T cell balance gene expression, compositions of matters and methods of use thereof
10822587 · 2020-11-03
Assignee
- The Broad Institute, Inc. (Cambridge, MA)
- Massachusetts Institute Of Technology (Cambridge, MA)
- President And Fellows Of Harvard College (Cambridge, MA)
- The Brigham And Women's Hospital, Inc. (Boston, MA)
Inventors
- Aviv Regev (Cambridge, MA)
- Vijay Kuchroo (Newton, MA, US)
- Hongkun Park (Lexington, MA)
- Nir Yosef (Richmond, CA, US)
- Alexander K. Shalek (Cambridge, MA)
- Jellert Gaublomme (Cambridge, MA, US)
- Nicole C. Joller (Brookline, MA, US)
- Chuan Wu (Boston, MA, US)
- Ana Carrizosa Anderson (Brookline, MA, US)
Cpc classification
C12N5/0637
CHEMISTRY; METALLURGY
A61K31/4745
HUMAN NECESSITIES
C12Q1/6881
CHEMISTRY; METALLURGY
A61K31/7076
HUMAN NECESSITIES
A61K31/198
HUMAN NECESSITIES
A61K48/00
HUMAN NECESSITIES
A61K33/00
HUMAN NECESSITIES
A61K31/661
HUMAN NECESSITIES
G01N2800/56
PHYSICS
A61K33/06
HUMAN NECESSITIES
A61P35/00
HUMAN NECESSITIES
A61K31/7088
HUMAN NECESSITIES
C12N15/113
CHEMISTRY; METALLURGY
C12Q2600/112
CHEMISTRY; METALLURGY
C07K2317/76
CHEMISTRY; METALLURGY
C07K16/28
CHEMISTRY; METALLURGY
A61K38/191
HUMAN NECESSITIES
G01N2570/00
PHYSICS
International classification
A61K31/198
HUMAN NECESSITIES
A61K31/4745
HUMAN NECESSITIES
A61K31/661
HUMAN NECESSITIES
A61K31/7088
HUMAN NECESSITIES
C12N5/00
CHEMISTRY; METALLURGY
A61K31/7076
HUMAN NECESSITIES
C07K16/28
CHEMISTRY; METALLURGY
C12N15/113
CHEMISTRY; METALLURGY
C12Q1/6881
CHEMISTRY; METALLURGY
A61K33/06
HUMAN NECESSITIES
A61K33/00
HUMAN NECESSITIES
Abstract
This invention relates generally to compositions and methods for identifying the regulatory network that modulates, controls or otherwise influences T cell balance, for example, Th17 cell differentiation, maintenance and/or function, as well compositions and methods for exploiting the regulatory network that modulates, controls or otherwise influences T cell balance in a variety of therapeutic and/or diagnostic indications. This invention also relates generally to identifying and exploiting target genes and/or target gene products that modulate, control or otherwise influence T cell balance in a variety of therapeutic and/or diagnostic indications.
Claims
1. A method for increasing a non-pathogenic phenotype and/or decreasing a pathogenic phenotype in a Th17 cell or a population of Th-17 cells comprising: delivering to a Th-17 cell, or a population of Th-17 cells, a vector comprising a nucleotide sequence encoding PROCR and configured to express PROCR, thereby increasing a non-pathogenic Th17 phenotype and/or decreasing a pathogenic phenotype in the Th17 cell or population of Th17 cells.
2. The method of claim 1, wherein the Th17 cell or population of Th17 cells comprise a pathogenic Th17 cell or pathogenic population of Th17 cells.
3. The method of claim 1, wherein the vector is delivered in vitro.
4. The method of claim 1, wherein the vector is a retroviral vector.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
(1) The following detailed description, given by way of example, but not intended to limit the invention solely to the specific embodiments described, may best be understood in conjunction with the accompanying drawings.
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DETAILED DESCRIPTION OF THE INVENTION
(37) This invention relates generally to compositions and methods for identifying the regulatory networks that control T cell balance, T cell differentiation, T cell maintenance and/or T cell function, as well compositions and methods for exploiting the regulatory networks that control T cell balance, T cell differentiation, T cell maintenance and/or T cell function in a variety of therapeutic and/or diagnostic indications.
(38) The invention provides compositions and methods for modulating T cell balance. The invention provides T cell modulating agents that modulate T cell balance. For example, in some embodiments, the invention provides T cell modulating agents and methods of using these T cell modulating agents to regulate, influence or otherwise impact the level of and/or balance between T cell types, e.g., between Th17 and other T cell types, for example, regulatory T cells (Tregs). For example, in some embodiments, the invention provides T cell modulating agents and methods of using these T cell modulating agents to regulate, influence or otherwise impact the level of and/or balance between Th17 activity and inflammatory potential. As used herein, terms such as Th17 cell and/or Th17 phenotype and all grammatical variations thereof refer to a differentiated T helper cell that expresses one or more cytokines selected from the group the consisting of interleukin 17A (IL-17A), interleukin 17F (IL-17F), and interleukin 17A/F heterodimer (IL17-AF). As used herein, terms such as Th1 cell and/or Th1 phenotype and all grammatical variations thereof refer to a differentiated T helper cell that expresses interferon gamma (IFN). As used herein, terms such as Th2 cell and/or Th2 phenotype and all grammatical variations thereof refer to a differentiated T helper cell that expresses one or more cytokines selected from the group the consisting of interleukin 4 (IL-4), interleukin 5 (IL-5) and interleukin 13 (IL-13). As used herein, terms such as Treg cell and/or Treg phenotype and all grammatical variations thereof refer to a differentiated T cell that expresses Foxp3.
(39) These compositions and methods use T cell modulating agents to regulate, influence or otherwise impact the level and/or balance between T cell types, e.g., between Th17 and other T cell types, for example, regulatory T cells (Tregs).
(40) The invention provides methods and compositions for modulating T cell differentiation, for example, helper T cell (Th cell) differentiation. The invention provides methods and compositions for modulating T cell maintenance, for example, helper T cell (Th cell) maintenance. The invention provides methods and compositions for modulating T cell function, for example, helper T cell (Th cell) function. These compositions and methods use T cell modulating agents to regulate, influence or otherwise impact the level and/or balance between Th17 cell types, e.g., between pathogenic and non-pathogenic Th17 cells. These compositions and methods use T cell modulating agents to influence or otherwise impact the differentiation of a population of T cells, for example toward the Th17 cell phenotype, with or without a specific pathogenic distinction, or away from the Th17 cell phenotype, with or without a specific pathogenic distinction. These compositions and methods use T cell modulating agents to influence or otherwise impact the maintenance of a population of T cells, for example toward the Th17 cell phenotype, with or without a specific pathogenic distinction, or away from the Th17 cell phenotype, with or without a specific pathogenic distinction. These compositions and methods use T cell modulating agents to influence or otherwise impact the differentiation of a population of Th17 cells, for example toward the pathogenic Th17 cell phenotype or away from the pathogenic Th17 cell phenotype, or toward the non-pathogenic Th17 cell phenotype or away from the non-pathogenic Th17 cell phenotype. These compositions and methods use T cell modulating agents to influence or otherwise impact the maintenance of a population of Th17 cells, for example toward the pathogenic Th17 cell phenotype or away from the pathogenic Th17 cell phenotype, or toward the non-pathogenic Th17 cell phenotype or away from the non-pathogenic Th17 cell phenotype. These compositions and methods use T cell modulating agents to influence or otherwise impact the differentiation of a population of T cells, for example toward a non-Th17 T cell subset or away from a non-Th17 cell subset. These compositions and methods use T cell modulating agents to influence or otherwise impact the maintenance of a population of T cells, for example toward a non-Th17 T cell subset or away from a non-Th17 cell subset.
(41) As used herein, terms such as pathogenic Th17 cell and/or pathogenic Th17 phenotype and all grammatical variations thereof refer to Th17 cells that, when induced in the presence of TGF-3, express an elevated level of one or more genes selected from Cxcl3, IL22, IL3, Ccl4, Gzmb, Lrmp, Ccl5, Casp1, Csf2, Ccl3, Tbx21, Icos, IL17r, Stat4, Lgals3 and Lag, as compared to the level of expression in a TGF-3-induced Th17 cells. As used herein, terms such as non-pathogenic Th17 cell and/or non-pathogenic Th17 phenotype and all grammatical variations thereof refer to Th17 cells that, when induced in the presence of TGF-3, express a decreased level of one or more genes selected from IL6st, IL1rn, Ikzf3, Maf, Ahr, IL9 and IL10, as compared to the level of expression in a TGF-3-induced Th17 cells.
(42) These compositions and methods use T cell modulating agents to influence or otherwise impact the function and/or biological activity of a T cell or T cell population. These compositions and methods use T cell modulating agents to influence or otherwise impact the function and/or biological activity of a helper T cell or helper T cell population. These compositions and methods use T cell modulating agents to influence or otherwise impact the function and/or biological activity of a Th17 cell or Th17 cell population. These compositions and methods use T cell modulating agents to influence or otherwise impact the function and/or biological activity of a non-Th17 T cell or non-Th17 T cell population, such as, for example, a Treg cell or Treg cell population, or another CD4+ T cell or CD4+ T cell population. These compositions and methods use T cell modulating agents to influence or otherwise impact the plasticity of a T cell or T cell population, e.g., by converting Th17 cells into a different subtype, or into a new state.
(43) The methods provided herein combine transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing perturbations in primary T cells to systematically derive and experimentally validate a model of the dynamic regulatory network that controls Th17 differentiation. See e.g., Yosef et al., Dynamic regulatory network controlling Th17 cell differentiation, Nature, vol. 496: 461-468 (2013)/doi: 10.1038/nature11981, the contents of which are hereby incorporated by reference in their entirety. The network consists of two self-reinforcing, but mutually antagonistic, modules, with novel regulators, whose coupled action may be essential for maintaining the level and/or balance between Th17 and other CD4+ T cell subsets. Overall, 9,159 interactions between 71 regulators and 1,266 genes were active in at least one network; 46 of the 71 are novel. The examples provided herein identify and validate 39 regulatory factors, embedding them within a comprehensive temporal network and reveals its organizational principles, and highlights novel drug targets for controlling Th17 differentiation.
(44) A Th17-negative module includes regulators such as SP4, ETS2, IKZF4, TSC22D3 and/or, IRF1. It was found that the transcription factor Tsc22d3, which acts as a negative regulator of a defined subtype of Th17 cells, co-localizes on the genome with key Th17 regulators. The Th17 positive module includes regulators such as MINA, PML, POU2AF1, PROCR, SMARCA4, ZEB1, EGR2, CCR6, and/or FAS. Perturbation of the chromatin regulator Mina was found to up-regulate Foxp3 expression, perturbation of the co-activator Pou2af1 was found to up-regulate IFN- production in stimulated nave cells, and perturbation of the TNF receptor Fas was found to up-regulate IL-2 production in stimulated nave cells. All three factors also control IL-17 production in Th17 cells.
(45) Effective coordination of the immune system requires careful balancing of distinct pro-inflammatory and regulatory CD4+ helper T cell populations. Among those, pro-inflammatory IL-17 producing Th17 cells play a key role in the defense against extracellular pathogens and have also been implicated in the induction of several autoimmune diseases (see e.g., Bettelli, E., Oukka, M. & Kuchroo, V. K. T(H)-17 cells in the circle of immunity and autoimmunity. Nat Immunol 8, 345-350, doi:10.1038/ni0407-345 (2007)), including for example, psoriasis, ankylosing spondylitis, multiple sclerosis and inflammatory bowel disease. Th17 differentiation from nave T-cells can be triggered in vitro by the cytokines TGF-1 and IL-6. While TGF-1 alone induces Foxp3+ regulatory T cells (iTreg) (see e.g., Zhou, L. et al. TGF-beta-induced Foxp3 inhibits T(H)17 cell differentiation by antagonizing RORgammat function. Nature 453, 236-240, doi:nature06878 [pii]10.1038/nature06878 (2008)), the presence of IL-6 inhibits iTreg and induces Th17 differentiation (Bettelli et al., Nat Immunol 2007).
(46) While TGF-1 is required for the induction of Foxp3+ induced Tregs (iTregs), the presence of IL-6 inhibits the generation of iTregs and initiates the Th17 differentiation program. This led to the hypothesis that a reciprocal relationship between pathogenic Th17 cells and Treg cells exists (Bettelli et al., Nat Immunol 2007), which may depend on the balance between the mutually antagonistic master transcription factors (TFs) ROR-t (in Th17 cells) and Foxp3 (in Treg cells) (Zhou et al., Nature 2008). Other cytokine combinations have also been shown to induce ROR-t and differentiation into Th17 cells, in particular TGF-1 and IL-21 or IL-1, TGF-3+IL-6, IL-6, and IL-23 (Ghoreschi, K. et al. Generation of pathogenic T(H)17 cells in the absence of TGF-beta signaling. Nature 467, 967-971, doi:10.1038/nature09447 (2010)). Finally, although a number of cytokine combinations can induce Th17 cells, exposure to IL-23 is critical for both stabilizing the Th17 phenotype and the induction of pathogenic effector functions in Th17 cells.
(47) Much remains unknown about the regulatory network that controls Th17 cells (O'Shea, J. et al. Signal transduction and Th17 cell differentiation. Microbes Infect 11, 599-611 (2009); Zhou, L. & Littman, D. Transcriptional regulatory networks in Th17 cell differentiation. Curr Opin Immunol 21, 146-152 (2009)). Developmentally, as TGF- is required for both Th17 and iTreg differentiation, it is not understood how balance is achieved between them or how IL-6 biases toward Th17 differentiation (Bettelli et al., Nat Immunol 2007). Functionally, it is unclear how the pro-inflammatory status of Th17 cells is held in check by the immunosuppressive cytokine IL-10 (O'Shea et al., Microbes Infect 2009; Zhou & Littman, Curr Opin Immunol 2009). Finally, many of the key regulators and interactions that drive development of Th17 remain unknown (Korn, T., Bettelli, E., Oukka, M. & Kuchroo, V. K. IL-17 and Th17 Cells. Annu Rev Immunol 27, 485-517, doi:10.1146/annurev.immuno1.021908.13271010.1146/annurev.immuno1.021908. 132710 [pii] (2009)).
(48) Recent studies have demonstrated the power of coupling systematic profiling with perturbation for deciphering mammalian regulatory circuits (Amit, I. et al. Unbiased reconstruction of a mammalian transcriptional network mediating pathogen responses. Science 326, 257-263, doi:10.1126/science.1179050 (2009); Novershtern, N. et al. Densely interconnected transcriptional circuits control cell states in human hematopoiesis. Cell 144, 296-309, doi:10.1016/j.cell.2011.01.004 (2011); Litvak, V. et al. Function of C/EBPdelta in a regulatory circuit that discriminates between transient and persistent TLR4-induced signals. Nat. Immunol. 10, 437-443, doi:10.1038/ni.1721 (2009); Suzuki, H. et al. The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line. Nat Genet 41, 553-562 (2009); Amit, I., Regev, A. & Hacohen, N. Strategies to discover regulatory circuits of the mammalian immune system. Nature reviews. Immunology 11, 873-880, doi:10.1038/nri3109 (2011); Chevrier, N. et al. Systematic discovery of TLR signaling components delineates viral-sensing circuits. Cell 147, 853-867, doi:10.1016/j.cell.2011.10.022 (2011); Garber, M. et al. A High-Throughput Chromatin Immunoprecipitation Approach Reveals Principles of Dynamic Gene Regulation in Mammals. Molecular cell, doi:10.1016/j.molcel.2012.07.030 (2012)). Most of these studies have relied upon computational circuit-reconstruction algorithms that assume one fixed network. Th17 differentiation, however, spans several days, during which the components and wiring of the regulatory network likely change. Furthermore, nave T cells and Th17 cells cannot be transfected effectively in vitro by traditional methods without changing their phenotype or function, thus limiting the effectiveness of perturbation strategies for inhibiting gene expression.
(49) These limitations are addressed in the studies presented herein by combining transcriptional profiling, novel computational methods, and nanowire-based siRNA delivery (Shalek, A. K. et al. Vertical silicon nanowires as a universal platform for delivering biomolecules into living cells. Proc. Natl. Acad. Sci. U.S.A. 107, 1870-1875, doi:10.1073/pnas.0909350107 (2010) (
(50) The methods provided herein combine a high-resolution transcriptional time course, novel methods to reconstruct regulatory networks, and innovative nanotechnology to perturb T cells, to construct and validate a network model for Th17 differentiation. The model consists of three consecutive, densely intra-connected networks, implicates 71 regulators (46 novel), and suggests substantial rewiring in 3 phases. The 71 regulators significantly overlap with genes genetically associated with inflammatory bowel disease (Jostins, L. et al. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119-124, doi:10.1038/nature11582 (2012)) (11 of 71, p<10.sup.9). Building on this model, 127 putative regulators (80 novel) were systematically ranked, and top ranking ones were tested experimentally.
(51) It was found that the Th17 regulators are organized into two tightly coupled, self-reinforcing but mutually antagonistic modules, whose coordinated action may explain how the balance between Th17, Treg, and other effector T cell subsets is maintained, and how progressive directional differentiation of Th17 cells is achieved. Within the two modules are 12 novel factors (
(52) This validated model highlights at least 12 novel regulators that either positively or negatively impact the Th17 program (
(53) The T cell modulating agents are used to modulate the expression of one or more target genes or one or more products of one or more target genes that have been identified as genes responsive to Th17-related perturbations. These target genes are identified, for example, by contacting a T cell, e.g., nave T cells, partially differentiated T cells, differentiated T cells and/or combinations thereof, with a T cell modulating agent and monitoring the effect, if any, on the expression of one or more signature genes or one or more products of one or more signature genes. In some embodiments, the one or more signature genes are selected from those listed in Table 1 or Table 2 shown below.
(54) TABLE-US-00001 TABLE 1 Signature Genes IL17A IL21R CCL1 PSTPIP1 IL7R BCL3 CD247 IER3 IRF4 DPP4 PROCR FZD7 CXCL10 TGFBR1 RELA GLIPR1 IL12RB1 CD83 HIF1A AIM1 TBX21 RBPJ PRNP CD4 ZNF281 CXCR3 IL17RA LMNB1 IL10RA NOTCH2 STAT1 MGLL CXCR4 CCL4 LRRFIP1 LSP1 TNFRSF13B TAL2 KLRD1 GJA1 ACVR1B IL9 RUNX1 LGALS3BP TGIF1 FAS ID2 ARHGEF3 ABCG2 SPRY1 STAT5A BCL2L11 REL PRF1 TNFRSF25 TGM2 ID3 FASLG BATF UBIAD1 ZEB1 MT2A KAT2B MAP3K5 MYD88 POU2AF1 NFATC2 RAB33A EGR2 IFNG CD70 CASP1 AES PLAC8 LITAF FOXP1 PML IL17F IL27RA MTA3 TGFBR3 DDR1 IL22 IFIH1 CCR8 IL4 MINA RASGRP1 ZFP161 CD28 XBP1 XRCC5 IRF1 TNFSF9 PRDM1 NCF1C CCR6 SMARCA4 AHR NUDT4 SMOX YAX2 SLAMF7 PDCD1LG2 ITGB1 IL21 IL1RN PYCR1 CASP6 SAP30 MBNL3 AQP3 NFKBIE CD9 ARID5A SEMA7A LAMP2 IL24 TRIM24 PRC1 GATA3 STAT5B CSF2 IFIT1 RORA SKI NFE2L2 DNTT SGK1 BCL6 IL23R PMEPA1 IL2RA ELK3 KLF6 GAP43 MT1A CD74 ACVR2A PRICKLE1 JAK3 STAT6 NR3C1 OAS2 IL4R TNFSF8 CCR4 ERRFI1 NAMPT IL3 CXCR5 LAD1 ITGA3 TGFB1 SKAP2 TMEM126A TGFB3 ETV6 PLEKHF2 LILRB1, LILRB2, LILRB3, LILRB4, LILRB5 INHBA CASP4 STAT2 KATNA1 KLF7 CEBPB IRF7 B4GALT1 RUNX3 TRAF3 FLI1 ANXA4 NFKBIZ TRPS1 IRF9 SULT2B1 SERPINE2 JUN GFI1 PHLDA1 RXRA STAT4 MXI1 PRKD3 SERTAD1 CMTM6 IFI35 TAP1 MAF SOCS3 MAX TRIM5 IL10 TSC22D3 ZNF238 FLNA BMPR1A LIF CHD7 GUSB PTPRJ DAXX FOXM1 C14ORF83 STAT3 KLF9 BCL11B VAV3 CCR5 IL6ST RUNX2 ARL5A CCL20 CLCF1 EMP1 GRN SPP1 NFIL3 PELI2 PRKCA CD80 IKZF4 SEMA4D PECI RORC ISG20 STARD10 ARMCX2 SERPINB1 CD86 TIMP2 SLC2A1 IL12RB2 IL2RB KLF10 RPP14 IFNGR2 NCOA1 CTSW PSMB9 SMAD3 NOTCH1 GEM CASP3 FOXP3 TNFRSF12A TRIM25 TRAT1 CD24 CD274 HLA-A PLAGL1 CD5L MAFF MYST4 RAD51AP1 CD2 ATF4 FRMD4B NKG7 TNFSF11 ARNTL RFK IFITM2 ICOS IL1R1 CD44 HIP1R IRF8 FOXO1 ERCC5
(55) TABLE-US-00002 TABLE 2 Subset of Signature Genes AHR HIF1A IRF4 REL ARID5A ICOS IRF8 RORA BATF ID2 ITGA3 RORC CASP4 ID3 KLF6 SERPINB1 CASP6 IFNG KLRD1 SGK1 CCL20 IL10 LIF SKAP2 CCL4 IL10RA LTA SKI CCR5 IL17A MAF SMOX CCR6 IL17F MAFF SOCS3 CD24 IL17RA MINA STAT1 CD5L IL2 MYC STAT3 CD80 IL21 NFATC2 STAT4 CEBPB IL21R NFE2L2 TBX21 CLCF1 IL22 NFIL3 TGFBR1 CSF2 IL23R NOTCH1 TGIF1 CXCR3 IL24 NUDT4 TNFRSF25 EGR2 IL2RA PML TNFSF8 ELK3 IL7R POU2AF1 TRIM24 ETV6 IL9 PROCR TRPS1 FAS INHBA PSMB9 TSC22D3 FOXP3 IRF1 RBPJ ZFP36L1 GATA3
(56) In some embodiments, the target gene is one or more Th17-associated cytokine(s) or receptor molecule(s) selected from those listed in Table 3. In some embodiments, the target gene is one or more Th17-associated transcription regulator(s) selected from those shown in Table 4.
(57) TABLE-US-00003 TABLE 3 Th17-Associated Receptor Molecules ACVR1B CXCR4 IL6ST PROCR ACVR2A CXCR5 IL7R PTPRJ BMPR1A DDR1 IRAK1BP1 PVR CCR4 FAS ITGA3 TLR1 CCR5 IL15RA KLRD1 TNFRSF12A CCR6 IL18R1 MYD88 TNFRSF13B CCR8 IL1RN PLAUR TRAF3 CXCR3
(58) TABLE-US-00004 TABLE 4 Th17-Associated Transcription Regulators TRPS1 SMARCA4 CDYL SIRT2 SMOX ZFP161 IKZF4 MAFF ARNTL TP53 NCOA1 CHMP1B UBE2B SUZ12 SS18 GATAD2B NR3C1 POU2AF1 PHF13 ZNF703 TRIM24 MYST4 MTA3 ZNRF1 FLI1 MXI1 ASXL1 JMJD1C SP4 CHD7 LASS4 ZFP36L2 EGR2 CREB3L2 SKIL TSC22D4 ZNF281 VAX2 FOSL2 NFE2L2 RELA KLF10 RUNX2 RNF11 IRF7 SKI TLE1 ARID3A STAT2 ELK3 ELL2 MEN1 IRF3 ZEB1 BCL11B CBX4 XBP1 LRRFIP1 KAT2B ZFP62 PRDM1 PAXBP1 KLF6 CIC ATF4 ID1 E2F8 HCLS1 CREB1 ZNF238 ZNRF2 ZFP36L1 IRF9 VAV1 TSC22D3 TGIF1 IRF2 MINA HMGB2 FOXJ2 BATF3 FUS
(59) In some embodiments, the target gene is one or more Th17-associated transcription regulator(s) selected from those shown in Table 5. In some embodiments, the target gene is one or more Th17-associated receptor molecule(s) selected from those listed in Table 6. In some embodiments, the target gene is one or more Th17-associated kinase(s) selected from those listed in Table 7. In some embodiments, the target gene is one or more Th17-associated signaling molecule(s) selected from those listed in Table 8. In some embodiments, the target gene is one or more Th17-associated receptor molecule(s) selected from those listed in Table 9.
(60) TABLE-US-00005 TABLE 5 Candidate Regulators % Interactions OR differential expression (compared to Th0) IL23R knockout Symbol Early Intermediate Late (late) IRF4 0.892473118 0.841397849 1 UNDER-EXPR IFI35 1 0.952380952 0.904761905 UNDER-EXPR ETS1 1 0.636363636 0.636363636 UNDER-EXPR NMI 1 0.857142857 0 UNDER-EXPR SAP18 0.785714286 0.928571429 1 OVER-EXPR FLI1 1 0.971590909 0.869318182 SP4 1 0.710900474 0.63507109 UNDER-EXPR SP100 1 0 0 UNDER-EXPR TBX21 0 1 0 OVER-EXPR POU2F2 0 1 0 OVER-EXPR ZNF281 0 1 0 UNDER-EXPR NFIL3 0.611111111 0.611111111 1 SMARCA4 0.805825243 0.757281553 1 OVER-EXPR CSDA 0 0 1 OVER-EXPR STAT3 0.855392157 0.970588235 1 UNDER-EXPR FOXO1 0.875 1 0.875 NCOA3 0.875 1 0.9375 LEF1 0.380952381 0.904761905 1 UNDER-EXPR SUZ12 0 1 0 OVER-EXPR CDC5L 0 1 0 UNDER-EXPR CHD7 1 0.860465116 0.686046512 UNDER-EXPR HIF1A 0.733333333 0.666666667 1 UNDER-EXPR RELA 0.928571429 1 0.880952381 UNDER-EXPR STAT2 1 0.821428571 0 STAT5B 1 0.848484848 0.515151515 UNDER-EXPR RORC 0 0 1 UNDER-EXPR STAT1 1 0.635658915 0 UNDER-EXPR MAZ 0 1 0 LRRFIP1 0.9 0.8 1 REL 1 0 0 OVER-EXPR CITED2 1 0 0 UNDER-EXPR RUNX1 0.925149701 0.925149701 1 UNDER-EXPR ID2 0.736842105 0.789473684 1 SATB1 0.452380952 0.5 1 UNDER-EXPR TRIM28 0 1 0 STAT6 0.54 0.64 1 OVER-EXPR STAT5A 0 0.642241379 1 UNDER-EXPR BATF 0.811732606 0.761255116 1 UNDER-EXPR EGR1 0.857142857 1 0 OVER-EXPR EGR2 0.896428571 0.839285714 1 OVER-EXPR AES 0.888888889 1 0.777777778 IRF8 0 1 0.824786325 OVER-EXPR SMAD2 0.806060606 0.781818182 1 NFKB1 0.266666667 0.706666667 1 UNDER-EXPR PHF21A 1 0.533333333 0.933333333 UNDER-EXPR CBFB 0.35 0.9 1 ZFP161 0.818181818 0.714876033 1 OVER-EXPR ZEB2 0 0.411764706 1 SP1 0 0.740740741 1 FOXJ2 0 1 1 IRF1 1 0 0 MYC 0 0.595505618 1 UNDER-EXPR IRF2 1 0 0 EZH1 1 0.8 0.44 UNDER-EXPR RUNX2 0 0 1 JUN 0.647058824 0.647058824 1 OVER-EXPR STAT4 1 0 0 UNDER-EXPR MAX 0.947368421 0.789473684 1 TP53 0.292307692 0.615384615 1 UNDER-EXPR IRF3 1 0.485294118 0.235294118 UNDER-EXPR BCL11B 0.666666667 0.611111111 1 E2F1 0 0 1 OVER-EXPR IRF9 1 0.440433213 0 UNDER-EXPR GATA3 1 0 0 OVER-EXPR TRIM24 0.965517241 1 0.965517241 UNDER-EXPR E2F4 0.083333333 0.5 1 NR3C1 1 1 0 UNDER-EXPR ETS2 1 0.925925926 0.864197531 OVER-EXPR CREB1 0.802197802 0.706959707 1 IRF7 1 0.777777778 0 OVER-EXPR TFEB 0.8 0.6 1 TRPS1 OVER-EXPR UNDER-EXPR SMOX OVER-EXPR OVER-EXPR UNDER-EXPR RORA OVER-EXPR OVER-EXPR UNDER-EXPR ARID5A OVER-EXPR OVER-EXPR OVER-EXPR OVER-EXPR ETV6 OVER-EXPR OVER-EXPR ARNTL OVER-EXPR UNDER-EXPR UBE2B OVER-EXPR UNDER-EXPR XBP1 OVER-EXPR PRDM1 OVER-EXPR OVER-EXPR UNDER-EXPR ATF4 OVER-EXPR OVER-EXPR POU2AF1 OVER-EXPR UNDER-EXPR CE6PB OVER-EXPR OVER-EXPR UNDER-EXPR CREM OVER-EXPR OVER-EXPR UNDER-EXPR MYST4 OVER-EXPR OVER-EXPR UNDER-EXPR MXI1 OVER-EXPR UNDER-EXPR RBPJ OVER-EXPR OVER-EXPR OVER-EXPR CREB3L2 OVER-EXPR OVER-EXPR UNDER-EXPR VAX2 OVER-EXPR OVER-EXPR KLF10 OVER-EXPR OVER-EXPR SKI OVER-EXPR OVER-EXPR UNDER-EXPR ELK3 OVER-EXPR OVER-EXPR ZEB1 OVER-EXPR OVER-EXPR OVER-EXPR PML OVER-EXPR OVER-EXPR UNDER-EXPR SERTAD1 OVER-EXPR UNDER-EXPR NOTCH1 OVER-EXPR OVER-EXPR OVER-EXPR AHR OVER-EXPR OVER-EXPR OVER-EXPR UNDER-EXPR C21ORF66 OVER-EXPR UNDER-EXPR SAP30 OVER-EXPR OVER-EXPR ID1 OVER-EXPR OVER-EXPR OVER-EXPR ZNF238 OVER-EXPR OVER-EXPR VAV1 OVER-EXPR UNDER-EXPR MINA OVER-EXPR OVER-EXPR UNDER-EXPR BATF3 OVER-EXPR OVER-EXPR CDYL UNDER-EXPR IKZF4 OVER-EXPR OVER-EXPR OVER-EXPR OVER-EXPR NCOA1 OVER-EXPR OVER-EXPR BCL3 OVER-EXPR OVER-EXPR OVER-EXPR UNDER-EXPR JUNB OVER-EXPR UNDER-EXPR SS18 OVER-EXPR OVER-EXPR PHF13 OVER-EXPR MTA3 OVER-EXPR UNDER-EXPR ASXL1 OVER-EXPR OVER-EXPR LASS4 OVER-EXPR UNDER-EXPR SKIL OVER-EXPR OVER-EXPR OVER-EXPR DDIT3 OVER-EXPR OVER-EXPR FOSL2 OVER-EXPR OVER-EXPR TLE1 OVER-EXPR OVER-EXPR ATF3 OVER-EXPR ELL2 OVER-EXPR OVER-EXPR OVER-EXPR JARID2 OVER-EXPR OVER-EXPR KLF9 OVER-EXPR OVER-EXPR OVER-EXPR KAT2B OVER-EXPR UNDER-EXPR KLF6 OVER-EXPR OVER-EXPR UNDER-EXPR E2F8 OVER-EXPR OVER-EXPR OVER-EXPR BCL6 OVER-EXPR UNDER-EXPR ZNRF2 UNDER-EXPR TSC22D3 OVER-EXPR UNDER-EXPR KLF7 OVER-EXPR HMGB2 OVER-EXPR FUS OVER-EXPR OVER-EXPR SIRT2 OVER-EXPR MAFF OVER-EXPR OVER-EXPR OVER-EXPR CHMP1B OVER-EXPR UNDER-EXPR GATAD2B OVER-EXPR OVER-EXPR SMAD7 OVER-EXPR OVER-EXPR ZNF703 OVER-EXPR OVER-EXPR ZNRF1 OVER-EXPR OVER-EXPR JMJD1C OVER-EXPR UNDER-EXPR ZFP36L2 OVER-EXPR UNDER-EXPR TSC22D4 NFE2L2 OVER-EXPR OVER-EXPR OVER-EXPR UNDER-EXPR RNF11 OVER-EXPR ARID3A OVER-EXPR OVER-EXPR UNDER-EXPR MEN1 OVER-EXPR OVER-EXPR RARA OVER-EXPR OVER-EXPR UNDER-EXPR CBX4 OVER-EXPR OVER-EXPR OVER-EXPR ZFP62 OVER-EXPR CIC OVER-EXPR HCLS1 UNDER-EXPR ZFP36L1 UNDER-EXPR TGIF1 UNDER-EXPR SMAD4 OVER-EXPR IL7R OVER EXPR OVER EXPR UNDER EXPR ITGA3 OVER EXPR OVER EXPR IL1R1 OVER EXPR OVER EXPR UNDER EXPR FAS OVER EXPR UNDER EXPR CCR5 OVER EXPR OVER EXPR OVER EXPR UNDER EXPR CCR6 OVER EXPR OVER EXPR ACVR2A OVER EXPR OVER EXPR UNDER EXPR IL6ST OVER EXPR OVER EXPR UNDER EXPR IL17RA OVER EXPR OVER EXPR UNDER EXPR CCR8 OVER EXPR DDR1 OVER EXPR OVER EXPR UNDER EXPR PROCR OVER EXPR OVER EXPR OVER EXPR IL2RA OVER EXPR OVER EXPR OVER EXPR OVER EXPR IL12RB2 OVER EXPR OVER EXPR UNDER EXPR MYD88 OVER EXPR OVER EXPR UNDER EXPR BMPR1A OVER EXPR UNDER EXPR PTPRJ OVER EXPR OVER EXPR OVER EXPR TNFRSF13B OVER EXPR OVER EXPR UNDER EXPR CXCR3 OVER EXPR UNDER EXPR IL1RN OVER EXPR OVER EXPR UNDER EXPR CXCR5 OVER EXPR OVER EXPR OVER EXPR UNDER EXPR CCR4 OVER EXPR OVER EXPR UNDER EXPR IL4R OVER EXPR OVER EXPR UNDER EXPR IL2RB OVER EXPR OVER EXPR TNFRSF12A OVER EXPR OVER EXPR OVER EXPR CXCR4 OVER EXPR OVER EXPR UNDER EXPR KLRD1 OVER EXPR OVER EXPR IRAK1BP1 OVER EXPR OVER EXPR PVR OVER EXPR OVER EXPR OVER EXPR UNDER EXPR IL15RA OVER EXPR OVER EXPR TLR1 OVER EXPR ACVR1B OVER EXPR OVER EXPR IL12RB1 OVER EXPR OVER EXPR OVER EXPR IL18R1 OVER EXPR OVER EXPR TRAF3 OVER EXPR OVER EXPR IFNGR1 OVER EXPR UNDER EXPR PLAUR OVER EXPR OVER EXPR IL21R UNDER EXPR IL23R OVER EXPR UNDER EXPR
(61) TABLE-US-00006 TABLE 6 Candidate Receptor Molecules % Differential expression (compared to Th0) IL23R knockout Symbol Early Intermediate Late (late) PTPLA UNDER EXPR PSTPIP1 OVER EXPR OVER EXPR UNDER EXPR TK1 UNDER EXPR EIF2AK2 OVER EXPR PTEN UNDER EXPR BPGM UNDER EXPR DCK OVER EXPR PTPRS OVER EXPR PTPN18 OVER EXPR MKNK2 OVER EXPR PTPN1 OVER EXPR UNDER EXPR PTPRE UNDER EXPR SH2D1A OVER EXPR DUSP22 OVER EXPR PLK2 OVER EXPR DUSP6 UNDER EXPR CDC25B UNDER EXPR SLK OVER EXPR UNDER EXPR MAP3K5 UNDER EXPR BMPR1A OVER EXPR UNDER EXPR ACP5 OVER EXPR OVER EXPR UNDER EXPR TXK OVER EXPR OVER EXPR UNDER EXPR RIPK3 OVER EXPR OVER EXPR UNDER EXPR PPP3CA OVER EXPR PTPRF OVER EXPR OVER EXPR OVER EXPR PACSIN1 OVER EXPR NEK4 OVER EXPR UNDER EXPR PIP4K2A UNDER EXPR PPME1 OVER EXPR OVER EXPR UNDER EXPR SRPK2 UNDER EXPR DUSP2 OVER EXPR PHACTR2 OVER EXPR OVER EXPR HK2 OVER EXPR OVER EXPR DCLK1 OVER EXPR PPP2R5A UNDER EXPR RIPK1 OVER EXPR UNDER EXPR GK OVER EXPR RNASEL OVER EXPR OVER EXPR GMFG OVER EXPR OVER EXPR OVER EXPR STK4 UNDER EXPR HINT3 OVER EXPR DAPP1 OVER EXPR UNDER EXPR TEC OVER EXPR OVER EXPR OVER EXPR UNDER EXPR GMFB OVER EXPR OVER EXPR PTPN6 UNDER EXPR RIPK2 UNDER EXPR PIM1 OVER EXPR OVER EXPR OVER EXPR NEK6 OVER EXPR OVER EXPR UNDER EXPR ACVR2A OVER EXPR OVER EXPR UNDER EXPR AURKB UNDER EXPR FES OVER EXPR OVER EXPR ACVR1B OVER EXPR OVER EXPR CDK6 OVER EXPR OVER EXPR UNDER EXPR ZAK OVER EXPR OVER EXPR UNDER EXPR VRK2 UNDER EXPR MAP3K8 OVER EXPR UNDER EXPR DUSP14 OVER EXPR UNDER EXPR SGK1 OVER EXPR OVER EXPR OVER EXPR UNDER EXPR PRKCQ OVER EXPR UNDER EXPR JAK3 OVER EXPR UNDER EXPR ULK2 OVER EXPR UNDER EXPR HIPK2 OVER EXPR OVER EXPR PTPRJ OVER EXPR OVER EXPR OVER EXPR SPHK1 OVER EXPR INPP1 UNDER EXPR TNK2 OVER EXPR OVER EXPR OVER EXPR PCTK1 OVER EXPR OVER EXPR OVER EXPR DUSP1 OVER EXPR NUDT4 UNDER EXPR MAP4K3 OVER EXPR TGFBR1 OVER EXPR OVER EXPR OVER EXPR PTP4A1 OVER EXPR HK1 OVER EXPR OVER EXPR DUSP16 OVER EXPR UNDER EXPR AMP32A OVER EXPR DDR1 OVER EXPR OVER EXPR UNDER EXPR ITK UNDER EXPR WNK1 UNDER EXPR NAGK OVER EXPR UNDER EXPR STK38 OVER EXPR BMP2K OVER EXPR OVER EXPR OVER EXPR OVER EXPR BUB1 UNDER EXPR AAK1 OVER EXPR SIK1 OVER EXPR DUSP10 OVER EXPR UNDER EXPR PRKCA OVER EXPR PIM2 OVER EXPR UNDER EXPR STK17B OVER EXPR UNDER EXPR TK2 UNDER EXPR STK39 OVER EXPR ALPK2 OVER EXPR OVER EXPR UNDER EXPR MST4 OVER EXPR PHLPP1 UNDER EXPR
(62) TABLE-US-00007 TABLE 7 Candidate Kinases % Differential expression (compared to Th) IL23R knockout Symbol Early Intermediate Late (late) SGK1 OVER EXPR OVER EXPR OVER EXPR UNDER EXPR HK2 OVER EXPR OVER EXPR OVER EXPR PRPS1 UNDER EXPR CAMK4 ZAP70 TXK OVER EXPR OVER EXPR OVER EXPR UNDER EXPR NEK6 OVER EXPR OVER EXPR MAPKAPK2 OVER EXPR MFHAS1 UNDER EXPR OVER EXPR PDXK PRKCH OVER EXPR UNDER EXPR CDK6 OVER EXPR OVER EXPR ZAK OVER EXPR OVER EXPR UNDER EXPR PKM2 OVER EXPR JAK2 OVER EXPR UNDER EXPR UNDER EXPR STK38 UNDER EXPR UNDER EXPR OVER EXPR ADRBK1 PTK2B UNDER EXPR DGUOK UNDER EXPR UNDER EXPR DGKA UNDER EXPR RIPK3 OVER EXPR OVER EXPR UNDER EXPR PIM1 OVER EXPR OVER EXPR OVER EXPR CDK5 STK17B OVER EXPR CLK3 CLK1 ITK UNDER EXPR AKT1 UNDER EXPR PGK1 TWF1 LIMK2 RFK UNDER EXPR WNK1 UNDER EXPR OVER EXPR HIPK1 AXL OVER EXPR UNDER EXPR UNDER EXPR RPS6KB1 CDC42BPA STK38L PRKCD PDK3 PI4KA PNKP CDKN3 STK19 PRPF4B UNDER EXPR MAP4K2 PDPK1 VRK1 TRRAP
(63) TABLE-US-00008 TABLE 8 Candidate Signaling Molecules From Single Cell Analysis % Differential expression (compared to Th) IL23R knockout Symbol Early Intermediate Late (late) CTLA4 OVER EXPR OVER EXPR UNDER EXPR CD9 UNDER EXPR UNDER EXPR UNDER EXPR IL2RA OVER EXPR OVER EXPR OVER EXPR OVER EXPR CD5L OVER EXPR OVER EXPR OVER EXPR CD24 OVER EXPR OVER EXPR UNDER EXPR CD200 OVER EXPR UNDER EXPR UNDER EXPR OVER EXPR CD53 UNDER EXPR OVER EXPR UNDER EXPR TNFRSF9 UNDER EXPR UNDER EXPR OVER EXPR CD44 UNDER EXPR CD96 UNDER EXPR UNDER EXPR CD83 UNDER EXPR UNDER EXPR IL27RA CXCR3 OVER EXPR OVER EXPR TNFRSF4 UNDER EXPR IL4R OVER EXPR OVER EXPR PROCR OVER EXPR OVER EXPR OVER EXPR LAMP2 OVER EXPR OVER EXPR UNDER EXPR CD74 UNDER EXPR UNDER EXPR OVER EXPR TNFRSF13B OVER EXPR OVER EXPR UNDER EXPR PDCD1 UNDER EXPR TNFRSF1B IL21R UNDER EXPR UNDER EXPR IFNGR1 OVER EXPR UNDER EXPR ICOS UNDER EXPR OVER EXPR PTPRC ADAM17 FCGR2B TNFSF9 UNDER EXPR UNDER EXPR UNDER EXPR MS4A6A UNDER EXPR UNDER EXPR UNDER EXPR CCR4 OVER EXPR OVER EXPR CD226 CD3G UNDER EXPR UNDER EXPR ENTPD1 ADAM10 UNDER EXPR UNDER EXPR UNDER EXPR CD27 UNDER EXPR UNDER EXPR UNDER EXPR UNDER EXPR CD84 UNDER EXPR UNDER EXPR ITGAL UNDER EXPR CCND2 UNDER EXPR BSG UNDER EXPR CD40LG PTPRCAP UNDER EXPR UNDER EXPR UNDER EXPR CD68 CD63 SLC3A2 HLA-DQA1 OVER EXPR CTSD CSF1R CD3D UNDER EXPR CD247 UNDER EXPR UNDER EXPR CD14 ITGAV FCER1G IL2RG OVER EXPR UNDER EXPR
(64) TABLE-US-00009 TABLE 9 Candidate Receptor Molecules From Single Cell Analysis % Differential expression (compared to Th) IL23R knockout Symbol Early Intermediate Late (late) PLEK OVER EXPR BHLH40 OVER EXPR OVER EXPR ARID5A OVER EXPR OVER EXPR OVER EXPR OVER EXPR ETS1 OVER EXPR OVER EXPR UNDER EXPR IRF4 OVER EXPR OVER EXPR OVER EXPR IKZF3 RORC OVER EXPR OVER EXPR UNDER EXPR STAT4 UNDER EXPR UNDER EXPR UNDER EXPR RORA OVER EXPR OVER EXPR UNDER EXPR PHF6 ID3 UNDER EXPR UNDER EXPR UNDER EXPR OVER EXPR ZBTB32 UNDER EXPR OVER EXPR IFI35 OVER EXPR ID2 OVER EXPR OVER EXPR OVER EXPR UNDER EXPR MDM4 CHMP2A ANKHD1 CHD7 OVER EXPR OVER EXPR UNDER EXPR STAT5B OVER EXPR OVER EXPR MAML2 ID1 OVER EXPR OVER EXPR OVER EXPR SS18 OVER EXPR MAF ETV6 OVER EXPR OVER EXPR CCRN4L OVER EXPR OVER EXPR NASP BLOC1S1 OVER EXPR XAB2 STAT5A OVER EXPR UNDER EXPR IKZF1 UNDER EXPR JUNB OVER EXPR OVER EXPR THRAP3 OVER EXPR SP100 OVER EXPR PYCR1 OVER EXPR OVER EXPR OVER EXPR HMGA1 TAF1B UNDER EXPR CNOT2 NOC4L OVER EXPR SKI UNDER EXPR OVER EXPR OVER EXPR VAV1 OVER EXPR OVER EXPR NR4A2 UNDER EXPR UNDER EXPR OVER EXPR LGTN NFKBIA UNDER EXPR KDM6B MAZ CDC5L UNDER EXPR HCLS1 UNDER EXPR OVER EXPR BAZ2B OVER EXPR MXD3 BATF OVER EXPR OVER EXPR E2F4 NFKBIB RBPJ OVER EXPR OVER EXPR OVER EXPR TOX4 CENPT CASP8AP2 ECE2 MIER1 AHR OVER EXPR OVER EXPR OVER EXPR SPOP UNDER EXPR BTG1 MATR3 UNDER EXPR JMJD1C OVER EXPR OVER EXPR HMGB2 OVER EXPR CREG1 OVER EXPR NFATC1 NFE2L2 OVER EXPR OVER EXPR OVER EXPR WHSC1L1 TBPL1 TRIP12 BTG2 HMGN1 UNDER EXPR ATF2 NR4A3 C16ORF80 MBNL1 UNDER EXPR UNDER EXPR WDHD1 LASS6 CREM OVER EXPR OVER EXPR CARM1 RNF5 UNDER EXPR SMARCA4 OVER EXPR GATAD1 TCERG1 UNDER EXPR CHRAC1 NFYC ATF3 OVER EXPR OVER EXPR ZNF326 OVER EXPR KLF13 TFDP1 LRRFIP1 OVER EXPR OVER EXPR MORF4L2 FOXN3 HDAC8 MORF4L1 DNAJC2 OVER EXPR MAFG YBX1
(65) Among the novel Th17 positive factors is the zinc finger E-box binding homeobox 1 Zeb1, which is early-induced and sustained in the Th17 time course (
(66) Conversely, among the novel Th17 negative factors is Sp4, an early-induced gene, predicted in the model as a regulator of ROR-t and as a target of ROR-t, Batf, Irf4, Stat3 and Smarca4 (
(67) These novel and known regulatory factors act coordinately to orchestrate intra- and intermodules interactions and to promote progressive differentiation of Th17 cells, while limiting modules that inhibit directional differentiation of this subset and promote differentiation of T cells into other T cell subsets. For instance, knockdown of Smarca4 and Zeb1 leads to decrease in Mina (due to all-positive interactions between Th17 positive regulators), while knockdown of Smarca4 or Mina leads to increase in Tsc22d3 31 expression, due to negative cross-module interactions. As shown using RNAseq, these effects extend beyond the expression of regulatory factors in the network and globally affect the Th17 transcriptional program: e.g. knock-down of Mina has substantial effects on the progression of the Th17 differentiation network from the intermediate to the late phase, as some of its affected down-regulated genes significantly overlap the respective temporal clusters (p<10.sup.5, e.g., clusters C9, C19). An opposite trend is observed for the negative regulators Tsc22d3 and Sp4. For example, the transcriptional regulator Sp4 represses differentiating Th17 cells from entering into the late phase of differentiation by inhibiting the cytokine signaling (C19; p<10.sup.7) and haematopoiesis (C20; p<10.sup.3) clusters, which include Ahr, Batf, ROR-t, etc. These findings emphasize the power of large-scale functional perturbation studies in understanding the action of complex molecular circuits that govern Th17 differentiation.
