepsis, comprising obtaining a biological sample
from the patient and determining the level of expression of at
least two, or at least three, or at least four, or at least five,
or at least six, or at least seven, or at least eight, or at least
nine, or at least ten, or at least eleven, or at least twelve, or
at least thirteen, or at least fourteen, or at least fifteen
different Endotoxin Tolerance Signature Genes (ETSGs) in the
biological sample, whereby the presence or high risk of severe
sepsis is indicated by the level of expression of the ETSGs. In one
embodiment the level of expression of more than 15 different ETGSs
is determined. In one embodiment the level of expression of more
than 20 different ETGSs is determined. In one embodiment the level
of expression of more than 25 different ETGSs is determined. In one
embodiment the level of expression of more than 30 different ETGSs
is determined. In one embodiment the level of expression of about
31 different ETGSs is determined.
[0161] In one embodiment, at least two, or at least three, or at
least four, or at least five, or at least six, or at least seven,
or at least eight, or at least nine, or at least ten, or at least
eleven, or at least twelve, or at least thirteen, or at least
fourteen, or at least fifteen, or up to 31 of the ETSGs are
selected from the group consisting of RNASE1, ADAM15, ADAMDEC1,
ALCAM, ALDH1A1, ANKRD1, C19orf59, CA12, CAMP, CCL1, CCL19, CCL22,
CCL24, CCL7, CD14, CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK,
CXCL10, CYP1B1, CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3,
FBP1, FCER1G, FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF,
HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1,
IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO,
MGST1, MMP7, MT1F, MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1,
NRIP3, OLIG2, PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR,
PSTPIP2, PTGES, PTGR1, RAB13, RARRES1, REIN, RHBDD2, RNASE1,
S100A12, S100A4, S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10,
SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4, UPP1, and VCAN.
[0162] In certain embodiments, the level of expression of 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, 39,
40, 41, 42, 43, 44, 45, 46, 47, 48, 49 50, 51, 52, 53, 54, 55, 56,
57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73,
74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
91, 92, 93, 94, 95, 96, 97, 98, or 99 of the ETSGs in Table 1 is
determined.
[0163] In certain embodiments, the level of expression of 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, or 31 of the following ETSGs is
determined: C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G,
FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, REIN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0164] In one embodiment, the method further comprises determining
the level of expression of the same ETSGs in a control sample from
an individual who does not have sepsis. Where the expression levels
of the ETSGs from the patient sample and the control sample are
different, the patient is identified as having severe sepsis or
being at high risk for severe sepsis.
[0165] In one embodiment, the patient has not yet been definitively
diagnosed as having severe sepsis. In another embodiment, the
patient has already been diagnosed with severe sepsis.
[0166] In one embodiment, the biological sample is selected from a
group consisting of blood, tissue, amniotic fluid, saliva, urine,
amniotic fluid, bronchoalveolar lavage fluid, and skin cells.
[0167] In one embodiment, the identification of a patient with
severe sepsis is used to guide optimal therapy for the patient.
[0168] In one embodiment, the level of ETSG expression is
determined by assessing the RNA or cDNA level in the biological
sample. In one embodiment, the level of ETSG expression is
determined using one or more methods selected from the polymerase
chain reaction (PCR), reverse transcriptase-(RT) PCR, Q-beta
replicase amplification, ligase chain reaction, nucleic acid
sequence amplification, signal amplification (Ampliprobe), light
cycling and other variations of PCR or non-PCR based amplification
methods, differential display, Northern analysis, hybridization,
microarrays, DNA sequencing, RNA-Seq, nucleic acid sequencing,
MassArray analysis, and MALDI-TOF mass spectrometry.
[0169] In one aspect, the invention provides a method of
identifying an individual who is at risk of organ failure,
comprising obtaining a biological sample from the individual and
determining the level of expression of at least two, or at least
three, or at least four, or at least five, or at least six, or at
least seven, or at least eight, or at least nine, or at least ten,
or at least eleven, or at least twelve, or at least thirteen, or at
least fourteen, or at least fifteen different ETSGs in the
biological sample whereby the risk of organ failure is indicated by
the level of expression of the ETSGs. In one embodiment the level
of expression of more than 15 different ETGSs is determined. In one
embodiment the level of expression of more than 20 different ETGSs
is determined. In one embodiment the level of expression of more
than 25 different ETGSs is determined. In one embodiment the level
of expression of more than 30 different ETGSs is determined. In one
embodiment the level of expression of about 31 different ETGSs is
determined.
[0170] In one embodiment, the method further comprises determining
the level of expression of the same ETSGs in a control sample from
an individual who does not have sepsis. Where the expression levels
of the ETSGs from the patient sample and the control sample are
different, the patient is identified as having a risk of organ
failure.
[0171] In one embodiment, at least two, or at least three, or at
least four, or at least five, or at least six, or at least seven,
or at least eight, or at least nine, or at least ten, or at least
eleven, or at least twelve, or at least thirteen, or at least
fourteen, or at least fifteen, or at least 31 of the ETSGs are
selected from the group consisting of RNASE1, ADAM15, ADAMDEC1,
ALCAM, ALDH1A1, ANKRD1, C19orf59, CA12, CAMP, CCL1, CCL19, CCL22,
CCL24, CCL7, CD14, CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK,
CXCL10, CYP1B1, CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3,
FBP1, FCER1G, FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF,
HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1,
IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO,
MGST1, MMP7, MT1F, MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1,
NRIP3, OLIG2, PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR,
PSTPIP2, PTGES, PTGR1, RAB13, RARRES1, RETN, RHBDD2, RNASE1,
S100A12, S100A4, S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10,
SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4, UPP1, and VCAN.
[0172] In certain embodiments, the level of expression of 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, 39,
40, 41, 42, 43, 44, 45, 46, 47, 48, 49 50, 51, 52, 53, 54, 55, 56,
57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73,
74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
91, 92, 93, 94, 95, 96, 97, 98, or 99 of the ETSGs in Table 1 is
determined.
[0173] In certain embodiments, the level of expression of 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, or 31 of the following ETSGs is
determined: C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G,
FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0174] In one aspect, the invention provides a method for treating
severe sepsis, comprising identifying a patient who has severe
sepsis or is at high risk of developing severe sepsis and treating
said patient with at least one potent antibiotic that is indicated
for the treatment of severe sepsis. In one embodiment, patient
identification comprises obtaining a biological sample from the
patient and determining the level of expression of at least two, or
at least three, or at least four, or at least five, or at least
six, or at least seven, or at least eight, or at least nine, or at
least ten, or at least eleven, or at least twelve, or at least
thirteen, or at least fourteen, or at least fifteen different ETSGs
in the biological sample, whereby the presence or high risk of
severe sepsis is indicated by the level of expression of said at
least two ETSGs. In one embodiment the level of expression of more
than 15 different ETGSs is determined. In one embodiment the level
of expression of more than 20 different ETGSs is determined. In one
embodiment the level of expression of more than 25 different ETGSs
is determined. In one embodiment the level of expression of more
than 30 different ETGSs is determined. In one embodiment the level
of expression of about 31 different ETGSs is determined.
[0175] In one embodiment, at least two, or at least three, or at
least four, or at least five, or at least six, or at least seven,
or at least eight, or at least nine, or at least ten, or at least
eleven, or at least twelve, or at least thirteen, or at least
fourteen, or at least fifteen, or at least 31 of the ETSGs are
selected from the group consisting of RNASE1, ADAM15, ADAMDEC1,
ALCAM, ALDH1A1, ANKRD1, C19orf59, CA12, CAMP, CCL1, CCL19, CCL22,
CCL24, CCL7, CD14, CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK,
CXCL10, CYP1B1, CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3,
FBP1, FCER1G, FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF,
HIST1H1C, HIST2H2AA3, HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1,
IL18BP, IL3RA, ITGB8, KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO,
MGST1, MMP7, MT1F, MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1,
NRIP3, OLIG2, PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR,
PSTPIP2, PTGES, PTGR1, RAB13, RARRES1, RETN, RHBDD2, RNASE1,
S100A12, S100A4, S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10,
SLC7A11, TGM2, TLR7, TMEM158, TREM1, TSPAN4, UPP1, and VCAN.
[0176] In certain embodiments, the level of expression of 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, 39,
40, 41, 42, 43, 44, 45, 46, 47, 48, 49 50, 51, 52, 53, 54, 55, 56,
57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73,
74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
91, 92, 93, 94, 95, 96, 97, 98, or 99 of the ETSGs in Table 1 is
determined.
[0177] In certain embodiments, the level of expression of 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, or 31 of the following ETSGs is
determined: C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G,
FPR1, FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0178] In one embodiment, the method further comprises determining
the level of expression of the same ETSGs in a control sample from
an individual who does not have sepsis. Where the expression levels
of the ETSGs from the patient sample and the control sample are
different, the patient is identified as having severe sepsis and a
therapeutically effective dose of at least one potent antibiotic
that is indicated for the treatment of severe sepsis is
administered to the patient.
[0179] In one aspect, the invention provides a test kit for the
identification of severe sepsis, comprising at least two, or at
least three, or at least four, or at least five, or at least six,
or at least seven, or at least eight, or at least nine, or at least
ten, or at least eleven, or at least twelve, or at least thirteen,
or at least fourteen, or at least fifteen different nucleic acids,
each of which comprises a nucleotide sequence that corresponds to
or is complementary to the nucleotide sequence of a different ETSG.
In one embodiment the kit comprises more than 15 different nucleic
acids. In one embodiment the kit comprises more than 20 different
nucleic acids. In one embodiment the kit comprises more than 25
different nucleic acids. In one embodiment the kit comprises more
than 30 different nucleic acids. In one embodiment the kit
comprises about 31 different nucleic acids.
[0180] In one embodiment, the kit comprises at least two, or at
least three, or at least four, or at least five, or at least six,
or at least seven, or at least eight, or at least nine, or at least
ten, or at least eleven, or at least twelve, or at least thirteen,
or at least fourteen, or at least fifteen, or at least 31 different
nucleic acids, each of which comprises a nucleotide sequence that
corresponds to or is complementary to the nucleotide sequence of a
different ETSG, wherein the ETSGs are selected from the group
consisting of RNASE1, ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1,
C19orf59, CA12, CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14,
CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1,
CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G,
FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3,
HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8,
KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F,
MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2,
PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES,
PTGR1, RAB13, RARRES1, RETN, RHBDD2, RNASE1, S100A12, S100A4,
S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7,
TMEM158, TREM1, TSPAN4, UPP1, and VCAN.
