Gene expression profile algorithm and test for determining prognosis of prostate cancer

|0002| The present disclosure relates to molecular diagnostic assays that provide information concerning gene expression profiles to determine prognostic information for cancer patients. Specifically, the present disclosure provides an algorithm comprising genes, or coexpressed genes, the expression levels of which may be used to determine the likelihood that a prostate cancer patient will experience a positive or a negative clinical outcome.

INTRODUCTION

[0003] The introduction of prostate-specific antigen (PSA) screening in 1987 has led to the diagnosis and aggressive treatment of many cases of indolent prostate cancer that would never have become clinically significant or caused death. The reason for this is that the natural history of prostate cancer is unusual among malignancies in that the majority of cases are indolent and even if untreated would not progress during the course of a man’s life to cause suffering or death. While approximately half of men develop invasive prostate cancer during their lifetimes (as detected by autopsy studies) (B. Halpert ct al, Cancer 16: 737-742 (1963); B. Holund, ScandJ Urol Nephrol 14: 29-35 (1980); S. Lundberg et al., ScandJUrol Nephrol 4: 93-97 ( 1970); M. Yin et al., J Urol 179: 892-895 (2008)), only 17% will be diagnosed with prostate cancer and only 3% will die as a result of prostate cancer. Cancer Facts and Figures. Atlanta, GA: American Cancer Society (2010); JE Damber et al.. Lancet 371; 1710-1721 (2008).

[0004] However, currently, over 90% of men who are diagnosed with prostate cancer, even low-risk prostate cancer, are treated with either immediate radical prostatectomy or definitive radiation therapy. MR Cooperberg et al., J Clin Oncol 28: 1117-1123 (2010); MR Cooperberg et al., J Clin Oncol 23: 8146-8151 (2005). Surgery and radiation therapy reduce the risk of recurrence and death from prostate cancer (AV D'Amico et al., Jama 280:969974 ( 1998); M Han et al., Urol Clin North Am 28:555-565 (2001 ); WU Shipley et al., Jama 1

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281:1598-1604 (1999); AJ Stephenson et al., J Clin Oncol 27:4300-4305 (2009)), however estimates of the number of men that must be treated to prevent one death from prostate cancer range from 12 to 100. A Bill-Axelson er al., J Natl Cancer Inst 100:1144-1154 (2008); J Hugosson et al., Lancet Oncol Π: 725-732 (2010); LH Klotz et al.. Can J Urol .13 Suppl I : 48-55 (2006); S Loeb et al., J Clin Oncol 29:464-467 (2011); FH Schroder et al, NEngl J Med 360:1320-1328 (2009). This over-treatment of prostale cancer comes at a cost of money and toxicity. For example, the majority of men who undergo radical prostatectomy suffer incontinence and impotence as a result of the procedure (MS Litwin et at, Cancer 109: 2239-2247 (2007); MG Sanda et al.. N Engl J Med 1250-1261 (2008), and as many as 25% of men regret their choice of treatment for prostate cancer. FR Schroeck et al., Eur Urol 54: 785-793 (2008).

[0005] One of the reasons for the over-treatment of prostate cancer is the lack of adequate prognostic tools to distinguish men who need immediate definitive therapy from those who are appropriate candidates to defer immediate therapy and undergo active surveillance instead. For example, of men who appear to have low-risk disease based on th© results of clinical staging, pre-treatment PSA, and biopsy Gleason score, and have been managed with active surveillance on protocols, 30-40 % experience disease progression (diagnosed by rising PSA, an increased Gleason score on repeat biopsy, or clinical progression) over the first few years of follow-up, and some of them may have lost th© opportunity for curative therapy. HB Carter et al., J Urol 178:2359-2364 and discussion 2364-2355 (2007); MA Dall'Eraet al., Cancer 112:2664-2670 (2008); L Klotz et al., J Clin Oncol 28:126-131 (2010). Also, of men who appear to be candidates for active surveillance, but who undergo immediate prostatectomy anyway, 30-40% are found at surgery to have higher risk disease than expected as defined by having high-grade (Gleason score of 3+4 or higher) or nonorgan-confined disease (extracapsuiar extension (ECE) or seminal vesicle involvement (SVI)). SLetal., J Uni W: 1628-1633 and discussion 1633-1624 (2009); CR Griffin et al„ J Urol 178: 860-863 (2007); PW Mufarrij et al., J Urol 181: 607-608 (2009).

[0006] Estimates of recurrence risk and treatment decisions in prostate cancer ar© currently based primarily on PSA levels and/or clinical tumor stage. Although clinical tumor stage has been demonstrated to have a significant association with outcome, sufficient to be included in pathology reports, the College of American Pathologists Consensus Statement noted that variations in approach to the acquisition, interpretation, reporting, and analysis of this information exist. C. Compton, et al., Arch Pathol Lab Med 124:979-992 (2000). As a

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βΜΧ

[0007] This application discloses molecular assays that involve measurement of expression level(s) of one or more genes or gene subsets from a biological sample obtained from a prostate cancer patient, and analysis of the measured expression levels to provide information concerning the likelihood of a clinical outcome. For example, the likelihood of a clinical outcome may be described in terms of a quantitative score based on clinical or biochemical recurrence-free interval, overall survival, prostate cancer-specific survival, upstaging/upgrading from biopsy to radical prostatectomy, or presence of high grade or nonorgan confined disease at radical prostatectomy.

[0008] In addition, this application discloses molecular assays that involve measurement of expression levei(s) of one or more genes or gene subsets from a biological sample obtained to identify a risk classification for a prostate cancer patient, For example, patients may be Stratified using expression level(s) of one or more genes, positively or negatively, with positive clinical outcome of prostate cancer, or with a prognostic factor. Tn an exemplary embodiment, the prognostic factor is Gleason score.