(68) In a recent work, Ciofani et al. (Ciofani, M. et al. A Validated Regulatory Network for Th17 Cell Specification. Cell, doi:10.1016/j.cell.2012.09.016 (2012)) systematically ranked Th17 regulators based on ChIPSeq data for known key factors and transcriptional profiles in wild type and knockout cells. While their network centered on known core Th17 TFs, the complementary approach presented herein perturbed many genes in a physiologically meaningful setting. Reassuringly, their core Th17 network significantly overlaps with the computationally inferred model (
(69) The wiring of the positive and negative modules (
(70) Automated Procedure for Selection of Signature Genes
(71) The invention also provides methods of determining gene signatures that are useful in various therapeutic and/or diagnostic indications. The goal of these methods is to select a small signature of genes that will be informative with respect to a process of interest. The basic concept is that different types of information can entail different partitions of the space of the entire genome (>20k genes) into subsets of associated genes. This strategy is designed to have the best coverage of these partitions, given the constraint on the signature size. For instance, in some embodiments of this strategy, there are two types of information: (i) temporal expression profiles; and (ii) functional annotations. The first information source partitions the genes into sets of co-expressed genes. The information source partitions the genes into sets of co-functional genes. A small set of genes is then selected such that there are a desired number of representatives from each set, for example, at least 10 representatives from each co-expression set and at least 10 representatives from each co-functional set. The problem of working with multiple sources of information (and thus aiming to cover multiple partitions) is known in the theory of computer science as Set-Cover. While this problem cannot be solved to optimality (due to its NP-hardness) it can be approximated to within a small factor. In some embodiments, the desired number of representatives from each set is one or more, at least 2, 5 or more, 10 or more, 15 or more, 20 or more, 25 or more, 30 or more, 35 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, or 100 or more.
(72) An important feature of this approach is that it can be given either the size of the signature (and then find the best coverage it can under this constraint); or the desired level of coverage (and then select the minimal signature size that can satisfy the coverage demand).
(73) An exemplary embodiment of this procedure is the selection of the 275-gene signature (Table 1), which combined several criteria to reflect as many aspect of the differentiation program as was possible. The following requirements were defined: (1) the signature must include all of the TFs that belong to a Th17 microarray signature (comparing to other CD4+ T cells, see e.g., Wei et al., in Immunity vol. 30 155-167 (2009)), see Methods described herein); that are included as regulators in the network and are at least slightly differentially expressed; or that are strongly differentially expressed; (2) it must include at least 10 representatives from each cluster of genes that have similar expression profiles; (3) it must contain at least 5 representatives from the predicted targets of each TF in the different networks; (4) it must include a minimal number of representatives from each enriched Gene Ontology (GO) category (computed over differentially expressed genes); and, (5) it must include a manually assembled list of 100 genes that are related to the differentiation process, including the differentially expressed cytokines, receptor molecules and other cell surface molecules. Since these different criteria might generate substantial overlaps, a set-cover algorithm was used to find the smallest subset of genes that satisfies all of five conditions. 18 genes whose expression showed no change (in time or between treatments) in the microarray data were added to this list.
(74) Use of Signature Genes
(75) The invention provides T cell related gene signatures for use in a variety of diagnostic and/or therapeutic indications. For example, the invention provides Th17 related signatures that are useful in a variety of diagnostic and/or therapeutic indications. Signatures in the context of the present invention encompasses, without limitation nucleic acids, together with their polymorphisms, mutations, variants, modifications, subunits, fragments, and other analytes or sample-derived measures.
(76) Exemplary signatures are shown in Tables 1 and 2 and are collectively referred to herein as, inter alia, Th17-associated genes, Th17-associated nucleic acids, signature genes, or signature nucleic acids.
(77) These signatures are useful in methods of diagnosing, prognosing and/or staging an immune response in a subject by detecting a first level of expression, activity and/or function of one or more signature genes or one or more products of one or more signature genes selected from those listed in Table 1 or Table 2 and comparing the detected level to a control of level of signature gene or gene product expression, activity and/or function, wherein a difference in the detected level and the control level indicates that the presence of an immune response in the subject.
(78) These signatures are useful in methods of monitoring an immune response in a subject by detecting a level of expression, activity and/or function of one or more signature genes or one or more products of one or more signature genes selected from those listed in Table 1 or Table 2 at a first time point, detecting a level of expression, activity and/or function of one or more signature genes or one or more products of one or more signature genes selected from those listed in Table 1 or Table 2 at a second time point, and comparing the first detected level of expression, activity and/or function with the second detected level of expression, activity and/or function, wherein a change in the first and second detected levels indicates a change in the immune response in the subject.
(79) These signatures are useful in methods of identifying patient populations at risk or suffering from an immune response based on a detected level of expression, activity and/or function of one or more signature genes or one or more products of one or more signature genes selected from those listed in Table 1 or Table 2. These signatures are also useful in monitoring subjects undergoing treatments and therapies for aberrant immune response(s) to determine efficaciousness of the treatment or therapy. These signatures are also useful in monitoring subjects undergoing treatments and therapies for aberrant immune response(s) to determine whether the patient is responsive to the treatment or therapy. These signatures are also useful for selecting or modifying therapies and treatments that would be efficacious in treating, delaying the progression of or otherwise ameliorating a symptom of an aberrant immune response. The signatures provided herein are useful for selecting a group of patients at a specific state of a disease with accuracy that facilitates selection of treatments.
(80) The present invention also may comprise a kit with a detection reagent that binds to one or more signature nucleic acids. Also provided by the invention is an array of detection reagents, e.g., oligonucleotides that can bind to one or more signature nucleic acids. Suitable detection reagents include nucleic acids that specifically identify one or more signature nucleic acids by having homologous nucleic acid sequences, such as oligonucleotide sequences, complementary to a portion of the signature nucleic acids packaged together in the form of a kit. The oligonucleotides can be fragments of the signature genes. For example the oligonucleotides can be 200, 150, 100, 50, 25, 10 or fewer nucleotides in length. The kit may contain in separate container or packaged separately with reagents for binding them to the matrix), control formulations (positive and/or negative), and/or a detectable label such as fluorescein, green fluorescent protein, rhodamine, cyanine dyes, Alexa dyes, luciferase, radiolabels, among others. Instructions (e.g., written, tape, VCR, CD-ROM, etc.) for carrying out the assay may be included in the kit. The assay may for example be in the form of a Northern hybridization or DNA chips or a sandwich ELISA or any other method as known in the art. Alternatively, the kit contains a nucleic acid substrate array which may comprise one or more nucleic acid sequences.
(81) Use of T Cell Modulating Agents
(82) Suitable T cell modulating agent(s) for use in any of the compositions and methods provided herein include an antibody, a soluble polypeptide, a polypeptide agent, a peptide agent, a nucleic acid agent, a nucleic acid ligand, or a small molecule agent. By way of non-limiting example, suitable T cell modulating agents or agents for use in combination with one or more T cell modulating agents are shown below in Table 10.
(83) TABLE-US-00010 TABLE 10 T cell Modulating Agents Target Agent CCR6 prostaglandin E2, lipopolysaccharide, mip-3alpha, vegf, rantes, calcium, bortezomib, ccl4, larc, tarc, lipid, E. coli B5 lipopolysaccharide CCR5 cholesterol, cyclosporin a, glutamine, methionine, guanine, simvastatin, threonine, indinavir, lipoxin A4, cysteine, prostaglandin E2, zinc, dapta, 17-alpha-ethinylestradiol, polyacrylamide, progesterone, zidovudine, rapamycin, rantes, glutamate, alanine, valine, ccl4, quinine, NSC 651016, methadone, pyrrolidine dithiocarbamate, palmitate, nor-binaltorphimine, interferon beta-1a, vitamin-e, tak779, lipopolysaccharide, cisplatin, albuterol, fluvoxamine, vicriviroc, bevirimat, carbon tetrachloride, galactosylceramide, ATP-gamma-S, cytochalasin d, hemozoin, CP 96345, tyrosine, etravirine, vitamin d, mip 1alpha, ammonium, tyrosine sulfate, isoleucine, isopentenyl diphosphate, il 10, serine, N-acetyl-L- cysteine, histamine, cocaine, ritonavir, tipranavir, aspartate, atazanavir, tretinoin, ATP, ribavirin, butyrate, N-nitro-L-arginine methyl ester, larc, buthionine sulfoximine, DAPTA, aminooxypentane-rantes, triamcinolone acetonide, shikonin, actinomycin d, bucladesine, aplaviroc, nevirapine, N-formyl-Met-Leu-Phe, cyclosporin A, lipoarabinomannan, nucleoside, sirolimus, morphine, mannose, calcium, heparin, c-d4i, pge2, beta- estradiol, mdms, dextran sulfate, dexamethasone, arginine, ivig, mcp 2, cyclic amp, U 50488H, N-methyl-D-aspartate, hydrogen peroxide, 8- carboxamidocyclazocine, latex, groalpha, xanthine, ccl3, retinoic acid, Maraviroc, sdf 1, opiate, efavirenz, estrogen, bicyclam, enfuvirtide, filipin, bleomycin, polysaccharide, tarc, pentoxifylline, E. coli B5 lipopolysaccharide, methylcellulose, maraviroc ITGA3 SP600125, paclitaxel, decitabine, e7820, retinoid, U0126, serine, retinoic acid, tyrosine, forskolin, Ca2+ IRF4 prostaglandin E2, phorbol myristate acetate, lipopolysaccharide, A23187, tacrolimus, trichostatin A, stallimycin, imatinib, cyclosporin A, tretinoin, bromodeoxyuridine, ATP-gamma-S, ionomycin BATF Cyclic AMP, serine, tacrolimus, beta-estradiol, cyclosporin A, leucine RBPJ zinc, tretinoin PROCR lipopolysaccharide, cisplatin, fibrinogen, 1,10-phenanthroline, 5-N- ethylcarboxamido adenosine, cystathionine, hirudin, phospholipid, Drotrecogin alfa, vegf, Phosphatidylethanolamine, serine, gamma- carboxyglutamic acid, calcium, warfarin, endotoxin, curcumin, lipid, nitric oxide ZEB1 resveratrol, zinc, sulforafan, sorafenib, progesterone, PD-0332991, dihydrotestosterone, silibinin, LY294002, 4-hydroxytamoxifen, valproic acid, beta-estradiol, forskolin, losartan potassium, fulvestrant, vitamin d POU2AF1 terbutaline, phorbol myristate acetate, bucladesine, tyrosine, ionomycin, KT5720, H89 EGR1 ghrelin, ly294002, silicone, sodium, propofol, 1,25 dihydroxy vitamin d3, tetrodotoxin, threonine, cyclopiazonic acid, urea, quercetin, ionomycin, 12-o-tetradecanoylphorbol 13-acetate, fulvestrant, phenylephrine, formaldehyde, cysteine, leukotriene C4, prazosin, LY379196, vegf, rapamycin, leupeptin, pd 98,059, ruboxistaurin, pCPT- cAMP, methamphetamine, nitroprusside, H-7, Ro31-8220, phosphoinositide, lysophosphatidylcholine, bufalin, calcitriol, leuprolide, isobutylmethylxanthine, potassium chloride, acetic acid, cyclothiazide, quinolinic acid, tyrosine, adenylate, resveratrol, topotecan, genistein, thymidine, D-glucose, mifepristone, lysophosphatidic acid, leukotriene D4, carbon monoxide, poly rI:rC-RNA, sp 600125, agar, cocaine, 4- nitroquinoline-1-oxide, tamoxifen, lead, fibrinogen, tretinoin, atropine, mithramycin, K+, epigallocatechin-gallate, ethylenediaminetetraacetic acid, h2o2, carbachol, sphingosine-1-phosphate, iron, 5- hydroxytryptamine, amphetamine, SP600125, actinomycin d, SB203580, cyclosporin A, norepinephrine, okadaic acid, ornithine, LY294002, pge2, beta-estradiol, glucose, erlotinib, arginine, 1-alpha,25-dihydroxy vitamin D3, dexamethasone, pranlukast, phorbol myristate acetate, nimodipine, desipramine, cyclic amp, N-methyl-D-aspartate, atipamezole, acadesine, losartan, salvin, methylnitronitrosoguanidine, EGTA, gf 109203x, nitroarginine, 5-N-ethylcarboxamido adenosine, 15-deoxy-delta-12,14- PGJ 2, dbc-amp, manganese superoxide, di(2-ethylhexyl) phthalate, egcg, mitomycin C, 6,7-dinitroquinoxaline-2,3-dione, GnRH-A, estrogen, ribonucleic acid, imipramine, bapta, L-triiodothyronine, prostaglandin, forskolin, nogalamycin, losartan potassium, lipid, vincristine, 2-amino-3-phosphonopropionic acid, prostacyclin, methylnitrosourea, cyclosporin a, vitamin K3, thyroid hormone, diethylstilbestrol, D-tubocurarine, tunicamycin, caffeine, phorbol, guanine, bisindolylmaleimide, apomorphine, arachidonic acid, SU6656, prostaglandin E2, zinc, ptx1, progesterone, cyclosporin H, phosphatidylinositol, U0126, hydroxyapatite, epoprostenol, glutamate, 5fluorouracil, indomethacin, 5-fluorouracil, RP 73401, Ca2+, superoxide, trifluoperazine, nitric oxide, lipopolysaccharide, cisplatin, diazoxide, tgf beta1, calmidazolium, anisomycin, paclitaxel, sulindac sulfide, ganciclovir, gemcitabine, testosterone, ag 1478, glutamyl-Se- methylselenocysteine, doxorubicin, tolbutamide, cytochalasin d, PD98059, leucine, SR 144528, cyclic AMP, matrigel, haloperidol, serine, sb 203580, triiodothyronine, reverse, N-acetyl-L-cysteine, ethanol, s- nitroso-n-acetylpenicillamine, curcumin, l-nmma, H89, tpck, calyculin a, chloramphenicol, A23187, dopamine, platelet activating factor, arsenite, selenomethylselenocysteine, ropinirole, saralasin, methylphenidate, gentamicin, reserpine, triamcinolone acetonide, methyl methanesulfonate, wortmannin, thapsigargin, deferoxamine, calyculin A, peptidoglycan, dihydrotestosterone, calcium, phorbol-12-myristate, ceramide, nmda, 6-cyano-7-nitroquinoxaline-2,3-dione, hydrogen peroxide, carrageenan, sch 23390, linsidomine, oxygen, clonidine, fluoxetine, retinoid, troglitazone, retinoic acid, epinephrine, n acetylcysteine, KN-62, carbamylcholine, 2-amino-5-phosphonovaleric acid, oligonucleotide, gnrh, rasagiline, 8-bromo-cAMP, muscarine, tacrolimus, kainic acid, chelerythrine, inositol 1,4,5 trisphosphate, yohimbine, acetylcholine, atp, 15-deoxy-delta-12,14-prostaglandin j2, ryanodine, CpG oligonucleotide, cycloheximide, BAPTA-AM, phenylalanine ETV6 lipopolysaccharide, retinoic acid, prednisolone, valproic acid, tyrosine, cerivastatin, vegf, agar, imatinib, tretinoin IL17RA rantes, lipopolysaccharide, 17-alpha-ethinylestradiol, camptothecin, E. coli B5 lipopolysaccharide EGR2 phorbol myristate acetate, lipopolysaccharide, platelet activating factor, carrageenan, edratide, 5-N-ethylcarboxamido adenosine, potassium chloride, dbc-amp, tyrosine, PD98059, camptothecin, formaldehyde, prostaglandin E2, leukotriene C4, zinc, cyclic AMP, GnRH-A, bucladesine, thapsigargin, kainic acid, cyclosporin A, mifepristone, leukotriene D4, LY294002, L-triiodothyronine, calcium, beta-estradiol, H89, dexamethasone, cocaine SP4 betulinic acid, zinc, phorbol myristate acetate, LY294002, methyl 2- cyano-3,12-dioxoolean-1,9-dien-28-oate, beta-estradiol, Ca2+ IRF8 oligonucleotide, chloramphenicol, lipopolysaccharide, estrogen, wortmannin, pirinixic acid, carbon monoxide, retinoic acid, tyrosine NFKB1 Bay 11-7085, Luteolin, Triflusal, Bay 11-7821, Thalidomide, Caffeic acid phenethyl ester, Pranlukast TSC22D3 phorbol myristate acetate, prednisolone, sodium, dsip, tretinoin, 3- deazaneplanocin, gaba, PD98059, leucine, triamcinolone acetonide, prostaglandin E2, steroid, norepinephrine, U0126, acth, calcium, ethanol, beta-estradiol, lipid, chloropromazine, arginine, dexamethasone PML lipopolysaccharide, glutamine, thyroid hormone, cadmium, lysine, tretinoin, bromodeoxyuridine, etoposide, retinoid, pic 1, arsenite, arsenic trioxide, butyrate, retinoic acid, alpha-retinoic acid, h2o2, camptothecin, cysteine, leucine, zinc, actinomycin d, proline, stallimycin, U0126 IL12RB1 prostaglandin E2, phorbol myristate acetate, lipopolysaccharide, bucladesine, 8-bromo-cAMP, gp 130, AGN194204, galactosylceramide- alpha, tyrosine, ionomycin, dexamethasone, il-12 IL21R azathioprine, lipopolysaccharide, okadaic acid, E. coli B5 lipopolysaccharide, calyculin A NOTCH1 interferon beta-1a, lipopolysaccharide, cisplatin, tretinoin, oxygen, vitamin B12, epigallocatechin-gallate, isobutylmethylxanthine, threonine, apomorphine, matrigel, trichostatin A, vegf, 2-acetylaminofluorene, rapamycin, dihydrotestosterone, poly rI:rC-RNA, hesperetin, valproic acid, asparagine, lipid, curcumin, dexamethasone, glycogen, CpG oligonucleotide, nitric oxide ETS2 oligonucleotide MINA phorbol myristate acetate, 4-hydroxytamoxifen SMARCA4 cyclic amp, cadmium, lysine, tretinoin, latex, androstane, testosterone, sucrose, tyrosine, cysteine, zinc, oligonucleotide, estrogen, steroid, trichostatin A, tpmp, progesterone, histidine, atp, trypsinogen, glucose, agar, lipid, arginine, vancomycin, dihydrofolate FAS hoechst 33342, ly294002, 2-chlorodeoxyadenosine, glutamine, cd 437, tetrodotoxin, cyclopiazonic acid, arsenic trioxide, phosphatidylserine, niflumic acid, gliadin, ionomycin, safrole oxide, methotrexate, rubitecan, cysteine, propentofylline, vegf, boswellic acids, rapamycin, pd 98,059, captopril, methamphetamine, vesnarinone, tetrapeptide, oridonin, raltitrexed, pirinixic acid, nitroprusside, H-7, beta-boswellic acid, adriamycin, concanamycin a, etoposide, trastuzumab, cyclophosphamide, ifn-alpha, tyrosine, rituximab, selenodiglutathione, chitosan, omega-N- methylarginine, creatinine, resveratrol, topotecan, genistein, trichostatin A, decitabine, thymidine, D-glucose, mifepristone, tetracycline, Sn50 peptide, poly rI:rC-RNA, actinomycin D, sp 600125, doxifluridine, agar, ascorbic acid, acetaminophen, aspirin, tamoxifen, okt3, edelfosine, sulforafan, aspartate, antide, n, n-dimethylsphingosine, epigallocatechin- gallate, N-nitro-L-arginine methyl ester, h2o2, cerulenin, sphingosine-1- phosphate, SP600125, sodium nitroprusside, glycochenodeoxycholic acid, ceramides, actinomycin d, SB203580, cyclosporin A, morphine, LY294002, n(g)-nitro-l-arginine methyl ester, 4-hydroxynonenal, piceatannol, valproic acid, beta-estradiol, 1-alpha,25-dihydroxy vitamin D3, arginine, dexamethasone, sulfadoxine, phorbol myristate acetate, beta-lapachone, nitrofurantoin, chlorambucil, methylnitronitrosoguanidine, CD 437, opiate, egcg, mitomycin C, estrogen, ribonucleic acid, fontolizumab, tanshinone iia, recombinant human endostatin, fluoride, L-triiodothyronine, bleomycin, forskolin, nonylphenol, zymosan A, vincristine, daunorubicin, prednisolone, cyclosporin a, vitamin K3, diethylstilbestrol, deoxyribonucleotide, suberoylanilide hydroxamic acid, orlistat, 3-(4,5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide, rottlerin, arachidonic acid, ibuprofen, prostaglandin E2, toremifene, depsipeptide, ochratoxin A, (glc)4, phosphatidylinositol, mitomycin c, rantes, sphingosine, indomethacin, 5fluorouracil, phosphatidylcholine, 5-fluorouracil, mg 132, thymidylate, trans-cinnamaldehyde, sterol, polyadenosine diphosphate ribose, nitric oxide, vitamin e succinate, lipopolysaccharide, cisplatin, herbimycin a, 5- aza-2deoxycytidine, proteasome inhibitor PSI, 2,5-hexanedione, epothilone B, caffeic acid phenethyl ester, glycerol 3-phosphate, tgf beta1, anisomycin, paclitaxel, gemcitabine, medroxyprogesterone acetate, hymecromone, testosterone, ag 1478, doxombicin, S-nitroso-N- acetylpenicillamine, adpribose, sulforaphane, vitamin d, annexin-v, lactate, reactive oxygen species, sb 203580, serine, N-acetyl-L-cysteine, dutp, infliximab, ethanol, curcumin, cytarabine, tpck, calyculin a, dopamine, gp 130, bromocriptine, apicidin, fatty acid, citrate, glucocorticoid, arsenite, butyrate, peplomycin, oxaliplatin, camptothecin, benzyloxycarbonyl-Leu-Leu-Leu aldehyde, clofibrate, carbon, wortmannin, fludarabine, N-(3-(aminomethyl)benzyl)acetamidine, sirolimus, peptidoglycan, c2ceramide, dihydrotestosterone, 7- aminoactinomycin d, carmustine, heparin, ceramide, paraffin, mitoxantrone, docosahexaenoic acid, vitamin a, ivig, hydrogen peroxide, 7-ethyl-10-hydroxy-camptomecin, oxygen, pydrin, bortezomib, retinoic acid, 1,4-phenylenebis(methylene)selenocyanate, teriflunomide, epinephrine, n acetylcysteine, noxa, irinotecan, oligonucleotide, d-api, rasagiline, 8-bromo-cAMP, atpo, agarose, fansidar, clobetasol propionate, teniposide, aurintricarboxylic acid, polysaccharide, CpG oligonucleotide, cycloheximide IRF1 tamoxifen, chloramphenicol, polyinosinic-polycytidylic acid, inosine monophosphate, suberoylanilide hydroxamic acid, butyrate, iron, gliadin, zinc, actinomycin d, deferoxamine, phosphatidylinositol, adenine, ornthine, rantes, calcium, 2,5-oligoadenylate, pge2, poly(i-c), indoleamine, arginine, estradiol, nitric oxide, etoposide, adriamycin, oxygen, retinoid, guanylate, troglitazone, ifn-alpha, retinoic acid, tyrosine, adenylate, am 580, guanosine, oligonucleotide, estrogen, thymidine, tetracycline, serine, sb 203580, pdtc, lipid, cycloheximide MYC cd 437, 1,25 dihydroxy vitamin d3, phenethyl isothiocyanate, threonine, arsenic trioxide, salicylic acid, quercetin, prostaglandin E1, ionomycin, 12-o-tetradecanoylphorbol 13-acetate, fulvestrant, phenylephrine, fisetin, 4-coumaric acid, dihydroartemisinin, 3-deazaadenosine, nitroprusside, pregna-4,17-diene-3,16-dione, adriamycin, bromodeoxyuridine, AGN 194204, STA-9090, isobutylmethylxanthine, potassium chloride, docetaxel, quinolinic acid, 5,6,7,8-tetrahydrobiopterin, propranolol, delta 7-pga1, topotecan, AVI-4126, trichostatin A, decitabine, thymidine, D-glucose, mifepristone, poly rI:rC-RNA, letrozole, L-threonine, 5- hydroxytryptamine, bucladesine, SB203580, 1-acetoxychavicol acetate, cyclosporin A, okadaic acid, dfmo, LY294002, hmba, piceatannol, 2,5- oligoadenylate, 4-hydroxytamoxifen, butylbenzyl phthalate, dexamethasone, ec 109, phosphatidic acid, grape seed extract, phorbol myristate acetate, coumermycin, tosylphenylalanyl chloromethyl ketone, CD 437, di(2-ethylhexyl) phthalate, butyrine, cytidine, sodium arsenite, tanshinone iia, L-triiodothyronine, niacinamide, glycogen, daunorubicin, vincristine, carvedilol, bizelesin, 3-deazaneplanocin, phorbol, neplanocin a, panobinostat, [alcl], phosphatidylinositol, U0126, dichlororibofuranosylbenzimidazole, flavopiridol, 5-fluorouracil, verapamil, cyclopamine, nitric oxide, cisplatin, hrgbeta1,5,6-dichloro-1- beta-d-ribofuranosylbenzimidazole, amsacrine, gemcitabine, aristeromycin, medroxyprogesterone acetate, gambogic acid, leucine, alpha-naphthyl acetate, cyclic AMP, reactive oxygen species, PD 180970, curcumin, chloramphenicol, A23187, crocidolite asbestos, 6- hydroxydopamine, cb 33, arsenite, gentamicin, benzyloxycarbonyl-Leu- Leu-Leu aldehyde, clofibrate, wortmannin, sirolimus, ceramide, melphalan, 3M-001, linsidomine, CP-55940, hyaluronic acid, ethionine, clonidine, retinoid, bortezomib, oligonucleotide, methyl 2-cyano-3,12- dioxoolean-1,9-dien-28-oate, tacrolimus, embelin, methyl-beta- cyclodextrin, 3M-011, folate, ly294002, PP1, hydroxyurea, aclarubicin, phenylbutyrate, PL) 0325901, methotrexate, Cd2+, prazosin, vegf, rapamycin, alanine, phenobarbital, pd 98,059, trapoxin, 4- hydroperoxycyclophosphamide, methamphetamine, s-(1,2- dichlorovinyl)-l-cysteine, aphidicolin, vesnarinone, ADI PEG20, pirinixic acid, wp631, H-7, carbon tetrachloride, bufalin, 2,2- dimethylbutyric acid, etoposide, calcitriol, trastuzumab, cyclophosphamide, harringtonine, tyrosine, N(6)-(3-iodobenzyl)-5-N- methylcarboxamidoadenosine, resveratrol, thioguanine, genistein, S- nitroso-N-acetyl-DL-penicillamine, zearalenone, lysophosphatidic acid, Sn50 peptide, roscovitine, actinomycin D, propanil, agar, tamoxifen, acetaminophen, imatinib, tretinoin, mithramycin, ATP, epigallocatechin- gallate, ferric ammonium citrate, acyclic retinoid, L-cysteine, nitroblue tetrazolium, actinomycin d, sodium nitroprusside, 1,2- dimethylhydrazine, dibutyl phthalate, ornithine, 4-hydroxynonenal, beta- estradiol, 1-alpha,25-dihydroxy vitamin D3, cyproterone acetate, nimodipine, nitrofurantoin, temsirolimus, 15-deoxy-delta-12, 14-PGJ 2, estrogen, ribonucleic acid, ciprofibrate, alpha-amanitin, SB 216763, bleomycin, forskolin, prednisolone, cyclosporin a, thyroid hormone, tunicamycin, phosphorothioate, suberoylanilide hydroxamic acid, pga2,3-(4,5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide, benzamide riboside, bisindolylmaleimide, SU6656, prostaglandin E2, depsipeptide, zidovudine, cerivastatin, progesterone, sethoxydim, indomethacin, mg 132, mezerein, pyrrolidine dithiocarbamate, vitamin e succinate, herbimycin a, 5-aza-2deoxycytidine, lipopolysaccharide, diazoxide, anisomycin, paclitaxel, sodium dodecylsulfate, nilotinib, oxysterol, doxombicin, lipofectamine, PD98059, steroid, delta-12-pgj2, serine, H-8, N-acetyl-L-cysteine, ethanol, n-(4-hydroxyphenyl)retinamide, tiazofurin, cytarabine, H89, 10-hydroxycamptothecin, everolimus, lactacystin, n(1), n(12)-bis(ethyl)spermine, silibinin, glucocorticoid, butyrate, camptothecin, triamcinolone acetonide, tocotrienol, n-ethylmaleimide, phorbol 12,13-didecanoate, thapsigargin, deferoxamine, R59949, bryostatin 1, paraffin, romidepsin, vitamin a, docosahexaenoic acid, hydrogen peroxide, droloxifene, saikosaponin, fluoxetine, retinoic acid, n acetylcysteine, dithiothreitol, cordycepin, agarose, 8-bromo-cAMP, D- galactosamine, tachyplesin i, theophylline, metoprolol, SU6657, 15- deoxy-delta-12,14-prostaglandin j2, dmso, 2-amino-5-azotoluene, cycloheximide
(84) It will be appreciated that administration of therapeutic entities in accordance with the invention will be administered with suitable carriers, excipients, and other agents that are incorporated into formulations to provide improved transfer, delivery, tolerance, and the like. A multitude of appropriate formulations can be found in the formulary known to all pharmaceutical chemists: Remington's Pharmaceutical Sciences (15th ed, Mack Publishing Company, Easton, Pa. (1975)), particularly Chapter 87 by Blaug, Seymour, therein. These formulations include, for example, powders, pastes, ointments, jellies, waxes, oils, lipids, lipid (cationic or anionic) containing vesicles (such as Lipofectin), DNA conjugates, anhydrous absorption pastes, oil-in-water and water-in-oil emulsions, emulsions carbowax (polyethylene glycols of various molecular weights), semi-solid gels, and semi-solid mixtures containing carbowax. Any of the foregoing mixtures may be appropriate in treatments and therapies in accordance with the present invention, provided that the active ingredient in the formulation is not inactivated by the formulation and the formulation is physiologically compatible and tolerable with the route of administration. See also Baldrick P. Pharmaceutical excipient development: the need for preclinical guidance. Regul. Toxicol Pharmacol. 32(2):210-8 (2000), Wang W. Lyophilization and development of solid protein pharmaceuticals. Int. J. Pharm. 203(1-2):1-60 (2000), Charman W N Lipids, lipophilic drugs, and oral drug delivery-some emerging concepts. J Pharm Sci. 89(8):967-78 (2000), Powell et al. Compendium of excipients for parenteral formulations PDA J Pharm Sci Technol. 52:238-311 (1998) and the citations therein for additional information related to formulations, excipients and carriers well known to pharmaceutical chemists.
(85) Therapeutic formulations of the invention, which include a T cell modulating agent, are used to treat or alleviate a symptom associated with an immune-related disorder or an aberrant immune response. The present invention also provides methods of treating or alleviating a symptom associated with an immune-related disorder or an aberrant immune response. A therapeutic regimen is carried out by identifying a subject, e.g., a human patient suffering from (or at risk of developing) an immune-related disorder or aberrant immune response, using standard methods. For example, T cell modulating agents are useful therapeutic tools in the treatment of autoimmune diseases and/or inflammatory disorders. In certain embodiments, the use of T cell modulating agents that modulate, e.g., inhibit, neutralize, or interfere with, Th17 T cell differentiation is contemplated for treating autoimmune diseases and/or inflammatory disorders. In certain embodiments, the use of T cell modulating agents that modulate, e.g., enhance or promote, Th17 T cell differentiation is contemplated for augmenting Th17 responses, for example, against certain pathogens and other infectious diseases. The T cell modulating agents are also useful therapeutic tools in various transplant indications, for example, to prevent, delay or otherwise mitigate transplant rejection and/or prolong survival of a transplant, as it has also been shown that in some cases of transplant rejection, Th17 cells might also play an important role. (See e.g., Abadja F, Sarraj B, Ansari M J., Significance of T helper 17 immunity in transplantation. Curr Opin Organ Transplant. 2012 February; 17(1):8-14. doi: 10.1097/MOT.0b013e32834ef4e4). The T cell modulating agents are also useful therapeutic tools in cancers and/or anti-tumor immunity, as Th17/Treg balance has also been implicated in these indications. For example, some studies have suggested that IL-23 and Th17 cells play a role in some cancers, such as, by way of non-limiting example, colorectal cancers. (See e.g., Ye J, Livergood R S, Peng G. The role and regulation of human Th17 cells in tumor immunity. Am J Pathol. 2013 January; 182(1):10-20. doi: 10.1016/j.ajpath.2012.08.041. Epub 2012 Nov. 14). The T cell modulating agents are also useful in patients who have genetic defects that exhibit aberrant Th17 cell production, for example, patients that do not produce Th17 cells naturally.