[0181] In certain embodiments, the kit comprises 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, 39, 40, 41,
42, 43, 44, 45, 46, 47, 48, 49 50, 51, 52, 53, 54, 55, 56, 57, 58,
59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75,
76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92,
93, 94, 95, 96, 97, 98, or 99 different nucleic acids, each of
which comprises a nucleotide sequence that corresponds to or is
complementary to the nucleotide sequence of a different ETSG in
Table 1.
[0182] In certain embodiments, the kit comprises 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, or 31 different nucleic acids, each of
which comprises a nucleotide sequence that corresponds to or is
complementary to the nucleotide sequence of one of the following
ETSGs: C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0183] In one aspect, the invention provides a test kit for
identifying an individual who is at high risk of developing severe
sepsis, comprising at least two, or at least three, or at least
four, or at least five, or at least six, or at least seven, or at
least eight, or at least nine, or at least ten, or at least eleven,
or at least twelve, or at least thirteen, or at least fourteen, or
at least fifteen different nucleic acids, each of which comprises a
nucleotide sequence that corresponds to or is complementary to the
nucleotide sequence of a different ETSG. In one embodiment the kit
comprises more than 15 different nucleic acids. In one embodiment
the kit comprises more than 20 different nucleic acids. In one
embodiment the kit comprises more than 25 different nucleic acids.
In one embodiment the kit comprises more than 30 different nucleic
acids. In one embodiment the kit comprises about 31 different
nucleic acids.
[0184] In one embodiment, the kit comprises at least two, or at
least three, or at least four, or at least five, or at least six,
or at least seven, or at least eight, or at least nine, or at least
ten, or at least eleven, or at least twelve, or at least thirteen,
or at least fourteen, or at least fifteen, or at least 31 different
nucleic acids, each of which comprises a nucleotide sequence that
corresponds to or is complementary to the nucleotide sequence of a
different ETSG, wherein the ETSGs are selected from the group
consisting of RNASE1, ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1,
C19orf59, CA12, CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14,
CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1,
CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G,
FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3,
HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8,
KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F,
MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2,
PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES,
PTGR1, RAB13, RARRES1, RETN, RHBDD2, RNASE1, S100A12, S100A4,
S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7,
TMEM158, TREM1, TSPAN4, UPP1, and VCAN.
[0185] In certain embodiments, the kit comprises 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, 39, 40, 41,
42, 43, 44, 45, 46, 47, 48, 49 50, 51, 52, 53, 54, 55, 56, 57, 58,
59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75,
76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92,
93, 94, 95, 96, 97, 98, or 99 different nucleic acids, each of
which comprises a nucleotide sequence that corresponds to or is
complementary to the nucleotide sequence of a different ETSG in
Table 1.
[0186] In certain embodiments, the kit comprises 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, or 31 different nucleic acids, each of
which comprises a nucleotide sequence that corresponds to or is
complementary to the nucleotide sequence of one of the following
ETSGs: C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0187] In one aspect, the invention provides a test kit for
identifying an individual who is at risk of organ failure,
comprising at least two, or at least three, or at least four, or at
least five, or at least six, or at least seven, or at least eight,
or at least nine, or at least ten, or at least eleven, or at least
twelve, or at least thirteen, or at least fourteen, or at least
fifteen different nucleic acids, each of which comprises a
nucleotide sequence that corresponds to or is complementary to the
nucleotide sequence of a different ETSG. In one embodiment the kit
comprises more than 15 different nucleic acids. In one embodiment
the kit comprises more than 20 different nucleic acids. In one
embodiment the kit comprises more than 25 different nucleic acids.
In one embodiment the kit comprises more than 30 different nucleic
acids. In one embodiment the kit comprises about 31 different
nucleic acids.
[0188] In one embodiment, the kit comprises at least two, or at
least three, or at least four, or at least five, or at least six,
or at least seven, or at least eight, or at least nine, or at least
ten, or at least eleven, or at least twelve, or at least thirteen,
or at least fourteen, or at least fifteen, or at least 31 different
nucleic acids, each of which comprises a nucleotide sequence that
corresponds to or is complementary to the nucleotide sequence of a
different ETSG, wherein the ETSGs are selected from the group
consisting of RNASE1, ADAM15, ADAMDEC1, ALCAM, ALDH1A1, ANKRD1,
C19orf59, CA12, CAMP, CCL1, CCL19, CCL22, CCL24, CCL7, CD14,
CD300LF, CD93, CDK5RAP2, CPVL, CST3, CST6, CTSK, CXCL10, CYP1B1,
CYP27B1, DDIT4, DHRS9, DPYSL3, EGR2, EMR1, EMR3, FBP1, FCER1G,
FCER2, FPR1, FPR2, GK, GPNMB, GPR137B, HBEGF, HIST1H1C, HIST2H2AA3,
HIST2H2AC, HK2, HK3, HPSE, HSD11B1, HTRA1, IL18BP, IL3RA, ITGB8,
KIAA1199, LILRA3, LILRA5, LIPA, LY86, MARCO, MGST1, MMP7, MT1F,
MT1G, MT1H, MT1M, MT1X, MXD1, MYADM, NEFH, NQO1, NRIP3, OLIG2,
PANX2, PAPLN, PDLIM7, PLAUR, PLD3, PPBP, PROCR, PSTPIP2, PTGES,
PTGR1, RAB13, RARRES1, RETN, RHBDD2, RNASE1, S100A12, S100A4,
S100A8, S100A9, SERPINA1, SERPINB7, SLC16A10, SLC7A11, TGM2, TLR7,
TMEM158, TREM1, TSPAN4, UPP1, and VCAN.23.
[0189] In certain embodiments, the kit comprises 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, 39, 40, 41,
42, 43, 44, 45, 46, 47, 48, 49 50, 51, 52, 53, 54, 55, 56, 57, 58,
59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75,
76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92,
93, 94, 95, 96, 97, 98, or 99 different nucleic acids, each of
which comprises a nucleotide sequence that corresponds to or is
complementary to the nucleotide sequence of a different ETSG in
Table 1.
[0190] In certain embodiments, the kit comprises 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, or 31 different nucleic acids, each of
which comprises a nucleotide sequence that corresponds to or is
complementary to the nucleotide sequence of one of the following
ETSGs: C19orf59, CCL22, CD14, CD300LF, CYP1B1, DHRS9, FCER1G, FPR1,
FPR2, GK, HISTH2H2AA3, HK2, HK3, HPSE, LILRA5, MGST1, PDLIM7,
PLAUR, PSTPIP2, RAB13, RETN, RHBDD2, S100A4, S100A9, S100A12,
SERPINA1, UPP1, CPVL, CST3, LY86 and PROCR.
[0191] In one embodiment, the test kits of the invention further
comprise instructions for use, a sample collection device, one or
more reagents for sample preparation, and a positive control
sample.
[0192] In one embodiment, the test kits of the invention further
comprise instructions for use, a sample collection device, one or
more reagents for sample preparation, and a negative control
sample.
[0193] In one embodiment, the test kits of the invention further
comprise instructions for use, a sample collection device, one or
more reagents for sample preparation, and a negative control sample
and a positive control sample.
[0194] In one aspect, the invention provides a method of treating a
patient with severe sepsis, comprising administering to the patient
a therapeutically effective amount of an agent that counteracts
endotoxin tolerance by changing the expression of at least two, or
at least three, or at least four, or at least five, or at least
six, or at least seven, or at least eight, or at least nine, or at
least ten, or at least eleven, or at least twelve, or at least
thirteen, or at least fourteen, or at least fifteen, or at least 31
different ETSGs in a cell from the individual.
[0195] In one embodiment, the agent is selected from the group
consisting of Interferon gamma; CpG-ODN with or without IL-10;
anti-CD40; inhibitors of STAT3, STAT6, p50 NF.kappa.B, and
IKK.beta.; imidazoquinolones; and zoledronic acid. In one
embodiment, the agent is an immune cell.
[0196] In one aspect, the invention provides a method of preventing
or delaying severe sepsis in a patient, comprising administering to
the patient an effective amount of an agent that counteracts
endotoxin tolerance by changing the expression of at least two, or
at least three, or at least four, or at least five, or at least
six, or at least seven, or at least eight, or at least nine, or at
least ten, or at least eleven, or at least twelve, or at least
thirteen, or at least fourteen, or at least fifteen, or up to 99
different ETSGs in a cell from the patient.
[0197] In one embodiment, the agent is selected from the group
consisting of Interferon gamma; CpG-ODN with or without IL-10;
anti-CD40; inhibitors of STAT3, STAT6, p50 NF.kappa.B, and
IKK.beta.; imidazoquinolones; and zoledronic acid. In one
embodiment, the agent is an immune cell.
[0198] In one aspect, the invention provides a method of treating
severe sepsis in a patient, comprising administering to the patient
a therapeutically effective amount of an agent that counteracts
endotoxin tolerance by changing the expression of at least two, or
at least three, or at least four, or at least five, or at least
six, or at least seven, or at least eight, or at least nine, or at
least ten, or at least eleven, or at least twelve, or at least
thirteen, or at least fourteen, or at least fifteen, or at least 31
different ETSGs in a cell from the patient, and further comprises
monitoring the expression of at least two, or at least three, or at
least four, or at least five, or at least six, or at least seven,
or at least eight, or at least nine, or at least ten, or at least
eleven, or at least twelve, or at least thirteen, or at least
fourteen, or at least fifteen, or at least 31 different ETSGs in
samples taken from the patient during therapy.
[0199] In one embodiment, the agent is selected from the group
consisting of Interferon gamma; CpG-ODN with or without IL-10;
anti-CD40; inhibitors of STAT3, STAT6, p50 NF.kappa.B, and
IKK.beta.; imidazoquinolones; and zoledronic acid. In one
embodiment, the agent is an immune cell.
[0200] In one aspect, the invention provides a method of preventing
or delaying severe sepsis in a patient, comprising administering to
the patient an effective amount of an agent that counteracts
endotoxin tolerance by changing the expression of at least two, or
at least three, or at least four, or at least five, or at least
six, or at least seven, or at least eight, or at least nine, or at
least ten, or at least eleven, or at least twelve, or at least
thirteen, or at least fourteen, or at least fifteen, or at least 31
different ETSGs in a cell from the patient, and further comprises
monitoring the expression of at least two, or at least three, or at
least four, or at least five, or at least six, or at least seven,
or at least eight, or at least nine, or at least ten, or at least
eleven, or at least twelve, or at least thirteen, or at least
fourteen, or at least fifteen, or at least 31 different ETSGs in
samples taken from the patient during preventative treatment.