[0009] The present invention provides a method of predicting the likelihood of a clinical outcome for a patient with prostate cancer comprising determination of a level of one or more RNA transcripts, or an expression product thereof, in a biological sample containing tumor cells obtained from the patient, wherein the RNA transcript, or its expression product, is selected from the 81 genes shown in Fig. I and listed in Tables 1A and IB, The method comprises assigning the one or more RNA transcripts, or an expression product thereof, to one or more gene groups selected from a cellular organization gene group, basal epithelia gene group, a stress response gene group, an androgen gene group, a stromal response gene group, and a proliferation gene group. The method further comprises calculating a quantitative score for the patient by weighting the level of the one or more RNA transcripts or an expression product thereof by their contribution to a clinical outcome and predicting the likelihood of a clinical outcome for the patient based on the quantitative score. In an embodiment of the invention, an increase in the quantitative score correlates with an increased likelihood of a negative clinical outcome.

[0610] in a particular embodiment, the one or more RNA transcripts, or an expression product thereof, is selected from BINI, 1GF1, C7, GSN, DES, TGFB1II, TPM2, VCL,

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FLNC, ÎTGA7, C0L6AI, PPP1R12A, GSTMI, GSTM2, PAGE4, PPAP2B, SRD5A2, PRKCA, IGFBP6, GPM6B, 0LFML3, HLF, CYP3A5, KRT15, KRT5, LAMB3, SDC1, DUSP1, EGFR1, FOS, JUN, EGR3, GADD45B, ZFP36, FAM13C, KLK2, ASPN, SFRP4, BGN, THBS2, INHBA, COL1A1, COL3A1, COL1A2, SPARC, COL8A1, COL4A1, FNl, FAP, COL5A2, CDC20. TPX2, UBE2T, MYBL2, and CDKN2C. BINI, IGFl, C7, GSN, DES, TGFBIH, TPM2, VCL, FLNC, ITGA7, C0L6A1, PPP1R12A, GSTM1, GSTM2, PAGE4, PPAP2B, SRD5A2, PRKCA, IGFBP6, GPM6B, OLFML3, and HLF are assigned to the cellular organization gene group. CYP3A5, KRTl 5, KRT5, LAMB3, and SDC1 are assigned to the basal epithelial gene group. DUSPI, EGFR1, FOS, JUN, EGR3, GADD45B, and ZFP36 are assigned to the stress response gene group. FAM13C, KLK2, AZGP1, and SRD5A2 are assigned to the androgen gene group. ASPN, SFRP4, BGN, THBS2, INHBA, C0UA1, COL3AL COL1A2, SPARC, COL8A1, COL4A1, FNl, FAP and COL5A2 are assigned to the stromal response gene group. CDC20, TPX2, UBE2T, MYBL2, and CDKN2C are assigned to the proliferation gene group. The method may further comprise determining the level of at least one RNA transcript, or an expression product thereof selected from STAT5B, NFAT5, AZGPL ANPEP, IGFBP2, SLC22A3, ERG, AR, SRD5A2, GSTMI, and GSTM2.

[0011] In an embodiment of the invention, the level of one or more RNA transcripts, or an expression product thereof, from each of the stromal response gene group and the cellular organization gene group are determined. In another embodiment, the level of one or more RNA transcripts, or expression products thereof from each of the stromal response gene group and PSA gene group are determined. Additionally, the level of one or more RNA transcripts, or expression products thereof, from the cellular organization gene group and/or proliferation gene group may be determined. In this embodiment, gene(s) to be assayed from the stromal response gene group may be selected from ASPN, BGN, COL I Al, SPARC, FNl, COL3AI, COL4A1, INHBA, THBS2, and SFRP4; gene(s) to be assayed from the androgen gene group may be selected from FAM13C and KLK2; gene(s) to be assayed from the cellular organization gene group may be selected from FLNC, GSN, GSTM2,1GFBP6, PPAP2B, PPP1R12A, BINI, VCL, IGFi, TPM2, C7, and GSTMI; and gene(s) to be assayed from the proliferation gene group may be selected from TPX2, CDC20, and MYBL2, J0012] In a particular embodiment, the RNA transcripts, or their expression products, are selected from BGN, COL1A1, SFRP4, FLNC, GSN, TPM2, TPX2, FAM13C, KLK2, AZGP1, GSTM2, and SRD5A2. BGN, COL1AI, and SFRP4 are assigned to the stromal response gene group; FLNC, GSN, and TPM2 are assigned to the cellular organization gene 4 group; and FAM13C and KLK2 are assigned to the androgen gene group. The level of the RNA transcripts, or their expression products, comprising at least one of the gene groups selected from the stromal response gene group, cellular organization gene group, and androgen gene group, may be determined for the method of the invention. In any of the embodiments, the androgen gene group may further comprise AZGP1 and SRD5A2.

[0013] In addition, the level of any one of the gene combinations show in Table 4 may be determined. For instance, the RSO model in Table 4 comprises determining the levels of the RNA transcripts, or gene expression products thereof, of ASPN, BGN, COL 1 Al, SPARC, FLNC, GSN, GSTM2, IGFBP6, PPAP2B, PPP1R12A, TPX2, CDC20, MYBL2, FAM13C, KLK2, STAT5B, and NFAT5. Furthermore, any one of the algorithms shown in Table 4 may be used to calculate the quantitative score for the patient.

[013a] In some embodiments, the invention provides a method of predicting a likelihood of a clinical outcome for a patient with prostate cancer, comprising:

(a) measuring levels of RNA transcripts of genes FAM13C, KLK2, AZGP1, and SRD5A2; at least one of genes BGN, COL1 Al, and SFRP4; and at least one of genes FLNC, GSN, GSTM2, and TPM2 in a biological sample comprising cancer cells obtained from the patient;

(b) normalizing the levels of the RNA transcripts to obtain normalized RNA expression levels;

(¢) calculating a stromal response group, a cellular organization group, and an androgen group score for the patient from the normalized RNA expression levels, wherein the genes are grouped into stromal response, cellular organization, and androgen groups as follows:

a) stromal response group: BGN, COL1A1, and SFRP4,

b) cellular organization group: FLNC, GSN, GSTM2, and TPM2, and c) androgen group: FAM13C, KLK2, AZGP1, and SRD5A2; and (d) predicting the likelihood of a clinical outcome for the patient based on the stromal response group, cellular organization group, and androgen group scores, wherein increased normalized RNA expression levels of BGN, COL1A1, and SFRP4 correlate with an increased likelihood of a negative clinical outcome, and wherein decreased normalized RNA expression levels of FLNC, GSN, GSTM2, TPM2, FAM13C, KLK2, AZGP1, and SRD5A2 correlate with an increased