(86) The T cell modulating agents are also useful in vaccines and/or as vaccine adjuvants against autoimmune disorders, inflammatory diseases, etc. The combination of adjuvants for treatment of these types of disorders are suitable for use in combination with a wide variety of antigens from targeted self-antigens, i.e., autoantigens, involved in autoimmunity, e.g., myelin basic protein; inflammatory self-antigens, e.g., amyloid peptide protein, or transplant antigens, e.g., alloantigens. The antigen may comprise peptides or polypeptides derived from proteins, as well as fragments of any of the following: saccharides, proteins, polynucleotides or oligonucleotides, autoantigens, amyloid peptide protein, transplant antigens, allergens, or other macromolecular components. In some instances, more than one antigen is included in the antigenic composition.
(87) Autoimmune diseases include, for example, Acquired Immunodeficiency Syndrome (AIDS, which is a viral disease with an autoimmune component), alopecia areata, ankylosing spondylitis, antiphospholipid syndrome, autoimmune Addison's disease, autoimmune hemolytic anemia, autoimmune hepatitis, autoimmune inner ear disease (AIED), autoimmune lymphoproliferative syndrome (ALPS), autoimmune thrombocytopenic purpura (ATP), Behcet's disease, cardiomyopathy, celiac sprue-dermatitis herpetiformis; chronic fatigue immune dysfunction syndrome (CFIDS), chronic inflammatory demyelinating polyneuropathy (CIDP), cicatricial pemphigoid, cold agglutinin disease, crest syndrome, Crohn's disease, Degos' disease, dermatomyositis-juvenile, discoid lupus, essential mixed cryoglobulinemia, fibromyalgia-fibromyositis, Graves' disease, Guillain-Barr syndrome, Hashimoto's thyroiditis, idiopathic pulmonary fibrosis, idiopathic thrombocytopenia purpura (ITP), IgA nephropathy, insulin-dependent diabetes mellitus, juvenile chronic arthritis (Still's disease), juvenile rheumatoid arthritis, Mnire's disease, mixed connective tissue disease, multiple sclerosis, myasthenia gravis, pernicious anemia, polyarteritis nodosa, polychondritis, polyglandular syndromes, polymyalgia rheumatica, polymyositis and dermatomyositis, primary agammaglobulinemia, primary biliary cirrhosis, psoriasis, psoriatic arthritis, Raynaud's phenomena, Reiter's syndrome, rheumatic fever, rheumatoid arthritis, sarcoidosis, scleroderma (progressive systemic sclerosis (PSS), also known as systemic sclerosis (SS)), Sjgren's syndrome, stiff-man syndrome, systemic lupus erythematosus, Takayasu arteritis, temporal arteritis/giant cell arteritis, ulcerative colitis, uveitis, vitiligo and Wegener's granulomatosis.
(88) In some embodiments, T cell modulating agents are useful in treating, delaying the progression of, or otherwise ameliorating a symptom of an autoimmune disease having an inflammatory component such as an aberrant inflammatory response in a subject. In some embodiments, T cell modulating agents are useful in treating an autoimmune disease that is known to be associated with an aberrant Th17 response, e.g., aberrant IL-17 production, such as, for example, multiple sclerosis (MS), psoriasis, inflammatory bowel disease, ulcerative colitis, Crohn's disease, uveitis, lupus, ankylosing spondylitis, and rheumatoid arthritis.
(89) Inflammatory disorders include, for example, chronic and acute inflammatory disorders. Examples of inflammatory disorders include Alzheimer's disease, asthma, atopic allergy, allergy, atherosclerosis, bronchial asthma, eczema, glomerulonephritis, graft vs. host disease, hemolytic anemias, osteoarthritis, sepsis, stroke, transplantation of tissue and organs, vasculitis, diabetic retinopathy and ventilator induced lung injury.
(90) Symptoms associated with these immune-related disorders include, for example, inflammation, fever, general malaise, fever, pain, often localized to the inflamed area, rapid pulse rate, joint pain or aches (arthralgia), rapid breathing or other abnormal breathing patterns, chills, confusion, disorientation, agitation, dizziness, cough, dyspnea, pulmonary infections, cardiac failure, respiratory failure, edema, weight gain, mucopurulent relapses, cachexia, wheezing, headache, and abdominal symptoms such as, for example, abdominal pain, diarrhea or constipation.
(91) Efficaciousness of treatment is determined in association with any known method for diagnosing or treating the particular immune-related disorder. Alleviation of one or more symptoms of the immune-related disorder indicates that the T cell modulating agent confers a clinical benefit.
(92) Administration of a T cell modulating agent to a patient suffering from an immune-related disorder or aberrant immune response is considered successful if any of a variety of laboratory or clinical objectives is achieved. For example, administration of a T cell modulating agent to a patient is considered successful if one or more of the symptoms associated with the immune-related disorder or aberrant immune response is alleviated, reduced, inhibited or does not progress to a further, i.e., worse, state. Administration of T cell modulating agent to a patient is considered successful if the immune-related disorder or aberrant immune response enters remission or does not progress to a further, i.e., worse, state.
(93) A therapeutically effective amount of a T cell modulating agent relates generally to the amount needed to achieve a therapeutic objective. The amount required to be administered will furthermore depend on the specificity of the T cell modulating agent for its specific target, and will also depend on the rate at which an administered T cell modulating agent is depleted from the free volume other subject to which it is administered.
(94) T cell modulating agents can be administered for the treatment of a variety of diseases and disorders in the form of pharmaceutical compositions. Principles and considerations involved in preparing such compositions, as well as guidance in the choice of components are provided, for example, in Remington: The Science And Practice Of Pharmacy 19th ed. (Alfonso R. Gennaro, et al., editors) Mack Pub. Co., Easton, Pa.: 1995; Drug Absorption Enhancement: Concepts, Possibilities, Limitations, And Trends, Harwood Academic Publishers, Langhorne, Pa., 1994; and Peptide And Protein Drug Delivery (Advances In Parenteral Sciences, Vol. 4), 1991, M. Dekker, New York.
(95) Where polypeptide-based T cell modulating agents are used, the smallest fragment that specifically binds to the target and retains therapeutic function is preferred. Such fragments can be synthesized chemically and/or produced by recombinant DNA technology. (See, e.g., Marasco et al., Proc. Natl. Acad. Sci. USA, 90: 7889-7893 (1993)). The formulation can also contain more than one active compound as necessary for the particular indication being treated, preferably those with complementary activities that do not adversely affect each other. Alternatively, or in addition, the composition may comprise an agent that enhances its function, such as, for example, a cytotoxic agent, cytokine, chemotherapeutic agent, or growth-inhibitory agent. Such molecules are suitably present in combination in amounts that are effective for the purpose intended.
(96) All publications and patent documents cited herein are incorporated herein by reference as if each such publication or document was specifically and individually indicated to be incorporated herein by reference. Citation of publications and patent documents is not intended as an admission that any is pertinent prior art, nor does it constitute any admission as to the contents or date of the same. The invention having now been described by way of written description, those of skill in the art will recognize that the invention can be practiced in a variety of embodiments and that the foregoing description and examples below are for purposes of illustration and not limitation of the claims that follow.
(97) Although the present invention and its advantages have been described in detail, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined in the appended claims.
(98) The present invention will be further illustrated in the following Examples which are given for illustration purposes only and are not intended to limit the invention in any way.
EXAMPLES
Example 1: Materials and Methods
(99) Briefly, gene expression profiles were measured at 18 time points (0.5 hr to 72 days) under Th17 conditions (IL-6, TGF-1) or control (Th0) using Affymetrix microarrays HT_MG-430A. Differentially expressed genes were detected using a consensus over four inference methods, and cluster the genes using k-means, with an automatically derived k. Temporal regulatory interactions were inferred by looking for significant (p<5*10.sup.5 and fold enrichment>1.5) overlaps between the regulator's putative targets (e.g., based on ChIPseq) and the target gene's cluster (using four clustering schemes). Candidates for perturbation were ordered lexicographically using network-based and expression-based features. Perturbations were done using SiNW for siRNA delivery. These methods are described in more detail below.
(100) Mice:
(101) C57BL/6 wild-type (wt), Mt.sup./, Irf1.sup./, Fas.sup./, Irf4.sup./, and Cd4.sup.Cre mice were obtained from Jackson Laboratory (Bar Harbor, Me.). Stat1.sup./ and 129/Sv control mice were purchased from Taconic (Hudson, N.Y.). IL-12r.sup./ mice were provided by Dr. Pahan Kalipada from Rush University Medical Center. IL-17Ra.sup./ mice were provided by Dr. Jay Kolls from Louisiana State University/University of Pittsburgh. Irf8.sup.fl/fl mice were provided by Dr. Keiko Ozato from the National Institute of Health. Both Irf4.sup.fl/fl and Irf8.sup.fl/fl mice were crossed to Cd4.sup.Cre mice to generate Cd4.sup.CrexIrf4.sup.fl/fl and Cd4.sup.CrexIrf8.sup.fl/fl mice. All animals were housed and maintained in a conventional pathogen-free facility at the Harvard Institute of Medicine in Boston, Mass. (IACUC protocols: 0311-031-14 (VKK) and 0609-058015 (AR)). All experiments were performed in accordance to the guidelines outlined by the Harvard Medical Area Standing Committee on Animals at the Harvard Medical School (Boston, Mass.). In addition, spleens from Mina.sup./ mice were provided by Dr. Mark Bix from St. Jude Children's Research Hospital (IACUC Protocol: 453). Pou2af1.sup./ mice were obtained from the laboratory of Dr. Robert Roeder (Kim, U. et al. The B-cell-specific transcription coactivator OCA-B/OBF-1/Bob-1 is essential for normal production of immunoglobulin isotypes. Nature 383, 542-547, doi:10.1038/383542a0 (1996)). Wild-type and Oct1.sup./ fetal livers were obtained at day E12.5 and transplanted into sub-lethally irradiated Rag1.sup./ mice as previously described (Wang, V. E., Tantin, D., Chen, J. & Sharp, P. A. B cell development and immunoglobulin transcription in Oct-1-deficient mice. Proc. Natl. Acad. Sci. U.S.A. 101, 2005-2010, doi:10.1073/pnas.0307304101 (2004)) (IACUC Protocol: 11-09003).
(102) Cell Sorting and In Vitro T-Cell Differentiation in Petri Dishes:
(103) Cd4+ T cells were purified from spleen and lymph nodes using anti-CD4 microbeads (Miltenyi Biotec) then stained in PBS with 1% FCS for 20 min at room temperature with anti-Cd4-PerCP, anti-Cd621-APC, and anti-Cd44-PE antibodies (all Biolegend, Calif.).
(104) Nave Cd4.sup.+ Cd621.sup.high Cd44.sup.low T cells were sorted using the BD FACSAria cell sorter. Sorted cells were activated with plate bound anti-Cd3 (2 g/ml) and anti-Cd28 (2 g/ml) in the presence of cytokines. For Th17 differentiation: 2 ng/mL rhTGF-1 (Miltenyi Biotec), 25 ng/mL mill-6 (Miltenyi Biotec), 20 ng/ml mill-23 (Miltenyi Biotec), and 20 ng/ml rmIL-1 (Miltenyi Biotec). Cells were cultured for 0.5-72 hours and harvested for RNA, intracellular cytokine staining, and flow cytometry.
(105) Flow Cytometry and Intracellular Cytokine Staining (ICC):
(106) Sorted nave T cells were stimulated with phorbol 12-myristate 13-acetate (PMA) (50 ng/ml, Sigma-aldrich, MO), ionomycin (1 g/ml, Sigma-aldrich, MO) and a protein transport inhibitor containing monensin (Golgistop) (BD Biosciences) for four hours prior to detection by staining with antibodies. Surface markers were stained in PBS with 1% FCS for 20 min at room temperature, then subsequently the cells were fixed in Cytoperm/Cytofix (BD Biosciences), permeabilized with Perm/Wash Buffer (BD Biosciences) and stained with Biolegend conjugated antibodies, i.e. Brilliant Violet 650 anti-mouse IFN- (XMG1.2) and allophycocyanin-anti-IL-17A (TC11-18H10.1), diluted in Perm/Wash buffer as described (Bettelli, E. et al. Reciprocal developmental pathways for the generation of pathogenic effector TH17 and regulatory T cells. Nature 441, 235-238 (2006)) (
(107) Quantification of Cytokine Secretion Using Enzyme-Linked Immunosorbent Assay (ELISA):
(108) Nave T cells from knockout mice and their wild type controls were cultured as described above, their supernatants were collected after 72 h, and cytokine concentrations were determined by ELISA (antibodies for IL-17 and IL-10 from BD Bioscience) or by cytometric bead array for the indicated cytokines (BD Bioscience), according to the manufacturers' instructions (
(109) Microarray Data:
(110) Nave T cells were isolated from WT mice, and treated with IL-6 and TGF-1. Affymetrix microarrays HT_MG-430A were used to measure the resulting mRNA levels at 18 different time points (0.5-72 h;
(111) Detecting Differentially Expressed Genes:
(112) Differentially expressed genes (comparing to the Th0 control) were found using four methods: (1) Fold change. Requiring a 2-fold change (up or down) during at least two time points. (2) Polynomial fit. The EDGE software (Storey, J., Xiao, W., Leek, J., Tompkins, R. & Davis, R. in Proc. Natl. Acad. Sci. U.S.A. vol. 102 12837 (2005); Leek, J. T., Monsen, E., Dabney, A. R. & Storey, J. D. EDGE: extraction and analysis of differential gene expression. Bioinformatics 22, 507-508, doi:10.1093/bioinformatics/btk005 (2006)), designed to identify differential expression in time course data, was used with a threshold of q-value0.01. (3) Sigmoidal fit. An algorithm similar to EDGE while replacing the polynomials with a sigmoid function, which is often more adequate for modeling time course gene expression data (Chechik, G. & Koller, D. Timing of gene expression responses to environmental changes. J Comput Biol 16, 279-290, doi:10.1089/cmb.2008.13TT10.1089/cmb.2008.13TT [pii] (2009)), was used. A threshold of q-value0.01. (4) ANOVA was used. Gene expression is modeled by: time (using only time points for which there was more than one replicate) and treatment (TGF-1+IL-6 or Th0). The model takes into account each variable independently, as well as their interaction. Cases in which the p-value assigned with the treatment parameter or the interaction parameter passed an FDR threshold of 0.01 were reported.
(113) Overall, substantial overlap between the methods (average of 82% between any pair of methods) observed. The differential expression score of a gene was defined as the number of tests that detected it. As differentially expressed genes, cases with differential expression score>3 were reported.
(114) For the Il23r.sup./ time course (compared to the WT T cells) methods 1.3 (above) were used. Here, a fold change cutoff of 1.5 was used, and genes detected by at least two tests were reported.
(115) Clustering:
(116) several ways for grouping the differentially expressed genes were considered, based on their time course expression data: (1) For each time point, two groups were defined: (a) all the genes that are over-expressed and (b) all the genes that are under-expressed relative to Th0 cells (see below); (2) For each time point, two groups were defined: (a) all the genes that are induced and (b) all the genes that are repressed, comparing to the previous time point; (3) K-means clustering using only the Th17 polarizing conditions. The minimal k was used, such that the within-cluster similarity (average Pearson correlation with the cluster's centroid) was higher than 0.75 for all clusters; and, (4) K-means clustering using a concatenation of the Th0 and Th17 profiles.
(117) For methods (1, 2), to decide whether to include a gene, its original mRNA expression profiles (Th0, Th17), and their approximations as sigmoidal functions (Chechik, G. & Koller, D. Timing of gene expression responses to environmental changes. J Comput Biol 16, 279-290, doi:10.1089/cmb.2008.13TT10.1089/cmb.2008.13TT [pii] (2009)) (thus filtering transient fluctuations) were considered. The fold change levels (compared to Th0 (method 1) or to the previous time point (method 2)) were required to pass a cutoff defined as the minimum of the following three values: (1) 1.7; (2) mean+std of the histogram of fold changes across all time points; or (3) the maximum fold change across all time points. The clusters presented in
(118) Regulatory Network Inference:
(119) potential regulators of Th17 differentiation were identified by computing overlaps between their putative targets and sets of differentially expressed genes grouped according to methods 1-4 above. regulator-target associations from several sources were assembled: (1) in vivo DNA binding profiles (typically measured in other cells) of 298 transcriptional regulators (Linhart, C., Halperin, Y. & Shamir, R. Transcription factor and microRNA motif discovery: the Amadeus platform and a compendium of metazoan target sets. Genome research 18, 1180-1189, doi:10.1101/gr.076117.108 (2008); Zheng, G. et al. ITFP: an integrated platform of mammalian transcription factors. Bioinformatics 24, 2416-2417, doi:10.1093/bioinformatics/btn439 (2008); Wilson, N. K. et al. Combinatorial transcriptional control in blood stem/progenitor cells: genome-wide analysis of ten major transcriptional regulators. Cell Stem Cell 7, 532-544, doi:S1934-5909(10)00440-6 [pii]10.1016/j.stem.2010.07.016 (2010); Lachmann, A. et al. in Bioinformatics Vol. 26 2438-2444 (2010); Liberzon, A. et al. Molecular signatures database (MSigDB) 3.0. Bioinformatics 27, 1739-1740, doi:10.1093/bioinformatics/btr260 (2011); Jiang, C., Xuan, Z., Zhao, F. & Zhang, M. TRED: a transcriptional regulatory element database, new entries and other development. Nucleic Acids Res 35, D137-140 (2007)); (2) transcriptional responses to the knockout of 11 regulatory proteins (Awasthi et al., J. Immunol 2009; Schraml, B. U. et al. The AP-1 transcription factor Batf controls T(H)17 differentiation. Nature 460, 405-409, doi:nature08114 [pii]10.1038/nature08114 (2009); Shi, L. Z. et al. HIF1alpha-dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of TH17 and Treg cells. The Journal of experimental medicine 208, 1367-1376, doi:10.1084/jem.20110278 (2011); Yang, X. P. et al. Opposing regulation of the locus encoding IL-17 through direct, reciprocal actions of STAT3 and STAT5. Nature immunology 12, 247-254, doi:10.1038/ni.1995 (2011); Durant, L. et al. Diverse Targets of the Transcription Factor STAT3 Contribute to T Cell Pathogenicity and Homeostasis. Immunity 32, 605-615, doi:10.1016/j.immuni.2010.05.003 (2010); Jux, B., Kadow, S. & Esser, C. Langerhans cell maturation and contact hypersensitivity are impaired in aryl hydrocarbon receptor-null mice. Journal of immunology (Baltimore, Md.: 1950) 182, 6709-6717, doi:10.4049/jimmuno1.0713344 (2009); Amit, I. et al. Unbiased reconstruction of a mammalian transcriptional network mediating pathogen responses. Science 326, 257-263, doi:10.1126/science.1179050 (2009); Xiao, S. et al. Retinoic acid increases Foxp3+ regulatory T cells and inhibits development of Th17 cells by enhancing TGF-beta-driven Smad3 signaling and inhibiting IL-6 and IL-23 receptor expression. J Immunol 181, 2277-2284, doi:181/4/2277 [pii] (2008)); (3) additional potential interactions obtained by applying the Ontogenet algorithm (Jojic et al., under review; regulatory model available at: to data from the mouse ImmGen consortium (January 2010 release (Heng, T. S. & Painter, M. W. The Immunological Genome Project: networks of gene expression in immune cells. Nature immunology 9, 1091-1094, doi:10.1038/ni1008-1091 (2008)), which includes 484 microarray samples from 159 cell subsets from the innate and adaptive immune system of mice; (4) a statistical analysis of cis-regulatory element enrichment in promoter regions (Elkon, R., Linhart, C., Sharan, R., Shamir, R. & Shiloh, Y. in Genome Research Vol. 13 773-780 (2003); Odabasioglu, A., Celik, M. & Pileggi, L. T. in Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design 58-65 (IEEE Computer Society, San Jose, Calif., United States, 1997)); and, (5) the TF enrichment module of the IPA software. For every TF in the database, the statistical significance of the overlap between its putative targets and each of the groups defined above using a Fisher's exact test was computed. Cases where p<5*10.sup.5 and the fold enrichment>1.5 were included.
(120) Each edge in the regulatory network was assigned a time stamp based on the expression profiles of its respective regulator and target nodes. For the target node, the time points at which a gene was either differentially expressed or significantly induced or repressed with respect to the previous time point (similarly to grouping methods 1 and 2 above) were considered. A regulator node was defined as absent at a given time point if: (i) it was under expressed compared to Th0; or (ii) the expression is low (<20% of the maximum value in time) and the gene was not over-expressed compared to Th0; or, (iii) up to this point in time the gene was not expressed above a minimal expression value of 100. As an additional constraint, protein expression levels were estimated using the model from Schwanhusser, B. et al. (Global quantification of mammalian gene expression control. Nature 473, 337-342, doi:10.1038/nature10098 (2011)) and using a sigmoidal fit (Chechik & Koller, J Comput Biol 2009) for a continuous representation of the temporal expression profiles, and the ProtParam software (Wilkins, M. R. et al. Protein identification and analysis tools in the ExPASy server. Methods Mol. Biol. 112, 531-552 (1999)) for estimating protein half-lives. It was required that, in a given time point, the predicted protein level be no less than 1.7 fold below the maximum value attained during the time course, and not be less than 1.7 fold below the Th0 levels. The timing assigned to edges inferred based on a time-point specific grouping (grouping methods 1 and 2 above) was limited to that specific time point. For instance, if an edge was inferred based on enrichment in the set of genes induced at 1 hr (grouping method #2), it will be assigned a 1 hr time stamp. This same edge could then only have additional time stamps if it was revealed by additional tests.
(121) Selection of Nanostring Signature Genes:
(122) The selection of the 275-gene signature (Table 1) combined several criteria to reflect as many aspect of the differentiation program as was possible. The following requirements were defined: (1) the signature must include all of the TFs that belong to a Th17 microarray signature (comparing to other CD4+ T cells (Wei et al., in Immunity vol. 30 155-167 (2009)), see Methods described herein); that are included as regulators in the network and have a differential expression score>1; or that are strongly differentially expressed (differential expression score=4); (2) it must include at least 10 representatives from each cluster of genes that have similar expression profiles (using clustering method (4) above); (3) it must contain at least 5 representatives from the predicted targets of each TF in the different networks; (4) it must include a minimal number of representatives from each enriched Gene Ontology (GO) category (computed across all differentially expressed genes); and, (5) it must include a manually assembled list of 100 genes that are related to the differentiation process, including the differentially expressed cytokines, receptor molecules and other cell surface molecules. Since these different criteria might generate substantial overlaps, a set-cover algorithm was used to find the smallest subset of genes that satisfies all of five conditions. To this list 18 genes whose expression showed no change (in time or between treatments) in the microarray data were added.
(123) The 85-gene signature (used for the Fluidigm BioMark qPCR assay) is a subset of the 275-gene signature, selected to include all the key regulators and cytokines discussed. To this list 10 control genes (2900064A13RIK, API5, CAND1, CSNK1A1, EIF3E, EIF3H, FIP1L1, GOLGA3, HSBP1, KHDRBS1, MED24, MKLN1, PCBP2, SLC6A6, SUFU, TMED7, UBE3A, ZFP410) were added.
(124) Selection of Perturbation Targets:
(125) an unbiased approach was used to rank candidate regulatorstranscription factor or chromatin modifier genesof Th17 differentiation. The ranking was based on the following features: (a) whether the gene encoding the regulator belonged to the Th17 microarray signature (comparing to other CD4+ T cells (Wei et al., in Immunity vol. 30 155-167 (2009)), see Methods described herein); (b) whether the regulator was predicted to target key Th17 molecules (IL-17, IL-21, IL23r, and ROR-t); (c) whether the regulator was detected based on both perturbation and physical binding data from the IPA software; (d) whether the regulator was included in the network using a cutoff of at least 10 target genes; (e) whether the gene encoding for the regulator was significantly induced in the Th17 time course. Only cases where the induction happened after 4 hours were considered to exclude non-specific hits; (0 whether the gene encoding the regulator was differentially expressed in response to Th17-related perturbations in previous studies. For this criterion, a database of transcriptional effects in perturbed Th17 cells was assembled, including: knockouts of Batf (Schraml et al., Nature 2009), ROR-t (Xiao et al., unpublished), Hif1a (Shi et al., J. Exp. Med. (2011)), Stat3 and Stat5 (Yang et al., Nature Immunol (2011); Durant, L. et al. in Immunity Vol. 32 605-615 (2010), Tbx21 (Awasthi et al., unpublished), IL23r (this study), and Ahr (Jux et al., J. Immunol 2009)). Data from the Th17 response to Digoxin (Huh, J. R. et al. Digoxin and its derivatives suppress TH17 cell differentiation by antagonizing RORgammat activity. Nature 472, 486-490, doi:10.1038/nature09978 (2011)) and Halofuginone (Sundrud, M. S. et al. Halofuginone inhibits TH17 cell differentiation by activating the amino acid starvation response. Science (New York, N.Y.) 324, 1334-1338, doi:10.1126/science.1172638 (2009)), as well as information on direct binding by ROR-t as inferred from ChIP-seq data (Xiao et al., unpublished) was also included. The analysis of the published expression data sets is described in the Methods described herein. For each regulator, the number of conditions in which it came up as a significant hit (up/down-regulated or bound) was counted; for regulators with 2 to 3 hits (quantiles 3 to 7 out of 10 bins), a score of 1 was then assign; for regulators with more than 3 hits (quantiles 8-10), a score of 2 (a score of 0 is assigned otherwise) was assigned; and, (g) the differential expression score of the gene in the Th17 time course.
(126) The regulators were ordered lexicographically by the above features according to the order: a, b, c, d, (sum of e and f), gthat is, first sort according to a then break ties according to b, and so on. Genes that are not over-expressed during at least one time point were excluded. As an exception, predicted regulators (feature d) that had additional external validation (feature 0 were retained. To validate this ranking, a supervised test was used: 74 regulators that were previously associated with Th17 differentiation were manually annotated. All of the features are highly specific for these regulators (p<10.sup.3). Moreover, using a supervised learning method (Nave Bayes), the features provided good predictive ability for the annotated regulators (accuracy of 71%, using 5-fold cross validation), and the resulting ranking was highly correlated with the unsupervised lexicographic ordering (Spearman correlation>0.86).
(127) This strategy was adapted for ranking protein receptors. To this end, feature c was excluded and the remaining protein-level features (b and d) were replaced with the following definitions: (b) whether the respective ligand is induced during the Th17 time course; and, (d) whether the receptor was included as a target in the network using a cutoff of at least 5 targeting transcriptional regulators.
(128) Gene Knockdown Using Silicon Nanowires:
(129) 44 mm silicon nanowire (NW) substrates were prepared and coated with 3 L of a 50 M pool of four siGENOME siRNAs (Dharmacon) in 96 well tissue culture plates, as previously described (Shalek, A. K. et al. Vertical silicon nanowires as a universal platform for delivering biomolecules into living cells. Proceedings of the National Academy of Sciences of the United States of America 107, 1870-1875, doi:10.1073/pnas.0909350107 (2010)). Briefly, 150,000 nave T cells were seeded on siRNA-laced NWs in 10 L of complete media and placed in a cell culture incubator (37 C., 5% CO.sub.2) to settle for 45 minutes before full media addition. These samples were left undisturbed for 24 hours to allow target transcript knockdown. Afterward, siRNA-transfected T cells were activated with aCd3/Cd28 dynabeads (Invitrogen), according to the manufacturer's recommendations, under Th17 polarization conditions (TGF-1 & IL-6, as above). 10 or 48 hr post-activation, culture media was removed from each well and samples were gently washed with 100 L of PBS before being lysed in 20 L of buffer TCL (Qiagen) supplemented with 2-mercaptoethanol (1:100 by volume). After mRNA was harvested in Turbocapture plates (Qiagen) and converted to cDNA using Sensiscript RT enzyme (Qiagen), qRT-PCR was used to validate both knockdown levels and phenotypic changes relative to 8-12 non-targeting siRNA control samples, as previously described (Chevrier, N. et al. Systematic discovery of TLR signaling components delineates viral-sensing circuits. Cell 147, 853-867, doi:10.1016/j.cell.2011.10.022 (2011)). A 60% reduction in target mRNA was used as the knockdown threshold. In each knockdown experiment, each individual siRNA pool was run in quadruplicate; each siRNA was tested in at least three separate experiments (
(130) mRNA Measurements in Perturbation Assays:
(131) the nCounter system, presented in full in Geiss et al. (Geiss, G. K. et al. Direct multiplexed measurement of gene expression with color-coded probe pairs. SI. Nature Biotechnology 26, 317-325, doi:10.1038/nbt1385 (2008)), was used to measure a custom CodeSet constructed to detect a total of 293 genes, selected as described above. The Fluidigm BioMark HD system was also used to measure a smaller set of 96 genes. Finally, RNA-Seq was used to follow up and validate 12 of the perturbations.
(132) A custom CodeSet constructed to detect a total of 293 genes, selected as described above, including 18 control genes whose expression remain unaffected during the time course was used. Given the scarcity of input mRNA derived from each NW knockdown, a Nanostring-CodeSet specific, 14 cycle Specific Target Amplification (STA) protocol was performed according to the manufacturer's recommendations by adding 5 L of TaqMan PreAmp Master Mix (Invitrogen) and 1 L of pooled mixed primers (500 nM each, see Table S6.1 for primer sequences) to 5 L of cDNA from a validated knockdown. After amplification, 5 L of the amplified cDNA product was melted at 95 C. for 2 minutes, snap cooled on ice, and then hybridized with the CodeSet at 65 C. for 16 hours. Finally, the hybridized samples were loaded into the nCounter prep station and product counts were quantified using the nCounter Digital Analyzer following the manufacturer's instructions. Samples that were too concentrated after amplification were diluted and rerun. Serial dilutions (1:1, 1:4, 1:16, & 1:64, pre-STA) of whole spleen and Th17 polarized cDNAs were used to both control for the effects of different amounts of starting input material and check for biases in sample amplification.
(133) Nanostring nCounter Data Analysis:
(134) For each sample, the count values were divided by the sum of counts that were assigned to a set of control genes that showed no change (in time or between treatments) in the microarray data (18 genes altogether). For each condition, a change fold ratio was computed, comparing to at least three different control samples treated with non-targeting (NT) siRNAs. The results of all pairwise comparisons (i.e. AB pairs for A repeats of the condition and B control (NT) samples) were then pooled together: a substantial fold change (above a threshold value t) in the same direction (up/down regulation) in more than half of the pairwise comparisons was required. The threshold t was determined as max {d1, d2}, where d1 is the mean+std in the absolute log fold change between all pairs of matching NT samples (i.e., form the same batch and the same time point; d1=1.66), and where d2 is the mean+1.645 times the standard deviation in the absolute log fold change shown by the 18 control genes (determined separately for every comparison by taking all the 18AB values; corresponding to p=0.05, under assumption of normality). All pairwise comparisons in which both NT and knockdown samples had low counts before normalization (<100) were ignored.
(135) A permutation test was used to evaluate the overlap between the predicted network model (
P=(1+# randomized datasets with equal of better F-score)/(1+# randomized datasets)
(136) mRNA Measurements on the Fluidigm BioMark HD:
(137) cDNA from validated knockdowns was prepared for quantification on the Fluidigm BioMark HD. Briefly, 5 L of TaqMan PreAmp Master Mix (Invitrogen), 1 L of pooled mixed primers (500 nM each, see Table S6.1 for primers), and 1.5 L of water were added to 2.5 L of knockdown validated cDNA and 14 cycles of STA were performed according to the manufacturer's recommendations. After the STA, an Exonuclease I digestion (New England Biosystems) was performed to remove unincorporated primers by adding 0.8 L Exonuclease I, 0.4 L Exonuclease I Reaction Buffer and 2.8 L water to each sample, followed by vortexing, centrifuging and heating the sample to 37 C. for 30 minutes. After a 15 minute 80 C. heat inactivation, the amplified sample was diluted 1:5 in Buffer TE. Amplified validated knockdowns and whole spleen and Th17 serial dilution controls (1:1, 1:4, 1:16, & 1:64, pre-STA) were then analyzed using EvaGreen and 9696 gene expression chips (Fluidigm BioMark HD) (Dalerba, P. et al. Single-cell dissection of transcriptional heterogeneity in human colon tumors. Nat Biotechnol 29, 1120-1127, doi:10.1038/nbt.2038 (2011)).
(138) Fluidigm Data Analysis:
(139) For each sample, the Ct values were subtracted from the geometric mean of the Ct values assigned to a set of four housekeeping genes. For each condition, a fold change ratio was computed, comparing to at least three different control samples treated with non-targeting (NT) siRNAs. The results of all pairwise comparisons (i.e. AB pairs for A repeats of the condition and B control (NT) samples) were then pooled together: a substantial difference between the normalized Ct values (above a threshold value) in the same direction (up/down regulation) in more than half of the pairwise comparisons was required. The threshold t was determined as max {log 2(1.5), d1(b), d2}, where d1(b) is the mean+std in the delta between all pairs of matching NT samples (i.e., from the same batch and the same time point), over all genes in expression quantile b (1<=b<=10). d2 is the mean+1.645 times the standard deviation in the deltas shown by 10 control genes (the 4 housekeeping genes plus 6 control genes from the Nanostring signature); d2 is determined separately for each comparison by taking all the 10AB values; corresponding to p=0.05, under assumption of normality). All pairwise comparisons in which both NT and knockdown samples had low counts before normalization (Ct<21 (taking into account the amplification, this cutoff corresponds to a conventional Ct cutoff of 35)) were ignored.
(140) mRNA Measurements Using RNA-Seq:
(141) Validated single stranded cDNAs from the NW-mediated knockdowns were converted to double stranded DNA using the NEBNext mRNA Second Strand Synthesis Module (New England BioLabs) according to the manufacturer's recommendations. The samples were then cleaned using 0.9SPRI beads (Beckman Coulter). Libraries were prepared using the Nextera XT DNA Sample Prep Kit (Illumina), quantified, pooled, and then sequenced on the HiSeq 2500 (Illumina) to an average depth 20M reads.
(142) RNA-Seq Data Analysis:
(143) a Bowtie index based on the UCSC known Gene transcriptome (Fujita, P. A. et al. The UCSC Genome Browser database: update 2011. Nucleic Acids Res. 39, D876-882, doi:10.1093/nar/gkq963 (2011)) was created, and paired-end reads were aligned directly to this index using Bowtie (Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10, R25, doi:10.1186/gb-2009-10-3-r25 (2009)). Next, RSEM v1.11 (Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12, 323, doi:10.1186/1471-2105-12-323 (2011)) was ran with default parameters on these alignments to estimate expression levels. RSEM's gene level expression estimates (tau) were multiplied by 1,000,000 to obtain transcript per million (TPM) estimates for each gene. Quantile normalization was used to further normalize the TPM values within each batch of samples. For each condition, a fold change ratio was computed, comparing to at least two different control samples treated with nontargeting (NT) siRNAs. The results of all pairwise comparisons (i.e. AB pairs for A repeats of the condition and B control (NT) samples) were then pooled together: a significant difference between the TPM values in the same direction (up/down regulation) in more than half of the pairwise comparisons was required. The significance cutoff t was determined as max {log 2(1.5), d1(b)}, where d1(b) is the mean+1.645*std in the log fold ratio between all pairs of matching NT samples (i.e., from the same batch and the same time point), over all genes in expression quantile b (1<=b<=20). All pairwise comparisons in which both NT and knockdown samples had low counts (TPM<10) were ignored. To avoid spurious fold levels due to low expression values a small constant, set to the value of the 1st quantile (out of 10) of all TPM values in the respective batch, was add to the expression values.
(144) A hypergeometric test was used to evaluate the overlap between the predicted network model (
(145) Profiling Tsc22d3 DNA Binding Using ChIP-Seq:
(146) ChIP-seq for Tsc22d3 was performed as previously described (Ram, O. et al. Combinatorial Patterning of Chromatin Regulators Uncovered by Genome-wide Location Analysis in Human Cells. Cell 147, 1628-1639 (2011)) using an antibody from Abcam. The analysis of this data was performed as previously described (Ram, O. et al. Combinatorial Patterning of Chromatin Regulators Uncovered by Genome-wide Location Analysis in Human Cells. Cell 147, 1628-1639 (2011)) and is detailed in the Methods described herein.
(147) Analysis of Tsc22d3 ChIP-Seq Data:
(148) ChIP-seq reads were aligned to the NCBI Build 37 (UCSC mm9) of the mouse genome using Bowtie (Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. in Genome Biol Vol. 10 R25 (2009)). Enriched binding regions (peaks) were detected using MACS (Zhang, Y. et al. in Genome Biol Vol. 9 R137 (2008)) with a pvalue cutoff of 10.sup.8. A peak was associated with a gene if it falls in proximity to its 5 end (10 kb upstream and 1 kb downstream from transcription start site) or within the gene's body. The RefSeq transcript annotations for gene's coordinates were used.
(149) The overlap of ChIP-seq peaks with annotated genomic regions was assessed. It was determined that a region A overlap with a peak B if A is within a distance of 50 bp from B's summit (as determined by MACS). The regions used included: (i) regulatory features annotations from the Ensemble database (Flicek, P. et al. Ensembl 2011. Nucleic Acids Res. 39, D800-806, doi:10.1093/nar/gkq1064 (2011)); (ii) regulatory 21 features found by the Oregano algorithm (Smith, R. L. et al. Polymorphisms in the IL-12beta and IL-23R genes are associated with psoriasis of early onset in a UK cohort. J Invest Dermatol 128, 1325-1327, doi:5701140 [pii] 10.1038/sj.jid.5701140 (2008)); (iii) conserved regions annotated by the multiz30way algorithm (here regions with multiz30way score>0.7 were considered); (iv) repeat regions annotated by RepeatMasker; (v) putative promoter regionstaking 10 kb upstream and 1 kb downstream of transcripts annotated in RefSeq (Pruitt, K. D., Tatusova, T. & Maglott, D. R. NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 35, D61-65, doi:10.1093/nar/gk1842 (2007)); (vi) gene body annotations in RefSeq; (vii) 3 proximal regions (taking 1 kb upstream and 5 kb downstream to 3 end); (viii) regions enriched in histone marks H3K4me3 and H3K27me3 in Th17 cells (Wei, G. et al. in Immunity Vol. 30 155-167 (2009)); (ix) regions enriched in binding of Stat3 and Stat5 (Yang, X. P. et al. Opposing regulation of the locus encoding IL-17 through direct, reciprocal actions of STAT3 and STAT5. Nat. Immunol. 12, 247-254, doi:10.1038/ni.1995 (2011)), Irf4 and Batf (Glasmacher, E. et al. A Genomic Regulatory Element That Directs Assembly and Function of Immune-Specific AP-1-IRF Complexes. Science, doi:10.1126/science.1228309 (2012)), and RORt (Xiao et al unpublished) in Th17 cells, and Foxp3 in iTreg (Xiao et al., unpublished).
(150) For each set of peaks x and each set of genomic regions y, a binomial pvalue was used to assess their overlap in the genome as described in Mclean, C. Y. et al. in Nature biotechnology Vol. 28 nbt.1630-1639 (2010). The number of hits is defined as the number of x peaks that overlap with y. The background probability in sets (i)-(vii) is set to the overall length of the region (in bp) divided by the overall length of the genome. The background probability in sets (viii)-(ix) is set to the overall length of the region divided by the overall length of annotated genomic regions: this includes annotated regulatory regions (as defined in sets i, and ii), regions annotated as proximal to genes (using the definitions from set v-vii), carry a histone mark in Th17 cells (using the definition from set viii), or bound by transcription regulators in Th17 cells (using the definitions from set ix).
(151) For the transcription regulators (set ix), an additional gene-level test was also included: here the overlap between the set of bound genes using a hypergeometric p-value was evaluated. A similar test was used to evaluate the overlap between the bound genes and genes that are differentially expressed in Tsc22d3 knockdown.
(152) The analysis was repeated with a second peak-calling software (Scripture) (Guttman, M. et al. in Nature biotechnology Vol. 28 503-510 (2010); Garber, M. et al. A High-Throughput Chromatin Immunoprecipitation Approach Reveals Principles of Dynamic Gene Regulation in Mammals. Molecular cell, doi:10.1016/j.molcel.2012.07.030 (2012)), and obtained consistent results in all the above tests. Specifically, similar levels of overlap with the Th17 factors tested, both in terms of co-occupied binding sites and in terms of common target genes, was seen.