[0201] In one embodiment, the agent is selected from the group
consisting of Interferon gamma; CpG-ODN with or without IL-10;
anti-CD40; inhibitors of STAT3, STAT6, p50 NF.kappa.B, and
IKK.beta.; imidazoquinolones; and zoledronic acid. In one
embodiment, the agent is an immune cell.
[0202] In one aspect, the invention provides a method of preventing
or delaying organ failure in a patient, comprising administering to
the patient an effective amount of an agent that counteracts
endotoxin tolerance by changing the expression of at least two, or
at least three, or at least four, or at least five, or at least
six, or at least seven, or at least eight, or at least nine, or at
least ten, or at least eleven, or at least twelve, or at least
thirteen, or at least fourteen, or at least fifteen, or at least 31
different ETSGs in a cell from the patient, and further comprises
monitoring the expression of at least two, or at least three, or at
least four, or at least five, or at least six, or at least seven,
or at least eight, or at least nine, or at least ten, or at least
eleven, or at least twelve, or at least thirteen, or at least
fourteen, or at least fifteen, or at least 31 different ETSGs in
samples taken from the patient during preventative treatment.
[0203] In one embodiment, the agent is selected from the group
consisting of Interferon gamma; CpG-ODN with or without IL-10;
anti-CD40; inhibitors of STAT3, STAT6, p50 NF.kappa.B, and
IKK.beta.; imidazoquinolones; and zoledronic acid. In one
embodiment, the agent is an immune cell.
[0204] In one aspect, the invention provides a method of treating
severe sepsis, comprising administering to a patient a
therapeutically effective amount of an agent selected from the
group consisting of Interferon gamma; CpG-ODN with or without
IL-10; anti-CD40; inhibitors of STAT3, STAT6, p50 NF.kappa.B, and
IKK.beta.; imidazoquinolones; and zoledronic acid. In one
embodiment, the method further comprises monitoring the expression
of at least two, or at least three, or at least four, or at least
five, or at least six, or at least seven, or at least eight, or at
least nine, or at least ten, or at least eleven, or at least
twelve, or at least thirteen, or at least fourteen, or at least
fifteen, or at least 31 different ETSGs in samples taken from the
patient during therapy.
[0205] In one aspect, the invention provides a method of preventing
or delaying severe sepsis, comprising administering to a patient an
effective amount of an agent selected from the group consisting of
Interferon gamma; CpG-ODN with or without IL-10; anti-CD40;
inhibitors of STAT3, STAT6, p50 NF.kappa.B, and IKK.beta.;
imidazoquinolones; and zoledronic acid. In one embodiment, the
method further comprises monitoring the expression of at least two,
or at least three, or at least four, or at least five, or at least
six, or at least seven, or at least eight, or at least nine, or at
least ten, or at least eleven, or at least twelve, or at least
thirteen, or at least fourteen, or at least fifteen, or at least 31
different ETSGs in samples taken from the patient during
preventative treatment.
[0206] In one aspect, the invention provides a method of preventing
or delaying organ failure, comprising administering to a patient an
effective amount of an agent selected from the group consisting of
Interferon gamma; CpG-ODN with or without IL-10; anti-CD40;
inhibitors of STAT3, STATE, p50 NF.kappa.B, and IKK.beta.;
imidazoquinolones; and zoledronic acid. In one embodiment, the
method further comprises monitoring the expression of at least two,
or at least three, or at least four, or at least five, or at least
six, or at least seven, or at least eight, or at least nine, or at
least ten, or at least eleven, or at least twelve, or at least
thirteen, or at least fourteen, or at least fifteen, or at least 31
different ETSGs in samples taken from the patient during
preventative treatment.
[0207] In one aspect, the invention provides a method of
identifying an agent that is capable of treating sepsis, comprising
contacting a cell with the agent and determining the expression of
at least two, or at least three, or at least four, or at least
five, or at least six, or at least seven, or at least eight, or at
least nine, or at least ten, or at least eleven, or at least
twelve, or at least thirteen, or at least fourteen, or at least
fifteen different ETSGs in the cell.
[0208] In one embodiment, the cell is an endotoxin tolerant cell.
In one embodiment, the method further comprises contacting the cell
with an endotoxin following contact of the cell with agent. In one
embodiment, the endotoxin is bacterial lipopolysaccharide or
lipoteichoic acid. In one embodiment, the bacterial
lipopolysaccharide or lipoteichoic acid is present in a
bacterium.
[0209] In one embodiment agents of the invention are obtained by
contacting a cell with a suitable dose of endotoxin, waiting 18
hours and then contacting the cell again with a similar dose of the
same or another endotoxin to create an endotoxin tolerant cell,
then incubating the endotoxin tolerant cell with an agent of the
invention and examining the restoration of cellular ability to
interact with a third dose of endotoxin (breaking tolerance).
[0210] In one embodiment, the method further comprises contacting a
second cell with Interferon gamma; CpG-ODN with or without IL-10;
anti-CD40; an inhibitor of STAT3, STAT6, p50 NF.kappa.B, or
IKK.beta.; an imidazoquinolone; or zoledronic acid, and determining
the expression of the same ETSGs in the second cell.
[0211] In one embodiment, the method further comprises assaying the
agent for the ability to alter macrophage phenotype from M2 to
M1.
[0212] Agents of the invention may be obtained by contacting a cell
with a suitable dose of endotoxin, waiting 18 hours and then
contacting the cell again with a similar dose of the same or
another endotoxin to create an endotoxin tolerant cell, then
incubating the endotoxin tolerant cell with an agent of the
invention and examining the restoration of cellular ability to
interact with a third dose of endotoxin (breaking tolerance). In
one embodiment, the endotoxin is bacterial lipopolysaccharide or
lipoteichoic acid.
[0213] In one aspect, the invention provides an agent capable of
treating sepsis, which agent is identified by a method of the
invention. In one embodiment, the agent is capable of altering
macrophage phenotypes from M2 to M1.
[0214] In one aspect, the invention provides a method for treating
sepsis by suppressing endotoxin tolerance. In one embodiment, an
agent that is capable of changing the expression of at least one,
or at least two, or at least three, or at least four, or at least
five, or at least six, or at least seven, or at least eight, or at
least nine, or at least ten, or at least eleven, or at least
twelve, or at least thirteen, or at least fourteen, or at least
fifteen, or at least 31 different ETSGs in a cell from a patient is
used.
[0215] To gain a better understanding of the invention described
herein, the following examples are set forth. It will be understood
that these examples are intended to describe illustrative
embodiments of the invention and are not intended to limit the
scope of the invention in any way.
EXAMPLES
Methods
[0216] Overview:
[0217] Endotoxin Tolerance and Inflammatory LPS gene signatures
were derived from published [Pena O M, et al. Journal of Immunology
2011; 186:7243-54] microarray analyses of human PBMC identifying
differentially expressed genes compared to control PBMCs. To enable
more direct comparisons between signatures, differentially
expressed inflammatory genes were further reduced from 178 to 93
genes by overlap with an experimental endotoxaemia microarray
dataset (GSE3284) [Calvano et al., Nature, 2005, 437:1032-1037]
from the PBMC of healthy individuals stimulated with low-dose LPS
in vivo at 2 and 6 hours. Analysis of the `Endotoxin Tolerance` and
`Inflammatory` signatures in patients and controls was performed
using the statistically rigorous gene set test ROAST [Wu D, et al.
Bioinformatics 2010; 26:2176-82]. The selection of datasets was
based on the following inclusion criteria: 1) Cross-sectional or
longitudinal cohort studies. 2) Whole blood or purified leukocyte
populations. 3) Pediatric or adult patients. 4) Healthy subjects
used as controls. 5) Only datasets published in a scientific
journal. Normalized datasets were downloaded from NCBI GEO using
the Bioconductor package GEOquery [Davis S, Meltzer P S.
Bioinformatics 2007; 23:1846-7]. All data processing was performed
in R using Bioconductor [Gentleman R C, et al. Genome Biology 2004;
5:R80]. For the RNA Seq study reported here, 73 patients (age
60.+-.17; 46 males, 27 females) were recruited with deferred
consent according to UBC human ethics approval at the time of first
examination in an emergency ward based on the opinion of physicians
that there was a potential for the patient's condition to develop
into sepsis. After the first blood draw, total RNA was prepared
from whole blood, converted to cDNA, sequenced on an Illumina
Genome Analyzer IIx, mapped to the human genome and converted into
expression Tables by standard methods. Normalization used the Limma
package function voom. All other clinical parameters based on
routine tests were obtained by examination of patient's charts.
[0218] Meta-Analysis Datasets.
[0219] Searches for sepsis datasets were performed in the public
repositories NCBI GEO and EBI Array Express. The selection of
datasets (Table 2) was based on the following inclusion criteria:
1) Cross-sectional or longitudinal cohort studies. 2) Whole blood
or purified leukocyte populations. 3) Paediatric or adult patients.
4) Healthy subjects used as controls. 5) Only datasets published as
part of a study in a scientific journal. A list of the datasets
accessed is given in Table 2.
TABLE-US-00002 TABLE 2 Description of re-analyzed public sepsis
datasets* Location; Samples Cell Type; Time GEO ID (Sepsis/ of
sample Pubmed Array N* (GSE #) Samples selected Controls)
collection #; Year Platform 1 28750 Used only samples from sepsis
10/20 Australia; 21682927; A subjects and healthy controls.
Leukocytes; 2011 Post-surgery subject group were ICU <24 H>
excluded from the analysis. 2 13015 Used only samples with sepsis
24/3 Thailand; 19903332; B due to organisms other than B. Whole
blood; 2009 pseudomallei, Controls were Within 24 h of healthy
without comorbidities. sepsis diagnosis 3 9692 Used all samples
provided by 30/15 USA; 18460642: A the study. Leukocytes; 2007 ICU
<24 H> 4 26378 Used all samples provided by 82/21 USA;
21738952; A the study. Leukocytes; 2011 ICU <24 H> 5 26440
Used all samples provided by 98/32 USA; 21738952; A the study.
Leukocytes; 2011 ICU <24 H> 6 4607 Used only samples from
69/15 USA; 17374846; A subjects undergoing septic Leukocytes; 2006
shock collected at day 1 and ICU <24 H> day 3 post-ICU
admission. SIRS & SIRS-resolved subject samples were excluded.