Date Reçue/Date Received 2021-02-01 likelihood of a negative clinical outcome, wherein the clinical outcome is upgrading of prostate cancer, upstaging of prostate cancer, recurrence of prostate cancer, non-organ-confmed disease, or adverse pathology.In some embodiments, the androgen group score is calculated as the sum of the normalized RNA expression levels of each of genes FAM13C, KLK2, AZGP1, and SRD5A2, wherein the normalized RNA expression level of each gene is multiplied by a coefficient representing the relative contribution of the gene to the clinical outcome, divided by 4. In some other embodiments, the androgen group score is calculated as the sum of the normalized RNA expression levels of each of genes FAM13C, KLK2, AZGP1, and SRD5A2, divided by 4.

BRIEF DESCRIPTION OF THE DRAWING

[0014] Figure 1 is a dendrogram depicting foe association of foe 81 genes selected from foe gene identification study.

[0015] Figures 2A-2E are scatter plots showing the comparison of normalized gene expression (Cp) for matched samples from each patient where foe x-axis is foe gene expression from foe primary Gleason pattern RP sample (PGP) and foe y-axis is foe gene expression from foe biopsy (BX) sample. Fig. 2A: All ECM (stomal response) genes; Fig. 2B: All migration (cellular organization) genes; Fig. 2C: All proliferation genes; Fig. 2D: PSA (androgen) genes; Fig. 2E: other genes from foe 81 gene list that do not fall within any of these four gene groups.

[0016] Figures 3A-3D are range plots of gene expression of individual genes within each gene group in foe biopsy (BX) and PGP RP samples. Fig. 3A: All ECM (stromal response) genes; Fig. 3B: All migration (cellular organization) genes; Fig. 3C: All proliferation genes; Fig. 3D: other genes from foe 81 gene list that do not fall within any of foe gene groups.

[0017] Figure 4 is a schematic illustration of the clique-stack method used to identify coexpressed genes.

[0018] Figure 5 shows examples of cliques and stacks. Fig. 5(a) is an example of a graph that is not a clique; Fig. 5(b) is an example of a clique; Fig. 5(c) is an example of a clique but is not a maximal clique.

[0019] Figure 6 is a graph showing two maximal cliques: 1-2-3-4-5 and 1-2-3-4-6.

[0020] Figure 7 schematically illustrates stacking of two maximal cliques.

5a

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[0021 ] Figure 8 is a graph showing that RS27 and CAPRA risk groups predict freedom from high-grade or non-organ-confined disease,

[0022] Figure 9 is a graph showing that RS27 and AUA risk groups predict freedom from high-grade or non-organ-confined disease,

[0023] Figure 10 is a graph showing time to clinical recurrence of PTEN low and PTEN normal patients from the gene identification study.

[0024] Figure 11 is a graph showing time to clinical recurrence of patients from the gene identification study stratified into PTEN low/normal and TMPRSS-ERG negative/positive.

[0025] Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Singleton et al., Dictionary of Microbiology and Molecular Biology 2nd ed._s J, Wiley & Sons (New York, NY 1994), and March, Advanced Organic Chemistry Reactions, Mechanisms and Structure 4th ed., John Wiley & Sons (New York, NY 1992), provide one skilled in the art with a general guide to many of the terms used in the present application.

10026] One skilled in the art will recognize many methods and materials similar or equivalent to those described herein, which could be used in the practice of the present invention.

Indeed, the present invention is in no way limited to the methods and materials described herein. For purposes of the invention, the following terms are defined below.

10027] The terms “tumor” and “lesion” as used herein, refer to ail neoplastic cell growth and proliferation, whether malignant or benign, and all pre-cancerous and cancerous cells and tissues. Those skilled in the art will realize that a tumor tissue sample may comprise multiple biological elements, such as one or more cancer cells, partial or fragmented cells, tumors in various stages, surrounding histologically normal-appearing tissue, and/or macro or microdissected tissue.

[0028] The terms “cancer” and “cancerous” refer to or describe the physiological condition in mammals that is typically characterized by unregulated cell growth. Examples of cancer in the present disclosure include cancer of the urogenital tract, such as prostate cancer.

[0029] As used herein, the term “prostate cancer” is used in the broadest sense and refers to all stages and all forms of cancer arising from the tissue of the prostate gland.

[0030] Staging of the cancer assists a physician in assessing how far the disease has progressed and to plan a treatment for the patient. Staging may be done clinically (clinical staging) by physical examination, blood tests, or response to radiation therapy, and/or

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PCT/US2013/023409 pathologically (pathologie staging) based on surgery, such as radical prostatectomy. According to the tumor, node, metastasis (TNM) staging system of the American Joint Committee on Cancer (AJCC), AJCC Cancer Staging Manual (7th Ed., 2010), die various stages of prostate cancer are defined as follows: Tumor: Tl; clinically inapparent tumor not palpable or visible by imaging, Tia: tumor incidental histological finding in 5% or less of tissue resected, Tib: tumor incidental histological finding in more than 5% of tissue resected. Tic: tumor identified by needle biopsy; T2: tumor confined within prostate, T2a: tumor involves one half of one lobe or less, T2b: tumor involves more than half of one lobe, but not both lobes, T2c: tumor involves both lobes; T3: tumor extends through the prostatic capsule, T3a: extracapsular extension (unilateral or bilateral), T3b: tumor invades seminal vesicle(s); T4: tumor is fixed or invades adjacent structures other than seminal vesicles (bladder neck, external sphincter, rectum, levator muscles, or pelvic wall). Generally, a clinical T (cT) stage is Tl or T2 and pathologic T (pl') stage is T2 ot higher, Node: NO: no regional lymph node metastasis; Nl: metastasis in regional lymph nodes. Metastasis: MO: no distant metastasis; Ml: distant metastasis present.