(153) Estimating Statistical Significance of Monochromatic Interactions Between Modules:
(154) The functional network in
(155) Using Literature Microarray Data for Deriving a Th17 Signature and for Identifying Genes Responsive to Th17-Related Perturbations:
(156) To define the Th17 signatures genes, the gene expression data from Wei et al., in Immunity, vol. 30 155-167 (2009) was downloaded and analyzed, and the data was preprocessed using the RMA algorithm, followed by quantile normalization using the default parameters in the ExpressionFileCreator module of the 23 GenePattern suite (Reich, M. et al. GenePattern 2.0. Nat. Genet. 38, 500-501, doi:10.1038/ng0506-500 (2006)). This data includes replicate microarray measurements from Th17, Th1, Th2, iTreg, nTreg, and Nave CD4+ T cells. For each gene, it was evaluated whether it is over-expressed in Th17 cells compared to all other cell subsets using a one-sided t-test. All cases that had a p-value<0.05 were retained. As an additional filtering step, it was required that the expression level of a gene in Th17 cells be at least 1.25 fold higher than its expression in all other cell subsets. To avoid spurious fold levels due to low expression values, a small constant (c=50) was added to the expression values.
(157) To define genes responsive to published Th17-related perturbations, gene expression data from several sources that provided transcriptional profiles of Th17 cells under various conditions (listed above) were downloaded and analyzed. These datasets were preprocessed as above. To find genes that were differentially expressed in a given condition (compared to their respective control), the fold change between the expression levels of each probeset in the case and control conditions was computed. To avoid spurious fold levels due to low expression values, a small constant as above was added to the expression values. Only cases where more than 50% of all of the possible case-control comparisons were above a cutoff of 1.5 fold change were reported. As an additional filter, when duplicates are available, a Z-score was computed as above and only cases with a corresponding p-value<0.05 were reported.
(158) Genes:
(159) The abbreviations set forth below in Table 11 are used herein to identify the genes used throughout the disclosure, including but not limited to those shown in Tables 1-9 of the specification.
(160) TABLE-US-00011 TABLE 11 Gene Abbreviations, Entrez ID Numbers and Brief Description Symbol Entrez ID Description AAK1 22848 AP2 associated kinase 1 ABCG2 9429 ATP-binding cassette, sub-family G (WHITE), member 2 ACP5 54 acid phosphatase 5, tartrate resistant ACVR1B 91 activin A receptor, type 1B ACVR2A 92 activin receptor IIA ADAM10 102 a disintegrin and metallopeptidase domain 10 ADAM17 6868 a disintegrin and metallopeptidase domain 17 ADRBK1 156 adrenergic receptor kinase, beta 1 AES 166 amino-terminal enhancer of split AHR 196 aryl-hydrocarbon receptor AIM1 202 absent in melanoma 1 AKT1 207 thymoma viral proto-oncogene 1 ALPK2 115701 alpha-kinase 2 ANKHD1 54882 ankyrin repeat and KH domain containing 1 ANP32A 8125 acidic (leucine-rich) nuclear phosphoprotein 32 family, member A ANXA4 307 annexin A4 AQP3 360 aquaporin 3 ARHGEF3 50650 Rho guanine nucleotide exchange factor (GEF) 3 ARID3A 1820 AT rich interactive domain 3A (BRIGHT-like) ARID5A 10865 AT rich interactive domain 5A (MRF1-like) ARL5A 26225 ADP-ribosylation factor-like 5A ARMCX2 9823 armadillo repeat containing, X-linked 2 ARNTL 406 aryl hydrocarbon receptor nuclear translocator-like ASXL1 171023 additional sex combs like 1 (Drosophila) ATF2 1386 activating transcription factor 2 ATF3 467 activating transcription factor 3 ATF4 468 activating transcription factor 4 AURKB 9212 aurora kinase B AXL 558 AXL receptor tyrosine kinase B4GALT1 2683 UDP-Gal: betaGlcNAc beta 1,4-galactosyltransferase, polypeptide 1 BATF 10538 basic leucine zipper transcription factor, ATF-like BATF3 55509 basic leucine zipper transcription factor, ATF-like 3 BAZ2B 29994 bromodomain adjacent to zinc finger domain, 2B BCL11B 64919 B-cell leukemia/lymphoma 11B BCL2L11 10018 BCL2-like 11 (apoptosis facilitator) BCL3 602 B-cell leukemia/lymphoma 3 BCL6 604 B-cell leukemia/lymphoma 6 BHLH40 8553 Basic Helix-Loop-Helix Family, Member E40 BLOC1S1 2647 biogenesis of lysosome-related organelles complex-1, subunit 1 BMP2K 55589 BMP2 inducible kinase BMPR1A 657 bone morphogenetic protein receptor, type 1A BPGM 669 2,3-bisphosphoglycerate mutase BSG 682 basigin BTG1 694 B-cell translocation gene 1, anti-proliferative BTG2 7832 B-cell translocation gene 2, anti-proliferative BUB1 699 budding uninhibited by benzimidazoles 1 homolog (S. cerevisiae) C14ORF83 161145 RIKEN cDNA 6330442E10 gene C16ORF80 29105 gene trap locus 3 C21ORF66 94104 RIKEN cDNA 1810007M14 gene CAMK4 814 calcium/calmodulin-dependent protein kinase IV CARM1 10498 coactivator-associated arginine methyltransferase 1 CASP1 834 caspase 1 CASP3 836 caspase 3 CASP4 837 caspase 4, apoptosis-related cysteine peptidase CASP6 839 caspase 6 CASP8AP2 9994 caspase 8 associated protein 2 CBFB 865 core binding factor beta CBX4 8535 chromobox homolog 4 (Drosophila Pc class) CCL1 6346 chemokine (C-C motif) ligand 1 CCL20 6364 chemokine (C-C motif) ligand 20 CCL4 6351 chemokine (C-C motif) ligand 4 CCND2 894 cyclin D2 CCR4 1233 chemokine (C-C motif) receptor 4 CCR5 1234 chemokine (C-C motif) receptor 5 CCR6 1235 chemokine (C-C motif) receptor 6 CCR8 1237 chemokine (C-C motif) receptor 8 CCRN4L 25819 CCR4 carbon catabolite repression 4-like (S. cerevisiae) CD14 929 CD14 antigen CD2 914 CD2 antigen CD200 4345 CD200 antigen CD226 10666 CD226 antigen CD24 934 CD24a antigen CD247 919 CD247 antigen CD27 939 CD27 antigen CD274 29126 CD274 antigen CD28 940 CD28 antigen CD3D 915 CD3 antigen, delta polypeptide CD3G 917 CD3 antigen, gamma polypeptide CD4 920 CD4 antigen CD40LG 959 CD40 ligand CD44 960 CD44 antigen CD53 963 CD53 antigen CD5L 922 CD5 antigen-like CD63 967 CD63 antigen CD68 968 CD68 antigen CD70 970 CD70 antigen CD74 972 CD74 antigen (invariant polypeptide of major histocompatibility complex, cl CD80 941 CD80 antigen CD83 9308 CD83 antigen CD84 8832 CD84 antigen CD86 942 CD86 antigen CD9 928 CD9 antigen CD96 10225 CD96 antigen CDC25B 994 cell division cycle 25 homolog B (S. pombe) CDC42BPA 8476 CDC42 binding protein kinase alpha CDC5L 988 cell division cycle 5-like (S. pombe) CDK5 1020 cyclin-dependent kinase 5 CDK6 1021 cyclin-dependent kinase 6 CDKN3 1033 cyclin-dependent kinase inhibitor 3 CDYL 9425 chromodomain protein, Y chromosome-like CEBPB 1051 CCAAT/enhancer binding protein (C/EBP), beta CENPT 80152 centromere protein T CHD7 55636 chromodomain helicase DNA binding protein 7 CHMP1B 57132 chromatin modifying protein 1B CHMP2A 27243 charged multivesicular body protein 2A CHRAC1 54108 chromatin accessibility complex 1 CIC 23152 capicua homolog (Drosophila) CITED2 10370 Cbp/p300-interacting transactivator, with Glu/Asp-rich carboxy-terminal dom CLCF1 23529 cardiotrophin-like cytokine factor 1 CLK1 1195 CDC-like kinase 1 CLK3 1198 CDC-like kinase 3 CMTM6 54918 CKLF-like MARVEL transmembrane domain containing 6 CNOT2 4848 CCR4-NOT transcription complex, subunit 2 CREB1 1385 cAMP responsive element binding protein 1 CREB3L2 64764 cAMP responsive element binding protein 3-like 2 CREG1 8804 cellular repressor of E1A-stimulated genes 1 CREM 1390 cAMP responsive element modulator CSDA 8531 cold shock domain protein A CSF1R 1436 colony stimulating factor 1 receptor CSF2 1437 colony stimulating factor 2 (granulocyte-macrophage) CTLA4 1493 cytotoxic T-lymphocyte-associated protein 4 CTSD 1509 cathepsin D CTSW 1521 cathepsin W CXCL10 3627 chemokine (C-X-C motif) ligand 10 CXCR3 2833 chemokine (C-X-C motif) receptor 3 CXCR4 7852 chemokine (C-X-C motif) receptor 4 CXCR5 643 chemochine (C-X-C motif) receptor 5 DAPP1 27071 dual adaptor for phosphotyrosine and 3- phosphoinositides 1 DAXX 1616 Fas death domain-associated protein DCK 1633 deoxycytidine kinase DCLK1 9201 doublecortin-like kinase 1 DDIT3 1649 DNA-damage inducible transcript 3 DDR1 780 discoidin domain receptor family, member 1 DGKA 1606 diacylglycerol kinase, alpha DGUOK 1716 deoxyguanosine kinase DNAJC2 27000 DnaJ (Hsp40) homolog, subfamily C, member 2 DNTT 1791 deoxynucleotidyltransferase, terminal DPP4 1803 dipeptidylpeptidase 4 DUSP1 1843 dual specificity phosphatase 1 DUSP10 11221 dual specificity phosphatase 10 DUSP14 11072 dual specificity phosphatase 14 DUSP16 80824 dual specificity phosphatase 16 DUSP2 1844 dual specificity phosphatase 2 DUSP22 56940 dual specificity phosphatase 22 DUSP6 1848 dual specificity phosphatase 6 E2F1 1869 E2F transcription factor 1 E2F4 1874 E2F transcription factor 4 E2F8 79733 E2F transcription factor 8 ECE2 9718 endothelin converting enzyme 2 EGR1 1958 early growth response 1 EGR2 1959 early growth response 2 EIF2AK2 5610 eukaryotic translation initiation factor 2-alpha kinase 2 ELK3 2004 ELK3, member of ETS oncogene family ELL2 22936 elongation factor RNA polymerase II 2 EMP1 2012 epithelial membrane protein 1 ENTPD1 953 ectonucleoside triphosphate diphosphohydrolase 1 ERCC5 2073 excision repair cross-complementing rodent repair deficiency, complementati ERRFI1 54206 ERBB receptor feedback inhibitor 1 ETS1 2113 E26 avian leukemia oncogene 1, 5 domain ETS2 2114 E26 avian leukemia oncogene 2, 3 domain ETV6 2120 ets variant gene 6 (TEL oncogene) EZH1 2145 enhancer of zeste homolog 1 (Drosophila) FAS 355 Fas (TNF receptor superfamily member 6) FASLG 356 Fas ligand (TNF superfamily, member 6) FCER1G 2207 Fc receptor, IgE, high affinity I, gamma polypeptide FCGR2B 2213 Fc receptor, IgG, low affinity IIb FES 2242 feline sarcoma oncogene FLI1 2313 Friend leukemia integration 1 FLNA 2316 filamin, alpha FOSL2 2355 fos-like antigen 2 FOXJ2 55810 forkhead box J2 FOXM1 2305 forkhead box M1 FOXN3 1112 forkhead box N3 FOXO1 2308 forkhead box O1 FOXP1 27086 forkhead box P1 FOXP3 50943 forkhead box P3 FRMD4B 23150 FERM domain containing 4B FUS 2521 fusion, derived from t(12; 16) malignant liposarcoma (human) FZD7 8324 frizzled homolog 7 (Drosophila) GAP43 2596 growth associated protein 43 GATA3 2625 GATA binding protein 3 GATAD1 57798 GATA zinc finger domain containing 1 GATAD2B 57459 GATA zinc finger domain containing 2B GEM 2669 GTP binding protein (gene overexpressed in skeletal muscle) GFI1 2672 growth factor independent 1 GJA1 2697 gap junction protein, alpha 1 GK 2710 glycerol kinase GLIPR1 11010 GLI pathogenesis-related 1 (glioma) GMFB 2764 glia maturation factor, beta GMFG 9535 glia maturation factor, gamma GRN 2896 granulin GUSB 2990 glucuronidase, beta HCLS1 3059 hematopoietic cell specific Lyn substrate 1 HDAC8 55869 histone deacetylase 8 HIF1A 3091 hypoxia inducible factor 1, alpha subunit HINT3 135114 histidine triad nucleotide binding protein 3 HIP1R 9026 huntingtin interacting protein 1 related HIPK1 204851 homeodomain interacting protein kinase 1 HIPK2 28996 homeodomain interacting protein kinase 2 HK1 3098 hexokinase 1 HK2 3099 hexokinase 2 HLA-A 3105 major histocompatibility complex, class I, A HLA-DQA1 3117 histocompatibility 2, class II antigen A, alpha HMGA1 3159 high mobility group AT-hook 1 HMGB2 3148 high mobility group box 2 HMGN1 3150 high mobility group nucleosomal binding domain 1 ICOS 29851 inducible T-cell co-stimulator ID1 3397 inhibitor of DNA binding 1 ID2 3398 inhibitor of DNA binding 2 ID3 3399 inhibitor of DNA binding 3 IER3 8870 immediate early response 3 IFI35 3430 interferon-induced protein 35 IFIH1 64135 interferon induced with helicase C domain 1 IFIT1 3434 interferon-induced protein with tetratricopeptide repeats 1 IFITM2 10581 interferon induced transmembrane protein 2 IFNG 3458 interferon gamma IFNGR1 3459 interferon gamma receptor 1 IFNGR2 3460 interferon gamma receptor 2 IKZF1 10320 IKAROS family zinc finger 1 IKZF3 22806 IKAROS family zinc finger 3 IKZF4 64375 IKAROS family zinc finger 4 IL10 3586 interleukin 10 IL10RA 3587 interleukin 10 receptor, alpha IL12RB1 3594 interleukin 12 receptor, beta 1 IL12RB2 3595 interleukin 12 receptor, beta 2 IL15RA 3601 interleukin 15 receptor, alpha chain IL17A 3605 interleukin 17A IL17F 112744 interleukin 17F IL17RA 23765 interleukin 17 receptor A IL18R1 8809 interleukin 18 receptor 1 IL1R1 3554 interleukin 1 receptor, type I IL1RN 3557 interleukin 1 receptor antagonist IL2 3558 interleukin 2 IL21 59067 interleukin 21 IL21R 50615 interleukin 21 receptor IL22 50616 interleukin 22 IL23R 149233 interleukin 23 receptor IL24 11009 interleukin 24 IL27RA 9466 interleukin 27 receptor, alpha IL2RA 3559 interleukin 2 receptor, alpha chain IL2RB 3560 interleukin 2 receptor, beta chain IL2RG 3561 interleukin 2 receptor, gamma chain IL3 3562 interleukin 3 IL4 3565 interleukin 4 IL4R 3566 interleukin 4 receptor, alpha IL6ST 3572 interleukin 6 signal transducer IL7R 3575 interleukin 7 receptor IL9 3578 interleukin 9 INHBA 3624 inhibin beta-A INPP1 3628 inositol polyphosphate-1-phosphatase IRAK1BP1 134728 interleukin-1 receptor-associated kinase 1 binding protein 1 IRF1 3659 interferon regulatory factor 1 IRF2 3660 interferon regulatory factor 2 IRF3 3661 interferon regulatory factor 3 IRF4 3662 interferon regulatory factor 4 IRF7 3665 interferon regulatory factor 7 IRF8 3394 interferon regulatory factor 8 IRF9 10379 interferon regulatory factor 9 ISG20 3669 interferon-stimulated protein ITGA3 3675 integrin alpha 3 ITGAL 3683 integrin alpha L ITGAV 3685 integrin alpha V ITGB1 3688 integrin beta 1 (fibronectin receptor beta) ITK 3702 IL2-inducible T-cell kinase JAK2 3717 Janus kinase 2 JAK3 3718 Janus kinase 3 JARID2 3720 jumonji, AT rich interactive domain 2 JMJD1C 221037 jumonji domain containing 1C JUN 3725 Jun oncogene JUNB 3726 Jun-B oncogene KAT2B 8850 K(lysine) acetyltransferase 2B KATNA1 11104 katanin p60 (ATPase-containing) subunit A1 KDM6B 23135 lysine (K)-specific demethylase 6B KLF10 7071 Kruppel-like factor 10 KLF13 51621 Kruppel-like factor 13 KLF6 1316 Kruppel-like factor 6 KLF7 8609 Kruppel-like factor 7 (ubiquitous) KLF9 687 Kruppel-like factor 9 KLRD1 3824 killer cell lectin-like receptor, subfamily D, member 1 LAD1 3898 ladinin LAMP2 3920 lysosomal-associated membrane protein 2 LASS4 79603 LAG1 homolog, ceramide synthase 4 LASS6 253782 LAG1 homolog, ceramide synthase 6 LEF1 51176 lymphoid enhancer binding factor 1 LGALS3BP 3959 lectin, galactoside-binding, soluble, 3 binding protein LGTN 1939 ligatin LIF 3976 leukemia inhibitory factor LILRB1, LILRB2, 10859, 10288, 11025, leukocyte immunoglobulin-like receptor, subfamily B LILRB3, LILRB4, 11006, 10990 (with TM and ITIM domains), members 1--5 LILRB5 LIMK2 3985 LIM motif-containing protein kinase 2 LITAF 9516 LPS-induced TN factor LMNB1 4001 lamin B1 LRRFIP1 9208 leucine rich repeat (in FLII) interacting protein 1 LSP1 4046 lymphocyte specific 1 LTA 4049 lymphotoxin A MAF 4094 avian musculoaponeurotic fibrosarcoma (v-maf) AS42 oncogene homolog MAFF 23764 v-maf musculoaponeurotic fibrosarcoma oncogene family, protein F (avian) MAFG 4097 v-maf musculoaponeurotic fibrosarcoma oncogene family, protein G (avian) MAML2 84441 mastermind like 2 (Drosophila) MAP3K5 4217 mitogen-activated protein kinase kinase kinase 5 MAP3K8 1326 mitogen-activated protein kinase kinase kinase 8 MAP4K2 5871 mitogen-activated protein kinase kinase kinase kinase 2 MAP4K3 8491 mitogen-activated protein kinase kinase kinase kinase 3 MAPKAPK2 9261 MAP kinase-activated protein kinase 2 MATR3 9782 matrin 3 MAX 4149 Max protein MAZ 4150 MYC-associated zinc finger protein (purine-binding transcription factor) MBNL1 4154 muscleblind-like 1 (Drosophila) MBNL3 55796 muscleblind-like 3 (Drosophila) MDM4 4194 transformed mouse 3T3 cell double minute 4 MEN1 4221 multiple endocrine neoplasia 1 MFHAS1 9258 malignant fibrous histiocytoma amplified sequence 1 MGLL 11343 monoglyceride lipase MIER1 57708 mesoderm induction early response 1 homolog (Xenopus laevis MINA 84864 myc induced nuclear antigen MKNK2 2872 MAP kinase-interacting serine/threonine kinase 2 MORF4L1 10933 mortality factor 4 like 1 MORF4L2 9643 mortality factor 4 like 2 MS4A6A 64231 membrane-spanning 4-domains, subfamily A, member 6B MST4 51765 serine/threonine protein kinase MST4 MT1A 4489 metallothionein 1 MT2A 4502 metallothionein 2 MTA3 57504 metastasis associated 3 MXD3 83463 Max dimerization protein 3 MXI1 4601 Max interacting protein 1 MYC 4609 myelocytomatosis oncogene MYD88 4615 myeloid differentiation primary response gene 88 MYST4 23522 MYST histone acetyltransferase monocytic leukemia 4 NAGK 55577 N-acetylglucosamine kinase NAMPT 10135 nicotinamide phosphoribosyltransferase NASP 4678 nuclear autoantigenic sperm protein (histone-binding) NCF1C 654817 neutrophil cytosolic factor 1 NCOA1 8648 nuclear receptor coactivator 1 NCOA3 8202 nuclear receptor coactivator 3 NEK4 6787 NIMA (never in mitosis gene a)-related expressed kinase 4 NEK6 10783 NIMA (never in mitosis gene a)-related expressed kinase 6 NFATC1 4772 nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 1 NFATC2 4773 nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 2 NFE2L2 4780 nuclear factor, erythroid derived 2, like 2 NFIL3 4783 nuclear factor, interleukin 3, regulated NFKB1 4790 nuclear factor of kappa light polypeptide gene enhancer in B-cells 1, p105 NFKBIA 4792 nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibito NFKBIB 4793 nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibito NFKBIE 4794 nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibito NFKBIZ 64332 nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibito NFYC 4802 nuclear transcription factor-Y gamma NKG7 4818 natural killer cell group 7 sequence NMI 9111 N-myc (and STAT) interactor NOC4L 79050 nucleolar complex associated 4 homolog (S. cerevisiae) NOTCH1 4851 Notch gene homolog 1 (Drosophila) NOTCH2 4853 Notch gene homolog 2 (Drosophila) NR3C1 2908 nuclear receptor subfamily 3, group C, member 1 NR4A2 4929 nuclear receptor subfamily 4, group A, member 2 NR4A3 8013 nuclear receptor subfamily 4, group A, member 3 NUDT4 11163 nudix (nucleoside diphosphate linked moiety X)-typemotif 4 OAS2 4939 2-5 oligoadenylate synthetase 2 PACSIN1 29993 protein kinase C and casein kinase substrate in neurons 1 PAXBP1 94104 PAX3 and PAX7 binding protein 1 PCTK1 5127 PCTAIRE-motif protein kinase 1 PDCD1 5133 programmed cell death 1 PDCD1LG2 80380 programmed cell death 1 ligand 2 PDK3 5165 pyruvate dehydrogenase kinase, isoenzyme 3 PDPK1 5170 3-phosphoinositide dependent protein kinase-1 PDXK 8566 pyridoxal (pyridoxine, vitamin B6) kinase PECI 10455 peroxisomal delta3, delta2-enoyl-Coenzyme A isomerase PELI2 57161 pellino 2 PGK1 5230 phosphoglycerate kinase 1 PHACTR2 9749 phosphatase and actin regulator 2 PHF13 148479 PHD finger protein 13 PHF21A 51317 PHD finger protein 21A PHF6 84295 PHD finger protein 6 PHLDA1 22822 pleckstrin homology-like domain, family A, member 1 PHLPP1 23239 PH domain and leucine rich repeat protein phosphatase 1 PI4KA 5297 phosphatidylinositol 4-kinase, catalytic, alpha polypeptide PIM1 5292 proviral integration site 1 PIM2 11040 proviral integration site 2 PIP4K2A 5305 phosphatidylinositol-5-phosphate 4-kinase, type II, alpha PKM2 5315 pyruvate kinase, muscle PLAC8 51316 placenta-specific 8 PLAGL1 5325 pleiomorphic adenoma gene-like 1 PLAUR 5329 plasminogen activator, urokinase receptor PLEK 5341 pleckstrin PLEKHF2 79666 pleckstrin homology domain containing, family F (with FYVE domain) member 2 PLK2 10769 polo-like kinase 2 (Drosophila) PMEPA1 56937 prostate transmembrane protein, androgen induced 1 PML 5371 promyelocytic leukemia PNKP 11284 polynucleotide kinase 3-phosphatase POU2AF1 5450 POU domain, class 2, associating factor 1 POU2F2 5452 POU domain, class 2, transcription factor 2 PPME1 51400 protein phosphatase methylesterase 1 PPP2R5A 5525 protein phosphatase 2, regulatory subunit B (B56), alpha isoform PPP3CA 5530 protein phosphatase 3, catalytic subunit, alpha isoform PRC1 9055 protein regulator of cytokinesis 1 PRDM1 639 PR domain containing 1, with ZNF domain PRF1 5551 perforin 1 (pore forming protein) PRICKLE1 144165 prickle like 1 (Drosophila) PRKCA 5578 protein kinase C, alpha PRKCD 5580 protein kinase C, delta PRKCH 5583 protein kinase C, eta PRKCQ 5588 protein kinase C, theta PRKD3 23683 protein kinase D3 PRNP 5621 prion protein PROCR 10544 protein C receptor, endothelial PRPF4B 8899 PRP4 pre-mRNA processing factor 4 homolog B (yeast) PRPS1 5631 phosphoribosyl pyrophosphate synthetase 1 PSMB9 5698 proteasome (prosome, macropain) subunit, beta type 9 (large multifunctional PSTPIP1 9051 proline-serine-threonine phosphatase-interactingprotein 1 PTEN 5728 phosphatase and tensin homolog PTK2B 2185 PTK2 protein tyrosine kinase 2 beta PTP4A1 7803 protein tyrosine phosphatase 4a1 PTPLA 9200 protein tyrosine phosphatase-like (proline instead of catalytic arginine), PTPN1 5770 protein tyrosine phosphatase, non-receptor type 1 PTPN18 26469 protein tyrosine phosphatase, non-receptor type 18 PTPN6 5777 protein tyrosine phosphatase, non-receptor type 6 PTPRC 5788 protein tyrosine phosphatase, receptor type, C PTPRCAP 5790 protein tyrosine phosphatase, receptor type, C polypeptide-associated prote PTPRE 5791 protein tyrosine phosphatase, receptor type, E PTPRF 5792 protein tyrosine phosphatase, receptor type, F PTPRJ 5795 protein tyrosine phosphatase, receptor type, J PTPRS 5802 protein tyrosine phosphatase, receptor type, S PVR 5817 poliovirus receptor PYCR1 5831 pyrroline-5-carboxylate reductase 1 RAB33A 9363 RAB33A, member of RAS oncogene family RAD51AP1 10635 RAD51 associated protein 1 RARA 5914 retinoic acid receptor, alpha RASGRP1 10125 RAS guanyl releasing protein 1 RBPJ 3516 recombination signal binding protein for immunoglobulin kappa J region REL 5966 reticuloendotheliosis oncogene RELA 5970 v-rel reticuloendotheliosis viral oncogene homolog A (avian) RFK 55312 riboflavin kinase RIPK1 8737 receptor (TNFRSF)-interacting serine-threonine kinase 1 RIPK2 8767 receptor (TNFRSF)-interacting serine-threonine kinase 2 RIPK3 11035 receptor-interacting serine-threonine kinase 3 RNASEL 6041 ribonuclease L (2,5-oligoisoadenylate synthetase- dependent) RNF11 26994 ring finger protein 11 RNF5 6048 ring finger protein 5 RORA 6095 RAR-related orphan receptor alpha RORC 6097 RAR-related orphan receptor gamma RPP14 11102 ribonuclease P 14 subunit (human) RPS6KB1 6198 ribosomal protein S6 kinase, polypeptide 1 RUNX1 861 runt related transcription factor 1 RUNX2 860 runt related transcription factor 2 RUNX3 864 runt related transcription factor 3 RXRA 6256 retinoid X receptor alpha SAP18 10284 Sin3-associated polypeptide 18 SAP30 8819 sin3 associated polypeptide SATB1 6304 special AT-rich sequence binding protein 1 SEMA4D 10507 sema domain, immunoglobulin domain (Ig), transmembrane domain (TM) and shor SEMA7A 8482 sema domain, immunoglobulin domain (Ig), and GPI membrane anchor, (semaphor SERPINB1 1992 serine (or cysteine) peptidase inhibitor, clade B, member 1a SERPINE2 5270 serine (or cysteine) peptidase inhibitor, clade E, member 2 SERTAD1 29950 SERTA domain containing 1 SGK1 6446 serum/glucocorticoid regulated kinase 1 SH2D1A 4068 SH2 domain protein 1A SIK1 150094 salt-inducible kinase 1 SIRT2 22933 sirtuin 2 (silent mating type information regulation 2, homolog) 2 (S. cere SKAP2 8935 src family associated phosphoprotein 2 SKI 6497 ski sarcoma viral oncogene homolog (avian) SKIL 6498 SKI-like SLAMF7 57823 SLAM family member 7 SLC2A1 6513 solute carrier family 2 (facilitated glucose transporter), member 1 SLC3A2 6520 solute carrier family 3 (activators of dibasic and neutral amino acid trans SLK 9748 STE20-like kinase (yeast) SMAD2 4087 MAD homolog 2 (Drosophila) SMAD3 4088 MAD homolog 3 (Drosophila) SMAD4 4089 MAD homolog 4 (Drosophila) SMAD7 4092 MAD homolog 7 (Drosophila) SMARCA4 6597 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, SMOX 54498 spermine oxidase SOCS3 9021 suppressor of cytokine signaling 3 SP1 6667 trans-acting transcription factor 1 SP100 6672 nuclear antigen Sp100 SP4 6671 trans-acting transcription factor 4 SPHK1 8877 sphingosine kinase 1 SPOP 8405 speckle-type POZ protein SPP1 6696 secreted phosphoprotein 1 SPRY1 10252 sprouty homolog 1 (Drosophila) SRPK2 6733 serine/arginine-rich protein specific kinase 2 SS18 6760 synovial sarcoma translocation, Chromosome 18 STARD10 10809 START domain containing 10 STAT1 6772 signal transducer and activator of transcription 1 STAT2 6773 signal transducer and activator of transcription 2 STAT3 6774 signal transducer and activator of transcription 3 STAT4 6775 signal transducer and activator of transcription 4 STAT5A 6776 signal transducer and activator of transcription 5A STAT5B 6777 signal transducer and activator of transcription 5B STAT6 6778 signal transducer and activator of transcription 6 STK17B 9262 serine/threonine kinase 17b (apoptosis-inducing) STK19 8859 serine/threonine kinase 19 STK38 11329 serine/threonine kinase 38 STK38L 23012 serine/threonine kinase 38 like STK39 27347 serine/threonine kinase 39, STE20/SPS1 homolog (yeast) STK4 6789 serine/threonine kinase 4 SULT2B1 6820 sulfotransferase family, cytosolic, 2B, member 1 SUZ12 23512 suppressor of zeste 12 homolog (Drosophila) TAF1B 9014 TATA box binding protein (Tbp)-associated factor, RNA polymerase I, B TAL2 6887 T-cell acute lymphocytic leukemia 2 TAP1 6890 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) TBPL1 9519 TATA box binding protein-like 1 TBX21 30009 T-box 21 TCERG1 10915 transcription elongation regulator 1 (CA150) TEC 7006 cytoplasmic tyrosine kinase, Dscr28C related (Drosophila) TFDP1 7027 transcription factor Dp 1 TFEB 7942 transcription factor EB TGFB1 7040 transforming growth factor, beta 1 TGFB3 7043 transforming growth factor, beta 3 TGFBR1 7046 transforming growth factor, beta receptor I TGFBR3 7049 transforming growth factor, beta receptor III TGIF1 7050 TGFB-induced factor homeobox 1 TGM2 7052 transglutaminase 2, C polypeptide THRAP3 9967 thyroid hormone receptor associated protein 3 TIMP2 7077 tissue inhibitor of metalloproteinase 2 TK1 7083 thymidine kinase 1 TK2 7084 thymidine kinase 2, mitochondrial TLE1 7088 transducin-like enhancer of split 1, homolog of Drosophila E(spl) TLR1 7096 toll-like receptor 1 TMEM126A 84233 transmembrane protein 126A TNFRSF12A 51330 tumor necrosis factor receptor superfamily, member 12a TNFRSF13B 23495 tumor necrosis factor receptor superfamily, member 13b TNFRSF1B 7133 tumor necrosis factor receptor superfamily, member 1b TNFRSF25 8718 tumor necrosis factor receptor superfamily, member 25 TNFRSF4 7293 tumor necrosis factor receptor superfamily, member 4 TNFRSF9 3604 tumor necrosis factor receptor superfamily, member 9 TNFSF11 8600 tumor necrosis factor (ligand) superfamily, member 11 TNFSF8 944 tumor necrosis factor (ligand) superfamily, member 8 TNFSF9 8744 tumor necrosis factor (ligand) superfamily, member 9 TNK2 10188 tyrosine kinase, non-receptor, 2 TOX4 9878 TOX high mobility group box family member 4 TP53 7157 transformation related protein 53 TRAF3 7187 Tnf receptor-associated factor 3 TRAT1 50852 T cell receptor associated transmembrane adaptor 1 TRIM24 8805 tripartite motif-containing 24 TRIM25 7706 tripartite motif-containing 25 TRIM28 10155 tripartite motif-containing 28 TRIM5 85363 tripartite motif containing 5 TRIP12 9320 thyroid hormone receptor interactor 12 TRPS1 7227 trichorhinophalangeal syndrome I (human) TRRAP 8295 transformation/transcription domain-associated protein TSC22D3 1831 TSC22 domain family, member 3 TSC22D4 81628 TSC22 domain family, member 4 TWF1 5756 twinfilin, actin-binding protein, homolog 1 (Drosophila) TXK 7294 TXK tyrosine kinase UBE2B 7320 ubiquitin-conjugating enzyme E2B, RAD6 homology (S. cerevisiae) UBIAD1 29914 UbiA prenyltransferase domain containing 1 ULK2 9706 Unc-51 like kinase 2 (C. elegans) VAV1 7409 vav 1 oncogene VAV3 10451 vav 3 oncogene VAX2 25806 ventral anterior homeobox containing gene 2 VRK1 7443 vaccinia related kinase 1 VRK2 7444 vaccinia related kinase 2 WDHD1 11169 WD repeat and HMG-box DNA binding protein 1 WHSC1L1 54904 Wolf-Hirschhorn syndrome candidate 1-like 1 (human) WNK1 65125 WNK lysine deficient protein kinase 1 XAB2 56949 XPA binding protein 2 XBP1 7494 X-box binding protein 1 XRCC5 7520 X-ray repair complementing defective repair in Chinese hamster cells 5 YBX1 4904 Y box protein 1 ZAK 51776 RIKEN cDNA B230120H23 gene ZAP70 7535 zeta-chain (TCR) associated protein kinase ZBTB32 27033 zinc finger and BTB domain containing 32 ZEB1 6935 zinc finger E-box binding homeobox 1 ZEB2 9839 zinc finger E-box binding homeobox 2 ZFP161 7541 zinc finger protein 161 ZFP36L1 677 zinc finger protein 36, C3H type-like 1 ZFP36L2 678 zinc finger protein 36, C3H type-like 2 ZFP62 92379 zinc finger protein 62 ZNF238 10472 zinc finger protein 238 ZNF281 23528 zinc finger protein 281 ZNF326 284695 zinc finger protein 326 ZNF703 80139 zinc finger protein 703 ZNRF1 84937 zinc and ring finger 1 ZNRF2 223082 zinc and ring finger 2
(161) Primers for Nanostring STA and qRT-PCR/Fluidigm and siRNA Sequences:
(162) Table S6.1 presents the sequences for each forward and reverse primer used in the Fluidigm/qRT-PCR experiments and Nanostring nCounter gene expression profiling. Table S6.2 presents the sequences for RNAi used for knockdown analysis.