7 8121 Used all samples provided by 60/15 USA; 17932561; A the
study. Leukocytes; 2007 ICU <24 H> 8 11755 Used only samples
from septic 5/3 Netherlands; 23842590; A subjects after 24 hours
(day 1) Leukocytes; 2008 and 72 hours (day 3) of ICU ICU <24
H> admission. Samples taken at 8 hours post-admission were
excluded from the analysis. 9 13904 Used only Samples from sepsis
158/18 USA 19325468; A and septic shock subjects. SIRS Leukocytes;
2008 subjects were excluded from ICU <24 H> analysis. Table 2
footnotes: *Microarray data were downloaded from the repository
Gene Expression Omnibus (GEO). The associated papers (given by
Pubmed number), numbers of patients analyzed and details of the
specific studies are presented. The Study description is included
as a footnote. Array Platform was A. GPL570 [HG-U133_Plus_2]
Affymetrix Human Genome U133 Plus 2.0 Array; B. GPL6947 Illumina
HumanHT-12 V3.0 expression beadchip. STUDY DESIGN by study in
column 1 of Table 2: 1. GSE 28750. Cross-sectional. Multi-centre,
prospective clinical trial conducted across 4 tertiary critical
care settings in Australia. Sepsis patients were recruited if they
met the 1992 Consensus Statement criteria and had clinical evidence
of systemic infection based on microbiology diagnoses. Healthy
subjects were used as normal controls in the study. 2. GSE 13015.
Cross-sectional. Study of patients with sepsis with a positive
blood culture due to Burkoldheria pseudomallei, and sepsis due to
other organisms cf. non-infected controls 3. GSE 9692.
Cross-sectional. Children <10 yr of age admitted to the
pediatric intensive care unit (PICU), with pediatric-specific
criteria for septic shock. Normal control patients were recruited
from the participating institutions using the following exclusion
criteria: a recent febrile illness (within 2 wk), recent use of
anti-inflammatory medications (within 2 wks), or any history of
chronic or acute disease associated with inflammation. 4. GSE
26378. Cross-sectional. Expression data from children with septic
shock was generated using whole blood-derived RNA samples
representing the first 24 hours of admission to the PICU. Healthy
subjects (children) were used as normal controls in the study. 5.
GSE 26440. Cross-sectional. Expression data from children with
septic shock were generated using whole blood-derived RNA samples
representing the first 24 hours of admission to the PICU. Healthy
subjects (children) were used as normal controls in the study. 6.
GSE 4607. Longitudinal. Children <10 years of age admitted to
the pediatric intensive care unit and meeting the criteria for
either SIRS or septic shock were eligible for the study. Control
patients were recruited from the outpatient or inpatient
departments of the participating institutions using the following
exclusion criteria: a recent febrile illness (within 2 weeks),
recent use of anti-inflammatory medications (within 2 weeks), or
any history of chronic or acute disease associated with
inflammation. 7. GSE 8121. Longitudinal. Genome-level expression
profiles were generated from whole blood-derived RNA of children
with septic shock corresponding to day 1 and day 3 of septic shock,
respectively. Control patients were recruited from the
participating institutions using the following exclusion criteria:
a recent febrile illness (within two weeks), recent use of
anti-inflammatory medications (within two weeks), or any history of
chronic or acute disease associated with inflammation. 8. GSE
11755. Longitudinal. Prospective case-control study, six children
with meningococcal sepsis were included. Blood was drawn at four
time points (t = 0, t = 8, t = 24 and t = 72 h after admission to
the pediatric intensive care unit. Healthy subjects (children) were
used as normal controls in the study. 9. GSE 13904. Longitudinal.
Genome-level expression profiles of critically ill children
representing the systemic inflammatory response syndrome (SIRS),
sepsis, and septic shock spectrum at day 1 and day 3
post-admission. Healthy subjects (children) were used as normal
controls in the study.
[0220] Patient Selection and Study Design.
[0221] In the blinded, observational, controlled cohort study,
patients with suspected sepsis, based on the opinion of the
attending physician, were enrolled from St. Paul's Hospital,
Vancouver Canada, at the first clinical suspicion of sepsis. To
determine the appropriate sample size for this study a standard
power calculation was used for adequate sensitivity [Jones S R, S
Carley, and M Harrison. Emergency medicine Journal 2003; 20,
453-458, 2003]. To achieve a sensitivity of at least 0.9 at a 95%
confidence level, a required sample size of 35 sepsis patients and
70 patients total (assuming 50% of patient with a suspicion of
sepsis actually have sepsis) was estimated. 72 total patients were
recruited, which were proved subsequently to include 37 sepsis
patients. The sole inclusion criterion for this study was the
suspicion of sepsis upon observation of the attending physician.
The majority of patients (83%) were enrolled from the emergency
room. As shown in Table 3, these individuals were heterogeneous.
UBC ethical approval protocol enabled deferred consent allowing
early patient recruitment in cohorts that spanned from non-infected
to septic shock. As controls, consenting healthy individuals, with
no evidence of infection, who were scheduled for non-urgent surgery
were recruited. Blood was collected in EDTA tubes at the time of
initial blood culture, and immediately placed on ice. Plasma and
buffy coat were separated and two 1-ml aliquots transferred into
bar-coded cryovials at -20.degree. C. until they were transferred
to a secure, alarmed -80.degree. C. freezer. Study identification
numbers were assigned on these secured enrolment forms and used
during all subsequent analyses; thus researchers analyzing gene
expression in these patients were blinded as to patient identity or
clinical course, which was only revealed during final data
analysis. Clinical data was stored in an ORACLE-based database on a
firewalled, RSS encrypted server at St Paul's Hospital.
[0222] Clinical data was collected retrospectively by physician
researchers blinded to the RNA-Seq data. New organ dysfunction was
defined based on laboratory values collected in the electronic
medical record system. Acute organ failures assessed were the
presence of shock (treatment with a vasopressor), acute respiratory
distress syndrome (need for mechanical ventilation), coagulopathy
(platelet count <80/.mu.L), hepatic failure (total bilirubin
>34 .mu.mol/L) and acute kidney injury (a serum creatinine rise
.gtoreq.26.5 .mu.mol/L or .gtoreq.1.5 fold from baseline. Initial
vital signs were retrospectively extracted from the paper
records.
TABLE-US-00003 TABLE 3 Details of individual patients recruited for
controlled cohort study Diagnostic Criteria.sup.2 Triage blood No.
of pressure Triage Triage First ICU or organ Micro- systolic/
Initial Triage Heart Respiratory Partial Lab ID non-ICU.sup.1
failures* biology.sup..sctn. diastolic WBC Temp/.degree. C. Rate
Rate CO.sub.2 SEPSIS GROUP 612920 ICU 4 Positive 94/62 17 37.8 170
40 NA.sup.3 154114 ICU 3 Positive 73/45 22.4 36.7 73 32 38 297580
ICU 4 Positive 86/40 10.4 35.3 56 16 30 212463 ICU 3 Positive
165/101 19.1 37.5 98 34 71 708631 ICU 2 Positive 100/61 8 38.2 96
10 42 799587 ICU 5 Positive 84/45 7.2 37 127 22 25 795380 ICU 3
Positive 139/90 4.2 30.4 53 22 61 913994 ICU 4 Positive 81/62 10.4
39.3 139 40 26 889485 ICU 4 Positive 67/53 16.3 36.1 142 26 30
137731 ICU 3 Positive 130/78 19.8 36.4 100 16 52 862476 ICU 4
Positive 136/80 25.8 39.2 110 30 49 864637 ICU 4 Positive 83/54
11.3 37.2 126 26 51 980414 ICU 3 Positive 112/62 26.3 37.9 126 44
35 375523 ICU 4 Positive 134/58 37.7 38.5 133 34 NA 364132 Non-ICU
0 Positive 98/68 9.4 38.3 119 22 NA 450578 Non-ICU 0 Positive 86/44
18.4 37.7 86 18 NA 694402 Non-ICU 1 Positive 175/81 2.2 37.4 118 22
NA 732740 Non-ICU 2 Positive 155/83 3.2 37.1 107 22 NA 826967
Non-ICU 1 Positive 129/66 23.8 37.2 109 20 NA 300271 ICU 3 Negative
103/57 15.3 36.7 102 22 42 679797 ICU 3 Negative 96/57 40 36.9 127
24 NA 266144 ICU 4 Negative 217/121 2.1 36.5 135 20 28 602395 ICU 3
Negative 105/95 12.9 37.5 92 NA 37 476146 ICU 3 Negative 106 15.2
36.2 105 --.sup.4 44 853176 Non ICU 0 Negative 139/69 14.4 37.1 105
23 NA 220171 Non ICU 2 Negative 76/51 3.3 39 109 18 NA 581691 Non
ICU 1 Negative 102/57 19.5 36.7 105 24 NA 823914 Non ICU 0 Negative
90/52 12.3 37.2 138 28 NA 155286 Non ICU 0 Negative 141/79 14.8
36.4 114 20 NA 658301 Non ICU 1 Negative 114/76 16.6 36.7 119 16 NA
800267 Non ICU 1 Negative 143/97 6.3 36.5 130 24 NA 235545 Non ICU
0 Negative 103/78 21.8 36.4 105 18 NA 342306 Non ICU 1 Negative
120/73 12.1 36.7 136 16 NA 468026 Non ICU 0 Negative 171/110 6.4
37.3 101 22 NA 522087 Non ICU 0 Negative 124/62 7 36.7 120 38 NA
716574 Non ICU 1 Negative 117/89 5.8 36.4 106 40 NA 746024 Non ICU
1 Negative 91/55 19.1 37.4 90 28 NA NO SEPSIS GROUP 402569 ICU 3
Positive 123/74 10.4 37.1 74 16 31 941715 Non ICU 0 Positive 119/65
5.1 36.8 82 16 NA 583654 Non ICU 0 Positive 180/96 7.6 36.4 64 20
NA 237093 Non ICU 0 Positive 102/58 10.3 36.6 82 16 NA 355472 Non
ICU 1 Positive 147/70 13.4 38 66 20 NA 416442 Non ICU 2 Positive
133/62 7 39.5 89 20 NA 439362 Non ICU 1 Positive 146/84 5.6 36.8 89
16 NA 701198 Non ICU 1 Positive 147/68 5.6 36.4 107 18 NA 583577
ICU 2 Negative 203/111 11.2 36 85 32 73 749752 ICU 3 Negative 85/50
12.3 36.6 60 18 NA 673143 ICU 4 Negative 162/87 9.1 36.8 90 20 40
362763 ICU 3 Negative 126/60 7.3 37 90 --.sup.3 39 377121 ICU 1
Negative 128/88 4.8 37.2 115 20 36 288187 Non-ICU 0 Negative 95/57
9.7 36.9 98 20 NA 993234 Non-ICU 0 Negative 152/57 6.8 36.6 88 24
NA 890426 Non-ICU 1 Negative 135/75 8.1 37.6 105 16 NA 290697
Non-ICU 0 Negative 100/61 8.4 36.7 91 20 NA 104582 Non-ICU 0
Negative 140/88 17.1 36.6 74 20 NA 245286 Non-ICU 0 Negative 136/75
5.7 36.8 105 20 NA 417642 Non-ICU 0 Negative 120/60 6.9 36.7 77 24
NA 911536 Non-ICU 0 Negative 123/80 4.3 39.4 90 18 NA 346081
Non-ICU 0 Negative 167/70 2.1 36.9 72 20 NA 449469 Non-ICU 0
Negative 127/78 5.9 37.3 104 16 NA 568243 Non-ICU 1 Negative 159/98
6.7 36.9 93 18 NA 695232 Non-ICU 1 Negative 142/84 19.1 37.8 90 16
NA 770905 Non-ICU 0 Negative 123/60 13.2 35.4 73 16 NA 929438
Non-ICU 1 Negative 170/102 12.8 37.4 83 16 NA 602005 Non-ICU 0
None.sup.5 130/66 1.8 36.6 64 14 NA 145305 Non-ICU 0 Negative
142/75 8.4 36.8 67 18 NA 366713 Non-ICU 0 Negative 91/58 10.8 36.6
71 16 NA 332278 Non-ICU 1 Negative 99/59 8.5 36.6 86 16 NA 379752
Non-ICU 0 Negative 130/69 10.6 36.9 65 16 NA 669339 Non-ICU 0
Negative 123/80 5.9 37 77 16 NA 310017 Non-ICU 0 Negative 141/96
11.4 36.9 88 20 NA 504886 Non-ICU 0 Negative 99/55 NA 36.4 66 16 NA
Table 3 Footnotes: *within 48 hr of suspected sepsis.