[0031] The Gleason Grading system is used to help evaluate the prognosis of men with prostate cancer. Together with other parameters, it is incorporated into a strategy of prostate cancer staging, which predicts prognosis and helps guide therapy. A Gleason “score” or “grade” is given to prostate cancer based upon its microscopic appearance. Tumors with a low Gleason score typically grow slowly enough that they may not pose a significant threat to the patients in their lifetimes. These patients are monitored (“watchful waiting” or “active surveillance”) over time. Cancers with a higher Gleason score are more aggressive and have a worse prognosis, and these patients are generally treated with surgery (e.g., radical prostatectomy) and, in some cases, therapy (e.g., radiation, hormone, ultrasound, chemotherapy). Gleason scores (or sums) comprise grades of the two most common tumor patterns. These patterns are referred to as Gleason patterns 1-5, with pattern 1 being the most well-differentiated. Most have a mixture of patterns. To obtain a G leason score or grade, the dominant pattern is added to the second most prevalent pattern to obtain a number between 2 and 10. The Gleason Grades include: Gl: well differentiated (slight anaplasia) (Gleason 2-4); G2: moderately differentiated (moderate anaplasia) (Gleason 5-6); G3-4; poorly differentiated/undifferentiated (marked anaplasia) (Gleason 7-10).

(0032] Stage groupings: Stage I: Tia NO M0 Gl; Stage 11: (TlaNO MO G2-4) or (Tib, c, Tl, T2, NO M0 Any G); Stage III: T3 NO M0 Any G; Stage IV: (T4 NO MO Any G) or (Any TNl M0 Any G) or (Any T Any N Ml Any G).

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[0033] The term “upgrading” as used herein refers to an increase in Gleason grade determined from biopsy to Gleason grade determined from radical prostatectomy (RP). For example, upgrading includes a change in Gleason grade from 3+3 or 3+4 on biopsy to 3+4 or greater on RP. “Significant upgrading” or “upgrade^” as used herein, refers to a change in Gleason grade from 3+3 or 3+4 determined from biopsy to 4+3 or greater, or seminal vessical involvement (SVI), or extracapsular involvement (ECE) as determined from RP.

[0034] The term “high grade” as used herein refers to Gleason score of >=3+4 or >=4+3 on RP. The term “low grade” as used herein refers to a Gleason score of 3+3 on RP. In a particular embodiment, “high grade” disease refers to Gleason score of at least major pattern 4. minor pattern 5, or tertiary pattern S.

[ÔÔ35J The term “upstaging” as used herein refers to an increase in tumor stage from biopsy to tumor stage at RP. For example, upstaging is a change in tumor stage from clinical T1 or T2 stage at biopsy to pathologic T3 stags at RP.

I0036] The term “non organ-confined disease” as used herein refers to having pathologic stage T3 disease at RP. The term “organ-confined” as used herein refers to pathologic stage pT2atRP.

[0037] The term “adverse pathology” as used herein refers to a high grade disease as defined above, or non organ-confined disease as defined above. In a particular embodiment, “adverse pathology” refers to prostate cancer with a Gleason score of >=3+4 or >=4+3 or pathologic stage T3.

[0038] In another embodiment, the term “high-grade or non-organ-confined disease” refers to prostate cancer with a Gleason score of at least major pattern 4. minor pattern 5, or tertiary' pattern 5, or pathologic stage T3.

[0039] As used herein, the terms “active surveillance” and “watchful waiting” mean closely monitoring a patient’s condition without giving any treatment until symptoms appear or change. For example, in prostate cancer, watchful waiting is usually used in older men with other medical problems and early-stage disease.

[9940] As used herein, the term “surgery'” applies to surgical methods undertaken for removal of cancerous tissue, including pelvic lymphadenectomy, radical prostatectomy, transurethral resection of the prostate (TURP), excision, dissection, and tumor biopsy/removal. The tumor tissue or sections used for gene expression analysis may have been obtained from any of these methods.

[ÔÔ41J As used herein, the term “biological sample containing cancer cells” refers to a sample comprising tumor material obtained from a cancer patient. The term encompasses 8

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PCT/US2013/023409 tumor tissue samples, for example, tissue obtained by radical prostatectomy and tissue obtained by biopsy, such as for example, a core biopsy or a fine needle biopsy'. The biological sample may be fresh, frozen, or a fixed, wax-embedded tissue sample, such as a formalin-fixed, paraffin-embedded tissue sample. A biological sample also encompasses bodily fluids containing cancer cells, such as blood, plasma, serum, urine, and the like. .Additionally, the term “biological sample containing cancer cells” encompasses a sample comprising tumor cells obtained from sites other than the primary tumor, e.g., circulating tumor cells. The term also encompasses cells that are the progeny of the patient’s tumor cells, e.g. cell culture samples derived from primary tumor cells or circulating tumor cells. The term further encompasses samples that may comprise protein or nucleic acid material shed from tumor cells in vivo, e.g., bone marrow, blood, plasma, serum, and the like. Ilie term also encompasses samples that have been enriched for tumor cells or otherwise manipulated after their procurement and samples comprising polynucleotides and/or polypeptides that are obtained from a patient’s tumor material.

[0942] Prognostic factors are those variables related to the natural history of cancer that influence the recurrence rates and outcome of patients once they have developed cancer. Clinical parameters that have been associated with a worse prognosis include, for example, increased tumor stage, high PSA level at presentation, and high Gleason grade or pattern. Prognostic factors are frequently used to categorize patients into subgroups with different baseline relapse risks.

[9043] The term “prognosis” is used herein to refer to the likelihood that a cancer patient will have a cancer-attributable death or progression, including recurrence, metastatic spread, and drug resistance, of a neoplastic disease, such as prostate cancer. For example, a “good prognosis” would include long term survival without recurrence and a “bad prognosis” would include cancer recurrence.