(163) TABLE-US-00012 TABLES6.1 PrimerSequences SEQ SEQ Gene ID ID Assay Name NO: ForwardSequence NO: ReverseSequence NanostringSTA 1700097 1 GGCCAGAGCTTGACCATC 2 AGCAAGCCAGCCAAACAG N02Rik NanostringSTA Aim1 3 AGCCAATTTTGAAGGGCA 4 GGAAGCCCTGCATTTCCT NanostringSTA Arnt1 5 TATAACCCCTGGGCCCTC 6 GTTGCAGCCCTCGTTGTC NanostringSTA Bcl6 7 GTCGGGACATCTTGACGG 8 GGAGGATGCAAAACCCCT NanostringSTA Ccl20 9 GCATGGGTACTGCTGGCT 10 TGAGGAGGTTCACAGCCC NanostringSTA Cd24a 11 GGACGCGTGAAAGGTTTG 12 TGCACTATGGCCTTATCG G NanostringSTA Cd80 13 TGCCTAAGCTCCATTGGC 14 ACGGCAAGGCAGCAATAG NanostringSTA Csnk1a1 15 GGGTATTGGGCGTCACTG 16 CCACGGCAGACTGGTTCT NanostringSTA Ddr1 17 ATGCACACTCTGGGAGCC 18 CCAAGGACCTGCAAAGAG G NanostringSTA Emp1 19 AGCTGCCATACCACTGGC 20 AGGCACATGGGATCTGGA NanostringSTA Flna 21 CTTCACTGCATTCGCCCT 22 CACAGGACAACGGAAGCA NanostringSTA Gata3 23 CACCGCCATGGGTTAGAG 24 TGGGATCCGGATTCAGTG NanostringSTA 2900064 25 AAGGAAAAATGCGAGCAA 26 TCTCCCGTCTCATGTCAG A13Rik GA G NanostringSTA Anxa4 27 ATGGGGGACAGACGAGGT 28 TGCCTAAGCCCTTCATGG NanostringSTA Atf4 29 GATGATGGCTTGGCCAGT 30 TGGCCAATTGGGTTCACT NanostringSTA Bmpr1a 31 CATTTGGGAAATGGCTCG 32 ATGGGCCCAACATTCTGA NanostringSTA Ccl4 33 AAGCTCTGCGTGTCTGCC 34 ACCACAGCTGGCTTGGAG NanostringSTA Cd274 35 CGTGGATCCAGCCACTTC 36 ATCATTCGCTGTGGCGTT NanostringSTA Cd86 37 ATCTGCCGTGCCCATTTA 38 ACGAGCCCATGTCCTTGA NanostringSTA Ctla2b 39 GGCTCAACAGCAGGAAGC 40 TTAATTTGAAGACATCAT GGCA NanostringSTA Dntt 41 CCCAGAAGCCACAGAGGA 42 TTCCAGCCCTTTCCTTCC NanostringSTA Ercc5 43 GTGCCATTTGACACAGCG 44 CTGGCCTACCCTCCACCT NanostringSTA Foxm1 45 CAAGCCAGGCTGGAAGAA 46 TGGGTCGTTTCTGCTGTG NanostringSTA Gem 47 GACACGCTTCGGGTTCAC 48 CAACTGTGATGAGGCCAG C NanostringSTA 6330442 49 CCCAGCATTAAGGCTCCA 50 AGGAGCAACAGGGGACCT E10Rik NanostringSTA Api5 51 CAGCTTTGAACACAGGGT 52 AGCTGACTGAAATTCCTC CTT CCT NanostringSTA B4galt1 53 TCACAGTGGACATCGGGA 54 CACTCACCCTGGGCATCT NanostringSTA Cand1 55 CTACTGCAGGGAGGAGCG 56 GGGTCCCTCTTTAGGGCA NanostringSTA Ccr4 57 GTCCGTGCAGTTTGGCTT 58 GGTTTGGGGACAGGCTTT NanostringSTA Cd28 59 CCTTTGCAGTGAGTTGGG 60 CGTTTTGAAAATCTGCAG A AGAA NanostringSTA Cd9 61 GCGGGAAACACTCAAAGC 62 TGCTGAAGATCATGCCGA NanostringSTA Ctsw 63 GCCACTGGAGCTGAAGGA 64 TGACCTCTCCTGCCCGTA NanostringSTA Dpp4 65 CCCTGCTCCTGCATCTGT 66 AAATCTTCCGACCCAGCC NanostringSTA Errfi1 67 TCCTGCTTTTCCCATCCA 68 CCAGCAACACAAGACCAG C NanostringSTA Foxo1 69 TCCACTCTGGGCAAGAGG 70 GGCAGCAGAGGGTGGATA NanostringSTA Gfi1 71 ATGTCTTCCCTGCCTCCC 72 AAGCCCAAAGCACAGACG NanostringSTA Abcg2 73 GGAACATCGGCCTTCAAA 74 CATTCCAGCGGCATCATA NanostringSTA Aqp3 75 CGGCACAGCTGGAATCTT 76 GGTTGACGGCATAGCCAG NanostringSTA Batf 77 CTACCCAGAGGCCCAGTG 78 AACTATCCACCCCCTGCC NanostringSTA Casp1 79 TCCTGAGGGCAAAGAGGA 80 GATTTGGCTTGCCTGGG NanostringSTA Ccr5 81 AACTGAATGGGGAGGTTG 82 TTACAGCCGCCTTTCAGG G NanostringSTA Cd4 83 CCAGCCCTGGATCTCCTT 84 GCCACTTTCATCACCACC A NanostringSTA Cebpb 85 TGCACCGAGGGGACAC 86 AACCCCGCAGGAACATCT NanostringSTA Cxcl10 87 TGCCGTCATTTTCTGCCT 88 CGTGGCAATGATCTCAAC A NanostringSTA Egr2 89 AGGACCTTGATGGAGCCC 90 CTGGCATCCAGGGTCAAC NanostringSTA Etv6 91 CATGAGGGAGGATGCTGG 92 AAATCCCTGCTATCAAAA ATCC NanostringSTA Foxp1 93 GCTCTCTGTCTCCAAGGG 94 ACTCACAACCCAGACCGC C NanostringSTA Gja1 95 GGCCTGATGACCTGGAGA 96 TCCCTACTTTTGCCGCCT NanostringSTA Acly 97 GAGGGCTGGGACCATTG 98 GCAGCTGCCCAGAATCTT NanostringSTA Arhgef3 99 GCAGCAGGCTGTTTCTTA 100 TTCCTCCCCACTCATCCA CC NanostringSTA BC021614 101 AAGGAGGGCAAGGACCAG 102 GAGCTTGGGTCGGGATTT NanostringSTA Casp3 103 GGAGATGGCTTGCCAGAA 104 ACTCGAATTCCGTTGCCA NanostringSTA Ccr6 105 GCCAGATCCATGACTGAC 106 TTTGGTTGCCTGGACGAT G NanostringSTA Cd44 107 CAGGGAACATCCACCAGC 108 TAGCATCACCCTTTGGGG NanostringSTA Chd7 109 CATTGTCAGTGGGCGTCA 110 GAATCACAGGCTCGCCC NanostringSTA Cxcr3 111 CCAGATCTACCGCAGGGA 112 CATGACCAGAAGGGGCAG NanostringSTA Eif3e 113 GTCAACCAGGGATGGCAG 114 CAGTTTTCCCCAGAGCGA NanostringSTA Fas 115 GCTGTGGATCTGGGCTGT 116 CCCCCATTCATTTTGCAG NanostringSTA Foxp3 117 TGGAAACACCCAGCCACT 118 GGCAAGACTCCTGGGGAT NanostringSTA Glipr1 119 TGGATGGCTTCGTCTGTG 120 TGCAGCTGTGGGTTGTGT NanostringSTA Acvr1b 121 GTGCCGACATCTATGCCC 122 GCACTCCCGCATCATCTT NanostringSTA Arid5a 123 GGCCTCGGGTCTTTCACT 124 CTAGGCAGCTGGGCTCAC NanostringSTA Bcll1b 125 GGAGGGGTGGCTTTCAA 126 AAGATTCTCGGGGTCCCA NanostringSTA Casp4 127 GGAACAGCTGGGCAAAGA 128 GCCTGGGTCCACACTGAA NanostringSTA Ccr8 129 GTGGGTGTTTGGGACTGC 130 ATCAAGGGGATGGTGGCT NanostringSTA Cd51 131 TGGGGGTACCACGACTGT 132 GGGCGTGTAGCCTTGAGA NanostringSTA Clcf1 133 AATCCTCCTCGACTGGGG 134 TGACACCTGCAATGCTGC NanostringSTA Cxcr4 135 CCGATAGCCTGTGGATGG 136 GTCGATGCTGATCCCCAC NanostringSTA Eif3h 137 AGCCTTCGCCATGTCAAC 138 CGCCTTCAGCGAGAGAGA NanostringSTA Fas1 139 GCAAATAGCCAACCCCAG 140 GTTGCAAGACTGACCCCG NanostringSTA Frmd4b 141 GGAGTCCCAGTCCCACCT 142 TGGACCTTCTTCTCCCCC NanostringSTA Golga3 143 TCCAACCAGGTGGAGCAC 144 TCATCTCAGAGTCCAGCC G NanostringSTA Acvr2a 145 ATGGCAAACTTGGACCCC 146 CAAGATCTGTGCAGGGCA NanostringSTA Arl5a 147 CGGATTTGAGCGCTTCTG 148 ACTCACTGGTGGGTGGGA NanostringSTA Bcl2l11 149 TGGCAAGCCCTCTCACTT 150 AAACACACACAACCACGC A NanostringSTA Casp6 151 TGCTCAAAATTCACGAGG 152 CACGGGTACGTCATGCTG TG NanostringSTA Cd2 153 CACCCTGGTCGCAGAGTT 154 GGTTGTGTTGGGGCATTC NanostringSTA Cd70 155 CTGGCTGTGGGCATCTG 156 GGAGTTGTGGTCAAGGGC NanostringSTA Cmtm6 157 TGCTGGTGTAGGCGTCTT 158 TCTCAGCAATCACAGTGC T AA NanostringSTA Cxcr5 159 TGGCCTTAATGTGCCTGT 160 TGCTGGCTTGCCCTTTAC C NanostringSTA Eif3m 161 TOGCTTGTTACATGAGCA 162 CCGATGTGTGCTGTGACT AAA G NanostringSTA Fipl11 163 GGATAGGAATGGGAGTGG 164 CCAACGCTTGAACTGGCT AA NanostringSTA Fzd7 165 TTCCCTGCAATAGAAGTC 166 TGAAGTAATCTGTCCTCC TGG CGA NanostringSTA Grn 167 CCGGCCTACTCATCCTGA 168 AACTTTATTGGAGCAACA CACG NanostringSTA Ahr 169 GTTGTGATGCCAAAGGGC 170 CAAGCGTGCATTGGACTG NanostringSTA Armcx2 171 TCCAATCTTGCCACCACC 172 TTCCAGCACTTTGGGAGC NanostringSTA Bcl3 173 CCAGGTTTTGCACCAAGG 174 CCTCCCAGACCCCTCTGT NanostringSTA Ccl1 175 CACTGATGTGCCTGCTGC 176 TGAGGCGCAGCTTTCTCT NanostringSTA Cd247 177 TACCATCCCAGGGAAGCA 178 GCAGGTTGGCAGCAGTCT NanostringSTA Cd74 179 GCTTCCGAAATCTGCCAA 180 CGCCATCCATGGAGTTCT NanostringSTA Csf2 181 GGCCATCAAAGAAGCCCT 182 GCTGTCATGTTCAAGGCG NanostringSTA Daxx 183 GTTGACCCCGCACTGTCT 184 ATTCCGAGGAGGCTTTGG NanostringSTA Elk3 185 CCTGTGGACCCAGATGCT 186 GACGGAGTTCAGCTCCCA NanostringSTA Fli1 187 GATTCTGAGAAAGGAGTA 188 GCCAGTGTTCCAGTTGCC CGCA NanostringSTA Gap43 189 GCGAGAGAGCGAGTGAGC 190 CCACGGAAGCTAGCCTGA NanostringSTA Gusb 191 ATGGAGCAGACGCAATCC 192 AAAGGCCGAAGTTTTGGG NanostringSTA H2-Q10 193 GTGGGCATCTGTGGTGGT 194 TGGAGCGGGAGCATAGTC NanostringSTA Ifi35 195 CAGAGTCCCACTGGACCG 196 AGGCACAACTGTCAGGGC NanostringSTA Il12rb2 197 GCAGCCAACTCAAAAGGC 198 GTGATGCTCCCTGGTTGG NanostringSTA Il22 199 TCAGACAGGTTCCAGCCC 200 TCTTCTCGCTCAGACGCA NanostringSTA Il4ra 201 CCTTCAGCCCCAGTGGTA 202 AGCTCAGCCTGGGTTCCT NanostringSTA Irf8 203 AAGGGACACTTCCCGGAG 204 TTTCCTGCAGTTCCCCAG NanostringSTA Katna1 205 CGGTGCGGGAACTATCC 206 CATTTGGTCAAGAACTCC CTG NanostringSTA Lad1 207 GAAGGAGCTGTCAGGCCA 208 GCATCCAGGGATGTGGAC NanostringSTA Ly6c2 209 GTCCTTCCAATGACCCCC 210 CCTCCAGGGCCAAGAATA G NanostringSTA Mina 211 GTCTGCCGGAGCATCAGT 212 TAATGTGGAGGGAGGCCC NanostringSTA Nampt 213 CAAGGAGATGGCGTGGAT 214 TGGGATCAGCAACTGGGT NanostringSTA Nkg7 215 TGGCCCTCTGGTCTCAAC 216 TTTCATACTCAGCCCGAC G NanostringSTA Hif1a 217 AAGAACTTTTGGGCCGCT 218 GCACTGTGGCTGGGAGTT NanostringSTA Ifih1 219 GCTGAAAACCCAAAATAC 220 ACTTCACTGCTGTGCCCC GA NanostringSTA Il17a 221 ATCAGGACGCGCAAACAT 222 GACGTGGAACGGTTGAGG NanostringSTA Il23r 223 CACTGCAAGGCAGCAGG 224 CGTTTGGTTTGTTGTTGT TTTG NanostringSTA Il6st 225 TCGGACGGCAATTTCACT 226 GTTGCTGGAGATGCTGGG NanostringSTA Irf9 227 ACTGATCGTCGCGTCTCC 228 TTGGTCTGTCTTCCAAGT GCT NanostringSTA Kcmf1 229 CTGACCACCCGATGCAGT 230 TCCAGGTAACGCTGCACA NanostringSTA Lamp2 231 GGCTGCAGCTGAACATCA 232 AAGCTGAGCCATTAGCCA AA NanostringSTA Maf 233 AGGCAGGAGGATGGCTTC 234 TCATGGGGGTGGAGGAC NanostringSTA Mkln1 235 GGTTTGCCCATCAACTCG 236 GGATCCATTTGGGCCTTT NanostringSTA Ncf1 237 GCAAAGGACAGGACTGGG 238 TTTGACACCCTCCCCAAA NanostringSTA Notch1 239 GCAGGCAAATGCCTCAAC 240 GTGGCCATTGTGCAGACA NanostringSTA Hip1r 241 CTCGAGCAGCTGGGACC 242 CCAGCAGGGACCCTCTTT NanostringSTA Ifit1 243 TCATTCGCTATGCAGCCA 244 GGCCTGTTGTGCCAATTC NanostringSTA Il17f 245 AAGAACCCCAAAGCAGGG 246 CAGCGATCTCTGAGGGGA NanostringSTA Il24 247 TCTCCACTCTGGCCAACA 248 CTGCATCCAGGTCAGGAG A NanostringSTA Il7r 249 TGGCCTACTCTCCCCGAT 250 CGAGCGGTTTGCACTGT NanostringSTA Isg20 251 CTGTGGAAGATGCCAGGG 252 GTGGTTGGTGGCAGTGGT NanostringSTA Khdrbs1 253 GTTCGTGGAACCCCAGTG 254 TCCCCTTGACTCTGGCTG NanostringSTA Lgals3bp 255 GGCCACAGAGCTTCAGGA 256 CCAGCTCACTCTTGGGGA NanostringSTA Maff 257 TCTGACTCTTGCAGGCCC 258 TGGCACAATCCAAAGCCT NanostringSTA Mt1 259 ACTATGCGTGGGCTGGAG 260 GCAGGAGCTGGTGCAAGT NanostringSTA Ncoa1 261 GCCTCCAGCCCATCCTAT 262 TGAGGGATTTATTCGGGG A NanostringSTA Notch2 263 TACGAGTGCACCTGCCAA 264 GCAGCGTCCTGGAATGTC NanostringSTA Hsbp1 265 ATCACGTGACCACAGCCC 266 CTCTGATACCCTGCCGGA NanostringSTA Ifng 267 TCTGGGCTTCTCCTCCTG 268 TCCTTTTGCCAGTTCCTC C NanostringSTA Il17ra 269 GGGGCTGAGCTGCAGACT 270 TGGTGTTCAGCTGCAGGA NanostringSTA Il27ra 271 AAGGCTGGCCTCGAACTT 272 GGGCAGGGAACCAAACTT NanostringSTA Il9 273 TGGTGACATACATCCTTG 274 TGTGTGGCATTGGTCAGC CC NanostringSTA Itga3 275 GCTTCACCCAGAACACCG 276 CCCATATGTTGGTGCCGT NanostringSTA Kif2a 277 TGCCGAATACACCAAGCA 278 TCCGCCGGTTCTTTACAA NanostringSTA Lif 279 GGGGCAGGTAGTTGCTCA 280 TCGGGATCAAGGACACAG A NanostringSTA Map3k5 281 CCATCTTGGAGTGCGAGA 282 GCTCAGTCAGGCCCTTCA A NanostringSTA Mt2 283 TGTGCTGGCCATATCCCT 284 AGGCACAGGAGCAGTTGG NanostringSTA Nfatc2 285 AGCTCCACGGCTACATGG 286 CGTTTCGGAGCTTCAGGA NanostringSTA Nr3c1 287 CAAGTGATTGCCGCAGTG 288 CATTGGTCATAGATGCAG GG NanostringSTA Icos 289 CGGCCGATCATAGGATGT 290 TTCCCTGGGAGCTGTCTG NanostringSTA Ifngr2 291 CGAAACAACAGCAAATGC 292 CGGTGAACCGTCCTTGTC C NanostringSTA Il1r1 293 ACCCGAGGTCCAGTGGTA 294 TCTCATTCCGAGGGCTCA NanostringSTA Il2ra 295 TGCAAGAGAGGTTTCCGA 296 GTTCCCAAGGAGGTGGCT NanostringSTA Inhba 297 AGCAGAAGCACCCACAGG 298 TCCTGGCACTGCTCACAA NanostringSTA Itgb1 299 TGGAAAATTCTGCGAGTG 300 TTGGCCCTTGAAACTTGG TG NanostringSTA Klf10 301 CCCTCCAAAAGGGCCTAA 302 GGCAAAAACAAAGTCCCC A NanostringSTA Litaf 303 AGTGCACAGAAGGGCTGC 304 CCAGCAAATGGAGAAATG G NanostringSTA Max 305 AGGACGCCTGCTCTACCA 306 GCTGCAAATCTGTCCCCA NanostringSTA Mta3 307 CGGAGAAGCAGAAGCACC 308 ACTTTGGGCCCACTCTGA NanostringSTA Nfe2l2 309 GCCGCTTAGAGGCTCATC 310 TGCTCCAGCTCGACAATG NanostringSTA Nudt4 311 TGGGGTGCCATCCAGTAT 312 ATTCCACATGGCTTTGGC NanostringSTA Id2 313 TCAGCCATTTCACCAGGA 314 TAACGTTTTCGCTCCCCA G NanostringSTA Ikzf4 315 GGGGTCTAGCCCAATTCC 316 GCCGGGGAGAGAGGTTAG NanostringSTA Il1rn 317 TGGTAAGCTTTCCTTCTT 318 TCATCACATCAGGAAGGG TCC C NanostringSTA Il2rb 319 GCACCCCATCCTCAGCTA 320 CAAGTCCAGCTCGGTGGT NanostringSTA Irf1 321 TAAGCACGGCTGGGACAT 322 CAGCAGAGCTGCCCTTGT NanostringSTA Jak3 323 CTCCCCAGCGATTGTCAT 324 CAGCCCAAACCAGTCAGG NanostringSTA Klf6 325 GAGCGGGAACTCAGGACC 326 GGGAAAATGACCACTGCG NanostringSTA Lmnb1 327 TGCCCTAGGGGACAAAAA 328 CAAGCGGGTCTCATGCTT NanostringSTA Mbnl3 329 TGGAGCATGAATCCACAC 330 TGAGGGTCCCATGAGTGG C NanostringSTA Mxi1 331 CTCAGGAGATGGAGCGGA 332 CCTCGTCACTCCCGACAC NanostringSTA Nfil3 333 CACGGTGGTGAAGGTTCC 334 GAAAGGAGGGAGGGAGGA NanostringSTA Oas2 335 TGCCTGTGCTTGCTCTGA 336 GAAGAAGGGCCAGAAGGG NanostringSTA Id3 337 CCGAGGAGCCTCTTAGCC 338 GTCTGGATCGGGAGATGC NanostringSTA Il10 339 ACTGCCTTCAGCCAGGTG 340 CAGCTTCTCACCCAGGGA NanostringSTA Il21 341 CCTGOAGTGGTATCATCG 342 TGCGTTGGTTCTGATTGT C G NanostringSTA Il3 343 CACACCATGCTGCTCCTG 344 CTCCTTGGCTTTCCACGA NanostringSTA Irf4 345 CAGAGAAACGCATTCCTG 346 AGTCCACCAGCTGGCTTT G T NanostringSTA Jun 347 TATTGGCCGGCAGACTTT 348 GCCTGGCACTTACAAGCC NanostringSTA Klf9 349 AGGGAAGGAAGACGCCAC 350 TGGCCATGTAAAAGCCAA A NanostringSTA Lrrfip1 351 GTCTCCAACGCCCAGCTA 352 ATCTCTTCCCTTTGCCGC NanostringSTA Med24 353 ACTGCTAGGGGTCCTGGG 354 TGAGCCATAGGTCTGGGC NanostringSTA Myd88 355 GAAGCTGTTTGGCTTCGC 356 TCATTCCTCCCCCAGACA NanostringSTA Nfkbie 357 TCGAGGCGCTCACATACA 358 CGGACAACATCTGGCTGA NanostringSTA Pcbp2 359 CTCAACTGAGCGGGCAAT 360 AGGGTTGAGGCACATGGA NanostringSTA Ier3 361 CCTTCTCCAGCTCCCTCC 362 CCTCTTGGCAATGTTGGG NanostringSTA Il10ra 363 GTAAAGGCCGGCTCCAGT 364 TTTCCAGTGGAGGATGTG C NanostringSTA Il21r 365 AGGTCTGGCCACAACACC 366 GGCCACAGTCACGTTCAA NanostringSTA Il4 367 AGGGCTTCCAAGGTGCTT 368 TGCTCTTTAGGCTTTCCA GG NanostringSTA Irf7 369 GAGGCTGAGGCTGCTGAG 370 ATCCTGGGGACACACCCT NanostringSTA Kat2b 371 GGTGCTTTGAGCAGTTGT 372 GCCCTGCACAAGCAAAGT GA NanostringSTA Klrd1 373 GCCTGGCTATGGGAGGAT 374 CCGTGGACCTTCCTTGTC NanostringSTA Lsp1 375 CCTGAGCCCTAGCACCAA 376 GGGCAGCTCTATGGAGGG NanostringSTA MgLL 377 CGCGCAGTAGTCTGGCTC 378 AAGATGAGGGCCTTGGGT NanostringSTA Myst4 379 CAACAAAGGGCAGCAAGC 380 TTCAACACAAGGGCAGAG G NanostringSTA Nfkbiz 381 TTAGCTGGATGAGCCCCA 382 ATGTTGCTGCTGTGGTGG NanostringSTA Peli2 383 GCCAGACGGTAGTGGTGG 384 CGTGCTGTGTATGGCTCG NanostringSTA Phlda1 385 GATGACGGAGGGCAAAGA 386 GGGGTTGAGGCTGGATCT NanostringSTA Prdm1 387 ACCCTGGCTATGCACCTG 388 GGGAAGCTGGATTGAGCA NanostringSTA Pstpip1 389 GAGAGCGAGGACCGAGTG 390 CCTTCCACATCACAGCCC NanostringSTA Rela 391 TGCGACAAGGTGCAGAAA 392 GAGCTCGCGATCAGAAGG NanostringSTA Runx3 393 GCCCCTTCCCACCATTTA 394 CTCCCCCTGCTGCTACAA NanostringSTA Sgk1 395 GGCTAGGCACAAGGCAGA 396 AGCGCTCCCTCTGGAGAT NanostringSTA Smox 397 ACAGCCTCGTGTGGTGGT 398 GGCCATTGGCTTCTGCTA NanostringSTA Stat4 399 GCCTCTATGGCCTCACCA 400 ACTTCCAGGAGTTGGCCC NanostringSTA Tbx21 401 TGGGAAGCTGAGAGTCGC 402 GCCTTCTGCCTTTCCACA NanostringSTA Tmed7 403 TGGTTAGCGTAGGGCAGG 404 CCCATGGGGATATGCACT NanostringSTA Traf3 405 ATCTGTGGGCGCTCTGAC 406 GGACTGTCAAGATGGGGC NanostringSTA Vav3 407 TTCTGGCAGGGACGAAAC 408 TTTGGTCCTGTGCCTTAC AA NanostringSTA Plac8 409 TGCTCCCCAAAATTCCAA 410 AGGAATGCCGTATCGGGT NanostringSTA Prf1 411 ACCAACCAGGACTGCTGC 412 CCCTGTGGACAGGAGCAC NanostringSTA Ptprj 413 TCACCTGGAGCAATGCAA 414 TGGTACCATTGGCATCCG NanostringSTA Rfk 415 TTTCCCTCTTGGTGGCCT 416 TCCCTCCCCACACCACTA NanostringSTA Rxra 417 TTGTTGGGCGACTTTTGC 418 TGGAGAGTTGAGGGACGA A NanostringSTA Skap2 419 TGGGTGAACATTCCTGCC 420 AAACAGCAACCCTCACCG NanostringSTA Socs3 421 TGCAGOAGAGCGGATTCT 422 GAACTGGCTGCGTGCTTC NanostringSTA Stat5a 423 CCTCCGCTAGAAGCTCCC 424 GCTCTTACACGAGAGGCC C NanostringSTA Tgfb1 425 CGCCTGAGTGGCTGTCTT 426 ATGTCATGGATGGTGCCC NanostringSTA Tmem126a 427 CTGCTTGAATATGGATCA 428 CCAACTAGTGCACCCCGT GCA NanostringSTA Trat1 429 CAATGGATGCCAACGTTT 430 CCTTGCCAGTCCCTGTGT C NanostringSTA Vax2 431 GGCCCCCGTGGACTATAG 432 CACACACACACGCACACG NanostringSTA Plag11 433 TTGAGACTGTATCCCCCA 434 GCAGGGTCTTCAAAGGTC GC AG NanostringSTA Prickle1 435 TGGGTTTCCACTTGCAGT 436 GCCTTTATTAAACACCTC T CCTG NanostringSTA Pycr1 437 CCCTGGGTGTGTGCAGTC 438 AAGGGGTTGAAAGGGGTG NanostringSTA Rngtt 439 CCCAAAAGACTGCATCGG 440 TCCACAGGGTAAGGCTGA A NanostringSTA Sav1 441 CGACCCCCAATGTAAGGA 442 TAGCCCACCCTGATGGAA NanostringSTA Ski 443 GGTCCCCTGCAGTGTCTG 444 CTTCCGTTTTCGTGGCTG NanostringSTA Spp1 445 CCATGACCACATGGACGA 446 CCAAGCTATCACCTCGGC NanostringSTA Stat5b 447 ACTCAGCGCCCACTTCAG 448 GCTCTGCAAAGGCGTTGT NanostringSTA Tgfb3 449 GCCAAAGTCCCCTGGAAT 450 AAGGAAGGCAGGAGGAGG NanostringSTA Tnfrsf12a 451 GGGAGCCTTCCAAGGTGT 452 GGCATTATAGCCCCTCCG NanostringSTA Trim24 453 CGGTGGTCCTTCGCC 454 TGCAGAGCCATTCAACAC A NanostringSTA Xbp1 455 GGACCTCATCAGCCAAGC 456 GCAGGTTTGAGATGCCCA NanostringSTA Plekhf2 457 CGGCAATATTGTTATCCA 458 GGGCGTCTTCCCACTTTT GAA NanostringSTA Prkca 459 TGCTGTCCCAGGGATGAT 460 CAAATAGCCCAGGATACC CA NanostringSTA Rab33a 461 GCTGGCTTGGCATCCTT 462 TTGATCTTCTCGCCCTCG NanostringSTA Rora 463 GATGTGGCAGCTGTGTGC 464 TTGAAGACATCGGGGCTC NanostringSTA Sema4d 465 TTCTTGGGCAGTGAACCC 466 TCGCGGGATCATCAACTT NanostringSTA Slamf7 467 CTCCATGAAGCTCAGCCA 468 TTGATTACGCAGGTGCCA A NanostringSTA Spry1 469 AGGACTTCCCTTCACGCC 470 AGCCAGGATTCAACTTTG TGA NanostringSTA Stat6 471 TGCTTTTGCCAGTGTGAC 472 ACGCCCAGGGAGTTTACA C NanostringSTA Tgfbr1 473 TGATGTCAGCTCTGGGCA 474 TCTGCAGCGAGAACCAAA NanostringSTA Tnfrsf13b 475 GGAAGGCACCAGGGATCT 476 CTCGTCGCAAGCCTCTGT NanostringSTA Trim25 477 TCTGCCTTGTGCCTGACA 478 ACGGGTGCATCAGCCTAA NanostringSTA Xrcc5 479 AGGGGACCTGGACTCTGG 480 GACAAGTTGGGGCCAATG NanostringSTA Pmepa1 481 GTGACCGCTTGATGGGG 482 GCTGTGTCGGCTGATGAA NanostringSTA Prkd3 483 CCTGGCCTCTCAGTTCCA 484 AGAGGCCTTTCAGCAGGC NanostringSTA Rad51ap1 485 AGCAGCCAAGTGCGGTAG 486 TGCCACAAGGAGAGGTCC NanostringSTA Rorc 487 CCTCTGACCCGTCTCCCT 488 GCTTCCAGAAGCCAGGGT NanostringSTA Sema7a 489 ATGAAAGGCTATGCCCCC 490 GTGCACAATGGTGGCCTT NanostringSTA Slc2a1 491 GACCCTGCACCTCATTGG 492 GAAGCCAGCCACAGCAAT NanostringSTA Stard10 493 AGGACCCAGGAGAGTCGG 494 ATCTCCACAGCCTGCACC NanostringSTA Sufu 495 ATGGGGAGTCCTTCTGCC 496 TAGGCCCTGCATCAGCTC NanostringSTA Tgfbr3 497 TCTGGGATTTGCCATCCA 498 GTGCAGGAAGAGCAGGGA NanostringSTA Tnfrsf25 499 CGAGCCATGTGGGAAAAG 500 GAGGCTGAGAGATGGGCA NanostringSTA Trps1 501 TTGTAACGCACTTTGAGA 502 CGTGCCTTTTTGGTAGCC TCC NanostringSTA Zeb1 503 AAGCGCTGTGTCCCTTTG 504 GTGAGATGCCCCACTGCT NanostringSTA Pm1 505 AATTTGGGTCCTCTCGGC 506 GCTCGAGATGCCAGTGCT NanostringSTA Prnp 507 CCTCCCACCTGGGATAGC 508 CCGTCACAGGAGGACCAA NanostringSTA Rasgrp1 509 CAAGCATGCAAAGTCTGA 510 CGTTATGAGCGGGGTTTG GC NanostringSTA Rpp14 511 GCAGCAGTGGTCTOGTCA 512 TGTCACCAACAGGGGCTT NanostringSTA Serpinb1a 513 CAAGGTGCTGGAGATGCC 514 GCGGCCCAGGTTAGAGTT NanostringSTA Slc6a6 515 GGTGCGTTCCTCATACCG 516 AGGCCAGGATGACGATGT NanostringSTA Stat1 517 GAGGTAGAGGCCTGGGGA 518 TTTAAGCTCTGCCGCCTC NanostringSTA Sult2b1 519 CGATGTCGTGGTCTCCCT 520 GTCCTCCTGCAGCTCCTC NanostringSTA Tgif1 521 GGACCCACTCCAAACCCT 522 CGGCAATCAGGACCGTAT NanostringSTA Tnfsfl1 523 AACAAGCCTTTCAGGGGG 524 AGAGATCTTGGCCCAGCC NanostringSTA Tsc22d3 525 TGCCAGTGTGCTCCAGAA 526 CTGTGCACAAAGCCATGC NanostringSTA Zfp161 527 CGCCAAGATTTCCGTGA 528 TCCCCGATTTCTTCCACA NanostringSTA Pou2af1 529 GCCCACTGGCCTTCATTT 530 TGGGATATCAAAGAAACT GTCA NanostringSTA Procr 533 GCCAAAACGTCACCATCC 532 ACGGCCACATCGAAGAAG NanostringSTA Rbpj 533 TCCCTTAAAACAGGAGCC 534 CTTCCCCTTGACAAGCCA A NanostringSTA Runx1 535 GCCTGAGAAAACGGTAGG 536 CATGTGCCTGATGGATTT G TT NanostringSTA Serpine2 537 TGAGCCATCAAAGGCAAA 538 GCTTGTTCACCTGGCCC NanostringSTA Smad3 539 ACGTGCCCCTGTCTGAAG 540 GAGTGGTGGGACAGGGC NanostringSTA Stat2 541 GCAACCAGGAACGCAGAC 542 TCTTCGGCAAGAACCTGG NanostringSTA Tal2 543 GGTGGAGGCAGCAGAGTG 544 CATCCTCATCTGGCAGGC NanostringSTA Tgm2 545 GAGTCTCAGTGCGAGCCA 546 ATGTCCTCCCGGTCATCA NanostringSTA Tnfsf8 547 ACGCCCCCAGAGAAGAGT 548 CTGGGTCAGGGGAAGGAG NanostringSTA Ube3a 549 TCGCATGTACAGTGAAAG 550 CTTTGGAAACGCCTCCCT AAGA NanostringSTA Zfp238 551 GCCTTGATTGACATGGGG 552 AAGAAAAAGGGAAAAACA ACCA NanostringSTA Prc1 553 TCCCAACCCTGTGCTCAT 554 CAGTGTGGGCAGAACTGG NanostringSTA Psmb9 555 TGGTTATGTGGACGCAGC 556 GGAAGGGACTTCTGGGGA NanostringSTA Re1 557 GCCCCTCTGGGATCAACT 558 GGGGTGAGTCACTGGTGG NanostringSTA Runx2 559 AAATCCTCCCCAAGTGGC 560 TGCAGAGTTCAGGGAGGG NanostringSTA Sertad1 561 CTGGGTGCCTTGGACTTG 562 CGCCTCATCCAACTCTGG NanostringSTA Smarca4 563 TACCGTGCCTCAGGGAAA 564 CCCCGGTCTTCTGCTTTT NanostringSTA Stat3 565 TTCAGCGAGAGCAGCAAA 556 AAATGCCTCCTCCTTGGG NanostringSTA Tap1 567 TCTCTCTTGCCTTGGGGA 568 GGCCCGAAACACCTCTCT NanostringSTA Timp2 569 GCTGGACGTTGGAGGAAA 570 CTCATCCGGGGAGGAGAT NanostringSTA Tnfsf9 571 GTTTCCCACATTGGCTGC 572 AGCCCGGGACTGTCTACC NanostringSTA Ubiad1 573 TACAGAGCGCTTGTCCCC 574 GCCACCATGCCATGTTTT NanostringSTA Zfp281 575 CCAGACGTAGTTGGGCAG 576 TGCTGCTGGCAGTTGGTA A NanostringSTA Zfp410 577 CTGAAAGAGCCTCACGGC 578 CCATCATGCACTCTGGGA Fluidigm&QPCR B2M 579 TTCTGGTGCTTGTCTCAC 580 CAGTATGTTCGGCTTCCC TGA ATTC Fluidigm&QPCR Aim1 581 GACGACTCCTTTCAGACC 582 AAATTTTCTCCATCATAA AAGT GCAACC Fluidigm&QPCR Cd44 583 GCATCGCGGTCAATAGTA 584 CACCGTTGATCACCAGCT GG T Fluidigm&QPCR Ifngr2 585 TCCTGTCACGAAACAACA 586 ACGGAATCAGGATGACTT GC GC Fluidigm&QPCR Il6st 587 TCCCATGGGCAGGAATAT 588 CCATTGGCTTCAGAAAGA AG GG Fluidigm&QPCR Klf7 589 AAGTGTAACCACTGCGAC 590 TCTTCATATGGAGCGCAA AGG GA Fluidigm&QPCR Mt2 591 CATGGACCCCAACTGCTC 592 AGCAGGAGCAGCAGCTTT Fluidigm&QPCR Nudt4 593 CTGCTGTGAGGGAAGTGT 594 CGAGCAGTCTGCCTAGCT ATGA TT Fluidigm&QPCR Pstpip1 595 AGCCCTCCTGTGGTGTGA 596 TGGTCTTGGGACTTCCAT TA GT Fluidigm&QPCR Rxra 597 GCTTCGGGACTGGTAGCC 598 GCGGCTTGATATCCTCAG TG Fluidigm&QPCR Sodl 599 CCAGTGCAGGACCTCATT 600 GGTCTCCAACATGCCTCT TT CT Fluidigm&QPCR Tgfb1 601 TGGAGCAACATGTGGAAC 602 CAGCAGCCGGTTACCAAG TC Fluidigm&QPCR GAPDH 603 GGCAAATTCAACGGCACA 604 AGATGGTGATGGGCTTCC GT C Fluidigm&QPCR Atf4 605 ATGATGGCTTGGCCAGTG 606 CCATTTTCTCCAACATCC AATC Fluidigm&QPCR Cmtm6 607 GATACTGGAAAAGTCAAG 608 AATGGGTGGAGACAAAAA TCATCG TGA Fluidigm&QPCR Il10 609 CAGAGCCACATGCTCCTA 610 GTCCAGCTGGTCCTTTGT GA TT Fluidigm&QPCR Il7r 611 CGAAACTCCAGAACCCAA 612 AATGGTGACACTTGGCAA GA GAC Fluidigm&QPCR Lamp2 613 TGCAGAATGGGAGATGAA 614 GGCACTATTCCGGTCATC TTT C Fluidigm&QPCR Myc 615 CCTAGTGCTGCATGAGGA 616 TCTTCCTCATCTTCTTGC GA TCTTC Fluidigm&QPCR Pcbp2 617 CAGCATTAGCCTGGCTCA 618 ATGGATGGGTCTGCTCTG GTA TT Fluidigm&QPCR Rasgrp1 619 GTTCATCCATGTGGCTCA 620 TCACAGCCATCAGCGTGT GA Fluidigm&QPCR Satb1 621 ATGGCGTTGCTGTCTCTA 622 CTTCCCAACCTGGATGAG GG C Fluidigm&QPCR Stat1 623 GCAGCACAACATACGGAA 624 TCTGTACGGGATCTTCTT AA GGA Fluidigm&QPCR Tgif1 625 CTCAGAGCAAGAGAAAGC 626 CGTTGATGAACCAGTTAG ACTG AGACC Fluidigm&QPCR HMBS 627 TCCCTGAAGGATGTGCCT 628 AAGGGTTTTCCCGTTTGC AC Fluidigm&QPCR B4galt1 629 GCCATCAATGGATTCCCT 630 CATTTGGACGTGATATAG AA ACATGC Fluidigm&QPCR Foxo1 631 CTTCAAGGATAAGGGCGA 632 GACAGATTGTGGCGAATT CA GA Fluidigm&QPCR Il16 633 CCACAGAAGGAGAGTCAA 634 GTGTTTTCCTGGGGATGC GGA T Fluidigm&QPCR Irf1 635 GAGCTGGGCCATTCACAC 636 TCCATGTCTTGGGATCTG G Fluidigm&QPCR Lmnb1 637 GGGAAGTTTATTCGCTTG 638 ATCTCCCAGCCTCCCATT AAGA Fluidigm&QPCR Myd88 639 TGGCCTTGTTAGACCGTG 640 AAGTATTTCTGGCAGTCC A TCCTC Fluidigm&QPCR Pmepa1 641 GCTCTTTGTTCCCCAGCA 642 CTACCACGATGACCACGA T TTT Fluidigm&QPCR Rkpj 643 AGTCTTACGGAAATGAAA 644 CCAACCACTGCCCATAAG AACGA AT Fluidigm&QPCR Sema4d 645 GACCCTGGTAACACCACA 646 TCACGACGTCATGCCAAG GG Fluidigm&QPCR Stat3 647 GGAAATAACGGTGAAGGT 648 CATGTCAAACGTGAGCGA GCT CT Fluidigm&QPCR Timp2 649 CGTTTTGCAATGCAGACG 650 GGAATCCACCTCCTTCTC TA G Fluidigm&QPCR HPRT 651 TCCTCCTCAGACCGCTTT 652 CCTGGTTCATCATCGCTA T ATC Fluidigm&QPCR Cand1 653 GAACTTCCGCCAGCTTCC 654 CTGGTAAGGCGTCCAGTA ATCT Fluidigm&QPCR Foxp1 655 CTGCACACCTCTCAATGC 656 GGAAGCGGTAGTGTACAG AG AGGT Fluidigm&QPCR Il17ra 657 TGGGATCTGTCATCGTGC 658 ATCACCATGTTTCTCTTG T ATCG Fluidigm&QPCR Irf4 659 ACAGCACCTTATGGCTCT 660 ATGGGGTGGCATCATGTA CTG GT Fluidigm&QPCR LOC100048299/// 661 CCAGCAAGACATTGATGA 662 GATCTTGCCTTCTCCAGT Max CC GC Fluidigm&QPCR Nampt 663 CCTGTTCCAGGCTATTCT 664 TCATGGTCTTTCCCCCAA GTTC G Fluidigm&QPCR Pml 665 AGGAACCCTCCGAAGACT 666 TTCCTCCTGTATGGCTTG ATG CT Fluidigm&QPCR Rel 667 TTGCAGAGATGGATACTA 668 CACCGAATACCCAAATTT TGAAGC TGAA Fluidigm&QPCR Sema7a 669 GGAGAGACCTTCCATGTG 670 AAGACAAAGCTATGGTCC CT TGGT Fluidigm&QPCR Stat5a 671 AAGATCAAGCTGGGGCAC 672 CATGGGACAGCGGTCATA TA C Fluidigm&QPCR Trim25 673 CCCTACGACCCTAAGTCA 674 TGTGGCTGTGCATGATAG AGC TG Fluidigm&QPCR pgk1 675 TACCTGCTGGCTGGATGG 676 CACAGCCTCGGCATATTT CT Fluidigm&QPCR Casp6 677 TGAAATGCTTTAACGACC 678 GTGGCTTGAAGTCGACAC TCAG CT Fluidigm&QPCR Hif1a 679 GCACTAGACAAAGTTCAC 680 CGCTATCCACATCAAAGC CTGAGA AA Fluidigm&QPCR Il21r 681 GGAGTGACCCCGTCATCT 682 AGGAGCAGCAGCATGTGA T G Fluidigm&QPCR Irf8 683 GAGCCAGATCCTCCCTGA 684 GGCATATCCGGTCACCAG CT T Fluidigm&QPCR Lsp1 685 CAAAGCGAGAGACCAGAG 686 AAGTGGACTTTGGCTTGG GA TG Fluidigm&QPCR Nfatc2 687 GATCGTAGGCAACACCAA 688 CTTCAGGATGCCTGCACA GG Fluidigm&QPCR Pou2af1 689 CATGCTCFGGCAAAAATC 690 ACTCGAACACCCTGGTAT C GG Fluidigm&QPCR Rela 691 CCCAGACCGCAGTATCCA 692 GCTCCAGGTCTCGCTTCT T T Fluidigm&QPCR Skap2 693 GTGCTCCCGACAAACGTA 694 CCCATTCCTCAGCATCTT TC TG Fluidigm&QPCR Stat5b 695 CGAGCTGGTCTTTCAAGT 696 CTGGCTGCCGTGAACAAT CA Fluidigm&QPCR Xbp1 697 TGACGAGGTTCCAGAGGT 698 TGCAGAGGTGCACATAGT G CTG Fluidigm&QPCR PPIA 699 ACGCCACTGTCGCTTTTC 700 GCAAACAGCTCGAAGGAG AC Fluidigm&QPCR Cd2 701 TGGGATGACTAGGCTGGA 702 AGTGGATCATGGGCTTTG GA AG Fluidigm&QPCR Icos 703 CGGCAGTCAACACAAACA 704 TCAGGGGAACTAGTCCAT A GC Fluidigm&QPCR Il24 705 AGAACCAGCCACCTTCAC 706 GTGTTGAAGAAAGGGCCA AC GT Fluidigm&QPCR Khdrbs1 707 CTCGACCCGTCCTTCACT 708 TTGACTCTCCCTTCTGAA C TCTTCT Fluidigm&QPCR Lta 709 TCCCTCAGAAGCACTTGA 710 GAGTTCTGCTTGCTGGGG CC TA Fluidigm&QPCR Nfatc3 711 GGGGCAGTGAAAGCCTCT 712 GCTTTTCACTATAGCCCA GGAG Fluidigm&QPCR Prf1 713 AATATCAATAACGACTGG 714 CATGTTTGCCTCTGGCCT CGTGT A Fluidigm&QPCR Rora 715 TTACGTGTGAAGGCTGCA 716 GGAGTAGGTGGCATTGCT AG CT Fluidigm&QPCR Ski 717 GAGAAAGAGACGTCCCCA 718 TCAAAGCTCTTGTAGGAG CA TAGAAGC Fluidigm&QPCR Stat6 719 TCTCCACGAGCTTCACAT 720 GACCACCAAGGGCAGAGA TG C Fluidigm&QPCR Xrcc5 721 GAAGATCACATCAGCATC 722 CAGGATTCACACTTCCAA TCCA CCT Fluidigm&QPCR RPL13A 723 ATCCCTCCACCCTATGAC 724 GCCCCAGGTAAGCAAACT AA T Fluidigm&QPCR Cd24a 725 ATCCCTCCACCCTATGAC 726 GCCCCAGGTAAGCAAACT AA T Fluidigm&QPCR Id2 727 GACAGAACCAGGCGTCCA 728 AGCTCAGAAGGGAATTCA GATG Fluidigm&QPCR Il2ra 729 TGTGCTCACAATGGAGTA 730 CTCAGGAGGAGGATGCTG TAAGG AT Fluidigm&QPCR Klf10 731 AGCCAACCATGCTCAACT 732 GGCTTTTCAGAAATTAGT TC TCCATT Fluidigm&QPCR Maf 733 TTCCTCTCCCGAATTTTT 734 CCACGGAGCATTTAACAA CA GG Fluidigm&QPCR Nfe212 735 CATGATGGACTTGGAGTT 736 CCTCCAAAGGATGTCAAT GC CAA Fluidigm&QPCR Prkca 737 ACAGACTTCAACTTCCTC 738 CTGTCAGCAAGCATCACC ATGGT TT Fluidigm&QPCR Runx1 739 CTCCGTGCTACCCACTCA 740 ATGACGGTGACCAGAGTG CT C Fluidigm&QPCR Slc2a1 741 ATGGATCCCAGCAGCAAG 742 CCAGTGTTATAGCCGAAC TGC Fluidigm&QPCR Sufu 743 TGTTGGAGGACTTAGAAG 744 AGGCCAGCTGTACTCTTT ATCTAACC GG Fluidigm&QPCR Zeb1 745 GCCAGCAGTCATGATGAA 746 TATCACAATACGGGCAGG AA TG Fluidigm&QPCR Ywhaz 747 AACAGCTTTCGATGAAGC 748 TGGGTATCCGATGTCCAC CAT AAT Fluidigm&QPCR Cd4 749 ACACACCTGTGCAAGAAG 750 GCTCTTGTTGGTTGGGAA CA TC Fluidigm&QPCR Ifi35 751 TGAGAGCCATGTCTGTGA 752 CTCCTGCAGCCTCATCTT CC G Fluidigm&QPCR Il4ra 753 GAGTGGAGTCCTAGCATC 754 CAGTGGAAGGCGCTGTAT ACG C Fluidigm&QPCR Klf6 755 TCCCACTTGAAAGCACAT 756 ACTTCTTGCAAAACGCCA CA CT Fluidigm&QPCR Mina 757 GAATCTGAGGACCGGATC 758 TGGGAAAGTACAACAAAT G CTCCA Fluidigm&QPCR Notch1 759 CTGGACCCCATGGACATC 760 AGGATGACTGCACACATT GC Fluidigm&QPCR Prkd3 761 TGGCTACCAGTATCTCCG 762 TGGTAAACGCTGCTGATG TGT TC Fluidigm&QPCR Runx3 763 TTCAACGACCTTCGATTC 764 TTGGTGAACACGGTGATT GT GT Fluidigm&QPCR Smarca4 765 AGAGAAGCAGTGGCTCAA 766 ATTTCTTCTGCCGGACCT GG C Fluidigm&QPCR Tap1 767 TTCCCTCAGGGCTATGAC 768 CTGTCGCTGACCTCCTGA AC C Fluidigm&QPCR Zfp36l1 769 TTCACGACACACCAGATC 770 TGAGCATCTTGTTACCCT CT TGC Fluidigm&QPCR B2M 771 TTCTGGTGCTTGTCTCAC 772 CAGTATGTTCGGCTTCCC TGA ATTC Fluidigm&QPCR 1700697 773 CCAGAGCTTGACCATCAT 774 TCCTTTACAAATCATACA N02Rik CAG GGACTGG Fluidigm&QPCR Armcx2 775 CCCTTCACCCTGGTCCTT 776 CTTCCTCGAATTAGGCCA GA Fluidigm&QPCR Ccr4 777 CTCAGGATCACTTTCAGA 778 GGCATTCATCTTTGGAAT AGAGC CG Fluidigm&QPCR Cebpb 779 TGATGCAATCCGGATCAA 780 CACGTGTGTTGCGTCAGT C Fluidigm&QPCR Emp1 781 AAGAGAGGACCAGACCAG 782 CTTTTTGGTGACTTCTGA CA GTAGAGAAT Fluidigm&QPCR Ier3 783 CAGCCGAAGGGTGCTCTA 784 AAATCTGGCAGAAGATGA C TGG Fluidigm&QPCR Itga3 785 AGGGGGAGACCAGAGTTC 786 GCCATTGGAGCAGGTCAA C Fluidigm&QPCR Lrrfip1 787 AGTCTCAGCGGCAATACG 788 GCAAACTGGAACTGCAGG AG AT Fluidigm&QPCR Nfkbiz 789 CAGCTGGGGAAGTCATTT 790 