.sup..sctn.most within 48 hr of suspected sepsis. .sup.1Indicates
whether the patient was transferred to the ICU after first clinical
examination. .sup.2Diagnostic Criteria for Sepsis as per [Bone R C,
R A Balk, F B Cerra, R P Dellinger, A M Fein, W A Knaus, R M
Schein, W J Sibbald, ASCC Committee. Definitions for sepsis and
organ failure and guidelines for the use of innovative therapies in
sepsis. The ACCP/SCCM Consensus Conference Committee. American
College of Chest Physicians/Soc Critical Care Medicine. 1992. Chest
2009; 136:e28; Hotchkiss, R S, I E Karl, The pathophysiology and
treatment of sepsis. N Engl J Med 2003; 348, 138-150]. Respiratory
Rate and Partial CO.sub.2 are no longer criteria but were added as
additional information. .sup.3NA: indicates not available.
.sup.4Patient was ventilated. .sup.5None means no culture was
requested.
[0223] RNA-Seq.
[0224] cDNA libraries were prepared from total RNA according to the
TruSeq Stranded Total RNA Sample Prep Kit with Ribo-Zero sample
preparation guide (Illumina). Unique adapter indexes (Illumina)
were attached during sample prep and samples were run pooled and
loaded into a single flow cell lane to reduce technical
variability. RNA-Seq was performed on a GAIIx instrument
(Illumina), using a single read run with 63 bp long sequence reads
(+adapter/index sequences). Raw basecall data was converted to
FASTQ sequence files using Off-Line Basecaller 1.9.4 (Ilumina) and
a custom Perl script. Reads were aligned to the hg19 human genome
with TopHat version 2.06 and Bowtie2 2.0.0-beta6. Reads were
initially mapped to Ensembl transcripts with the search for novel
junctions disabled. Genomic coordinates were then transformed into
counts of protein-coding Ensembl genes. To do this, a chimeric
gene-model was first defined by merging all protein-coding
transcripts for a given gene. Transcripts that had reads in less
than 50% of their exons in all samples were defined as not
expressed and were excluded from the chimeric transcriptome. Reads
that overlapped the chimeric genes were counted using the
htseq-count script in the intersection-nonempty mode (see EMBL
website). The script discards multi-mapped reads as well as reads
that overlap multiple distinct genes, to generate a file of
uniquely mapped gene counts.
[0225] Data Analysis.
[0226] All data processing was performed in R using Bioconductor.
For the meta-analysis, normalized datasets were downloaded from
NCBI GEO using the Bioconductor package GEOquery. An additional
quantile normalization step was included if the data required
further normalization. For the RNA-Seq analysis, data was
normalized using the Voom function in the Limma package which
converts read counts to weighted log base 2 counts per million. For
both the meta-analysis and RNA-Seq analyses, data was summarized
using the linear model in the Limma package.
[0227] Gene Signature Definition and Analysis.
[0228] Endotoxin Tolerance and Inflammatory gene signatures were
derived from previously published [Pena et al 2011] microarray
analyses of human PBMC identifying differentially expressed genes
compared to control PBMCs. To enable more direct comparisons
between signatures, differentially expressed inflammatory genes
were further reduced from 178 to 93 genes using an experimental
endotoxaemia microarray dataset (GSE3284) obtained from the PBMC of
healthy individuals stimulated in vivo with low-dose LPS for 2 and
6 hours. Importantly the two primary gene expression datasets
(GSE22248 & GSE3284) used to derive signatures were then
excluded from subsequent gene-set validation tests. Analysis of the
presence or absence of the Endotoxin Tolerance and Inflammatory
signatures in patients and controls was performed using the
well-established, statistically-rigorous gene set test ROAST. Gene
set tests essentially ask whether a given gene set/signature is
signature enriched in a dataset. The ROAST method additionally
allows for the consideration of a gene's direction of expression
when calculating the enrichment, which increases the accuracy of
the test in cases where the direction of the gene's expression is
known (Wu et al., Bioinformatics, 20101 26(17):2176-82). ROAST was
run with 99999 rotations and so the most significant p-value
resulting from this test is 0.00001. Additional endotoxin
tolerance-related signatures were also defined at multiple
significance cut-offs from the previously published dataset (FIG.
4) and from an alternate, independent endotoxin tolerance dataset
[Del Fresno C, et al. Journal of Immunology 2009; 182:6494-507]
from cystic fibrosis patients with essentially identical
results.
[0229] Random Forest Analysis of Diagnostic Predictions.
[0230] Each dataset was split into training (containing 75% of
sepsis patients and controls) and test (containing 25% of sepsis
patients and controls) sets using random sampling. Datasets
GSE13015 and GSE11755 were omitted from this analysis due to low
numbers of controls (N=3) in each dataset. For each of the
remaining 8 datasets, the model was defined on the training set and
then assessed on the test set using the randomForest package [Liaw
A, Wiener M. R News 2002; 2:18-22] with ntree set to 1000. The
procedure was repeated 100 times, and the average prediction
accuracies recorded for each data set.
Example 1
Definition and Characterization of the Signature
[0231] Confirmed Sepsis Patients Express an "Endotoxin Tolerance
Signature."
[0232] To characterize the development of the immunosuppressive
stage in sepsis and to conclusively determine its links with
endotoxin tolerance, a robust bioinformatics approach was taken. To
define an endotoxin tolerance gene signature, microarray analyses
of human peripheral blood mononuclear cells (PBMC) treated either
once with LPS to model inflammatory signalling, or twice to model
endotoxin tolerance was used. An "Endotoxin Tolerance Signature"
(Table A below), comprising 99 genes was identified based on genes
uniquely differentially expressed in endotoxin-tolerant PBMCs, but
not inflammatory PBMCs, as compared to controls. For comparison, we
defined an "Inflammatory Signature" from previous PBMC microarray
data (Pena et al., 2011) and an in vivo experimental endotoxemia
dataset (Calvano et al., 2005) (FIG. 1, Table 4). Having defined a
genetic signature for endotoxin tolerance, we performed a global
meta-analysis on 9 published, independent and blinded clinical
sepsis cohorts, encompassing 536 early sepsis patients (1 or 3 days
post-ICU admission) and 142 healthy controls (Table 2; FIGS. 2, 3,
4). In all of these reanalyzed datasets, patients had been
recruited at either 1 or 3 days post-ICU admission.