[0044] A “positive clinical outcome” can be assessed using any endpoint indicating a benefit to tiie patient, including, without limitation, (1) inhibition, to some extent, of tumor growth, including slowing down and complete growth arrest; (2) reduction in the number of tumor cells; (3) reduction in tumor size; (4) inhibition (i.e., reduction, slowing down, or complete stopping) of tumor cell infiltration into adjacent peripheral organs and/or tissues; (5) inhibition of metastasis; (6) enhancement of anti-tumor immune response, possibly resulting in regression or rejection of the tumor; (7) relief to some extent, of one or more symptoms associated with the tumor; (S) increase in the duration of survival following treatment; and/or (9) decreased mortality at a given point of time following treatment. Positive clinical

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PCT/US2013/023409 outcome can also be considered in the context of an individual’s outcome relative to an outcome ofa population of patients having a comparable clinical diagnosis, and can be assessed using various endpoints such as an increase in the duration of Recurrence-Free Interval (RFI), an increase in survival time (Overall Survival (OS)) or prostate cancerspecific survival time (Prostate Cancer-Specific Survival (PCSS)) in a population, no upstaging or upgrading in tumor stage or Gleason grade between biopsy and radical prostatectomy, presence of 3+3 grade and organ-confined disease at radical prostatectomy, and the like.

[0045] The term “risk classification” means a grouping of subjects by the level of risk (or likelihood) that the subject will experience a particular negative clinical outcome. A subject may be classified into a risk group or classified at a level of risk based on the methods of the present disclosure, e.g. high, medium, or low risk. A “risk group” is a group of subjects or individuals with a similar level of risk for a particular clinical outcome,

[0046] The term “long-term” survival is used herein to refer to survival for a particular time period, e.g., for at least 5 years, or for at least 10 years.

[Ô047J The term “recurrence” is used herein to refer to local or distant recurrence (i.e., metastasis) of cancer. For example, prostate cancer can recur locally in the tissue next to the prostate or in the seminal vesicles. The cancer may also affect the surrounding lymph nodes in the pelvis or lymph nodes outside this area. Prostate cancer can also spread to tissues next to the prostate, such as pelvic muscles, bones, or other organs. Recurrence can be determined by clinical recurrence detected by, for example, imaging study or biopsy, or biochemical recurrence detected by, for example, sustained follow-up prostate-specific antigen (PSA) levels > 0.4 ng/mL or die initiation of salvage therapy as a result of a rising PSA level.

[0048] The term “clinical recurrence-free interval (cRFI)” is used herein as time from surgery to first clinical recurrence or death due io clinical recurrence of prostate cancer. If follow-up ended without occurrence of clinical recurrence, or other primary cancers or death occurred prior to clinical recurrence, time to cRPi is considered censored; when this occurs, the only information known is that up through the censoring time, clinical recurrence has not occurred in this subject. Biochemical recurrences are ignored for the purposes of calculating cRFI.

[0049] The term “biochemical recurrence-free interval (bRFI)” is used herein to mean the time from surgery to first biochemical recurrence of prostate cancer. If clinical recurrence occurred before biochemical recurrence, follow-up ended without occurrence of bRH, or other primary cancers or death occurred prior to biochemical recurrence, time to biochemical recurrence is considered censored at the first of these.

(0050] The term “Overall Survival (OS)” is used herein to refer to the time from surgery to death from any cause. If the subject was still alive at the time of last follow-up, survival time is considered censored at the time of last follow-up. Biochemical recurrence and clinical recurrence are ignored for the purposes of calculating OS.

[0051 ] The term “Prostate Cancer-Specific Survival (PCSS)” is used herein to describe the time from surgery to death from prostate cancer. If the patient did not die of prostate cancer before end of followup, or died due to other causes, PCSS is considered censored at this time. Clinical recurrence and biochemical recurrence are ignored for the purposes of calculating PCSS.

[0052] In practice, the calculation of the time-to-event measures listed above may vary from study to study depending on the definition of events to be considered censored.

[0053] As used herein, the term “expression level” as applied to a gene refers to the normalized level of a gene product, e.g. the normalized value determined for the RNA level of a gene or for the polypeptide level of a gene.

[0054] The term “gene product” or “expression product” are used herein to refer to the RNA (ribonucleic acid) transcription products (transcripts) of the gene, including mRNA, and the polypeptide translation products of such RNA transcripts. A gene product can be, for example, an unspliced RNA, an mRNA, a splice variant mRNA, a microRNA, a fragmented RNA, a polypeptide, a post-translationally modified polypeptide, a splice variant polypeptide, etc.

[0055] The term “RNA transcript” as used herein refers to the RNA transcription products of a gene, including, for example, mRNA, an unspliced RNA, a splice variant mRNA, a microRNA, and a fragmented RNA.

[0056] Unless indicated otherwise, each gene name used herein corresponds to the Official Symbol assigned to the gene and provided by Entrez Gene as of the filing date of this application.

[0057] The term “microarray” refers to an ordered arrangement of hybridizable array elements, e.g. oligonucleotide or polynucleotide probes, on a substrate.

[0058] The term “polynucleotide” generally refers to any polyribonucleotide or polydeoxribonucleotide, which may be unmodified RNA or DNA or modified RNA or DNA. Thus, for instance, polynucleotides as defined herein include, without limitation, single- and double-stranded DNA, DNA including single-and double-stranded regions, single- and double-stranded RNA, and RNA including single- and double-stranded regions, hybrid molecules comprising DNA and RNA that may be single-stranded Or, more typically, doubleII

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WO 2013/116144 PCT/US2013/023409 stranded or include single- and double-stranded regions. In addition, the term “polynucleotide” as used herein refers to triple-stranded regions comprising RNA or DNA or both RNA and DNA. The strands in such regions may be from the same molecule or from different molecules. The regions may include all of one or more of the molecules, but more typically involve only a region of some of the molecules. One of the molecules of a triplehelical region often is an oligonucleotide. The term “polynucleotide” specifically includes cDNAs. The term includes DNAs (including cDNAs) and RNAs that contain one or more modified bases. Thus, DNAs or RNAs with backbones modified for stability or for other reasons, are “polynucleotides” as that term is intended herein, Moreover, DNAs or RNAs comprising unusual bases, such as inosine, or modified bases, such as tritiated bases, are included within the term “polynucleotides” as defined herein. In general, the term “polynucleotide” embraces all chemically, enzymatically and/or metabolically modified forms of unmodified polynucleotides, as well as the chemical forms of DNA and RNA characteristic of viruses and cells, including simple and complex cells.