GGCAACAGCAATATGGAG TT AAA Fluidigm&QPCR Ptprj 791 CCAATGAGACCTTGAACA 792 GTAGGAGGCAGTGCCATT AAACT TG Fluidigm&QPCR Stat4 793 CGGCATCTGCTAGCTCAG 794 TGCCATAGTTTCATTGTT T AGAAGC Fluidigm&QPCR GAPDH 795 GGCAAATTCAACGGCACA 796 AGATGGTGATGGGCTTCC GT C Fluidigm&QPCR Acvr1b 797 AGAGGGTGGGGACCAAAC 798 TGCTTCATGTTGATTGTC TCG Fluidigm&QPCR Arnt1 799 GCCCCACCGACCTACTCT 800 TGTCTGTGTCCATACTTT CTTGG Fluidigm&QPCR Ccr8 801 AGAAGAAAGGCTCGCTCA 802 GGCTCCATCGTGTAATCC GA AT Fluidigm&QPCR Chd7 803 GAGGACGAAGACCCAGGT 804 CAGTGTATCGCTTCCTCT G TCAC Fluidigm&QPCR Fas 805 TGCAGACATGCTGTGGAT 806 CTTAACTGTGAGCCAGCA CT AGC Fluidigm&QPCR Il17f 807 CCCAGGAAGACATACTTA 808 CAACAGTAGCAAAGACTT GAAGAAA GACCA Fluidigm&QPCR Itgb1 809 TGGCAACAATGAAGCTAT 810 ATGTCGGGACCAGTAGGA CG CA Fluidigm&QPCR Map3k5 811 CAAGAAATTAGGCACCTG 812 ACACAGGAAACCCAGGGA AAGC TA Fluidigm&QPCR Notch2 813 TGCCTGTTTGACAACTTT 814 GTGGTCTGCACAGTATTT GAGT GTCAT Fluidigm&QPCR Rorc 815 ACCTCTTTTCACGGGAGG 816 TCCCACATCTCCCACATT A G Fluidigm&QPCR Tgfbr1 817 CAGCTCCTCATCGTGTTG 818 CAGAGGTGGCAGAAACAC G TG Fluidigm&QPCR HMBS 819 TCCCTGAAGGATGTGCCT 820 AAGGGTTTTCCCGTTTGC AC Fluidigm&QPCR Aes 821 TGCAAGCGCAGTATCACA 822 TGACGTAATGCCTCTGCA G TC Fluidigm&QPCR Batf 823 AGAAAGCCGACACCCTTC 824 CGGAGAGCTGCGTTCTGT A Fluidigm&QPCR Cd247 825 CCAGAGATGGGAGGCAAA 826 AGTGCATTGTATACGCCT C TCC Fluidigm&QPCR Clcf1 827 TATGACCTCACCCGCTAG 828 GGGCCCCAGGTAGTTCAG CT Fluidigm&QPCR Fip1l1 829 CGTTTCCCTATGGCAATG 830 CCCACTGCTTGGTGGTGT TC Fluidigm&QPCR Il1r1 831 TTGACATAGTGCTTTGGT 832 TCGTATGTCTTTCCATCT ACAGG GAAGC Fluidigm&QPCR Jun 833 CCAGAAGATGGTGTGGTG 834 CTGACCCTCTCCCCTTGC TTT Fluidigm&QPCR Mbnl3 835 GCCAAGAGTTTGCCATGT 836 CTTGCAGTTCTCACGAGT G GC Fluidigm&QPCR Nr3c1 837 TGACGTGTGGAAGCTGTA 838 CATTTCTTCCAGCACAAA AAGT GGT Fluidigm&QPCR Rppl4 839 GGAACGCGGTTATTCCAG 840 CATCTTCCAACATGGACA T CCT Fluidigm&QPCR Tmem126a 841 TAGCGAAGGTTGCGGTAG 842 GGTTTATGACTTTCCATC AC TTGGAC Fluidigm&QPCR HPRT 843 TCCTCCTCAGACCGCTTT 844 CCTGGTTCATCATCGCTA T ATC Fluidigm&QPCR Ahr 845 TGCACAAGGAGTGGACGA 846 AGGAAGCTGGTCTGGGGT AT Fluidigm&QPCR BC021614 847 CACATTCAAGGCTTCCTG 848 GTATTGGATTGGTACAGG TTT GTGAG Fluidigm&QPCR Cd274 849 CCATCCTGTTGTTCCTCA 850 TCCACATCTAGCATTCTC TTG ACTTG Fluidigm&QPCR Cmtm7 851 TCGCCTCCATAGTGATAG 852 CTCGCTAGGCAGAGGAAG CC C Fluidigm&QPCR Flna 853 GCAAGTGCACAGTCACAG 854 TTGCCTGCTGCTTTTGTG GT T Fluidigm&QPCR Il2 855 GCTGTTGATGGACCTACA 856 TTCAATTCTGTGGCCTGC GGA TT Fluidigm&QPCR Lad1 857 CTACAGCAGTTCCCTCAA 858 TGTCTTTCCTGGGGCTCA ACG T Fluidigm&QPCR Mta3 859 CTTTGTCGTGTATCATTG 860 TTGGTAGCTGGAGTTTGC GGTATT AG Fluidigm&QPCR Peci 861 AACGGTGCTGTGTTACTG 862 CAGCTGGGCCATTTACTA AGG CC Fluidigm&QPCR Sap30 863 CGGTGCAGTGTCAGGTTC 864 CTCCCGCAAACAACAGAG TT Fluidigm&QPCR Tnfrsfl2a 865 CCGCCGGAGAGAAAAGTT 866 CTGGATCAGTGCCACACC T Fluidigm&QPCR Pgk1 867 TAGCTGCTGGCTGGATGG 868 CACAGCCTCGGCATATTT CT Fluidigm&QPCR AI451617/// 869 CAACTGCAGAGTTTGGAG 870 TGTGTCTGCCTGTCCTGA Trim30 GA CT Fluidigm&QPCR Bcl11b 871 TCCCAGAGGGAACTCATC 872 CCAGACCCTCGTCTTCCT AC C Fluidigm&QPCR Cd28 873 CTGGCCCTCATCAGAACA 874 GGCGACTGCTTTACCAAA AT ATC Fluidigm&QPCR Ctla2b 875 GCCTCCTCTGTCAGTTGC 876 AAGCAGAGGATGAGCAGG TC AA Fluidigm&QPCR Foxp3 877 TCAGGAGCCCACCAGTAC 878 TCTGAAGGCAGAGTCAGG A AGA Fluidigm&QPCR Il21 879 GACATTCATCATTGACCT 880 TCACAGGAAGGGCATTTA CGTG GC Fluidigm&QPCR Lif 881 AAACGGCCTGCATCTAAG 882 AGCAGCAGTAAGGGCACA G AT Fluidigm&QPCR Myst4 883 GCAACAAAGGGCAGCAAG 884 AGACATCTTTAGGAAACC AAGACC Fluidigm&QPCR Peli2 885 TACACCTTGCGAGAGACC 886 GGACGTTGGTCTCACTTT AG CC Fluidigm&QPCR Sgk1 887 GATTGCCAGCAACACCTA 888 TTGATTTGTTCAGAGGGA TG CTTG Fluidigm&QPCR Tnfrsf25 889 CCCTGGCTTATCCCAGAC 890 AGATGCCAGAGGAGTTCC T AA Fluidigm&QPCR PPIA 891 ACQCCACFGTCGCTTTTC 892 GCAAACAGCTCGAAGGAG AC Fluidigm&QPCR Aqp3 893 CTGGGGACCCTCATCCTT 894 TGGTGAGGAAGCCACCAT Fluidigm&QPCR Bcl3 895 GAACAACAGCCTGAACAT 896 TCTGAGCGTTCACGTTGG GG Fluidigm&QPCR Cd74 897 GCCCTAGAGAGCCAGAAA 898 TGGTACAGGAAGTAAGCA GG GTGG Fluidigm&QPCR Ctsw 899 GGTTCAACCGGAGTTACT 900 TGGGCAAAGATGCTCAGA GG C Fluidigm&QPCR Gem 901 GACAGCATGGACAGCGAC 902 ACGACCAGGGTACGCTCA T TA Fluidigm&QPCR Il27ra 903 ACTTCCGOTACAAGGAAT 904 ACAGGAGTCAGCCCATCT GC GT Fluidigm&QPCR Litaf 905 TCCTGTGGCAGTCTGTGT 906 CTACGCAGAACGGGATGA CT AG Fluidigm&QPCR Ncf1 907 GGACACCTTCATTCGCCA 908 CTGCCACTTAACCAGGAA TA CAT Fluidigm&QPCR Plekhf2 909 GTCGGCGACTAGGAGGAC 910 TCCACCATCTTTTGCTAA T TAACC Fluidigm&QPCR Smad3 911 TCAAGAAGACGGGGCAGT 912 CCGACCATCCAGTGACCT T Fluidigm&QPCR Tnfsf8 913 GAGGATCTCTTCTGTACC 914 TTGTTGAGATGCTTTGAC CTGAAA ACTTG Fluidigm&QPCR RPL13A 915 ATCOCTCCACCCTATGAC 916 GCCCCAGGTAAGCAAACT AA T Fluidigm&QPCR Arhgef3 917 GTTGOTCCCATCCTCGTG 918 GATTGCTGCAGTAGCTGT CG Fluidigm&QPCR Bcl6 919 CTGCAGATGGAGCATGTT 920 GCCATTTCTGCTTCACTG GT G Fluidigm&QPCR Cd86 921 GAAGCCGAATCAGCCTAG 922 CAGCGTTACTATCCCGCT C CT Fluidigm&QPCR Cxcr4 923 TGCAACCGATCAGTGTGA 924 GGGCAGGAAGATCCTATT GT GA Fluidigm&QPCR Glipr1 925 TCCCCTAATGGAGCAAAT 926 TTATATGGCCACGTTGGG TTTA TAA Fluidigm&QPCR Il2rb 927 AGCATGGGGGAGACCTTC 928 GGGGCTGAAGAAGGACAA G Fluidigm&QPCR LOC100045833/// 929 TCTTGTGGCCCTACTGTG 930 GCAATGCAGAATCCATCA Ly6c1///Ly6c2 TG GA Fluidigm&QPCR Ncoa1 931 TGGCATGAACATGAGGTC 932 GCCAACATCTGAGCATTC AG AA Fluidigm&QPCR Prc1 933 TGGAAACTTTTCCTAGAG 934 TTTCCCCCTCGGTTTGTA TTTGAGA A Fluidigm&QPCR Smox 935 GATGGTTCGACAGTTCAC 936 GGAACCCCGGAAGTATGG AGG Fluidigm&QPCR Ubiad1 937 GTCTGGCTCCTTTCTCTA 938 ACTGATGAGGATGACGAG CACAG GTC Fluidigm&QPCR Ywhaz 939 AACAGCTTTCGATGAAGC 940 TGGGTATCCGATGTCCAC CAT AAT Fluidigm&QPCR Arid5a 941 CAGAGCAGGAGCCAGAGC 942 GCCAAGTTCATCATACAC GTTC Fluidigm&QPCR Casp3 943 GAGGCTGACTTCCTGTAT 944 AACCACGACCCGTCCTTT GCTT Fluidigm&QPCR Cd9 945 GATATTCGCCATTGAGAT 946 TGGTAGGTGTCCTTGTAA AGCC AACTCC Fluidigm&QPCR Elk3 947 GAGGGGCTTTGAGAGTGC 948 TGTCCTGTGTGCCTGTCT T TG Fluidigm&QPCR Golga3 949 ACAGAAAGTGGCAGATGC 950 TCTCGCTGGAACAATGTC AG AG Fluidigm&QPCR Irf9 951 TGAGGCCACCATTAGAGA 952 AGCAGCAGCGAGTAGTCT GG GA Fluidigm&QPCR LOC100046232/// 953 GGACCAGGGAGCAGAACC 954 GTCCGGCACAGGGTAAAT Nfil3 C Fluidigm&QPCR Nfkbie 955 CCTGGACCTCCAACTGAA 956 TCCTCTGCAATGTGGCAA GA T Fluidigm&QPCR Prnp 957 TCCAATTTAGGAGAGCCA 958 GCCGACATCAGTCCACAT AGC AG Fluidigm&QPCR Stat2 959 GGAACAGCTGGAACAGTG 960 GTAGCTGCCGAAGGTGGA GT Fluidigm&QPCR Zfp161 961 GGAGTGAGGAAGTTCGGA 962 TGGATTCGGGAGTCTCCA AA T Fluidigm&QPCR B2M 963 TTCTGGTGCTTGTCTCAC 964 CAGTATGTTCGGCTTCCC TGA ATTC Fluidigm&QPCR Abcg2 965 GCCTTGGAGTACTTTGCA 966 AAATCCGCAGGGTTGTTG TCA TA Fluidigm&QPCR Ccr5 967 GAGACATCCGTTCCCCCT 968 GTCGGAACTGACCCTTGA AC AA Fluidigm&QPCR Cxcr3 969 AGOCAGCACGAGACCTGA 970 GGCATCTAGCACTTGACG TTC Fluidigm&QPCR Fli1 971 AGACCATGGGCAAGAACA 972 GCCCCAGGATCTGATAAG CT G Fluidigm&QPCR Gzmb 973 GCTGCTCACTGTGAAGGA 974 TGGGGAATGCATTTTACC AGT AT Fluidigm&QPCR Il10ra 975 GCTCCCATTCCTCGTCAC 976 AAGGGCTTGGCAGTTCTG T Fluidigm&QPCR Il3 977 TACATCTGCGAATGACTC 978 GGCTGAGGTGGTCTAGAG TGC GTT Fluidigm&QPCR Klrd1 979 GGATTGGAATGCATTATA 980 TGCTCTGGCCTGATAACT GTGAAAA GAG Fluidigm&QPCR Plac8 981 CAGACCAGCCTGTGTGAT 982 CCAAGACAAGTGAAACAA TG AAGGT Fluidigm&QPCR Sertad1 983 TCCCTCTTCGTTCTGATT 984 GCTTGCGCTTCAGACCTT GG T Fluidigm&QPCR Tnfsf9 985 CGCCAAGCTACTGGCTAA 986 CGTACCTCAGACCTTGAG AA ATAGGT Fluidigm&QPCR GAPDH 987 GGCAAATTCAACGGCACA 988 AGATGGTGATGGGCTTCC GT C Fluidigm&QPCR Acvr2a 989 CCCTCCTGTACTTGTTCC 990 GCAATGGCTTCAACCCTA TACTCA GT Fluidigm&QPCR Ccr6 991 TTCGCCACTCTAATCAGT 992 TCTGGTGTAGAAAGGGAA AGGAC GTGG Fluidigm&QPCR Cxcr5 993 GAATGACGACAGAGGTTC 994 GCCCAGGTTGGCTTCTTA CTG T Fluidigm&QPCR Foxm1 995 ACTTTAAGCACATTGCCA 996 GGAGAGAAAGGTTGTGAC AGC GAA Fluidigm&QPCR Hip1r 997 AGTGAGCAAGCTGGACGA 998 GAAGCCAGGTACTGGGTG C TG Fluidigm&QPCR Il12rb1 999 CGCAGCCGAGTAATGTAC 1000 AACGGGAAATCTGCACCT AAG C Fluidigm&QPCR Il9 1001 GCCTCTGTTTTGCTCTTC 1002 GCATTTTGACGGTGGATC AGTT A Fluidigm&QPCR LOC100046643/// 1003 TAGGTCAGATCGGGTCAT 1004 GTGGGGTCCTCTTTCAAG Spry1 CC G Fluidigm&QPCR Prdm1 1005 TGCGGAGAGGCTCCACTA 1006 TGGGTTGCTTTCCGTTTG Fluidigm&QPCR Socs3 1007 ATTTCGCTTCGGGACTAG 1008 AACTTGCTGTGGGTGACC C AT Fluidigm&QPCR Trim24 1009 ATCCAGCAGCCTTCCATC 1010 GGCTTAGGGCTGTGATTC T TG Fluidigm&QPCR HMBS 1011 TCCCTGAAGGATGTGCCT 1012 AAGGGTTTTCCCGTTTGC AC Fluidigm&QPCR Anxa4 1013 TGATGCTCTTATGAAGCA 1014 CGTCTGTCCCCCATCTCT GGAC T Fluidigm&QPCR Cd51 1015 GAGGACACATGGATGGAA 1016 ACCCTTGTGTAGCACCTC TGT CA Fluidigm&QPCR Daxx 1017 CAGGCCACTGGTCTCTCC 1018 TCCGTCTTACACACTTCA AGGA Fluidigm&QPCR Gap43 1019 CGGAGACTGCAGAAAGCA 1020 GGTTTGGCTTCGTCTACA G GC Fluidigm&QPCR Id3 1021 GAGGAGCTTTTGCCACTG 1022 GCTCATCCATGCCCTCAG AC Fluidigm&QPCR Il12rb2 1023 TGTGGGGTGGAGATCTCA 1024 TCTCCTTCCTGGACACAT GT GA Fluidigm&QPCR Inhba 1025 ATCATCACCTTTGCCGAG 1028 TCACTGCCTTCCTTGGAA TC AT Fluidigm&QPCR Maff 1027 GACAAGCACGCACTGAGC 1026 CATTTTCGCAGAAGATGA CCT Fluidigm&QPCR Prickle1 1029 ATGGATTCTTTGGCGTTG 1030 TGACGGTCTTGGCTTGCT TC Fluidigm&QPCR Spp1 1031 GGAGGAAACCAGCCAAGG 1032 TGCCAGAATCAGTCACTT TCAC Fluidigm&QPCR Trps1 1033 ACTCTGCAAACAACAGAA 1034 TCTTTTTCCGGACCATAT GACG CTGT Fluidigm&QPCR HPRT 1035 TCCTCCTCAGACCGCTTT 1036 CCTGGTTCATCATCGCTA T ATC Fluidigm&QPCR Bcl2l11 1037 GGAGACGAGTTCAACGAA 1038 AACAGTTGTAAGATAACC ACTT ATTTGAGG Fluidigm&QPCR Cd80 1039 TCGTCTTTCACAACTGTC 1040 TTGCCAGTAGATTCGGTC TTCAG TTC Fluidigm&QPCR Dntt 1041 GAGCAGCAGCTCTTGCAT 1042 GATGTCGCAGTACAAAAG AA CAAC Fluidigm&QPCR Gata3 1043 TTATCAAGCCCAAGCGAA 1044 TGGTGGTGGTCTGACAGT G TC Fluidigm&QPCR Ifih1 1045 CTATTAACCGTGTTCAAA 1046 CACCTGCAATTCCAAAAT ACATGAA CTTA Fluidigm&QPCR Il15ra 1047 CCAGTGCCAACAGTAGTG 1048 TTGGGAGAGAAAGCTTCT ACA GG Fluidigm&QPCR Irf7 1049 CTTCAGCACTTTCTTCCG 1050 TGTAGTGTGGTGACCCTT AGA GC Fluidigm&QPCR Mgl1 1051 TCGGAACAAGTCGGAGGT 1052 TCAGCAGCTGTATGCCAA AG Fluidigm&QPCR Procr 1053 AGCGCAAGGAGAACGTGT 1054 GGGTTCAGAGCCCTCCTC Fluidigm&QPCR Stard10 1055 GAGCTGCGTCATCACCTA 1056 TGCAGGCCTTGTACATCT CC TCT Fluidigm&QPCR Tsc22d3 1057 GGTGGCCCTAGACAACAA 1058 TCAAGCAGCTCACGAATC GA TG Fluidigm&QPCR Pgk1 1059 TAGCTGCTGGCTGGATGG 1060 CACAGCCTCGGCATATTT CT Fluidigm&QPCR Casp1 1061 CCCACTGCTGATAGGGTG 1062 GCATAGGTACATAAGAAT AC GAACTGGA Fluidigm&QPCR Cd83 1063 TGGTTCTGAAGGTGACAG 1064 CAACCAGAGAGAAGAGCA GA ACAC Fluidigm&QPCR Dpp4 1065 CGGTATCATTTAGTAAAG 1066 GTAGAGTGTAGAGGCGCA AGGCAAA GACC Fluidigm&QPCR Gfi1 1067 TCCGAGTTCGAGGACTTT 1068 GAGCGGCACAGTGACTTC TG T Fluidigm&QPCR Ifit1 1069 TCTAAACAGGGCCTTGCA 1070 GCAGAGCCCTTTTTGATA G ATGT Fluidigm&QPCR Il17a 1071 CAGGGAGAGCTTCATCTG 1072 GCTGAGCTTTGAGGGATG TGT AT Fluidigm&QPCR Isg20 1073 TTGGTGAAGCCAGGCTAG 1074 CTTCAGGGCATTGAAGTC AG GT Fluidigm&QPCR Mt1 1075 CACCAGATCTCGGAATGG 1076 AGGAGCAGCAGCTCTTCT AC TG Fluidigm&QPCR Psmb9 1077 CGCTCTGCTGAGATGCTG 1078 CTCCACTGCCATGATGGT T Fluidigm&QPCR Sult2b1 1079 ACTTCCTGTTTATCACCT 1080 AACTCACAGATGCGTTGC ATGAGGA AC Fluidigm&QPCR Vav3 1081 TTACACGAAGATGAGTGC 1082 CAACACTGGATAGGACTT AAATG TATTCATC Fluidigm&QPCR PPIA 1083 ACGCCACTGTCGCTTTTC 1084 GCAAACAGCTCGAAGGAG AC Fluidigm&QPCR Casp4 1085 TCCAGACATTCTTCAGTG 1086 TCTGGTTCCTCCATTTCC TGGA AG Fluidigm&QPCR Creb3l2 1087 CCAGCCAGCATCCTCTGT 1088 AGCAGGTTCCTGGATCTC AC Fluidigm&QPCR Egr2 1089 CTACCCGGTGGAAGACCT 1090 AATGTTGATCATGCCATC C TCC Fluidigm&QPCR Gja1 1091 TCCTTTGACTTCAGCCTC 1092 CCATGTCTGGGCACCTCT CA Fluidigm&QPCR Ifitm2 1093 TGGTCTGGTCCCTGTTCA 1094 CTGGGCTCCAACCACATC AT Fluidigm&QPCR Il1rn 1095 TGTGCCAAGTCTGGAGAT 1096 TTCTTTGTTCTTGCTCAG GA ATCAGT Fluidigm&QPCR Jak3 1097 TGGAAGACCCGGATAGCA 1098 GTCTAGCGCTGGGTCCAC Fluidigm&QPCR Mxi1 1099 CAAAGCCAAAGCACACAT 1100 AGTCGCCGCTTTAAAAAC CA CT Fluidigm&QPCR Rad51ap1 1101 AAAGCAAGAGGCCCAACT 1102 TGCATTGCTGCTAGAGTT G CC Fluidigm&QPCR Tbx21 1103 TCAACCAGCACCAGACAG 1104 AAACATCCTGTAATGGCT AG TGTG Fluidigm&QPCR Xcl1 1105 GAGACTTCTCCTCCTGAC 1106 GGACTTCAGTCCCCACAC TTTCC C Fluidigm&QPCR RPL13A 1107 ATCCCTCCACCCTATGAC 1108 GCCCCAGGTAAGCAAACT AA T Fluidigm&QPCR Ccl20 1109 AACTGGGTGAAAAGGGCT 1110 GTCCAATTCCATCCCAAA GT AA Fluidigm&QPCR Csf2 1111 GCATGTAGAGGCCATCAA 1112 CGGGTCTGCACACATGTT AGA A Fluidigm&QPCR Errfi1 1113 TGCTCAGGAGCACCTAAC 1114 TGGAGATGGACCACACTC AAC TG Fluidigm&QPCR Gp49a/// 1115 TGCACTCCTGGTGTCATT 1116 TGTGTGTTCTTCACAGAA Lilrb4 CC GCATT Fluidigm&QPCR Ifng 1117 ATCTGGAGGAACTGGCAA 1118 TTCAAGACTTCAAAGAGT AA CTGAGGTA Fluidigm&QPCR Il22/// 1119 TTTCCTGACCAAACTCAG 1120 TCTGGATGTTCTGGTCGT Iltifb CA CA Fluidigm&QPCR Kat2b 1121 GGAGAAACTCGGCGTGTA 1122 CAGCCATTGCATTTACAG CT GA Fluidigm&QPCR Nkg7 1123 TCTACCTAGGCTGGGTCT 1124 CCGACGGGTTCTACAGTG CCT AG Fluidigm&QPCR Serpinb1a 1125 GGATTTTCTGCATGCCTC 1126 GACAACAGTTCTGGGATT TG TTCC Fluidigm&QPCR Tgm2 1127 CTCACGTTCGGTGCTGTG 1128 TCCCTCCTCCACATTGTC A Fluidigm&QPCR Zfp238 1129 TGCATCTGTCTCTCTTAG 1130 TCTGGAAACTCCATACTG TCTGCT TCTTCA Fluidigm&QPCR Ywhaz 1131 AACAGCTTTCGATGAAGC 1132 TGGGTATCCGATGTCCAC CAT AAT Fluidigm&QPCR Ccl4 1133 GCCCTCTCTCTCCTCTTG 1134 GAGGGTCAGAGCCCATTG CT Fluidigm&QPCR Cxcl10 1135 GCTGCCGTCATTTTCTGC 1336 TCTCACTGGCCCGTCATC Fluidigm&QPCR Etv6 1137 TCCCTTTCGCTGTGAGAC 1138 GGGCGTGTATGAAATTCG AT TT Fluidigm&QPCR Grn 1139 TGGCTAATGGAAATTGAG 1140 CATCAGGACCCACATGGT GTG CT Fluidigm&QPCR Ikzf4 1141 GCAGACATGCACACACCA 1142 TGAGAGCTCCCTCTCCAG C AT Fluidigm&QPCR Il23r 1143 CCAAGTATATTGTGCATG 1144 AGCTTGAGGCAAGATATT TGAAGA GTTGT Fluidigm&QPCR Klf9 1145 CTCCGAAAAGAGGCACAA 1146 GCGAGAACTTTTTAAGGC GT AGTC Fluidigm&QPCR Phlda1 1147 CGCACCAGCCTCTTCACT 1148 TTCCGAAGTCCTCAAAAC CTT Fluidigm&QPCR Serpine2 1149 TTGGGTCAAAAATGAGAC 1150 CCTTGAAATACACTGCAT CAG TAACGA Fluidigm&QPCR Tnfrsfl3b 1151 GAGCTCGGGAGACCACAG 1152 TGGTCGCTACTTAGCCTC AAT Fluidigm&QPCR Zfp281 1153 GGAGAGGACGGCGTTATT 1154 TTTTCATACCCCGGAGGA TT G
(164) TABLE-US-00013 TABLES6.2 RNAisequences Duplex SEQ Catalog Gene GENE Gene ID Number Symbol ID Accession NO: Sequence D-040676-01 Acvr2a 11480 NM_007396 1155 CAAAGAAUCUAGUCUAUGA D-040676-02 Acvr2a 11480 NM_007396 1156 UGACAGGACUGAUUGUAUA D-040676-03 Acvr2a 11480 NM_007396 1157 GCAGAAACAUGCAGGAAUG D-040676-04 Acvr2a 11480 NM_007396 1158 GGCAAUAUGUGUAAUGAAA D-044066-01 Ahr 11622 NM_013464 1159 CCAAUGCACGCUUGAUUUA D-044066-02 Ahr 11622 NM_013464 1160 GAAGGAGAGUUCUUGUUAC D-044066-03 Ahr 11622 NM_013464 1161 CCGCAAGAUGUUAUUAAUA D-044066-04 Ahr 11622 NM_013464 1162 CCAGUUCUCUUAUGAGUGC D-054696-01 Arid5a 214855 NM_145996 1163 GGAAGAACGUGUAUGAUGA D-054696-02 Arid5a 214855 NM_145996 1164 GAAGAGGGAUUCGCUCAUG D-054696-03 Arid5a 214855 NM_145996 1165 CCUCUAAACUUCACCGGUA D-054696-04 Arid5a 214855 NM_145996 1166 GGUCAUCCCUGCUUUCCCA D-040483-02 ARNTL 11865 NM_007489 1167 GCAUCGAUAUGAUAGAUAA D-040483-03 ARNTL 11865 NM_007489 1168 CAGUAAAGGUGGAAGAUAA D-040483-04 ARNTL 11865 NM_007489 1169 GAAAUACGGGUGAAAUCUA D-040483-17 ARNTL 11865 NM_007489 1170 UGUCGUAGGAUGUGACCGA D-049093-01 Batf 53314 NM_016767 1171 GAACGCAGCUCUCCGCAAA D-049093-02 Batf 53314 NM_016767 1172 UCAAACAGCUCACCGAGGA D-049093-03 Batf 53314 NM_016767 1173 GAGGAAAGUUCAGAGGAGA D-049093-04 Batf 53314 NM_016767 1174 UCAAGUACUUCACAUCAGU D-058452-01 CCR5 12774 NM_009917 1175 GGAGUUAUCUCUCAGUGUU D-058452-02 CCR5 12774 NM_009917 1176 UGAAGUUUCUACUGGUUUA D-058452-03 CCR5 12774 NM_009917 1177 CCUAUGACAUCGAUUAUGG D-058452-04 CCR5 12774 NM_009917 1178 UGAAACAAAUUGCGGCUCA D-062489-01 CCR6 12458 NM_009835 1179 GCACAUAUGCGGUCAACUU D-062489-02 CCR6 12458 NM_009835 1180 CCAAUUGCCUACUCCUUAA D-062489-03 CCR6 12458 NM_009835 1181 GAACGGAUGAUUAUGACAA D-062489-04 CCR6 12458 NM_009835 1182 UGUAUGAGAAGGAAGAAUA D-040286-04 EGR1 13653 NM_007913 1183 CGACAGCAGUCCCAUCUAC D-040286-01 EGR1 13653 NM_007913 1184 UGACAUCGCUCUGAAUAAU D-040286-02 EGR1 13653 NM_007913 1185 ACUCCACUAUCCACUAUUA D-040286-03 EGR1 13653 NM_007913 1186 AUGCGUAACUUCAGUCGUA D-040303-01 Egr2 13654 NM_010118 1187 GAAGGUAUCAUCAAUAUUG D-040303-02 Egr2 13654 NM_010118 1188 GAUCUCCCGUAUCCGAGUA D-040303-03 Egr2 13654 NM_010118 1189 UCUCUACCAUCCGUAAUUU D-040303-04 Egr2 13654 NM_010118 1190 UGACAUGACUGGAGAGAAG D-058294-01 ELK3 13713 NM_013508 1191 GUAGAGAUCAGCCGGGAGA D-058294-02 ELK3 13713 NM_013508 1192 GAUCAGGUUUGUGACCAAU D-058294-03 ELK3 13713 NM_013508 1193 UCUUUAAUGUUGCCAAAUG D-058294-04 ELK3 13713 NM_013508 1194 UGAGAUACUAUUACGACAA D-050997-21 Ets1 23871 NM_001038642 1195 GCUUAGAGAUGUAGCGAUG D-050997-22 Ets1 23871 NM_001038642 1196 CCUGUUACACCUCGGAUUA D-050997-23 Ets1 23871 NM_001038642 1197 CAGCUACGGUAUCGAGCAU D-050997-24 Ets1 23871 NM_001038642 1198 UCAAGUAUGAGAACGACUA D-040983-01 ETS2 23872 NM_011809 1199 GAUCAACAGCAAUACAUUA D-040983-02 ETS2 23872 NM_011809 1200 UCAAUUUGCUCAACAACAA D-040983-03 ETS2 23872 NM_011809 1201 UAGAGCAGAUGAUCAAAGA D-040983-04 ETS2 23872 NM_011809 1202 GAAUGACUUUGGAAUCAAG D-058395-01 Etv6 14011 NM_007961 1203 GAACAAACAUGACCUAUGA D-058395-02 Etv6 14011 NM_007961 1204 CAAAGAGGAUUUCCGCUAC D-058395-03 Etv6 14011 NM_007961 1205 GCAUUAAGCAGGAACGAAU D-058395-04 Etv6 14011 NM_007961 1206 CGCCACUACUACAAACUAA D-045283-04 Fas 14102 NM_007987 1207 GAGUAAAUACAUCCCGAGA D-045283-03 Fas 14102 NM_007987 1208 GGAGGCGGGUUCAUGAAAC D-045283-02 Fas 14102 NM_007987 1209 CGCAGAACCUUAGAUAAAU D-045283-01 Fas 14102 NM_007987 1210 GUACCAAUCUCAUGGGAAG D-041127-01 Foxo1 56458 NM_019739 1211 GAAGACACCUUUACAAGUC D-041127-02 Foxo1 56458 NM_0i9739 1212 GGACAACAACAGUAAAUUU D-041127-03 Foxo1 56458 NM_019739 1213 GGAGAUACCUUGGAUUUUA D-041127-04 Foxo1 56458 NM_019739 1214 GAAAUCAGCAAUCCAGAAA D-040670-01 GATA3 14462 NM_008091 1215 GAAGAUGUCUAGCAAAUCG D-040670-02 GATA3 14462 NM_008091 1216 CGGAAGAUGUCUAGCAAAU D-040670-03 GATA3 14462 NM_008091 1217 GUACAUGGAAGCUCAGUAU D-040670-04 GATA3 14462 NM_008091 1218 AGAAAGAGUGCCUCAAGUA D-060495-01 Id2 15902 NM_010496 1219 CAUCUGAAUUCCCUUCUGA D-060495-02 Id2 15902 NM_010496 1220 GAACACGGACAUCAGCAUC D-060495-03 Id2 15902 NM_010496 1221 GUCGAAUGAUAGCAAAGUA D-060495-04 Id2 15902 NM_010496 1222 CGGUGAGGUCCGUUAGGAA D-051517-01 Ikzf4 22781 NM_011772 1223 GAUGGUGCCUGACUCAAUG D-051517-02 Ikzf4 22781 NM_011772 1224 CGACUGAACGGCCAACUUU D-051517-03 Ikzf4 22781 NM_011772 1225 GUGAAGGCCUUUAAGUGUG D-051517-04 Ikzf4 22781 NM_011772 1226 GAACUCACACCUGUCAUCA D-040810-01 IL17RA 16172 NM_008359 1227 GGACAGAUUUGAGGAGGUU D-040810-02 IL17RA 16172 NM_008359 1228 GAAUAGUACUUGUCUGGAU D-040810-03 IL17RA 16172 NM_008359 1229 UCUGGGAGCUCGAGAAGAA D-040810-04 IL17RA 16172 NM_008359 1230 GAGAGCAACUCCAAAAUCA D-040007-04 IL6ST 16195 NM_010560 1231 GUCCAGAGAUUUCACAUUU D-040007-03 IL6ST 16195 NM_010560 1232 AGACUUACCUUGAAACAAA D-040007-02 IL6ST 16195 NM_010560 1233 GAACUUCACUGCCAUUUGU D-040007-01 IL6ST 16195 NM_010560 1234 GCACAGAGCUGACCGUGAA D-057981-04 IL7R 16197 NM_008372 1235 GGAUUAAACCUGUCGUAUG D-057981-03 IL7R 16197 NM_008372 1236 UAAGAUGCCUGGCUAGAAA D-057981-02 IL7R 16197 NM_008372 1237 GCAAACCGCUCGCCUGAGA D-057981-01 IL7R 16197 NM_008372 1238 GAAAGUCGUUUAUCGCAAA D-043796-04 IRF4 16364 NM_013674 1239 CCAUAUCAAUGUCCUGUGA D-043796-03 IRF4 16364 NM_013674 1240 CGAGUUACCUGAACACGUU D-043796-02 IRF4 16364 NM_013674 1241 UAUCAGAGCUGCAAGUGUU D-043796-01 IRF4 16364 NM_013674 1242 GGACACACCUAUGAUGUUA D-040737-01 Irf8 15900 NM_008320 1243 GGACAUUUCUGAGCCAUAU D-040737-02 Irf8 15900 NM_008320 1244 GAGCGAAGUUCCUGAGAUG D-040737-03 Irf8 15900 NM_008320 1245 GCAAGGGCGUGUUCGUGAA D-040737-04 Irf8 15900 NM_008320 1246 GCAACGCGGUGGUGUGCAA D-042246-04 ITGA3 16400 NM_013565 1247 GCGAUGACUGGCAGACAUA D-042246-03 ITGA3 16400 NM_013565 1248 GAGUGGCCCUAUGAAGUUA D-042246-02 ITGA3 16400 NM_013565 1249 GGACAAUGUUCGCGAUAAA D-042246-01 ITGA3 16400 NM_013565 1250 CCAGACACCUCCAACAUUA D-043776-01 Jun 16476 NM_010591 1251 GAACAGGUGGCACAGCUUA D-043776-02 Jun 16476 NM_010591 1252 GAAACGACCUUCUACGACG D-043776-03 Jun 16476 NM_010591 1253 CCAAGAACGUGACCGACGA D-043776-04 Jun 16476 NM_010591 1254 GCCAAGAACUCGGACCUUC D-041158-04 JUNB 16477 NM_008416 1255 CAACCUGGCGGAUCCCUAU D-041158-03 JUNB 16477 NM_008416 1256 CAACAGCAACGGCGUGAUC D-041158-02 JUNB 16477 NM_008416 1257 UGGAACAGCCUUUCUAUCA D-041158-01 JUNB 16477 NM_008416 1258 ACACCAACCUCAGCAGUUA D-049885-01 Kat2b 18519 NM_020005 1259 GCAGUAACCUCAAAUGAAC D-049885-02 Kat2b 18519 NM_020005 1260 UCACAUAUGCAGAUGAGUA D-049885-03 Kat2b 18519 NM_020005 1261 GAAGAACCAUCCAAAUGCU D-049885-04 Kat2b 18519 NM_020005 1262 AAACAAGCCCAGAUUCGAA D-047145-02 LRRFIP1 16978 NM_001111312 1263 GAAGGGCUCCCGUAACAUG D-047145-17 LRRFIP1 16978 NM_001111312 1264 AAAGAGGCCCUGCGGCAAA D-047145-18 LRRFIP1 16978 NM_001111312 1265 GCUCGAGAGAUCCGGAUGA D-047145-19 LRRFIP1 16978 NM_001111312 1266 AGACACAGUAAAUGACGUU D-063455-01 Mina 67014 NM_025910 1267 GUNNACAGUUGCCAAGGUU D-063455-02 Mina 67014 NM_025910 1268 GCACCUACCAGAACAAUUC D-063455-03 Mina 67014 NM_025910 1269 GAAAUGGAACGGAGACGAU D-063455-04 Mina 67014 NM_025910 1270 GGUCACCAAUUCGUGUUAA D-040813-01 MYC 17869 NM_010849 1271 GACGAGACCUUCAUCAAGA D-040813-02 MYC 17869 NM_010849 1272 GACAGCAGCUCGCCCAAAU D-040813-03 MYC 17869 NM_010849 1273 GAAUUUCUAUCACCAGCAA D-040813-04 MYC 17869 NM_010849 1274 CUACAGCCCUAUUUCAUCU D-063057-04 MYD88 17874 NM_010851 1275 GAUGAUCCGGCAACUAGAA D-063057-03 MYD88 17874 NM_010851 1276 GUUAGACCGUGAGGAUAUA D-063057-02 MYD88 17874 NM_010851 1277 CGACUGAUUCCUAUUAAAU D-063057-01 MYD88 17874 NM_010851 1278 GCCUAUCGCUGUUCUUGAA D-041128-01 NCOA1 17977 NM_010881 1279 GAACAUGAAUCCAAUGAUG D-041128-02 NCOA1 17977 NM_010881 1280 GAACAUGGGAGGACAGUUU D-041128-03 NCOA1 17977 NM_010881 1281 UCAAGAAUCUGCUACCAAA D-041128-04 NCOA1 17977 NM_010881 1282 CCAAGAAGAUGGUGAAGAU D-047764-01 Nfkb1 18033 NM_008689 1283 GACAUGGGAUUUCAGGAUA D-047764-02 Nfkb1 18033 NM_008689 1284 GGAUUUCGAUUCCGCUAUG D-047764-03 Nfkb1 18033 NM_008689 1285 CUACGGAACUGGGCAAAUG D-047764-04 Nfkb1 18033 NM_008689 1286 GGAAACGCCAGAAGCUUAU D-041110-01 NOTCH1 18128 NM_008714 1287 GAACAACUCCUUCCACUUU D-041110-02 NOTCH1 18128 NM_008714 1288 GGAAACAACUGCAAGAAUG D-041110-03 NOTCH1 18128 NM_008714 1289 GAACCACGCUACACAGGAA D-041110-04 NOTCH1 18128 NM_008714 1290 GAAGGUGUAUACUGUGAAA D-045970-01 Nr3c1 14815 NM_008173 1291 GAUCGAGCCUGAGGUGUUA D-045970-02 Nr3c1 14815 NM_008173 1292 UUACAAAGAUUGCAGGUAU D-045970-03 Nr3G1 14815 NM_008173 1293 GCCAAGAGUUAUUUGAUGA D-045970-04 Nr3c1 14815 NM_008173 1294 GCAUGUAUGACCAAUGUAA D-048514-04 PML 18854 NM_008884 1295 GCGCAAGUCCAAUAUCUUC D-048514-03 PML 18854 NM_008884 1296 AGUGGUACCUCAAGCAUGA D-048514-02 PML 18854 NM_008884 1297 GCGCAGACAUUGAGAAGCA D-048514-01 PML 18854 NM_008884 1298 CAGCAUAUCUACUCCUUUA D-048879-01 POU2AF1 18985 NM_011136 1299 GAAGAAAGCGUGGCCAUAC D-048879-02 POU2AF1 18985 NM_011136 1300 CGGAGUAUGUGUCCCAUGA D-048879-03 POU2AF1 18985 NM_011136 1301 UCACUAAUGUCACGCCAAG D-048879-04 POU2AF1 18985 NM_011136 1302 GCAACACGUACGAGCUCAA D-043089-09 Prdm1 12142 NM_007548 1303 GGAGAGACCCACCUACAUA D-043069-10 Prdm1 12142 NM_007548 1304 CCAAUACAGUAGUGAGAAA D-043069-11 Prdm1 12142 NM_007548 1305 GGAAGGACAUCUACCGUUC D-043069-21 Prdm1 12142 NM_007548 1306 GUACAUACAUAGUGAACGA D-042664-04 PROCR 19124 NM_011171 1307 UAUCUGACCCAGUUCGAAA D-042664-03 PROCR 19124 NM_011171 1308 UAACUCCGAUGGCUCCCAA D-042664-02 PROCR 19124 NM_011171 1309 GUAAGUUUCCGGCCAAAGA D-042664-01 PROCR 19124 NM_011171 1310 CCAAACAGGUCGCUCUUAC D-042742-01 Rbpj 19664 NM_001080928 1311 CCAAACGACUCACUAGGGA D-042742-02 Rbpj 19664 NM_001080928 1312 UCUCAACCCUGUGCGUUUA D-042742-03 Rbpj 19664 NM_001080928 1313 GCAGACGGCAUUACUGGAU D-042742-04 Rbpj 19664 NM_001080928 1314 GUAGAAGCCGAAACAAUGU D-040776-01 Rela 19697 NM_009045 1315 GGAGUACCCUGAAGCUAUA D-040776-02 Rela 19697 NM_009045 1316 GAAGAAGAGUCCUUUCAAU D-040776-03 Rela 19697 NM_009045 1317 UAUGAGACCUUCAAGAGUA D-040776-04 Rela 19697 NM_009045 1318 GAAUCCAGACCAACAAUAA D-042209-01 Rorc 19885 NM_011281 1319 UGAGUAUAGUCCAGAACGA D-042209-02 Rorc 19885 NM_011281 1320 CAAUGGAAGUCGUCCUAGU D-042209-03 Rorc 19885 NM_011281 1321 GAGUGGAACAUCUGCAAUA D-042209-04 Rorc 19885 NM_011281 1322 GCUCAUCAGCUCCAUAUUU D-048982-01 RUNX1 12394 NM_001111022 1323 UGACCACCCUGGCGAGCUA D-048982-02 RUNX1 12394 NM_001111022 1324 GCAACUCGCCCACCAACAU D-048982-03 RUNX1 12394 NM_001111022 1325 GAGCUUCACUCUGACCAUC D-048982-04 RUNX1 12394 NM_001111022 1326 ACAAAUCCGCCACAAGUUG D-045547-01 Satb1 20230 NM_009122 1327 CAAAGGAUAUGAUGGUUGA D-045547-02 Satb1 20230 NM_009122 1328 GAAACGAGCCGGAAUCUCA D-045547-03 Satb1 20230 NM_009122 1329 GAAGGGAGCACAGACGUUA D-045547-04 Satb1 20230 NM_009122 1330 GCACGCGGAAUUUGUAUUG D-042265-01 SKI 20481 NM_011385 1331 GACCAUCUCUUGUUUCGUG D-042265-02 SKI 20481 NM_011385 1332 GGAAAGAGAUUGAGCGGCU D-042265-03 SKI 20481 NM_011385 1333 GCUGGUUCCUCCAAUAAGA D-042265-04 SKI 20481 NM_011385 1334 UGAAGGAGAAGUUCGACUA D-040687-04 SMAD4 17128 NM_008540 1335 GAAGGACUGUUGCAGAUAG D-040687-03 SMAD4 17128 NM_008540 1336 GCAAAGGAGUGCAGUUGGA D-040687-02 SMAD4 17128 NM_008540 1337 GAAGUAGGACUGCACCAUA D-040687-01 SMAD4 17128 NM_008540 1338 AAAGAGCAAUUGAGAGUUU D-041135-01 Smarca4 20586 NM_011417 1339 GGUCAACGGUGUCCUCAAA D-041135-02 Smarca4 20586 NM_011417 1340 GAUAAUGGCCUACAAGAUG D-041135-03 Smarca4 20586 NM_011417 1341 GAGCGAAUGCGGAGGCUUA D-041135-04 Smarca4 20586 NM_011417 1342 CAACGGGCCUUUCCUCAUC D-051590-01 SMOX 228608 NM_145533 1343 GCACAGAGAUGCUUCGACA D-051590-02 SMOX 228608 NM_145533 1344 CCACGGGAAUCCUAUCUAU D-051590-03 SMOX 228608 NM_145533 1345 AGAAUGGCGUGGCCUGCUA D-051590-04 SMOX 228608 NM_145533 1346 UGAGGAAUUCAGCGAUUUA D-043282-01 Sp4 20688 NM_009239 1347 GGACAACAGCAGAUUAUUA D-043282-02 Sp4 20688 NM_009239 1348 GACAAUAGGUGCUGUUAGU D-043282-03 Sp4 20688 NM_009239 1349 AAUUAGACCUGGCGUUUCA D-043282-04 Sp4 20688 NM_009239 1350 GGAGUUCCAGUAACAAUCA D-061490-01 Tgif1 21815 NM_009372 1351 GCAAAUAGCACCCAGCAAC D-061490-02 Tgif1 21815 NM_009372 1352 CAAACGAGCGGCAGAGAUG D-061490-03 Tgif1 21815 NM_009372 1353 UCAGUGAUCUGCCAUACCA D-061490-04 Tgif1 21815 NM_009372 1354 GCCAAGAUUUCAGAAGCUA D-047483-04 TRIM24 21848 NM_145076 1355 AAACUGACCUGUCGAGACU D-047483-03 TRIM24 21848 NM_145076 1356 CCAAUACGUUCACCUAGUG D-047483-02 TRIM24 21848 NM_145076 1357 GAUCAGCCUAGCUCAGUUA D-047483-01 TRIM24 21848 NM_145076 1358 GCAAGCGGCUGAUUACAUA D-065500-01 TRPS1 83925 NM_032000 1359 GCAAAUGGCGGAUAUGUAU D-065500-02 TRPS1 83925 NM_032000 1360 GCGAGCAGAUUAUUAGAAG D-065500-03 TRPS1 83925 NM_032000 1361 CUACGGUUCUGGAGUAAAU D-065500-04 TRPS1 83925 NM_032000 1362 GAAGUUCGAGAGUCAAACA D-055209-02 Tsc22d3 14605 NM_010286 1363 GUGAGCUGCUUGAGAAGAA D-055209-17 Tsc22d3 14605 NM_010286 1364 CUGUACGACUCCAGGAUUU D-055209-18 Tsc22d3 14605 NM_010286 1365 CUAUAUAGCCAUAAUGCGU D-055209-19 Tsc22d3 14605 NM_010286 1366 CAGUGAGCCUGUCGUGUCA D-060426-04 UBE2B 22210 NM_009458 1367 CAGAAUCGAUGGAGUCCCA D-060426-03 UBE2B 22210 NM_009458 1368 GAUGGUAGCAUAUGUUUAG D-060426-02 UBE2B 22210 NM_009458 1369 GGAAUGCAGUUAUAUUUGG D-060426-01 U8E2B 22210 NM_009458 1370 GAAGAGAGUUUCGGCCAUU D-047149-02 VAX2 24113 NM_011912 1371 GGACUUGCCUGCUGGCUAC D-047149-03 VAX2 24113 NM_011912 1372 UGACACAGGUAGCGCGAGU D-047149-04 VAX2 24113 NM_011912 1373 CUACAGCAGACUAGAACAA D-047149-17 VAX2 24113 NM_011912 1374 GCACUGAGUUGGCCCGACA D-040825-04 XBP1 22433 NM_013842 1375 UCUCAAACCUGCUUUCAUC D-040825-03 XBP1 22433 NM_013842 1376 GAGUCAAACUAACGUGGUA D-040825-02 XBP1 22433 NM_013842 1377 GGAUCACCCUGAAUUCAUU D-040825-01 XBP1 22433 NM_013842 1378 UGACAUGUCUUCUCCACUU D-051513-01 Zeb1 21417 NM_011546 1379 GAACCCAGCUUGAACGUCA D-051513-02 Zeb1 21417 NM_011546 1380 GAAAGAGCACUUACGGAUU D-051513-03 Zeb1 21417 NM_011546 1381 GGUUUGGUAUCUCCCAUAA D-051513-04 Zeb1 21417 NM_011546 1382 GAAGUGUAUUAGCUUGAUG D-058937-01 ZFP161 22666 NM_009547 1383 CCUCCGCUCUGACAUAUUU D-058937-02 ZFP161 22666 NM_009547 1384 GAUUCUCGGUAUCCGGUUU D-058937-03 ZFP161 22666 NM_009547 1385 CCGCCAAGAUUUCCGUGAA D-058937-04 ZFP161 22666 NM_009547 1386 AAAGACCAUUUGCGUGUCA D-057818-01 ZFP281 226442 NM_177643 1387 GCACCACCGCGAUGUAUUA D-057818-02 ZFP281 226442 NM_177643 1388 GAACAACGUACCAGAUUGA D-057818-03 ZFP281 226442 NM_177643 1389 AAGCAAGGCCCGAUAAGUA D-057818-04 ZFP281 226442 NM_177643 1390 GAUCAGUACUCUGGCAAAU D-041703-01 ZFP36L1 12192 NM_007564 1391 UCAAGACGCCUGCCCAUUU D-041703-02 ZFP36L1 12192 NM_007564 1392 UCAGCAGCCUUAAGGGUGA D-041703-03 ZFP36L1 12192 NM_007564 1393 GGAGCUGGCGAGCCUCUUU D-041703-04 ZFP36L1 12192 NM_007564 1394 CGAAUCCCCUCACAUGUUU