TABLE-US-00004 TABLE A Endotoxin Tolerance Signature Genes and
Their Relative Expression in Endotoxin Tolerant PBMCs vs. Controls
Gene Symbol Description Fold Change ADAM15 ADAM metallopeptidase
domain 15 -2.1 ADAMDEC1 ADAM-like, decysin 1 3.0 ALCAM Activated
leukocyte cell adhesion molecule -2.0 ALDH1A1 Aldehyde
dehydrogenase 1 family, member A1 -3.8 ANKRD1 Ankyrin repeat domain
1 (cardiac muscle) 4.1 C19orf59 Chromosome 19 open reading frame 59
12.6 CA12 Carbonic anhydrase XII 8.2 CAMP Cathelicidin
antimicrobial peptide -3.9 CCL1 Chemokine (C-C motif) ligand 1;
SCYA1 7.1 CCL19 Chemokine (C-C motif) ligand 19; MIP3.beta. 4.1
CCL22 Chemokine (C-C motif) ligand 22; MDC 7.0 CCL24 Chemokine (C-C
motif) ligand 24; Eotaxin-2 19.8 CCL7 Chemokine (C-C motif) ligand
7 21.0 CD14 CD14 molecule 2.5 CD300LF CD300 molecule-like family
member F 2.1 CD93 CD93 molecule 4.6 CDK5RAP2 CDK5 regulatory
subunit associated protein 2 2.2 CPVL Carboxypeptidase,
Vitellogenic-like -3.6 CST3 Cystatin C -4.2 CST6 Cystatin E/M -2.5
CTSK Cathepsin K -2.4 CXCL10 Chemokine (C-X-C motif) ligand 10 -9.9
CYP1B1 Cytochrome P450, family 1, subfamily B, polypeptide 1 2.1
CYP27B1 Cytochrome P450, family 27, subfamily B, polypeptide 1 3.0
DDIT4 DNA-damage-inducible transcript 4 2.2 DHRS9
Dehydrogenase/reductase (SDR family) member 9 -5.7 DPYSL3
Dihydropyrimidinase-like 3 2.6 EGR2 Early growth response 2 2.0
EMR1 EGF-like module containing, mucin-like, hormone receptor- 2.1
like 1 EMR3 EGF-like module containing, mucin-like, hormone
receptor- 2.4 like 3 FBP1 Fructose-1,6-bisphosphatase 1 3.2 FCER1G
Fc fragment of IgE, high affinity I, receptor for; gamma 2.0
polypeptide FCER2 Fc fragment of Ige, low affinity II, receptor for
(CD23) 2.9 FPR1 Formyl peptide receptor 1 5.7 FPR2 Formyl peptide
receptor 2 4.9 GK Glycerol kinase 2.3 GPNMB Glycoprotein
(transmembrane) NMB -8.1 GPR137B G protein-coupled receptor 137B
2.2 HBEGF Heparin-binding EGF-like growth factor 2.5 HIST1H1C
Histone cluster 1, H1C 2.3 HIST2H2AA3 Histone cluster 2, H2AA3 4.0
HIST2H2AC Histone cluster 2, H2AC 3.6 HK2 Hexokinase 2 2.4 HK3
Hexokinase 3 (white cell) 2.1 HPSE Heparanase 2.4 HSD11B1
Hydroxysteroid (11-beta) dehydrogenase 1 4.1 HTRA1 HTRA serine
peptidase 1 -3.3 IL18BP Interleukin 18 binding protein -3.5 IL3RA
Interleukin 3 receptor, alpha (low affinity) 4.2 ITGB8 Integrin,
beta 8 2.1 KIAA1199 KIAA1199 4.1 LILRA3 Leukocyte
immunoglobulin-like receptor, subfamily A 14.0 (without TM domain),
member 3 LILRA5 Leukocyte immunoglobulin-like receptor, subfamily A
(with 2.6 TM domain), member 5 LIPA Lipase A, lysosomal acid,
cholesterol esterase -4.5 LY86 Lymphocyte antigen 86 -2.6 MARCO
Macrophage receptor with collagenous structure 3.7 MGST1 Microsomal
glutathione S-transferase 1 2.7 MMP7 Matrix metallopeptidase 7
(matrilysin, uterine) 12.0 MT1F Metallothionein 1F 16.2 MT1G
Metallothionein 1G 61.1 MT1H Metallothionein 1H 51.1 MT1M
Metallothionein 1M 23.8 MT1X Metallothionein 1X 14.8 MXD1 MAX
dimerization protein 1 2.0 MYADM Myeloid-associated differentiation
marker 2.1 NEFH Neurofilament, heavy polypeptide 2.1 NQO1 NAD(P)H
dehydrogenase, Quinone 1 -2.3 NRIP3 Nuclear receptor interacting
protein 3 2.2 OLIG2 Oligodendrocyte lineage transcription factor 2
2.5 PANX2 Pannexin 2 2.7 PAPLN Papilin, proteoglycan-like sulfated
glycoprotein 2.0 PDLIM7 PDZ and LIM domain 7 (enigma) 3.1 PLAUR
Plasminogen activator, Urokinase receptor 2.7 PLD3 Phospholipase D
family, member 3 -3.1 PPBP Pro-platelet basic protein (chemokine
(C-X-C motif) ligand 6.8 7) PROCR Protein C receptor, endothelial
2.0 PSTPIP2 Proline-serine-threonine phosphatase interacting
protein 2 -2.1 PTGES Prostaglandin E synthase 3.3 PTGR1
Prostaglandin reductase 1 2.6 RAB13 RAB13, member RAS oncogene
family 2.3 RARRES1 Retinoic acid receptor responder (Tazarotene
induced) 1 -3.8 RETN Resistin 4.4 RHBDD2 Rhomboid domain containing
2 2.9 RNASE1 Ribonuclease, RNAse A family, 1 (pancreatic) -10.4
S100A12 S100 calcium binding protein A12 3.7 S100A4 S100 calcium
binding protein A4 -2.7 S100A8 S100 calcium binding protein A8 2.1
S100A9 S100 calcium binding protein A9 2.5 SERPINA1 Serpin
peptidase inhibitor, Clade A (.alpha.-1 anti-proteinase, 5.7
anti-trypsin), member 1 SERPINB7 Serpin peptidase inhibitor, Clade
B (ovalbumin), member 7 4.3 SLC16A10 Solute carrier family 16,
member 10 (aromatic amino acid 2.9 transporter) SLC7A11 Solute
carrier family 7 (anionic amino acid transporter light 2.3 chain,
xc- system), member 11 TGM2 Transglutaminase 2 2.1 TLR7 Toll-like
receptor 7 -2.2 TMEM158 Transmembrane protein 158 (gene/pseudogene)
2.1 TREM1 Triggering receptor expressed on myeloid cells 1 3.5
TSPAN4 Tetraspanin 4 -2.4 UPP1 Uridine phosphorylase 1 2.1 VCAN
Versican 5.3
TABLE-US-00005 TABLE 4 Inflammatory Signature Genes and Their
Relative Expression in Inflammatory PBMCs vs Controls Gene Symbol
Description Fold Change CCL20 Chemokine (C-C motif) ligand 20;
MIP3.alpha. 14.6 CCL3L1 Chemokine (C-C motif) ligand 3-like 1;
MIP1AP 9.2 G0S2 G0/G1 switch 2 7.2 CFB Complement factor B 6.1 AK4
Adenylate kinase 4 5.4 IFIT3 Interferon-induced protein with
tetratricopeptide repeats 3 5.1 HERC5 HECT and RLD domain
containing E3 ubiquitin protein 4.8 ligase 5 PDSS1 Prenyl
(decaprenyl) diphosphate synthase, Subunit 1 4.8 BATF Basic leucine
zipper transcription factor, ATF-like 4.7 DNAAF1 Dynein, axonemal,
assembly factor 1 4.7 XAF1 XIAP associated factor 1 4.4 PIM2 PIM-2
oncogene 4.2 IFI44 Interferon-induced protein 44 3.7 F3 Coagulation
factor III (thromboplastin, tissue factor) 3.6 FAM129A Family with
sequence similarity 129, member A 3.5 IFIT2 Interferon-induced
protein with tetratricopeptide repeats 2 3.4 KCNJ2 Potassium
inwardly-rectifying channel, subfamily J, member 3.4 2 MX2
Myxovirus (influenza virus) resistance 2 (mouse) 3.4 EIF2AK2
Eukaryotic translation initiation factor 2-alpha kinase 2 3.2
CCL3L3 Chemokine (C-C motif) ligand 3-like 3; LD78 3.1 IRF7
Interferon regulatory factor 7 3.1 CXCL2 Chemokine (C-X-C motif)
ligand 2; MIP2.alpha. 3.0 FFAR2 Free fatty acid receptor 2 3.0
RIPK2 Receptor-interacting serine-threonine kinase 2 3.0 ADORA2A
Adenosine A2a receptor 2.9 SAMD9L Sterile alpha motif domain
containing 9-like 2.9 GRAMD1A GRAM domain containing 1A 2.8 SOD2
Superoxide dismutase 2, mitochondrial 2.8 SOCS1 Suppressor of
cytokine signaling 1 2.7 CD80 CD80 molecule 2.6 TNF Tumor necrosis
factor 2.6 CASP5 Caspase 5, apoptosis-related cysteine peptidase
2.5 CD83 CD83 molecule 2.5 IFI35 Interferon-induced protein 35 2.5
PIM1 Pim-1 oncogene 2.5 SLAMF7 SLAM family member 7 2.5 TRIM25
Tripartite motif containing 25 2.5 C1orf122 Chromosome 1 open
reading frame 122 2.4 GBP4 Guanylate binding protein 4 2.4 PIM3
Pim-3 oncogene 2.4 GBP2 Guanylate binding protein 2,
interferon-inducible 2.3 RNF144B Ring finger protein 144B 2.3 TXN
Thioredoxin 2.3 YRDC Yrdc domain containing (E. Coli) 2.3 ALCAM
Activated leukocyte cell adhesion molecule 2.2 ANTXR2 Anthrax toxin
receptor 2 2.2 ISG20 Interferon stimulated exonuclease gene 20 kda
2.2 OASL 2'-5'-oligoadenylate synthetase-like 2.2 PARP9 Poly
(ADP-ribose) polymerase family, member 9 2.2 PTX3 Pentraxin 3, long
2.2 TNFAIP2 Tumor necrosis factor, alpha-induced protein 2 2.2
TNFSF10 Tumor necrosis factor (ligand) superfamily, member 10 2.2
B4GALT5 UDP-Gal:betaglcnac beta 1,4-galactosyltransferase, 2.1
polypeptide 5 BCL3 B-cell CLL/lymphoma 3 2.1 EDN1 Endothelin 1 2.1
GADD45B Growth arrest and DNA-damage-inducible, beta 2.1 IRAK2
Interleukin-1 receptor-associated kinase 2 2.1 JUNB Jun B
proto-oncogene 2.1 MTF1 Metal-regulatory transcription factor 1 2.1
NFKB2 Nuclear factor of kappa light polypeptide gene enhancer in
2.1 B-cells 2 SAMD9 Sterile alpha motif domain containing 9 2.1
UPB1 Ureidopropionase, beta 2.1 GCH1 GTP cyclohydrolase 1 2.0 HSH2D
Hematopoietic SH2 domain containing 2.0 NFKBIZ Nuclear factor of
kappa light polypeptide gene enhancer in 2.0 B-cells inhibitor,
zeta TNIP1 TNFAIP3 interacting protein 1 2.0 ZC3H12A Zinc finger
CCCH-type containing 12A 2.0 CORO1B Coronin, actin binding protein,
1B -2.0 H2AFY H2A histone family, member Y -2.0 IFFO1 Intermediate
filament family orphan 1 -2.0 SPIRE1 Spire homolog 1 (Drosophila)
-2.0 TSC22D3 TSC22 domain family, member 3 -2.0 CSF1R Colony
stimulating factor 1 receptor -2.1 PLIN2 Perilipin 2 -2.1 ZMIZ1
Zinc finger, MIZ-type containing 1 -2.1 CTSB Cathepsin B -2.2 LPAR6
Lysophosphatidic acid receptor 6 -2.2 MS4A7 Membrane-spanning
4-domains, subfamily A, member 7 -2.2 SLAMF8 SLAM family member 8
-2.2 IDH1 Isocitrate dehydrogenase 1 (NADP+), soluble -2.3 LTA4H
Leukotriene A4 hydrolase -2.4 CAMK1 Calcium/calmodulin-dependent
protein kinase I -2.5 CORO1C Coronin, actin binding protein, 1C
-2.5 CLEC10A C-type lectin domain family 10, member A -2.9 CD86
CD86 molecule -3.1 PDK4 Pyruvate dehydrogenase kinase, isozyme 4
-3.1 ACP5 Acid phosphatase 5, tartrate resistant -3.2 HAVCR2
Hepatitis A virus cellular receptor 2 -3.2 ASGR1 Asialoglycoprotein
receptor 1 -3.4 NCEH1 Neutral cholesterol ester hydrolase 1 -3.6
RCBTB2 Regulator chromosome condensation (RCC1) & BTB (POZ)
-3.9 domain 2 ADAP2 ArfGAP with dual PH domains 2 -4.6 HMOX1 Heme
oxygenase (decycling) 1 -5.5
[0233] To assess the relative expression of the Endotoxin Tolerance
and Inflammatory signatures in sepsis patients versus healthy
controls, a gene-set test approach was used, which examines whether
a given signature (gene-set) is significantly enriched between
groups in a dataset. Sepsis patients in all 9 cohorts were found to
show an immunological expression profile strongly associated with
the Endotoxin Tolerance Signature when compared to controls (FIG.