[0059] The term “oligonucleotide” refers to a relatively short polynucleotide, including, without limitation, single-stranded deoxyribonucleotides, single- or double-stranded ribonucleotides, RN ArDNA hybrids and double-stranded DNAs. Oligonucleotides, such as single-stranded DNA probe oligonucleotides, are often synthesized by chemical methods, for example using automated oligonucleotide synthesizers that are commercially available. However, oligonucleotides can be made by a variety of other methods, including in vitro recombinant DNA-mediated techniques and by expression of DNAs in ceils and organisms. [0060] The term Ct” as used herein refers to threshold cycle, the cycle number in quantitative polymerase chain reaction (qPCR) at which the fluorescence generated within a reaction well exceeds the defined threshold, i.e. the point during the reaction at which a sufficient number of amplicons have accumulated to meet the defined threshold.

[0061] The term “Cp” as used herein refers to “crossing point.” The Cp value is calculated by determining the second derivatives of entire qPCR amplification curves and their maximum value. The Cp value represents the cycle at which the increase of fluorescence is highest and where the logarithmic phase of a PCR begins.

[0062] The terms “threshold” or “thresholding” refer to a procedure used to account for nonlinear relationships between gene expression measurements and clinical response as well as to further reduce variation in reported patient scores. When thresholding is applied, all measurements below or above a threshold are set to that threshold value. A non-linear relationship between gene expression and outcome could be examined using smoothers or 12

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PCT/US2013/023409 cubic splines io model gene expression on recurrence free interval using Cox PH regression or on adverse pathology status using logistic regression. D. Cox, Journal of the Royal Statistical Society, Series B 34:187-220 (1972). Variation in reported patient scores could be examined as a function of variability in gene expression at the limit of quantitation and/or detection for a particular gene.

[0063] As used herein, the term “amplicon,” refers to pieces of DNA that have been synthesized using amplification techniques, such as polymerase chain reactions (PCR) and ligase chain reactions.

[0064] “Stringency” of hybridization reactions is readily determinable by one of ordinary skill in the art, and generally is an empirical calculation dependent upon probe length, washing temperature, and salt concentration. In general, longer probes require higher temperatures for proper annealing, while shorter probes need lower temperatures. Hybridization generally depends on the ability of denatured DNA to re-anneal when complementary strands are present in an environment below their melting temperature. The higher the degree of desired homology between the probe and hybridizable sequence, the higher the relative temperature which can be used. As a result, it follows that higher relative temperatures would tend to make the reaction conditions more stringent, while tower temperatures less so. For additional details and explanation of stringency of hybridization reactions, see /kusubel et al.. Current Protocols in Molecular Biology (Wiley Interscience Publishers, 1995).

[0065] “Stringent conditions” or “high stringency conditions”, as defined herein, typically: (1) employ low ionic strength and high temperature for washing, for example 0.015 M sodium chloride/0.0015 M sodium citrate/0.1% sodium dodecyl sulfate at 50^cC; (2) employ during hybridization a denaturing agent, such as formamide, for example, 50% (v/v) formamide with 0.1% bovine serum albumin/0.1% Ficoll/0.1% polyvinylpyrrolidone/SOmM sodium phosphate buffer at pH 6.5 with 750 mM sodium chloride, 75 mM sodium citrate at 42°C; or (3) employ 50% formamide, S x SSC (0.75 M NaCI. 0.075 M sodium citrate), 50 mM sodium phosphate (pH 6.8), 0,1% sodium pyrophosphate, 5 x Denhardt's solution, sonicated salmon sperm DNA (50 pg/ml), 0.1% SDS, and 10% dextran sulfate at 42^CC, with washes at 42^CC in 0.2 x SSC (sodium chioride/sodium citrate) and 50% formamide, followed by a high-stringency wash consisting of 0.1 x SSC containing EDTA at 55°C.

[0066] “Moderately stringent conditions” may be identified as described by Sambrook et al.. Molecular Cloning: A Laboratory Manual, New York: Cold Spring Harbor Press, 1989, and include the use of washing solution and hybridization conditions (e.g., temperature, ionic

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WO 2013/116144 PCT/US2013/023409 strength and %SDS) less stringent that those described above. An example of moderately stringent conditions is overnight incubation at 37°C in a solution comprising: 20% formamide, 5 x SSC (150 mM NaCl, 15 mM trisodium citrate), 50 mM sodium phosphate (pH 7.6), 5 x Denhardt's solution, 10% dextran sulfate, and 20 mg/ml denatured sheared salmon sperm DNA, followed by washing the filters in 1 x SSC at about 37-500C. The skilled artisan will recognize how to adjust the temperature, ionic strength, etc. as necessary to accommodate factors such as probe length and the like.

(0067] The terms “splicing” and “RNA splicing” are used interchangeably and refer to RNA processing that removes introns and joins exons to produce mature mRNA with continuous coding sequence that moves into the cytoplasm of an eukaryot ic cell.

[0068] As used herein, the term “TMPRSS fusion” and “TMPRSS2 fusion” are used interchangeably and refer to a fusion of the androgen-driven TMPRSS2 gene with the ERG oncogene, which has been demonstrated to have a significant association with prostate cancer. S. Pemer, et aL, Urologe A. 46(7):754-760 (2007); S.A. Narod, et at, Br J Cancer 99(6):847-851 (2008). As used herein, positive TMPRSS fusion status indicates that the TMPRSS fusion is present in a tissue sample, whereas negative TMPRSS fusion status indicates that the TMPRSS fusion is not present in a tissue sample. Experts skilled in the an will recognize that there are numerous ways to determine TMPRSS fusion status, such as real-time, quantitative PCR or high-throughput sequencing. See, e.g., K. Mertz, et al„ Neoplasis 9(3):200-206 (2007); C. Maher, Nature 458(7234):97-101 (2009).