Example 2: A Transcriptional Time Course of Th17 Differentiation
(165) The differentiation of nave CD4+ T-cells into Th17 cells was induced using TGF-1 and IL-6, and measured transcriptional profiles using microarrays at eighteen time points along a 72 hr time course during the differentiation of nave CD4+ T-cells into Th17 cells, induced by a combination of the anti-inflammatory cytokine TGF-1 and the proinflammatory cytokine IL-6 (
(166) Three Main Waves of Transcription and Differentiation:
(167) There are three transcriptional phases as the cells transition from a nave-like state (t=0.5 hr) to Th17 (t=72 hr;
(168) The early phase is characterized by transient induction (e.g., Cluster C5,
(169) Some early induced genes display sustained expression (e.g., Cluster C10,
(170) The transition to the intermediate phase (t=4 hr) is marked by induction of ROR-t (master TF;
(171) During the transition to the late phase (t=20 hr), mRNAs of Th17 signature cytokines are induced (e.g., IL-17a, IL-9; cluster C19) whereas mRNAs of cytokines that signal other T cell lineages are repressed (e.g., IFN- and IL-4). Regulatory cytokines from the IL-10 family are also induced (IL-10, IL-24), possibly as a self-limiting mechanism related to the emergence of pathogenic or non-pathogenic Th17 cells (Lee et al., Induction and Molecular Signature of Pathogenic Th17 Cells, Nature Immunol 13, 991-999; doi:10.1038/ni.2416). Around 48 hr, the cells induce IL23r (data not shown), which plays an important role in the late phase (
(172) Between 20 and 42 hrs post activation (i.e., starting 16 hrs after the induction of ROR-t expression), there is a substantial change compared to Th0 in the expression of 821 genes, including many major cytokines (e.g., cluster C19,
(173) Most expression changes in the 1,055 genes differentially expressed in the remainder of the time course (>48 hr) are mild, occur in genes that responded during the 20-42 hr period (
(174) The peak of induction of IL-23r mRNA expression occurs at 48 hr and, at this time point one begins to see IL-23r protein on the cell surface (data not shown). The late phase response depends in part on IL-23, as observed when comparing temporal transcriptional profiles between cells stimulated with TGF-1+IL-6 versus TGF-1+IL-6+IL-23, or between WT and IL-23r/ cells treated with TGF-1+IL-6+IL-23 (
Example 3: Inference of Dynamic Regulatory Interactions
(175) It was hypothesized that each of the clusters (
(176) The general network of regulator-target associations from published genomics profiles was assembled as follows: in vivo protein-DNA binding profiles for 298 regulators (Linhart, C., Halperin, Y. & Shamir, R. Transcription factor and microRNA motif discovery: the Amadeus platform and a compendium of metazoan target sets. Genome research 18, 1180-1189, doi:10.1101/gr.076117.108 (2008); Zheng, G. et al. ITFP: an integrated platform of mammalian transcription factors. Bioinformatics 24, 2416-2417, doi:10.1093/bioinformatics/btn439 (2008); Wilson, N. K. et al. Combinatorial transcriptional control in blood stem/progenitor cells: genome-wide analysis of ten major transcriptional regulators. Cell Stem Cell 7, 532-544, doi:10.1016/j.stem.2010.07.016 (2010); Lachmann, A. et al. in Bioinformatics Vol. 26 2438-2444 (2010); Liberzon, A. et al. Molecular signatures database (MSigDB) 3.0. Bioinformatics 27, 1739-1740, doi:10.1093/bioinformatics/btr260 (2011); Jiang, C., Xuan, Z., Zhao, F. & Zhang, M. TRED: a transcriptional regulatory element database, new entries and other development. Nucleic Acids Res 35, D137-140 (2007), 825 DNA cis-regulatory elements scored in each gene's promoter (Elkon, R., Linhart, C., Sharan, R., Shamir, R. & Shiloh, Y. Genome-wide in silico identification of transcriptional regulators controlling the cell cycle in human cells. Genome research 13, 773-780, doi:10.1101/gr.947203 (2003)), transcriptional responses to the knockout of 11 regulatory proteins, and regulatory relations inferred from co-expression patterns across 159 immune cell types (Heng, T. S. & Painter, M. W. The Immunological Genome Project: networks of gene expression in immune cells. Nat. Immunol. 9, 1091-1094, doi:10.1038/ni1008-1091 (2008)) (see Methods in Example 1). While most protein-DNA binding profiles were not measured in Th17 cells, DNA-binding profiles in Th17 cells of a number of key TFs, including Irf4 and Batf (Glasmacher, E. et al. A Genomic Regulatory Element That Directs Assembly and Function of Immune-Specific AP-1-IRF Complexes. Science, doi:10.1126/science.1228309 (2012)), Stat3 and Stat5 (Yang, X. P. et al. Opposing regulation of the locus encoding IL-17 through direct, reciprocal actions of STAT3 and STAT5. Nat. Immunol. 12, 247-254, doi:10.1038/ni.1995 (2011)), and Rorc (Xiao et al., unpublished) has been included.
(177) A regulator was then connected to a gene from its set of putative targets only if there was also a significant overlap between the regulator's putative targets and that gene's cluster (see Methods in Example 1). Since different regulators act at different times, the connection between a regulator and its target may be active only within a certain time window. To determine this window, each edge was labeled with a time stamp denoting when both the target gene is regulated (based on its expression profile) and the regulator node is expressed at sufficient levels (based on its mRNA levels and inferred protein levels (Schwanhusser, B. et al. Global quantification of mammalian gene expression control. Nature 473, 337-342, doi:10.1038/nature10098 (2011)); see Methods in Example 1). For the target gene, the time points in which it is either differentially expressed compared to the Th0 condition or is being induced or repressed compared with preceding time points in the Th17 time course were considered. For the regulator node, only time points where the regulator is sufficiently expressed and not repressed relative to the Th0 condition were included. To this end, the regulator's predicted protein expression level was inferred from its mRNA level using a recently proposed model (Schwanhusser, B. et al. Global quantification of mammalian gene expression control. Nature 473, 337-342, doi:10.1038/nature10098 (2011)) (see Methods in Example 1). In this way, a network snapshot was derived for each of the 18 time points (
(178) Substantial Regulatory Re-Wiring During Differentiation:
(179) The active factors and interactions change from one network to the next. The vast majority of interactions are active only at some time window (
(180) Densely Interconnected Transcriptional Circuits in Each Network:
(181) At the heart of each network is its transcriptional circuit, connecting active TFs to target genes that themselves encode TFs. For example, the transcriptional circuit in the early response network connects 48 factors that are predicted to act as regulators to 72 factors whose own transcript is up- or down-regulated during the first four hours (a subset of this model is shown in
(182) As in the early network, there is substantial cross-regulation between the 64 TFs in the intermediate and late transcriptional circuits, which include major Th17 regulators such as ROR-t, Irf4, Batf, Stat3, and Hif1a (
(183) Ranking Novel Regulators for Systematic Perturbation:
(184) In addition to known Th17 regulators, the network includes dozens of novel factors as predicted regulators (FIG. 2d), induced target genes, or both (
(185) Candidate regulators were ranked for perturbation (
(186) To this end, a scoring scheme was devised to rank candidate regulators for perturbation (
(187) The genes were computationally ordered to emphasize certain features (e.g., a predicted regulator of key Th17 genes) over others (e.g., differential expression in the time course data). A similar scheme was used to rank receptor proteins (see Methods in Example 1). Supporting their quality, the top-ranked factors are enriched (p<10.sup.3) for manually curated Th17 regulators (
Example 4: Nanowire-Based Perturbation of Primary T Cells
(188) While testing the response of nave CD4+ T cells from knock-out mice deleted for key factors is a powerful strategy, it is limited by the availability of mouse strains or the ability to generate new ones. In unstimulated primary mouse T cells, viral- or transfection-based siRNA delivery has been nearly impossible because it either alters differentiation or cell viability (Dardalhon, V. et al. Lentivirus-mediated gene transfer in primary T cells is enhanced by a central DNA flap. Gene therapy 8, 190-198 (2001); McManus, M. et al. Small interfering RNA-mediated gene silencing in T lymphocytes. The Journal of Immunology 169, 5754 (2002)). a new delivery technology based on silicon nanowires (NWs) (Shalek et al., Proc Natl Acad Sci U.S.A. 2010; Shalek, A. K. et al. Nanowire-Mediated Delivery Enables Functional Interrogation of Primary Immune Cells: Application to the Analysis of Chronic Lymphocytic Leukemia. Nano Lett. 12, 6498-6504, doi:10.1021/n13042917 (2012)) was, therefore, used, which was optimized to effectively (>95%) deliver siRNA into nave T cells without activating them (
(189) Recently, it was demonstrated that NWs are able to effectively penetrate the membranes of mammalian cells and deliver a broad range of exogenous molecules in a minimally invasive, non-activating fashion (Shalek et al., Proc. Natl. Acad. Sci. U.S.A. 2010; Shalek, et al., Nano Lett. 2012). In particular, the NW-T cell interface (
(190) It was then attempted to perturb 60 genes with NW-mediated siRNA delivery and efficient knockdown (<60% transcript remaining at 48 hr post activation) was achieved for 34 genes (
(191) Nanowire-Based Screen Validates 39 Regulators in the Th17 Network:
(192) the effects of the perturbation on gene expression were profiled at two time points. 28 of the perturbations were profiled at 10 hr after the beginning of differentiation, soon after the induction of ROR-t (
(193) In particular, the effects of perturbations at 48 hr post-activation on the expression of 275 signature genes were measured using the Nanostring nCounter system (Il17ra and Il21r knockouts were also measured at 60 hr).
(194) The signature genes were computationally chosen to cover as many aspects of the differentiation process as possible (see Methods in Example 1): they include most differentially expressed cytokines, TFs, and cell surface molecules, as well as representatives from each cluster (
(195) The signature genes for expression analysis were computationally chosen to cover as many aspects of the differentiation process as possible (see Methods in Example 1). They include the majority of the differentially expressed cytokines, TFs, and cell surface genes, as well as representative genes from each expression cluster (
(196) The statistical significance of a perturbation's effect on a signature gene was scored by comparing to non-targeting siRNAs and to 18 control genes that were not differentially expressed (see Methods in Example 1,
(197) To study the network's dynamics, the effect of 28 of the perturbations at 10 hr (shortly after the induction of ROR-t) was measured using the Fluidigm Biomark system. It was found that 30% of the functional interactions are present with the same activation/repression logic at both 10 hr and 48 hr, whereas the rest are present only in one time point (
(198) Whenever possible, the function of each regulator was classified as either positive or negative for Th17 differentiation. Specifically, at the 48 hr time point, perturbation of 22 of the regulators significantly attenuated IL-17A or IL-17F expression (Th17 positive regulators,
(199) Two Coupled Antagonistic Circuits in the Th17 Network:
(200) Characterizing each regulator by its effect on Th17 signature genes (e.g. IL17A, IL17F,
(201) The two antagonistic modules may play a key role in maintaining the balance between Th17 and other T cell subsets and in self-limiting the pro-inflammatory status of Th17 cells. Indeed, perturbing Th17 positive factors also induces signature genes of other T cell subsets (e.g., Gata3,
Example 5: Validation and Characterization of Novel Factors
(202) The studies presented herein focused on the role of 12 of the positive or negative factors (including 11 of the 12 novel factors that have not been associated with Th17 cells;
(203) Next, the designation of each of the 12 factors as Th17 positive or Th17 negative was assessed by comparing the set of genes that respond to that factor's knockdown (in RNA-Seq) to each of the 20 clusters (
(204) Mina Promotes the Th17 Program and Inhibits the Foxp3 Program:
(205) Knockdown of Mina, a chromatin regulator from the Jumonji C (JmjC) family, represses the expression of signature Th17 cytokines and TFs (e.g. ROR-t, Batf, Irf4) and of late-induced genes (clusters C9, C19; p10.sup.5), while increasing the expression of Foxp3, the master TF of Treg cells. Mina is strongly induced during Th17 differentiation (cluster C7), is down-regulated in IL23r/ Th17 cells, and is a predicted target of Batf (Glasmacher, E. et al. A Genomic Regulatory Element That Directs Assembly and Function of Immune-Specific AP-1-IRF Complexes. Science, doi:10.1126/science.1228309 (2012)), ROR-t (Glasmacher et al., Science 2012), and Myc in the model (
(206) To further analyze the role of Mina, IL-17a and Foxp3 expression was measured following differentiation of nave T cells from Mina/ mice. Mina/ cells had decreased IL-17a and increased Foxp3 compared to wild-type (WT) cells, as detected by intracellular staining (
(207) The reciprocal relationship between Tregs/Th17 cells has been well described (Korn, T. et al. IL-21 initiates an alternative pathway to induce proinflammatory T(H)17 cells. Nature 448, 484-487, doi:10.1038/nature05970 (2007)), and it was assumed that this is achieved by direct binding of the ROR-t/Foxp3 TFs. However, the analysis suggests a critical role for the regulator Mina in mediating this process. This suggests a model where Mina, induced by ROR-t and Batf, promotes transcription of ROR-t, while suppressing induction of Foxp3, thus affecting the reciprocal Tregs/Th17 balance (Korn, et al., Nature 2007)) by favoring rapid Th17 differentiation.
(208) Fas Promotes the Th17 Program and Suppresses IFN- Expression:
(209) Fas, the TNF receptor superfamily member 6, is another Th17 positive regulator (
(210) To explore this, T cells from Fas/ mice (
(211) Pou2af1 Promotes the Th17 Program and Suppresses IL-2 Expression:
(212) Knockdown of Pou2af1 (OBF1) strongly decreases the expression of Th17 signature genes (
(213) TSC22d3 May Limit Th17 Differentiation and Pro-Inflammatory Function:
(214) Knockdown of the TSC22 domain family protein 3 (Tsc22d3) increases the expression of Th17 cytokines (IL-17a, IL-21) and TFs (ROR-t, Rbpj, Batf), and reduces Foxp3 expression. Previous studies in macrophages have shown that Tsc22d3 expression is stimulated by glucocorticoids and IL-10, and it plays a key role in their anti-inflammatory and immunosuppressive effects (Choi, S.-J. et al. Tsc-22 enhances TGF-beta signaling by associating with Smad4 and induces erythroid cell differentiation. Mol. Cell. Biochem. 271, 23-28 (2005)). Tsc22d3 knockdown in Th17 cells increased the expression of IL-10 and other key genes that enhance its production (
(215) To further characterize Tsc22d3's role, ChIP-Seq was used to measure its DNA-binding profile in Th17 cells and RNA-Seq following its knockdown to measure its functional effects. There is a significant overlap between Tsc22d3's functional and physical targets (P<0.01, e.g., IL-21, Irf4; see Methods in Example 1). For example, Tsc22d3 binds in proximity to IL-21 and Irf4, which also become up regulated in the Tsc22d3 knockdown. Furthermore, the Tsc22d3 binding sites significantly overlap those of major Th17 factors, including Batf, Stat3, Irf4, and ROR-t (>5 fold enrichment;
Example 6. Protein C Receptor (PROCR) Regulates Pathogenic Phenotype of Th17 Cells
(216) Th17 cells, a recently identified T cell subset, have been implicated in driving inflammatory autoimmune responses as well as mediating protective responses against certain extracellular pathogens. Based on factors such as molecular signature, Th17 cells are classified as pathogenic or non-pathogenic. (See e.g., Lee et al., Induction and molecular signature of pathogenic Th17 cells, Nature Immunology, vol. 13(10): 991-999 and online methods).
(217) It should be noted that the terms pathogenic or non-pathogenic as used herein are not to be construed as implying that one Th17 cell phenotype is more desirable than the other. As will be described herein, there are instances in which inhibiting the induction of pathogenic Th17 cells or modulating the Th17 phenotype towards the non-pathogenic Th17 phenotype or towards another T cell phenotype is desirable. Likewise, there are instances where inhibiting the induction of non-pathogenic Th17 cells or modulating the Th17 phenotype towards the pathogenic Th17 phenotype or towards another T cell phenotype is desirable. For example, pathogenic Th17 cells are believed to be involved in immune responses such as autoimmunity and/or inflammation. Thus, inhibition of pathogenic Th17 cell differentiation or otherwise decreasing the balance of Th17 T cells towards non-pathogenic Th17 cells or towards another T cell phenotype is desirable in therapeutic strategies for treating or otherwise ameliorating a symptom of an immune-related disorder such as an autoimmune disease or an inflammatory disorder. In another example, depending on the infection, non-pathogenic or pathogenic Th17 cells are believed to be desirable in building a protective immune response in infectious diseases and other pathogen-based disorders. Thus, inhibition of non-pathogenic Th17 cell differentiation or otherwise decreasing the balance of Th17 T cells towards pathogenic Th17 cells or towards another T cell phenotype or vice versa is desirable in therapeutic strategies for treating or otherwise ameliorating a symptom of an immune-related disorder such as infectious disease.
(218) Th17 cells are considered to be pathogenic when they exhibit a distinct pathogenic signature where one or more of the following genes or products of these genes is upregulated in TGF-3-induced Th17 cells as compared to TGF-1-induced Th17 cells: Cxcl3, Il22, Il3, Ccl4, Gzmb, Lrmp, Ccl5, Casp1, Csf2, Ccl3, Tbx21, Icos, Il7r, Stat4, Lgals3 or Lag3. Th17 cells are considered to be non-pathogenic when they exhibit a distinct non-pathogenic signature where one or more of the following genes or products of these genes is down-regulated in TGF-3-induced Th17 cells as compared to TGF-1-induced Th17 cells: Il6st, Il1rn, lkzf3, Maf Ahr, 119 or 1110.
(219) A temporal microarray analysis of developing Th17 cells was performed to identify cell surface molecules, which are differentially expressed in Th17 cells and regulate the development of Th17 cells. PROCR was identified as a receptor that is differentially expressed in Th17 cells and found its expression to be regulated by Th17-specific transcription regulators.
(220) Protein C receptor (PROCR; also called EPCR or CD201) is primarily expressed on endothelial cells, CD8.sup.+ dendritic cells and was also reported to be expressed to lower levels on other hematopoietic and stromal cells. It binds to activated protein C as well as factor VII/VIIa and factor Xa and was shown to have diverse biological functions, including anticoagulant, cytoprotective, anti-apoptotic and anti-inflammatory activity. However, prior to these studies, the function of PROCR in T cells had not been explored.
(221) The biological function of PROCR and its ligand activated protein C in Th17 cells was analyzed, and it was found that it decreased the expression of some of the genes identified as a part of the pathogenic signature of Th17 cells. Furthermore, PROCR expression in Th17 cells reduced the pathogenicity of Th17 cells and ameliorated disease in a mouse model for human multiple sclerosis.
(222) These results imply that PROCR functions as a regulatory gene for the pathogenicity of Th17 cells through the binding of its ligand(s). It is therefore conceivable that the regulation of this pathway might be exploited for therapeutic approaches to inflammatory and autoimmune diseases.
(223) These studies are the first to describe the Th17-specific expression of PROCR and its role in reducing autoimmune Th17 pathogenicity. Thus, activation of PROCR through antibodies or other agonists are useful as a therapeutic strategy in an immune response such as inflammatory autoimmune disorders. In addition, blocking of PROCR through antibodies or other inhibitors could be exploited to augment protective Th17 responses against certain infectious agents and pathogens.
(224) PROCR is Expressed in Th17 Cells:
(225) The membrane receptor PROCR (Protein C receptor; also called EPCR or CD201) is present on epithelial cells, monocytes, macrophages, neutrophils, eosinophils, and natural killer cells but its expression had not previously been reported on T cells (Griffin J H, Zlokovic B V, Mosnier L O. 2012. Protein C anticoagulant and cytoprotective pathways. Int J Hematol 95: 333-45). However, the detailed transcriptomic analysis of Th17 cells described herein has identified PROCR as an important node for Th17 cell differentiation (Yosef N, Shalek A K, Gaublomme J T, Jin H, Lee Y, Awasthi A, Wu C, Karwacz K, Xiao S, Jorgolli M, Gennert D, Satija R, Shakya A, Lu D Y, Trombetta J J, Pillai M R, Ratcliffe P J, Coleman M L, Bix M, Tantin D, Park H, Kuchroo V K, Regev A. 2013. Dynamic regulatory network controlling TH17 cell differentiation. Nature 496: 461-8). PROCR shares structural homologies with the CD1/MHC molecules and binds activated protein C (aPC) as well as blood coagulation factor VII and the V4V5 TCR of T cells. Due to its short cytoplasmic tail PROCR does not signal directly, but rather signals by associating with the G-protein-coupled receptor PAR1 (
(226) Knockdown Analysis of PROCR in Tumor Model:
(227)
(228) PD-1 and PROCR Affect Th17 Pathogenicity:
(229) Th17 cells are very heterogeneous and the pathogenicity of Th17 subsets differs depending on the cytokine environment during their differentiation (Zielinski C E, Mele F, Aschenbrenner D, Jarrossay D, Ronchi F, Gattorno M, Monticelli S, Lanzavecchia A, Sallusto F. 2012. Pathogen-induced human TH17 cells produce IFN-gamma or IL-10 and are regulated by IL-1beta. Nature 484: 514-8; Lee Y, Awasthi A, Yosef N, Quintana F J, Peters A, Xiao S, Kleinewietfeld M, Kunder S, Sobel R A, Regev A, Kuchroo V. 2012. Induction and molecular signature of pathogenic Th17 cells. Nat Immunol In press; and Ghoreschi K, Laurence A, Yang X P, Tato C M, McGeachy M J, Konkel J E, Ramos H L, Wei L, Davidson T S, Bouladoux N, Grainger J R, Chen Q, Kanno Y, Watford W T, Sun H W, Eberl G, Shevach E M, Belkaid Y, Cua D J, Chen W, O'Shea J J. 2010. Generation of pathogenic T(H)17 cells in the absence of TGF-beta signalling. Nature 467: 967-71). In addition to the cytokine milieu, several costimulatory pathways have been implicated in regulating differentiation and function of T helper subsets, including Th17 cells. CTLA-4-B7 interactions inhibit Th17 differentiation (Ying H, Yang L, Qiao G, Li Z, Zhang L, Yin F, Xie D, Zhang J. 2010. Cutting edge: CTLA-4B7 interaction suppresses Th17 cell differentiation. J Immunol 185: 1375-8). Furthermore, the work described herein revealed that ICOS plays a critical role in the maintenance of Th17 cells (Bauquet A T, Jin H, Paterson A M, Mitsdoerffer M, Ho I C, Sharpe A H, Kuchroo V K. 2009. The costimulatory molecule ICOS regulates the expression of c-Maf and IL-21 in the development of follicular T helper cells and TH-17 cells. Nat Immunol 10: 167-75).
(230) Based on the detailed genomic analysis of pathogenic vs. non-pathogenic Th17 cells herein, it has been determined that the molecular signatures that define pathogenic vs. non-pathogenic effector Th17 cells in autoimmune disease (Lee Y, Awasthi A, Yosef N, Quintana F J, Peters A, Xiao S, Kleinewietfeld M, Kunder S, Sobel R A, Regev A, Kuchroo V. 2012. Induction and molecular signature of pathogenic Th17 cells. Nat Immunol In press). Interestingly, PROCR is part of the signature for non-pathogenic Th17 cells and its expression is highly increased in non-pathogenic subsets (
(231) Several co-inhibitory molecules have been implicated in T cell dysfunction during antigen persistence. PD-1 and Tim-3, in particular, have wide implications in cancer and chronic viral infections such as HIV, HCV in human and LCMV in mice. Autoreactive T cell responses in mice and human are characterized with reduced expression of inhibitory molecules. The ability to induce T cell dysfunction in autoimmune settings could be clinically beneficial. MS patients that respond to Copaxone treatment show significantly elevated levels of expression of PROCR and PD-L1. It has been previously demonstrated that increasing Tim-3 expression and promoting T cell exhaustion provides the ability to limit encephalitogenecity of T cells and reduce EAE severity (Rangachari M, Zhu C, Sakuishi K, Xiao S, Karman J, Chen A, Angin M, Wakeham A, Greenfield E A, Sobel R A, Okada H, McKinnon P J, Mak T W, Addo M M, Anderson A C, Kuchroo V K. 2012. Bat3 promotes T cell responses and autoimmunity by repressing Tim-3-mediated cell death and exhaustion. Nat Med 18: 1394-400). Studies were, therefore, designed to determine whether the novel inhibitory molecule PROCR, which is selectively enriched in Th17 cells, could also play a role in T cell exhaustion. It was found that PROCR is expressed in exhausted tumor infiltrating lymphocytes that express both PD-1 and Tim-3 (
Example 7. Fas in Th Cell Differentiation
(232) Fas, also known as FasR, CD95, APO-1, TNFRSF6, is a member of the TNF receptor superfamily. Binding of FasL leads to FAS trimers that bind FADD (death domains), which activates caspase-8 and leads to apoptosis. Fas also exhibits apoptosis independent effects such as interaction with Akt, STAT3, and NF-B in liver cells and interaction with NF-B and MAPK pathways in cancer cells.