2). These results were independent of the fold-change/statistical
cut-offs used to define the Endotoxin Tolerance Signature (FIG. 4).
While the Inflammatory Signature was significantly associated with
most of the datasets, this association was consistently weaker than
for the Endotoxin Tolerance Signature (FIG. 3). In contrast to
previous reports associating endotoxin tolerance only with late
stage sepsis (Cavaillon J, C Adrie, C Fitting, M Adib-Conquy. J
Endotoxin Res 2005; 11:311-320; Otto, G P, M Sossdorf, R A Claus, J
Rodel, K Menge, K Reinhart, M Bauer, N C Riedemann. Critical Care
2011; 15:R183; Schefold J C, D Hasper, H D Volk, PReinke. Medical
hypotheses 2008; 71:203-208), the association with the "Endotoxin
Tolerance Signature" was present in sepsis patients as early as Day
1 post-ICU admission, and was maintained on Day 3, consistent with
the early development of a "stable" endotoxin tolerance profile in
sepsis patients (FIG. 2). Thus the immune dysfunction in sepsis
appears to be characterized by endotoxin tolerance.
[0234] The "Endotoxin Tolerance Signature" Develops Very Early in
Patients with Sepsis and is Detectable Before Diagnosis.
[0235] One limitation of all 9 previously published datasets used
in the prior meta-analysis was the analysis of the sepsis patient
transcriptome following "confirmed diagnosis" of sepsis and not at
first presentation. Accordingly a unique cohort of patients at the
earliest possible stage of clinical disease was generated to better
understand the timing of endotoxin tolerance development and the
diagnostic utility of the signature identified herein. Patients
were recruited immediately after clinical suspicion of sepsis,
based on the attending physician's analysis of patient history,
physical examination and stat request for microbial culture
testing. RNA-Seq was performed on RNA isolated from the initial
blood sample taken for cultures to aid in sepsis
diagnosis/microbial identification. An appropriate power
calculation was performed and based on this, 72 very early
suspected sepsis patients (Table 3) were recruited, as well as an
additional 11 control patients who were recruited prior to elective
surgery with no underlying morbidities. Investigating the potential
for an early means of differential diagnosis in this clinically
challenging cohort of patients who initially presented with
variable serious derangements in physiology (potentially caused by
sepsis) has major clinical implications.
[0236] Based on the earliest recorded clinical assessments
following sample isolation (Table 3), patients in the cohort of 72
suspected sepsis patients were retrospectively classified as
"Sepsis" (n=37), or "No Sepsis" (n=35), consistent with current
sepsis diagnostic criteria (R. C. Bone, et al., 2009). Strikingly,
even at the earliest stage of clinical sepsis, the Endotoxin
Tolerance Signature was significantly enriched only in patients who
were subsequently confirmed to have sepsis and not those with other
diagnoses ("No Sepsis"), as compared with healthy controls (FIG.
5A). When combined with the results from the prior meta-analysis,
sepsis appears to be strongly associated with endotoxin tolerance
throughout all initial stages of clinical disease (FIGS. 2 &
5A). Additionally, while the Inflammatory Signature did not reach
statistical significance in the "No Sepsis" group, the contrasting
relative enrichment of the Endotoxin Tolerance and Inflammatory
Signatures in the 2 groups may indicate a fundamental difference in
the balance of endotoxin tolerance and inflammation unique to
sepsis patients. Finally, the Endotoxin Tolerance Signature was
also enriched in the "Sepsis" group when directly compared to the
"No Sepsis" group (FIG. 5B), which supports the specificity of
endotoxin tolerance to sepsis and not just to "ill" patients.
[0237] One of the challenges in diagnosing sepsis is the
confirmation of infection due to the low sensitivity of bacterial
cultures (RC Bone, et al., 2009). Indeed the current sepsis
diagnostic criteria are based on "suspected infection," rather than
confirmed infection due to these sensitivity issues (RC Bone, et
al., 2009). This concept was highlighted by comparing signature
enrichment with microbial culture results in both the patient
groups. In agreement with previous results, the Endotoxin Tolerance
Signature was higher in the "Sepsis group" (FIG. 5C) and the
Inflammatory Signature in the "No Sepsis" group regardless of the
microbial culture result (FIG. 5D), further highlighting the
interesting inverse trend of the signatures among these two groups
of "ill" patients. As expected, given the sensitivity issues of
microbial cultures, while the Endotoxin Tolerance Signature showed
more significant enrichment in the culture positive group, there
was also strong enrichment in the culture negative group,
consistent with the presence of possibly incorrectly identified
"infection negative" patients in this group (FIG. 5C). As the
RNA-Seq analysis was performed on the same blood samples used for
diagnostic microbial cultures, the strong association between
sepsis and the Endotoxin Tolerance Signature, suggests the
Endotoxin Tolerance Signature may provide a more sensitive tool for
diagnostics than microbial culture.
[0238] Together these data show that endotoxin tolerance is present
throughout the initial clinical course of sepsis, detectable before
"diagnosis," and can be used to differentiate patients who develop
sepsis in a cohort of patients where there was a suspicion of
sepsis.
TABLE-US-00006 TABLE 5 Statistics regarding Organ Failure and Sites
of Infection in the Cohort of Patients Number of Patients A. Site
of Organ Failure Lung (Respiratory Failure) 22 Kidney (Acute Kidney
Injury) 41 Liver 9 Cardiovascular System 22 B. Site of Infections
Blood 9 Urinary Tract 10 Respiratory Tract 6 Gastrointestinal Tract
4 Skin and Soft Tissues 3 Bone 1
[0239] Next, the relevance of the endotoxin tolerance-driven
immunosuppressive state (as detected by the Endotoxin Tolerance
Signature) to the severity of sepsis as defined by the subsequent
development of organ dysfunction in the suspected sepsis patient
cohort was investigated. Subsequent organ dysfunction development
was assessed within 48 hours of study enrolment (cardiovascular,
coagulation, kidney, liver, and respiratory; Tables 4 & 5) with
patients retrospectively grouped into organ-dysfunction positive
and negative groups, independent of sepsis diagnosis. These groups
were then subjected to the same gene-set test analysis as above.
Interestingly, the Endotoxin Tolerance Signature was found to be
significantly associated with the development of individual or
multiple (3+) organ dysfunction (FIG. 6A; except coagulation
failure). Although ICU admission may depend on the inherent
subjectivity of hospital regulations, such as space or number of
beds available in each department, patients that are moved to the
ICU are generally in a deteriorating condition with an increased
risk of mortality. Therefore, the requirement for ICU admission was
also assessed as a second, less precise measure of disease severity
and showed that the Endotoxin Tolerance Signature was again
associated with increased disease severity (FIG. 6B). These results
indicate that endotoxin tolerance is associated with sepsis
severity and specifically the subsequent development of organ
failure.
[0240] Given the strong association between endotoxin tolerance and
sepsis across more than 600 patients from 10 independent datasets,
the utility of the Endotoxin Tolerance Signature as a tool in
sepsis diagnosis was investigated. While the full 99 gene,
Endotoxin Tolerance Signature was useful for characterizing the
immune dysfunction in sepsis, a smaller number of genes is of more
use in a diagnostic test. Thus, the 99-gene signature was further
analysed to identify useful subsets of this initial signature that
could subsequently tested for diagnostic utility. To do this, genes
that showed greater than 1.5 fold differential expression between
sepsis patients and controls across the majority (7+) of the 9
literature datasets were selected. This identified a subset of 31
genes from the original 99-gene Endotoxin Tolerance Signature (FIG.
7).
[0241] The classification algorithm randomForest was used to assess
the ability of the genes in the identified 31-gene subset to
classify sepsis patients from controls. Each dataset (external and
internal) was divided into training and test sets and randomForest
classification was performed independently on each dataset. The
31-gene subset showed excellent accuracy when separating sepsis
patients from controls with an average accuracy of 95.7% across all
datasets (Table 6). The 31-gene subset also showed strong
performance in predicting sepsis and individual/combined organ
failure in a group of patients with a suspicion of sepsis, with
accuracies ranging from 62.4-87.4% (Table 6). This same analysis
was also performed using the full 99-gene Endotoxin Tolerance
Signature, and this gene set was found to provide equivalent
performance supporting the suitability of the gene reduction
strategy (Table 7). Area under the curve of receiver operating
characteristic (AUC) assessments performed similarly. The strong
performance of the 31-gene subset across multiple distinct datasets
and at a clinically relevant time-point (current time of diagnostic
cultures) supports the use of the 31-gene subset in the diagnosis
of sepsis. The strong association between endotoxin tolerance and
sepsis was identified across 10 distinct datasets and was
independent of location, method, gender, age, ethnicity, and sepsis
diagnostic criteria variables. Accordingly, both the full 99-gene
Endotoxin Tolerance Signature and the 31-gene subset will have
utility as a tool in sepsis diagnosis. Accurate diagnostic tools
for sepsis are of high clinical priority due to the importance of
early intervention in sepsis and the lack of clinical features
specific to sepsis [Hotchkiss R S, Monneret G, Payen D. Lancet
Infectious Diseases 2013; 13: 260-8]. An additional benefit to
using endotoxin tolerance-related biomarkers is that they would
also provide information regarding the patients' immune functional
status.
TABLE-US-00007 TABLE 6 Diagnostic Potential of the Endotoxin
Tolerance Signature* Accuracy using 31- Accuracy using 99- gene
Endotoxin gene Endotoxin Variable Tolerance Subset Tolerance
Signature Sepsis (patient numbers in brackets) vs. Controls
In-house Sepsis study (37) 93.3% 92.7% vs. Controls GSE28750 study
(30) vs. 99.3% 97.4% Controls GSE9692 study (45) vs. 95.1% 96.6%
Controls GSE13904 study (227) vs. 96.3% 94.2% Controls GSE26440
study (130) vs. 96.3% 96.0% Controls GSE4607 study (84) vs. 93.6%
92.6% Controls GSE8121 study (71) vs. 93.2% 92.2% Controls GSE26378
study (70) vs. 98.3% 98.6% Controls Mean 95.7% 95.0% Sepsis vs. No
Sepsis Sepsis vs. No Sepsis 62.4% 64.2% Organ Failure vs. No Organ
Failure Respiratory 77.5% 75.5% Cardiovascular 77.2% 73.6% Liver
77.8% 78.0% Acute Kidney Injury 71.5% 74.1% Coagulation 87.4% 86.4%
Combined (3+) 77.3% 73.7% Table 6 Footnotes: *Each dataset was
split into training (containing 2/3 of sepsis patients and
controls) and test (containing 1/3 of sepsis patients and controls)
sets using random sampling. Datasets GSE13015 and GSE11755 were
omitted from this analysis due to low numbers of controls (N = 3)
in each dataset. For each of the remaining 8 datasets, the model
was defined on the training set and then assessed on the test set
using the randomForest package with ntree set to 1000. The
procedure was repeated 1000 times, and the average prediction
accuracies recorded for each data set. This analysis was repeated
on the dataset to classify patients with an initial suspicion of
sepsis who did or did not go on to develop sepsis or organ
failure.