[0069] The terms “correlated” and “associated” are used interchangeably herein to refer to the association between two measurements (or measured entities). Ilie disclosure provides genes or gene subsets, the expression levels of which are associated with clinical outcome. For example, the increased expression level of a gene may be positively correlated (positively associated) with a good or positive clinical outcome. Such a positive correlation may be demonstrated statistically in various ways, e.g. by a cancer recurrence hazard ratio less than one or by a cancer upgrading or upstaging odds ratio of less than one. In another example, the increased expression level of a gene may be negatively correlated (negatively associated) with a good or positive clinical outcome. In that case, for example, the patient may experience a cancer recurrence or upgrading/upstaging of the cancer, and this may be demonstrated statistically in various ways, e.g., a hazard ratio greater than lor an odds ratio greater titan one. “Correlation” is also used herein to refer to the strength of association between the expression levels of two different genes, such that the expression level of a first gene can be substituted with an expression level of a second gene in a given algorithm if their

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WO 2013/116144 PCT/US2013/023409 expression levels are highly correlated. Such “correlated expression” of two genes that are substitutable in an algorithm are usually gene expression levels that are positively correlated with one another, e.g,, if increased expression of a first gene is positively correlated with an outcome (e.g,, increased likelihood of good clinical outcome), then the second gene that is co-expressed and exhibits correlated expression with the first gene is also positively correlated with the same outcome.

[0670] The terms “co-express” and “co-expressed”, as used herein, refer to a statistical correlation between the amounts of different transcript sequences across a population of different patients. Pairwise co-expression may be calculated by various methods known in the art, e.g., by calculating Pearson correlation coefficients or Spearman correlation coefficients. Co-expressed gene cliques may also be identified by seeding and stacking the maximal clique enumeration (MCE) described in Example 4 herein, An analysis of co-exprcssion may be calculated using normalized expression data. Genes within the same gene subset are also considered to be co-expressed.

(0071) A “computer-based system” refers to a system of hardware, software, and data storage medium used to analyze information. The minimum hardware of a patient computer-based system comprises a central processing unit (CPU), and hardware for data input, data output (e.g., display), and data storage. An ordinarily skilled artisan can readily appreciate that any currently available computer-based systems and/or components thereof are suitable for use in connection with the methods of the present disclosure. The data storage medium may comprise any manufacture comprising a recording of the present information as described above, or a memory access device that can access such a manufacture.

(0072] To “record” data, programming or other information on a computer readable medium refers to a process for storing information, using any such methods as known in the art. Any convenient data storage structure may be chosen, based on the means used to access the stored information. A variety of data processor programs and formats can be used for storage, e.g. word processing text file, database format, etc.

(0073] A “processor” or “computing means” references any hardware and/or software combination that will perform the functions required of it. For example, a suitable processor may be a programmable digital microprocessor such as available in the form of an electronic controller, mainframe, server or personal computer (desktop or portable). Where the processor is programmable, suitable programming can be communicated from a remote location to the processor, or previously saved in a computer program product (such as a portable or fixed computer readable storage medium, whether magnetic, optical or solid state 15

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WO 2013/116144 PCT/US2013/023409 device based). For example, a magnetic medium or optical disk may carry the programming, and can be read by a suitable reader communicating with each processor at its corresponding station.

Algorithm-Based methods and Gene Subsets

[0074] The present invention provides an algorithm-based molecular diagnostic assay for predicting a clinical outcome for a patient with prostate cancer. The expression level of one or more genes may be used alone or arranged into functional gene subsets to calculate a quantitative score that can be used to predict the likelihood of a clinical outcome. The algorithm-based assay and associated information provided by the practice of the methods of the present invention facilitate optimal treatment decision-making in prostate cancer. For example, such a clinical tool would enable physicians to identify patients who have a low likelihood of having an aggressive cancer and therefore would not need RP, or who have a high likelihood of having an aggressive cancer and therefore would need RP.

[0075] As used herein, a “quantitative score” is an arithmetically or mathematically calculated numerical value for aiding in simplifying or disclosing or informing the analysis of more complex quantitative information, such as the correlation of certain expression levels of the disclosed genes or gene subsets to a likelihood of a clinical outcome of a prostate cancer patient. A quantitative score may be determined by the application of a specific algorithm. The algorithm used to calculate the quantitative score in the methods disclosed herein may group tire expression level values of genes. The grouping of genes may be performed at least in part based on knowledge of the relative contribution of the genes according to physiologic functions or component cellular characteristics, such as in the groups discussed herein. A quantitative score may be determined for a gene group (“gene group score”). The formation of groups, in addition, can facilitate the mathematical weighting of the contribution of various expression levels of genes or gene subsets to the quantitative score. The weighting of a gene or gene group representing a physiological process or component cellular characteristic can reflect the contribution of that process or characteristic to the pathology of the cancer and clinical outcome, such as recurrence or upgrading/upstaging of the cancer. Ilie present invention provides a number of algorithms for calculating the quantitative scores, for example, as set forth in Table 4. Jn an embodiment of the invention, an increase in the quantitative score indicates an increased likelihood of a negative clinical outcome.

[9976] In an embodiment, a quantitative score is a “recurrence score,” which indicates the likelihood of a cancer recurrence, upgrading or upstaging of a cancer, adverse pathology', non-organ-confined disease, high-grade disease, and/or highgrade or non-organ-confined 16

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PCT/US2013/023409 disease. An increase in the recurrence score may correlate with an increase in the likelihood of cancer recurrence, upgrading or upstaging of a cancer, adverse pathology, non-organconfined disease, high-grade disease, and/or highgrade or non-organ-confmed disease.

[0077] The gene subsets of the present invention include an ECM gene group, migration gene group, androgen gene group, proliferation gene group, epithelia gene group, and stress gene group.

[0078] The gene subsets referred to herein as the “ECM gene group,” “stromal gene group,” and “stromal response gene group” are used interchangeably and include genes that are synthesized predominantly by stromal cells and are involved in stromal response and genes that co-express with the genes of the ECM gene group. “Stromal cells” are referred to herein as connective tissue cells that make up die support structure of biological tissues. Stromal cells include fibroblasts, immune cells, pericytes, endothelial cells, and inflammatory cells. “Stromal response” refers to a desmoplastic response of the host tissues at the site of a primary tumor or invasion. See, e.g., E. Rubin, J. Farber, Pathlogy, 985-986 (end Ed. 1994). The ECM gene group includes, for example, ASPN, SFRP4, BGN, THBS2, ÎNHBA, COLIA1, COL3A1, COL1A2, SPARC, COL8A1, COL4A1, FN1, FAP, and COL5A2, and co-expressed genes thereof. Exemplary «©-expressed genes include the genes and/or gene cliques shown in Table 8.