(233) Lpr mice are dominant negative for Fas (transposon intron 1), creating a functional knockout (KO). These mice exhibit lymphoproliferative disease (lpr); age dependent>25-fold size increase of LN, Spleen; expansion of Thy1+B220+CD4-CD8-TCRa/b+ T cells. These mice produce spontaneous anti-dsDNA Ab, systemic autoimmunity, which makes them a model of systemic lupus erythematosus (SLE), but these mice are resistant to experimental autoimmune encephalomyelitis (EAE). Gld mice are dominant negative for FasL.
(234) Fas flox mice that are CD4Cre-/CD19Cre-/CD4Cre-CD19Cre-/LckCre-Fasflox exhibit no lymphoproliferation and no expansion of Thy1+B220+CD4-CD8-TCRa/b+ T cells. These mice do exhibit progressive lymphopenia, inflammatory lung fibrosis, and wasting syndrome. Fas flox mice that are MxCre+poly(IC)-Fasflox exhibit an 1pr phenotype. Fas flox mice that are MOGCre-Fasflox are resistant to EAE. Fas flox mice that are LysMCre-Fasflox exhibit lymphoproliferation and glomerulonephritis.
(235) Although Fas (CD95) has been identified as a receptor mediating apoptosis, the data herein clearly show that Fas is important for Th17 differentiation and development of EAE. The data herein demonstrates that Fas-deficient mice have a defect in Th17 cell differentiation and preferentially differentiate into Th1 and Treg cells. The expansion of Treg cells and inhibition of Th17 cells in Fas-deficient mice might be responsible for disease resistance in EAE.
(236) Fas-deficient cells are impaired in their ability to differentiate into Th17 cells, and they produce significantly lower levels of IL-17 when cultured in vitro under Th17 conditions (IL-1+IL-6+IL-23). Furthermore, they display reduced levels of IL-23R, which is crucial for Th17 cells as IL-23 is required for Th17 stability and pathogenicity. In contrast, Fas inhibits IFN- production and Th1 differentiation, as cells derived from Fas-deficient mice secrete significantly higher levels of IFN-. Similarly, Fas-deficient cells more readily differentiate into Foxp3+ Tregs and secrete higher levels of the Treg effector cytokine IL-10. It therefore seems as if Fas suppresses the differentiation into Tregs and IFN--producing Th1 cells while promoting Th17 differentiation. In inflammatory autoimmune disorders, such as EAE, Fas therefore seems to promote disease progression by shifting the balance in T helper cells away from the protective Tregs and from IFN--producing Th1 cells towards pathogenic Th17 cells.
(237) The invention having now been described by way of written description and example, those of skill in the art will recognize that the invention can be practiced in a variety of embodiments and that the description and examples above are for purposes of illustration and not limitation of the claims.
(238) The invention is further described by the following numbered paragraphs:
(239) 1. A method of modulating T cell balance, the method comprising contacting a T cell or a population of T cells with a T cell modulating agent in an amount sufficient to modify differentiation, maintenance and/or function of the T cell or population of T cells by altering balance between Th17 cells, regulatory T cells (Tregs) and other T cell subsets as compared to differentiation, maintenance and/or function of the T cell or population of T cells in the absence of the T cell modulating agent.
(240) 2. The method of paragraph 1, wherein the T cell modulating agent is an agent that modulates the expression, activity and/or function of one or more target genes or one or more products of one or more target genes selected from those listed in Tables 3-9.
(241) 3. The method of paragraph 2, wherein a desired gene or combination of target genes is selected and identified as a positive regulator of Th17 differentiation, maintenance and/or function or a negative regulator of Th17 differentiation, maintenance and/or function.
(242) 4. The method of paragraph 3, wherein the gene or combination of target genes is a positive regulator of Th17 differentiation, maintenance and/or function, and wherein the T cell modulating agent is an antagonist in an amount sufficient to shift differentiation, maintenance and/or function away from the Th17 phenotype.
(243) 5. The method of paragraph 3, wherein the target gene or combination of target genes is a positive regulator of Th17 differentiation, maintenance and/or function, and wherein the T cell modulating agent is an agonist in an amount sufficient to shift differentiation, maintenance and/or function toward the Th17 phenotype.
(244) 6. The method of paragraph 3, wherein the target gene or combination of target genes is a negative regulator of Th17 differentiation, maintenance and/or function, and wherein the T cell modulating agent is an antagonist in an amount sufficient to shift differentiation, maintenance and/or function toward the Th17 phenotype.
(245) 7. The method of paragraph 3, wherein the target gene or combination of target genes is a negative regulator of Th17 differentiation, maintenance and/or function, and wherein the T cell modulating agent is an agonist in an amount sufficient to shift differentiation away from the Th17 phenotype and/or maintenance.
(246) 8. The method of paragraph 3, wherein the positive regulator of Th17 differentiation, maintenance and/or function is selected from MINA, MYC, NKFB1, NOTCH, PML, POU2AF1, PROCR, RBPJ, SMARCA4, ZEB1, BATF, CCR5, CCR6, EGR1, EGR2, ETV6, FAS, IL12RB1, IL17RA, IL21R, IRF4, IRF8, ITGA3 and combinations thereof.
(247) 9. The method of paragraph 3, wherein the positive regulator of Th17 differentiation, maintenance and/or function is selected from MINA, PML, POU2AF1, PROCR, SMARCA4, ZEB1, EGR2, CCR6, FAS and combinations thereof.
(248) 10. The method of paragraph 3, wherein the negative regulator of Th17 differentiation, maintenance and/or function is selected from SP4, ETS2, IKZF4, TSC22D3, IRF1 and combinations thereof.
(249) 11. The method of paragraph 3, wherein the negative regulator of Th17 differentiation, maintenance and/or function is selected from SP4, IKZF4, TSC22D3 and combinations thereof.
(250) 12. The method of paragraph 1, wherein the T cell modulating agent alters the balance between Th17 cells and other T cell subtypes.
(251) 13. The method of paragraph 12, wherein the other T cell subtype is regulatory T cell (Treg).
(252) 14. The method of paragraph 1, wherein the T cell modulating agent is a soluble Fas polypeptide or a polypeptide derived from FAS in an amount sufficient to induce T cell differentiation toward Th17 cells or an agonist that enhances or increases the expression, activity and/or function of FAS in Th17 cells in an amount sufficient to induce T cell differentiation toward Th17 cells.
(253) 15. The method of paragraph 1, wherein the T cell modulating agent is an antagonist that inhibits the expression, activity and/or function of FAS in an amount sufficient to induce differentiation toward regulatory T cells (Tregs), Th1 cells, or a combination of Tregs and Th1 cells.
(254) 16. The method of paragraph 1, wherein the T cell modulating agent alters the balance between pathogenic Th17 cells and non-pathogenic Th17 cells.
(255) 17. The method of paragraph 16, wherein the T cell modulating agent is a soluble Protein C Receptor (PROCR) polypeptide or a polypeptide derived from PROCR in an amount sufficient to switch Th17 cells from a pathogenic to non-pathogenic signature or an agonist that enhances or increases the expression, activity and/or function of PROCR in Th17 cells in an amount sufficient to switch Th17 cells from a pathogenic to non-pathogenic signature.
(256) 18. The method of paragraph 16, wherein the T cell modulating agent is an antagonist of PROCR in Th17 cells in an amount sufficient to switch Th17 cells from a non-pathogenic to a pathogenic signature.
(257) 19. The method according to any one of paragraphs 1 to 18, wherein the T cell modulating agent is an antibody, a soluble polypeptide, a polypeptide agent, a peptide agent, a nucleic acid agent, a nucleic acid ligand, or a small molecule agent.
(258) 20. The method according to any one of paragraphs 1 to 19, wherein the T cell modulating agent is one or more agents selected from those listed in Table 10.
(259) 21. The method according to any one of paragraphs 1 to 20, wherein the T cells are nave T cells, partially differentiated T cells, differentiated T cells, a combination of nave T cells and partially differentiated T cells, a combination of nave T cells and differentiated T cells, a combination of partially differentiated T cells and differentiated T cells, or a combination of nave T cells, partially differentiated T cells and differentiated T cells.
(260) 22. A method of inhibiting tumor growth in a subject in need thereof, the method comprising administering to said subject a therapeutically effective amount of an inhibitor of Protein C Receptor (PROCR).
(261) 23. The method of paragraph 22, wherein the inhibitor of PROCR is an antibody, a soluble polypeptide, a polypeptide agent, a peptide agent, a nucleic acid agent, a nucleic acid ligand, or a small molecule agent.
(262) 24. The method of paragraph 22, wherein the inhibitor of PROCR is one or more agents selected from the group consisting of lipopolysaccharide; cisplatin; fibrinogen; 1, 10-phenanthroline; 5-N-ethylcarboxamido adenosine; cystathionine; hirudin; phospholipid; Drotrecogin alfa; VEGF; Phosphatidylethanolamine; serine; gamma-carboxyglutamic acid; calcium; warfarin; endotoxin; curcumin; lipid; and nitric oxide.
(263) 25. A method of inhibiting Th17 differentiation in a cell population and/or increasing expression, activity and/or function of one or more non-Th17-associated cytokines or non-Th17-associated transcription regulators selected from FOXP3, interferon gamma (IFN-), GATA3, STAT4, BCL6 and TBX21, comprising contacting a T cell with an agent that inhibits expression, activity and/or function of MINA, MYC, NKFB1, NOTCH, PML, POU2AF1, PROCR, RBPJ, SMARCA4, ZEB1, BATF, CCR5, CCR6, EGR1, EGR2, ETV6, FAS, IL12RB1, IL17RA, IL21R, IRF4, IRF8, ITGA3 or combinations thereof.
(264) 26. The method of paragraph 25, wherein the agent inhibits expression, activity and/or function of at least one of MINA, PML, POU2AF1, PROCR, SMARCA4, ZEB1, EGR2, CCR6, FAS or combinations thereof.
(265) 27. The method of paragraph 25 or paragraph 26, wherein the agent is an antibody, a soluble polypeptide, a polypeptide antagonist, a peptide antagonist, a nucleic acid antagonist, a nucleic acid ligand, or a small molecule antagonist.
(266) 28. A method of inhibiting Th17 differentiation in a cell population and/or increasing expression, activity and/or function of one or more non-Th17-associated cytokines or non-Th17-associated transcription factor selected from FOXP3, interferon gamma (IFN-), GATA3, STAT4 and TBX21, comprising contacting a T cell with an agent that enhances expression, activity and/or function of SP4, ETS2, IKZF4, TSC22D3, IRF1 or combinations thereof.
(267) 29. The method of paragraph 28, wherein the agent enhances expression, activity and/or function of at least one of SP4, IKZF4, TSC22D3 or combinations thereof.
(268) 30. The method of paragraph 28 or paragraph 29, wherein the agent is an antibody, a soluble polypeptide, a polypeptide agonist, a peptide agonist, a nucleic acid agonist, a nucleic acid ligand, or a small molecule agonist.
(269) 31. A method of enhancing Th17 differentiation in a cell population increasing expression, activity and/or function of one or more Th17-associated cytokines or one or more Th17-associated transcription regulators selected from interleukin 17F (IL-17F), interleukin 17A (IL-17A), STAT3, interleukin 21 (IL-21) and RAR-related orphan receptor C (RORC), and/or decreasing expression, activity and/or function of one or more non-Th17-associated cytokines or non-Th17-associated transcription regulators selected from FOXP3, interferon gamma (IFN-), GATA3, STAT4 and TBX21, comprising contacting a T cell with an agent that inhibits expression, activity and/or function of SP4, ETS2, IKZF4, TSC22D3, IRF1 or combinations thereof.
(270) 32. The method of paragraph 31, wherein the agent inhibits expression, activity and/or function of at least one of SP4, IKZF4 or TSC22D3.
(271) 33. The method of paragraph 31 or paragraph 32, wherein the agent is an antibody, a soluble polypeptide, a polypeptide antagonist, a peptide antagonist, a nucleic acid antagonist, a nucleic acid ligand, or a small molecule antagonist.
(272) 34. A method of enhancing Th17 differentiation in a cell population, increasing expression, activity and/or function of one or more Th17-associated cytokines or one or more Th17-associated transcription regulators selected from interleukin 17F (IL-17F), interleukin 17A (IL-17A), STAT3, interleukin 21 (IL-21) and RAR-related orphan receptor C (RORC), and/or decreasing expression, activity and/or function of one or more non-Th17-associated cytokines or non-Th17-associated transcription regulators selected from FOXP3, interferon gamma (IFN-), GATA3, STAT4 and TBX21, comprising contacting a T cell with an agent that enhances expression, activity and/or function of MINA, MYC, NKFB1, NOTCH, PML, POU2AF1, PROCR, RBPJ, SMARCA4, ZEB1, BATF, CCR5, CCR6, EGR1, EGR2, ETV6, FAS, IL12RB1, IL17RA, IL21R, IRF4, IRF8, ITGA3 or combinations thereof.
(273) 35. The method of paragraph 34, wherein the agent enhances expression, activity and/or function of at least one of MINA, PML, POU2AF1, PROCR, SMARCA4, ZEB1, EGR2, CCR6 or FAS.
(274) 36. The method of paragraph 34 or paragraph 35, wherein the agent is an antibody, a soluble polypeptide, a polypeptide agonist, a peptide agonist, a nucleic acid agonist, a nucleic acid ligand, or a small molecule agonist.
(275) 37. The method of paragraph 27, wherein the agent is one or more agents selected from those listed in Table 10.
(276) 38. The method of paragraph 30, wherein the agent is one or more agents selected from those listed in Table 10.
(277) 39. The method of paragraph 33, wherein the agent is one or more agents selected from those listed in Table 10.
(278) 40. The method of paragraph 36, wherein the agent is one or more agents selected from those listed in Table 10.
(279) 41. The method of paragraph 27, wherein the agent is an antibody.
(280) 42. The method of paragraph 30, wherein the agent is an antibody.
(281) 43. The method of paragraph 33, wherein the agent is an antibody.
(282) 44. The method of paragraph 36, wherein the agent is an antibody.
(283) 45. The method of paragraph 41, wherein the antibody is a monoclonal antibody.
(284) 46. The method of paragraph 42, wherein the antibody is a monoclonal antibody.
(285) 47. The method of paragraph 43, wherein the antibody is a monoclonal antibody.
(286) 48. The method of paragraph 44, wherein the antibody is a monoclonal antibody.
(287) 49. The method of paragraph 41, wherein the antibody is a chimeric, humanized or fully human monoclonal antibody.
(288) 50. The method of paragraph 42, wherein the antibody is a chimeric, humanized or fully human monoclonal antibody.
(289) 51. The method of paragraph 43, wherein the antibody is a chimeric, humanized or fully human monoclonal antibody.
(290) 52. The method of paragraph 44, wherein the antibody is a chimeric, humanized or fully human monoclonal antibody.
(291) 53. The method of paragraph 25, wherein the T cell is a nave T cell, a combination of nave T cells and partially differentiated T cells, a combination of nave T cells and differentiated T cells, or a combination of nave T cells, partially differentiated T cells and differentiated T cells.
(292) 54. The method of paragraph 28, wherein the T cell is a nave T cell, a combination of nave T cells and partially differentiated T cells, a combination of nave T cells and differentiated T cells, or a combination of nave T cells, partially differentiated T cells and differentiated T cells.
(293) 55. The method of paragraph 31, wherein the T cell is a nave T cell, a combination of nave T cells and partially differentiated T cells, a combination of nave T cells and differentiated T cells, or a combination of nave T cells, partially differentiated T cells and differentiated T cells.
(294) 56. The method of paragraph 34, wherein the T cell is a nave T cell, a combination of nave T cells and partially differentiated T cells, a combination of nave T cells and differentiated T cells, or a combination of nave T cells, partially differentiated T cells and differentiated T cells.
(295) 57. The method of paragraph 25, wherein the T cell is a partially differentiated T cell, a differentiated T cell, or a combination of partially differentiated T cells and differentiated T cells.
(296) 58. The method of paragraph 28, wherein the T cell is a partially differentiated T cell, a differentiated T cell, or a combination of partially differentiated T cells and differentiated T cells.
(297) 59. The method of paragraph 31, wherein the T cell is a partially differentiated T cell, a differentiated T cell, or a combination of partially differentiated T cells and differentiated T cells.
(298) 60. The method of paragraph 34, wherein the T cell is a partially differentiated T cell, a differentiated T cell, or a combination of partially differentiated T cells and differentiated T cells.
(299) 61. The method of paragraph 25 or paragraph 28, wherein the T cell is a Th17 T cell, and wherein the agent is administered in an amount that is sufficient to modulate the phenotype of the Th17 T cell to produce a CD4+ T cell phenotype other than a Th17 T cell phenotype.
(300) 62. The method of paragraph 31 or paragraph 34, wherein the T cell is a CD4+ T cell other than a Th17 T cell, and wherein the agent is administered in an amount that is sufficient to modulate the phenotype of the non-Th17 T cell to produce a Th17 T cell phenotype.
(301) 63. A method of identifying a signature gene, a gene signature or other genetic element associated with Th17 differentiation, maintenance and/or function comprising:
(302) a) contacting a T cell with an inhibitor of Th17 differentiation or an agent that enhances Th17 differentiation; and
(303) b) identifying a signature gene, a gene signature or other genetic element whose expression is modulated by step (a).
(304) 64. The method of paragraph 63, further comprising
(305) c) perturbing expression of the signature gene, gene signature or genetic element identified in step (b) in a T cell that has been contact with an inhibitor of Th17 differentiation or an agent that enhances Th17 differentiation; and
(306) d) identifying a target gene whose expression is modulated by step (c).
(307) 65. The method of paragraph 63 or paragraph 64, wherein the inhibitor of Th17 differentiation is an agent that inhibits the expression, activity and/or function of a target gene or one or more products of one or more target genes selected from those listed in Tables 3-9.
(308) 66. The method of paragraph 63 or paragraph 64, wherein the inhibitor of Th17 differentiation is an agent that inhibits the expression, activity and/or function of MINA, MYC, NKFB1, NOTCH, PML, POU2AF1, PROCR, RBPJ, SMARCA4, ZEB1, BATF, CCR5, CCR6, EGR1, EGR2, ETV6, FAS, IL12RB1, IL17RA, IL21R, IRF4, IRF8, ITGA3 or combinations thereof.
(309) 67. The method of paragraph 66, wherein the agent inhibits expression, activity and/or function of at least one of MINA, PML, POU2AF1, PROCR, SMARCA4, ZEB1, EGR2, CCR6 or FAS.
(310) 68. The method of paragraph 66, wherein the agent is an antibody, a soluble polypeptide, a polypeptide antagonist, a peptide antagonist, a nucleic acid antagonist, a nucleic acid ligand, or a small molecule antagonist.
(311) 69. The method of paragraph 67, wherein the agent is an antibody, a soluble polypeptide, a polypeptide antagonist, a peptide antagonist, a nucleic acid antagonist, a nucleic acid ligand, or a small molecule antagonist.
(312) 70. The method of paragraph 66, wherein the agent is one or more agents selected from those listed in Table 10.
(313) 71. The method of paragraph 67, wherein the agent is one or more agents selected from those listed in Table 10.
(314) 72. The method of paragraph 63 or paragraph 64, wherein the inhibitor of Th17 differentiation is an agent that enhances expression, activity and/or function of SP4, ETS2, IKZF4, TSC22D3, IRF1 or combinations thereof.
(315) 73. The method of paragraph 72, wherein the agent enhances expression, activity and/or function of at least one of SP4, IKZF4, TSC22D3 or combinations thereof.
(316) 74. The method of paragraph 72, wherein the agent is an antibody, a soluble polypeptide, a polypeptide agonist, a peptide agonist, a nucleic acid agonist, a nucleic acid ligand, or a small molecule agonist.
(317) 75. The method of paragraph 73, wherein the agent is an antibody, a soluble polypeptide, a polypeptide agonist, a peptide agonist, a nucleic acid agonist, a nucleic acid ligand, or a small molecule agonist.
(318) 76. The method of paragraph 72, wherein the agent is one or more agents selected from those listed in Table 10.
(319) 77. The method of paragraph 73, wherein the agent is one or more agents selected from those listed in Table 10.
(320) 78. A method of modulating induction of Th17 differentiation comprising contacting a T cell with an agent that modulates expression, activity and/or function of one or more target genes or one or more products of one or more target genes selected from IRF1, IRF8, IRF9, STAT2, STAT3, IRF7, STAT1, ZFP281, IFI35, REL, TBX21, FLI1, BATF, IRF4, AES, AHR, ARID5A, BCL11B, BCL3, CBFB, CBX4, CHD7, CITED2, CREB1, E2F4, EGR1, EGR2, ELL2, ETS1, ETS2, ETV6, EZH1, FOXO1, GATA3, GATAD2B, HIF1A, ID2, IKZF4, IRF2, IRF3, JMJD1C, JUN, LEF1, LRRFIP1, MAX, NCOA3, NFE2L2, NFIL3, NFKB1, NMI, NOTCH1, NR3C1, PHF21A, PML, PRDM1, RELA, RUNX1, SAP18, SATB1, SMAD2, SMARCA4, SP100, SP4, STAT4, STATSB, STAT6, TFEB, TP53, TRIM24, ZFP161, and any combination thereof.
(321) 79. A method of modulating onset of Th17 phenotype and amplification of Th17 T cells comprising contacting a T cell with an agent that modulates expression, activity and/or function of one or more target genes or one or more products of one or more target genes selected from IRF8, STAT2, STAT3, IRF7, JUN, STATSB, ZPF2981, CHD7, TBX21, FLI1, SATB1, RUNX1, BATF, RORC, SP4, AES, AHR, ARID3A, ARID5A, ARNTL, ASXL1, BATF, BCL11B, BCL3, BCL6, CBFB, CBX4, CDC5L, CEBPB, CREB1, CREB3L2, CREM, E2F4, E2F8, EGR1, EGR2, ELK3, ELL2, ETS1, ETS2, ETV6, EZH1, FOSL2, FOXJ2, FOXO1, FUS, HIF1A, HMGB2, ID1, ID2, IFI35, IKZF4, IRF3, IRF4, IRF9, JUNB, KAT2B, KLF10, KLF6, KLF9, LEF1, LRRFIP1, MAFF, MAX, MAZ, MINA, MTA3, MYC, MYST4, NCOA1, NCOA3, NFE2L2, NFIL3, NFKB1, NMI, NOTCH1, NR3C1, PHF21A, PML, POU2AF1, POU2F2, PRDM1, RARA, RBPJ, RELA, RORA, SAP18, SKI, SKIL, SMAD2, SMAD7, SMARCA4, SMOX, SP1, SS18, STAT1, STAT5A, STAT6, SUZ12, TFEB, TLE1, TP53, TRIM24, TRIM28, TRPS1, VAV1, ZEB1, ZEB2, ZFP161, ZFP62, ZNF238, ZNF281, ZNF703, and any combination thereof.
(322) 80. A method of modulating stabilization of Th17 cells and/or modulating Th17-associated interleukin 23 (IL-23) signaling comprising contacting a T cell with an agent that modulates expression, activity and/or function of one or more target genes or one or more products of one or more target genes selected from STAT2, STAT3, JUN, STATSB, CHD7, SATB1, RUNX1, BATF, RORC, SP4, IRF4, AES, AHR, ARID3A, ARID5A, ARNTL, ASXL1, ATF3, ATF4, BATF3, BCL11B, BCL3, BCL6, C210RF66, CBFB, CBX4, CDC5L, CDYL, CEBPB, CHMP1B, CIC, CITED2, CREB1, CREB3L2, CREM, CSDA, DDIT3, E2F1, E2F4, E2F8, EGR1, EGR2, ELK3, ELL2, ETS1, ETS2, EZH1, FLI1, FOSL2, FOXJ2, FOXO1, FUS, GATA3, GATAD2B, HCLS1, HIF1A, ID1, ID2, IFI35, IKZF4, IRF3, IRF7, IRF8, IRF9, JARID2, JMJD1C, JUNB, KAT2B, KLF10, KLF6, KLF7, KLF9, LASS4, LEF1, LRRFIP1, MAFF, MAX, MEN1, MINA, MTA3, MXI1, MYC, MYST4, NCOA1, NCOA3, NFE2L2, NFIL3, NFKB1, NMI, NOTCH1, NR3C1, PHF13, PHF21A, PML, POU2AF1, POU2F2, PRDM1, RARA, RBPJ, REL, RELA, RNF11, RORA, RUNX2, SAP18, SAP30, SERTAD1, SIRT2, SKI, SKIL, SMAD2, SMAD4, SMAD7, SMARCA4, SMOX, SP1, SP100, SS18, STAT1, STAT4, STAT5A, STAT6, SUZ12, TBX21, TFEB, TGIF1, TLE1, TP53, TRIM24, TRPS1, TSC22D3, UBE2B, VAV1, VAX2, XBP1, ZEB1, ZEB2, ZFP161, ZFP36L1, ZFP36L2, ZNF238, ZNF281, ZNF703, ZNRF1, ZNRF2, and any combination thereof.
(323) 81. A method of modulating one or more of target genes associated with the early stage of Th17 differentiation, maintenance and/or function, wherein the target gene is selected from:
(324) (a) one or more of the target genes listed in Table 5 as being associated with the early stage of Th17 differentiation, maintenance and/or function selected from the group consisting of AES, AHR, ARID5A, BATF, BCL11B, BCL3, CBFB, CBX4, CHD7, CITED2, CREB1, E2F4, EGR1, EGR2, ELL2, ETS1, ETS2, ETV6, EZH1, FLI1, FOXO1, GATA3, GATAD2B, HIF1A, ID2, IFI35, IKZF4, IRF1, IRF2, IRF3, IRF4, IRF7, IRF9, JMJD1C, JUN, LEF1, LRRFIP1, MAX, NCOA3, NFE2L2, NFIL3, NFKB1, NMI, NOTCH1, NR3C1, PHF21A, PML, PRDM1, REL, RELA, RUNX1, SAP18, SATB1, SMAD2, SMARCA4, SP100, SP4, STAT1, STAT2, STAT3, STAT4, STATSB, STAT6, TFEB, TP53, TRIM24, ZFP161, and any combination thereof;
(325) (b) one or more of the target genes listed in Table 6 as being associated with the early stage of Th17 differentiation, maintenance and/or function selected from the group consisting of FAS, CCR5, IL6ST, IL17RA, IL2RA, MYD88, CXCR5, PVR, IL15RA, IL12RB1, and any combination thereof;
(326) (c) one or more of the target genes listed in Table 7 as being associated with the early stage of Th17 differentiation, maintenance and/or function selected from the group consisting of EIF2AK2, DUSP22, HK2, RIPK1, RNASEL, TEC, MAP3K8, SGK1, PRKCQ, DUSP16, BMP2K, PIM2, and any combination thereof;
(327) (d) one or more of the target genes listed in Table 8 as being associated with the early stage of Th17 differentiation, maintenance and/or function selected from the group consisting of HK2, CDKN1A, DUT, DUSP1, NADK, LIMK2, DUSP11, TAOK3, PRPS1, PPP2R4, MKNK2, SGK1, BPGM, TEC, MAPK6, PTP4A2, PRPF4B, ACP1, CCRN4L, and any combination thereof; and
(328) (e) one or more of the target genes listed in Table 9 as being associated with the early stage of Th17 differentiation, maintenance and/or function selected from the group consisting of CD200, CD40LG, CD24, CCND2, ADAM17, BSG, ITGAL, FAS, GPR65, SIGMAR1, CAP1, PLAUR, SRPRB, TRPV2, IL2RA, KDELR2, TNFRSF9, and any combination thereof.
(329) 82. A method of modulating one or more of target genes associated with the intermediate stage of Th17 differentiation, maintenance and/or function, wherein the target gene is selected from:
(330) (a) one or more of the target genes listed in Table 5 as being associated with the intermediate stage of Th17 differentiation, maintenance and/or function selected from the group consisting of AES, AHR, ARID3A, ARID5A, ARNTL, ASXL1, BATF, BCL11B, BCL3, BCL6, CBFB, CBX4, CDC5L, CEBPB, CHD7, CREB1, CREB3L2, CREM, E2F4, E2F8, EGR1, EGR2, ELK3, ELL2, ETS1, ETS2, ETV6, EZH1, FLI1, FOSL2, FOXJ2, FOXO1, FUS, HIF1A, HMGB2, ID1, ID2, IFI35, IKZF4, IRF3, IRF4, IRF7, IRF8, IRF9, JUN, JUNB, KAT2B, KLF10, KLF6, KLF9, LEF1, LRRFIP1, MAFF, MAX, MAZ, MINA, MTA3, MYC, MYST4, NCOA1, NCOA3, NFE2L2, NFIL3, NFKB1, NMI, NOTCH1, NR3C1, PHF21A, PML, POU2AF1, POU2F2, PRDM1, RARA, RBPJ, RELA, RORA, RUNX1, SAP18, SATB1, SKI, SKIL, SMAD2, SMAD7, SMARCA4, SMOX, SP1, SP4, SS18, STAT1, STAT2, STAT3, STAT5A, STATSB, STAT6, SUZ12, TBX21, TFEB, TLE1, TP53, TRIM24, TRIM28, TRPS1, VAV1, ZEB1, ZEB2, ZFP161, ZFP62, ZNF238, ZNF281, ZNF703, and any combination thereof;
(331) (b) one or more of the target genes listed in Table 6 as being associated with the intermediate stage of Th17 differentiation, maintenance and/or function selected from the group consisting of IL7R, ITGA3, IL1R1, CCR5, CCR6, ACVR2A, IL6ST, IL17RA, CCR8, DDR1, PROCR, IL2RA, IL12RB2, MYD88, PTPRJ, TNFRSF13B, CXCR3, IL1RN, CXCR5, CCR4, IL4R, IL2RB, TNFRSF12A, CXCR4, KLRD1, IRAK1BP1, PVR, IL12RB1, IL18R1, TRAF3, and any combination thereof;
(332) (c) one or more of the target genes listed in Table 7 as being associated with the intermediate stage of Th17 differentiation, maintenance and/or function selected from the group consisting of PSTPIP1, PTPN1, ACP5, TXK, RIPK3, PTPRF, NEK4, PPME1, PHACTR2, HK2, GMFG, DAPP1, TEC, GMFB, PIM1, NEK6, ACVR2A, FES, CDK6, ZAK, DUSP14, SGK1, JAK3, ULK2, PTPRJ, SPHK1, TNK2, PCTK1, MAP4K3, TGFBR1, HK1, DDR1, BMP2K, DUSP10, ALPK2, and any combination thereof;
(333) (d) one or more of the target genes listed in Table 8 as being associated with the intermediate stage of Th17 differentiation, maintenance and/or function selected from the group consisting of HK2, ZAP70, NEK6, DUSP14, SH2D1A, ITK, DUT, PPP1R11, DUSP1, PMVK, TK1, TAOK3, GMFG, PRPS1, SGK1, TXK, WNK1, DUSP19, TEC, RPS6KA1, PKM2, PRPF4B, ADRBK1, CKB, ULK2, PLK1, PPP2R5A, PLK2, and any combination thereof; and
(334) (e) one or more of the target genes listed in Table 9 as being associated with the intermediate stage of Th17 differentiation, maintenance and/or function selected from the group consisting of CTLA4, CD200, CD24, CD6L, CD9, IL2RB, CD53, CD74, CAST, CCR6, IL2RG, ITGAV, FAS, IL4R, PROCR, GPR65, TNFRSF18, RORA, IL1RN, RORC, CYSLTR1, PNRC2, LOC390243, ADAM10, TNFSF9, CD96, CD82, SLAMF7, CD27, PGRMC1, TRPV2, ADRBK1, TRAF6, IL2RA, THY1, IL12RB2, TNFRSF9, and any combination thereof.
(335) 83. A method of modulating one or more of target genes associated with the late stage of Th17 differentiation, maintenance and/or function, wherein the target gene is selected from:
(336) (a) one or more of the target genes listed in Table 5 as being associated with the late stage of Th17 differentiation, maintenance and/or function selected from the group consisting of AES, AHR, ARID3A, ARID5A, ARNTL, ASXL1, ATF3, ATF4, BATF, BATF3, BCL11B, BCL3, BCL6, C210RF66, CBFB, CBX4, CDC5L, CDYL, CEBPB, CHD7, CHMP1B, CIC, CITED2, CREB1, CREB3L2, CREM, CSDA, DDIT3, E2F1, E2F4, E2F8, EGR1, EGR2, ELK3, ELL2, ETS1, ETS2, EZH1, FLI1, FOSL2, FOXJ2, FOXO1, FUS, GATA3, GATAD2B, HCLS1, HIF1A, ID1, ID2, IFI35, IKZF4, IRF3, IRF4, IRF7, IRF8, IRF9, JARID2, JMJD1C, JUN, JUNB, KAT2B, KLF10, KLF6, KLF7, KLF9, LASS4, LEF1, LRRFIP1, MAFF, MAX, MEN1, MINA, MTA3, MXI1, MYC, MYST4, NCOA1, NCOA3, NFE2L2, NFIL3, NFKB1, NMI, NOTCH1, NR3C1, PHF13, PHF21A, PML, POU2AF1, POU2F2, PRDM1, RARA, RBPJ, REL, RELA, RNF11, RORA, RORC, RUNX1, RUNX2, SAP18, SAP30, SATB1, SERTAD1, SIRT2, SKI, SKIL, SMAD2, SMAD4, SMAD7, SMARCA4, SMOX, SP1, SP100, SP4, SS18, STAT1, STAT3, STAT4, STAT5A, STATSB, STAT6, SUZ12, TBX21, TFEB, TGIF1, TLE1, TP53, TRIM24, TRPS1, TSC22D3, UBE2B, VAV1, VAX2, XBP1, ZEB1, ZEB2, ZFP161, ZFP36L1, ZFP36L2, ZNF238, ZNF281, ZNF703, ZNRF1, ZNRF2, and any combination thereof;
(337) (b) one or more of the target genes listed in Table 6 as being associated with the late stage of Th17 differentiation, maintenance and/or function selected from the group consisting of IL7R, ITGA3, IL1R1, FAS, CCR5, CCR6, ACVR2A, IL6ST, IL17RA, DDR1, PROCR, IL2RA, IL12RB2, MYD88, BMPR1A, PTPRJ, TNFRSF13B, CXCR3, IL1RN, CXCR5, CCR4, IL4R, IL2RB, TNFRSF12A, CXCR4, KLRD1, IRAK1BP1, PVR, IL15RA, TLR1, ACVR1B, IL12RB1, IL18R1, TRAF3, IFNGR1, PLAUR, IL21R, IL23R, and any combination thereof;
(338) (c) one or more of the target genes listed in Table 7 as being associated with the late stage of Th17 differentiation, maintenance and/or function selected from the group consisting of PTPLA, PSTPIP1, TK1, PTEN, BPGM, DCK, PTPRS, PTPN18, MKNK2, PTPN1, PTPRE, SH2D1A, PLK2, DUSP6, CDC25B, SLK, MAP3K5, BMPR1A, ACP5, TXK, RIPK3, PPP3CA, PTPRF, PACSIN1, NEK4, PIP4K2A, PPME1, SRPK2, DUSP2, PHACTR2, DCLK1, PPP2R5A, RIPK1, GK, RNASEL, GMFG, STK4, HINT3, DAPP1, TEC, GMFB, PTPN6, RIPK2, PIM1, NEK6, ACVR2A, AURKB, FES, ACVR1B, CDK6, ZAK, VRK2, MAP3K8, DUSP14, SGK1, PRKCQ, JAK3, ULK2, HIPK2, PTPRJ, INPP1, TNK2, PCTK1, DUSP1, NUDT4, TGFBR1, PTP4A1, HK1, DUSP16, ANP32A, DDR1, ITK, WNK1, NAGK, STK38, BMP2K, BUB1, AAK1, SIK1, DUSP10, PRKCA, PIM2, STK17B, TK2, STK39, ALPK2, MST4, PHLPP1, and any combination thereof;
(339) (d) is one or more of the target genes listed in Table 8 as being associated with the late stage of Th17 differentiation, maintenance and/or function selected from the group consisting of ZAP70, PFKP, NEK6, DUSP14, SH2D1A, INPP5B, ITK, PFKL, PGK1, CDKN1A, DUT, PPP1R11, DUSP1, PMVK, PTPN22, PSPH, TK1, PGAM1, LIMK2, CLK1, DUSP11, TAOK3, RIOK2, GMFG, UCKL1, PRPS1, PPP2R4, MKNK2, DGKA, SGK1, TXK, WNK1, DUSP19, CHP, BPGM, PIP5K1A, TEC, MAP2K1, MAPK6, RPS6KA1, PTP4A2, PKM2, PRPF4B, ADRBK1, CKB, ACP1, ULK2, CCRN4L, PRKCH, PLK1, PPP2R5A, PLK2, and any combination thereof;
(340) (e) one or more of the target genes listed in Table 9 as being associated with the late stage of Th17 differentiation, maintenance and/or function selected from the group consisting of CTLA4, TNFRSF4, CD44, PDCD1, CD200, CD247, CD24, CD6L, CCND2, CD9, IL2RB, CD53, CD74, ADAM17, BSG, CAST, CCR6, IL2RG, CD81, CD6, CD48, ITGAV, TFRC, ICAM2, ATP1B3, FAS, IL4R, CCR7, CD52, PROCR, GPR65, TNFRSF18, FCRL1, RORA, IL1RN, RORC, P2RX4, SSR2, PTPN22, SIGMAR1, CYSLTR1, LOC390243, ADAM10, TNFSF9, CD96, CAP1, CD82, SLAMF7, PLAUR, CD27, SIVA1, PGRMC1, SRPRB, TRPV2, NR1H2, ADRBK1, GABARAPL1, TRAF6, IL2RA, THY1, KDELR2, IL12RB2, TNFRSF9, SCARB1, IFNGR1, and any combination thereof.
(341) 84. A method of diagnosing an immune response in a subject, comprising detecting a level of expression, activity and/or function of one or more signature genes or one or more products of one or more signature genes selected from those listed in Table 1 and those listed in Table 2 and comparing the detected level to a control of level of signature gene or gene product expression, activity and/or function, wherein a difference in the detected level and the control level indicates that the presence of an immune response in the subject.
(342) 85. The method of paragraph 84, wherein the immune response is an autoimmune response.
(343) 86. The method of paragraph 84, wherein the immune response is an inflammatory response.
(344) 87. A method of monitoring an immune response in a subject, comprising detecting a first level of expression, activity and/or function of one or more signature genes or one or more products of one or more signature genes selected from those listed in Table 1 or Table 2 at a first time point, detecting a second level of expression, activity and/or function of the one or more signature genes or one or more products of one or more signature genes selected from those listed in Table 1 or Table 2 at a second time point, and comparing the first detected level of expression, activity and/or function with the second detected level of expression, activity and/or function, wherein a change in the first and second detected levels indicates a change in the immune response in the subject.
(345) 88. The method of paragraph 87, wherein the immune response is an autoimmune response.
(346) 89. The method of paragraph 87, wherein the immune response is an inflammatory response.
(347) 90. A method of monitoring an immune response in a subject, comprising isolating a population of T cells from the subject at a first time point, determining a first ratio of T cell subtypes within the T cell population at the first time point, isolating a population of T cells from the subject at a second time point, determining a second ratio of T cell subtypes within the T cell population at the second time point, and comparing the first and second ratio of T cell subtypes, wherein a change in the first and second detected ratios indicates a change in the immune response in the subject.
(348) 91. The method of paragraph 90, wherein the first ratio and the second ratio comprise a comparison of the level of Th17 cells to non-Th17 cells in the first and second T cell populations.
(349) 92. The method of paragraph 90, wherein the non-Th17 cell is a regulatory T cell (Treg).
(350) 93. The method of paragraph 90, wherein the first ratio and the second ratio comprise a comparison of the level of pathogenic Th17 cells to non-pathogenic Th17 cells in the first and second T cell populations.
(351) 94. The method of paragraph 90, wherein the immune response is an autoimmune response.
(352) 95. The method of paragraph 90, wherein the immune response is an inflammatory response.
(353) Having thus described in detail preferred embodiments of the present invention, it is to be understood that the invention defined by the above paragraphs is not to be limited to particular details set forth in the above description as many apparent variations thereof are possible without departing from the spirit or scope of the present invention.