[0242] The Endotoxin Tolerance Signature showed excellent accuracy
when separating sepsis patients from controls (Overall Accuracy:
randomForest=95%; Area under the curve=98.9%), and demonstrated
similar accuracy with individual studies containing 19-227 patients
(Table 6).
[0243] The association between the Endotoxin Tolerance Signature
and confirmed sepsis was strong and statistically significant in 10
distinct datasets (FIGS. 2 & 5, Table 6) and was independent of
sample size, location, method, gender, age and ethnicity. These
results confirm that the Endotoxin Tolerance Signature is robustly
associated with very early sepsis. The Endotoxin Tolerance
Signature was also associated with disease severity measured
primarily by the development of organ dysfunction. Therefore, an
updated model of sepsis pathogenesis mediated by an endotoxin
tolerance-mediated immune dysfunction is indicated. Furthermore,
the results demonstrate that immune dysfunction could be detected
at a clinically relevant diagnostic time-point, providing unique
information regarding the patients' functional immune status. The
Endotoxin Tolerance Signature or subset could therefore help to
define a subset of patients who might benefit from immunomodulation
(e.g. anti-endotoxin tolerance) and supportive therapies.
[0244] Sepsis is generally classified as an excessive inflammatory
response (early stage), followed by a transition to an
anti-inflammatory/immunosuppression dominated stage (Hotchkiss et
al, 2013). However, the nature and timing of this later stage had
not been well characterized. In contrast to previous reports
associating endotoxin tolerance only with late stage sepsis, the
results described herein revealed that all 10 sepsis patient
cohorts showed an immunological expression profile strongly
associated with the Endotoxin Tolerance Signature and subset and
throughout all stages of early clinical disease (FIGS. 2, 5 &
6). From a general clinical perspective, characterizing the nature
and timing of the excessive inflammatory and
anti-inflammatory/immunosuppression stages is essential when
considering how to treat this disease. This is especially important
when different therapeutic approaches have been largely
unsuccessful to date, likely due to a lack of knowledge regarding
the immunological status of the patient. The data provided herein
also shows that this signature was able to predict the development
of sepsis, suggesting that the Endotoxin Tolerance Signature and
subset have utility as a diagnostic tool.
[0245] Most importantly, this study was able to clearly demonstrate
the association of the Endotoxin Tolerance Signature and subset
with disease severity and organ dysfunction (FIG. 6). Organ
dysfunction is considered the main factor contributing to patient
deterioration and ultimately death. Importantly, the Endotoxin
Tolerance Signature was present up to 48 hours prior to the
development of organ dysfunction, indicating that the signature or
subset can additionally be used as a screening method to assess
which patients are at a higher risk for developing a worsening
condition.
[0246] It is important to note that while the data indicated that
the endotoxin tolerant state predominates during early sepsis, the
Inflammatory Signature was also significantly enriched, albeit at
relatively lower levels, in many of the comparisons performed in
this study. From a biological perspective, these observations
suggest that in individuals with localized infections (e.g.
patients in the No Sepsis group), when an initial insult occurs,
the brief inflammatory response quickly subsides to balance
inflammation and bring the system to homeostasis. However, in
sepsis, where there is an uncontrolled source of infection and
possible contributing genetic factors (Murkin J M, and K R Walley,
The Journal of Extra-Corporeal Technology 41, P43-49, 2009), the
immunological balance between inflammation and endotoxin tolerance
becomes detrimentally unbalanced towards a state increasingly
dominated by endotoxin tolerance. The findings herein thus indicate
that there is an initial (uncontrolled) infection, during which
resting immune cells, such as neutrophils and
monocytes/macrophages, get activated resulting in the patient
developing the first strong clinical symptoms. In septic patients,
a second endotoxin stimulus likely leads to the rapid activation of
an endotoxin tolerance profile. By the time of first hospital
admission, this endotoxin tolerance profile predominates in
peripheral blood mononuclear cells systemically, while residual
neutrophilic inflammation still occurs in this rapidly turning over
population.
[0247] Thus, while there remains an inflammatory component to
sepsis, the endotoxin tolerance-driven state is contributing to the
overall immune dysfunction in sepsis and thus the severity of the
disease.
[0248] At a cellular level, the major cause of the immune
dysfunction in sepsis is likely the rapid accumulation of tolerized
monocytes/macrophages, locking the system into an M2-like state
(Pena, O M, et al., J Immunol 2011, 186:7243-7254) in an attempt to
reduce excessive neutrophilic inflammation and its consequences,
such as vascular leakage, coagulation, lymphocyte death, etc.
However, weakening the patient's monocyte/macrophage responses can
also lead to an inability to clear the primary infection and
increased susceptibility to secondary infections, despite the
continued activation of other immune cell populations, such as
neutrophils. Due to their continuous replenishment from the bone
marrow, neutrophils are probably the main drivers of
pro-inflammatory cytokine responses, although they too are likely
to eventually enter an endotoxin tolerant state (Parker L C, et
al., J Leukocyte Biology 2005; 78:1301-1305).
[0249] Additionally, it is demonstrated herein that the Endotoxin
Tolerance Signature and subset had a higher association with
positive cultures among the sepsis group, and a similar higher
trend with those who had negative cultures (FIG. 5C). In contrast,
the Inflammatory Signature predominated among the "No Sepsis"
patients with a stronger presence among those with positive
cultures (FIG. 5D). It is interesting to observe the different
trends among each group of patients, which are aligned with
previously discussed points: An initial Inflammatory Signature that
increased in the direction of negative to positive cultures in the
"No Sepsis" group indicating the early increasing phase of
inflammation during a possibly localized infection or an initial
sterile inflammatory process. Subsequently, in patients who rapidly
get extremely ill, as is the case of those patients in the "Sepsis"
group, there is a rapid transition towards a systemic infection-led
tolerant state, leading to a stronger and increasing presence of an
endotoxin tolerant state, as observed in the described results,
indicating a culture negative to culture positive trend.
[0250] Characterizing the contributions of the inflammatory and
immunosuppressive programs during clinical disease is critical when
considering host-directed therapies for treatment. The results
described herein demonstrate that an endotoxin tolerance state
predominates throughout the earliest stages of clinical sepsis and
is likely driving immune dysfunction in sepsis. Thus, if there is
an immunological phase characterized solely by excessive
inflammation, it likely occurs pre-clinically. However, given the
significant enrichment of the Inflammatory Signature in many sepsis
patient groups, it is likely the combination of endotoxin tolerance
and inflammation that contributes to the unique pattern of sepsis
pathogenesis. These findings necessitate a shift away from a two
stage model and towards a clinically relevant immune etiology
characterized by endotoxin tolerance-driven immune dysfunction at
the earliest stages of clinical disease. Detection of a predominant
Endotoxin Tolerance Signature is supportive of the suspicion of
sepsis and will, therefore, direct the treating team to consider
appropriate supportive and immunomodulation therapies to balance
the immune response.
[0251] In conclusion, these studies have provided the first
description of a unique endotoxin tolerance profile, present very
early in the course of sepsis, linked to sepsis pathogenesis, and
strongly associated with the risk of organ dysfunction.
Example 2
New Therapies Based on the Endotoxin Tolerance Signature
[0252] Network analysis of the Endotoxin Tolerance genes revealed
that most of the genes formed a very tight subnetwork strongly
suggesting that the signature reflects critical mechanisms likely
related to immune dysfunction in sepsis patients (FIG. 8).
[0253] One implication of knowing that a patient is going to soon
suffer from sepsis is that one can apply an appropriate antibiotic
therapy comprising a cocktail of the most potent drugs. Current
clinical guidelines indicate that while waiting for culture
results, a patient should be started on intravenous ceftriaxone and
azithromycin. The purpose of this regimen is to try to avoid major
resistance issues since only a portion of the patients who are
thought to have the potential to acquire sepsis actually do so (see
e.g. Table 3). Knowing that a patient has sepsis very early in the
course of disease would enable physicians to prescribe the most
aggressive therapies to try to reduce the influence of
infection.
[0254] A second therapeutic strategy would be to try to break
tolerance, reversing the immunosuppressive state of macrophages. To
date virtually all therapies tried to treat sepsis have been in an
attempt to do the opposite, i.e. suppress a hyperinflammatory state
and this has the potential to worsen the patient's ability to
defend against sepsis. Consistently, in more than 31 clinical
trials to suppress the hyperinflammatory state, this approach has
failed.
[0255] Examples of methods to break endotoxin tolerance include
immune cells [Heusinkveld M, et al. Journal of Immunology 2011;
187:1157-1165], interferon gamma, CpG-ODN with or without IL-10,
anti-CD40, inhibitors of STAT3, inhibitors of STATE, inhibitors of
p50, inhibitors of NF.kappa.B, inhibitors of IKK.beta.,
imidazoquinolones and zoledronic acid [Sica A, A Mantovani. Journal
of Clinical Investigation 2012; 122:787-795]. Other potential
agents include those chemical agents, cells or natural products
that suppress the expression of one or more genes from the
Endotoxin Tolerance Signature in M2 polarized macrophages, or to
revert the properties of M2 macrophages in vitro and in vivo to
those of an M1 macrophage [Sica and Mantovani, 2012].
[0256] The disclosures of all patents, patent applications,
publications and database entries referenced in this specification
are hereby specifically incorporated by reference in their entirety
to the same extent as if each such individual patent, patent
application, publication and database entry were specifically and
individually indicated to be incorporated by reference.
[0257] Although the invention has been described with reference to
certain specific embodiments, various modifications thereof will be
apparent to those skilled in the art without departing from the
spirit and scope of the invention. All such modifications as would
be apparent to one skilled in the art are intended to be included
within the scope of the following claims.
* * * * *