[0079] The gene subsets referred to herein as the “migration gene group” or “migration regulation gene group” or “cytoskeletal gene group” or “cellular organization gene group” are used interchangeably and include genes and co-expressed genes that are part of a dynamic microfilament network of actin and accessory proteins and that provide intracellular support to cells, generate the physical forces for cell movement and cell division, as well as facilitate intracellular transport of vesicles and cellular organelle. The migration gene group includes, for example, BIN1, IGF1, C7, GSN, DES, TGFB1I1, TPM2, VCL, FLNC, ITGA7, COL6A1, PPP1R12A, GSTM1, GSTM2, PAGE4, PPAP2B, SRD5A2, PRKCA, IGFBP6, GPM6B, OLFML3, and ULF, and co-expressed genes thereof. Exemplary co-expressed genes and/or gene cliques are provided in Table 9.

[0080] The gene subset referred to herein as tlw “androgen gene group,” “PSA gene group,” and “PSA regulation gene group” are used interchangeably and include genes that are members of the kaliikrein family of serine proteases (e.g. kaliikrein 3 [PSA]), and genes that co-express with genes of the androgen gene group. The androgen gene group includes, for example, FAM13C and KLK2, and co-expressed genes thereof. The androgen gene group may further comprise AZGP1 and SRD5A2, and co-expressed genes thereof.

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[0081 ] Oie gene subsets referred to herein as the “proliferation gene group” and “cell cycle gene group” are used interchangeably and include genes that are involved with cell cycle functions and genes that co-express with genes of the proliferation gene group. “Cell cycle functions” as used herein refers to cell proliferation and cell cycle control, e.g., checkpoinVGl to S phase transition. The proliferation gene group thus includes, for example, CDC20, TPX2, UBE2T, MYBL2, and CDKN2C, and co-expressed genes thereof.

Exemplary co-expressed genes and/or gene cliques are provided in Table 10.

[0082] The gene subsets referred to herein as the “epithelia gene group” and “basal epithelia gene group” are used interchangeably and include genes that are expressed during the differentiation of a polarized epithelium and that provide intracellular structural integrity to facilitate physical interactions with neighboring epithelial cells, and genes that co-express with genes of the epithelia gene group. The epithelia gene group includes, for example, CYP3A5, KRT15, KRT5, LAMB3, and SDC1 and co-expressed genes thereof.

(0083] The gene subset referred to herein as the “stress gene group,” “stress response gene group,” and “early response gene group” are used interchangeably and includes genes and coexpressed genes that are transcription factors and DNA-binding proteins activated rapidly and transiently in response to cellular stress and other extracellular signals. These factors, in turn, regulate the transcription of a diverse range of genes. The stress gene group includes, for example, DUSP1, EGR1. FOS, JUN, EGR3, GADD45B, and ZFP36, and co-expressed genes thereof. Exemplary co-expressed genes and/or gene cliques are provided in Table 11.

[0084] Expression levels of other genes and their co-expressed genes may be used with one more of the above gene subsets to predict a likelihood of a clinical outcome of a prostate cancer patient. For example, the expression level of one or more genes selected from the 81 genes of Figure 1 or Tabic 1A or IB that do not fall within any of the disclosed gene subsets may be used with one or more of the disclosed gene subsets. In an embodiment of the invention, one or more of STAT5B, NFAT5, AZGP1, ANPEP, IGFBP2, SLC22A3, ERG. AR, SRD5A2, GSTM1, and GSTM2 may be used in one or more gene subsets described above to predict a likelihood of a clinical outcome.

[0085] The present invention also provides methods to determine a threshold expression level for a particular gene. A threshold expression level may be calculated for a specific gene. A threshold expression level for a gene may be based on a normalized expression level. In one example, a Cpthreshold expression level may be calculated by assessing functional forms using logistic regression or Cox proportional hazards regression.

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[0086] ÏTie present invention further provides methods to determine genes that co-express with particular genes identified by, e.g., quantitative RT-PCR (qRT-PCR), as validated biomaikers relevant to a particular type of cancer. The co-expressed genes are themselves useful biomarkers. The co-expressed genes may be substituted for the genes with which they co-express. The methods can include identifying gene cliques from microarray data, normalizing the microarray data, computing a pairwise Spearman correlation matrix for the array probes, filtering out significant co-expressed probes across different studies, building a graph, mapping the probe to genes, and generating a gene clique report. An exemplary method for identifying co-expressed genes is described in Example 3 below, and coexpressed genes identified using this method are provided in Tables 8-11. 'Hie expression levels of one or more genes of a gene clique may be used to calculate the likelihood that a patient with prostate cancer will experience a positive clinical outcome, such as a reduced likelihood of a cancer recurrence.

[0087] Any one or more combinations of gene groups may be assayed in the method of the present invention. For example, a stromal response gene group may be assayed, alone or in combination, with a cellular organization gene group, a proliferation gene group, and/or an androgen gene group. In addition, any number of genes within each gene group may be assayed.

[0088] In a specific embodiment of the invention, a method for predicting a clinical outcome for a patient with prostate cancer comprises measuring an expression level of at least one gene from a stromal response gene group, or a co-expressed gene thereof, and at least one gene from a cellular organization gene group, or a co-expressed gene thereof. In another embodiment, the expression level of at least two genes from a stromal response gene group, or a co-expressed gene thereof and at least two genes from a cellular organization gene group, or a co-expressed gene thereof, are measured. In yet another embodiment, the expression levels of at least three genes are measured from each of the stromal response gene group and the cellular organization gene group. In a further embodiment, the expression levels of at least four genes are measured from each of the stromal response gene group and the cellular organization gene group. In another embodiment, the expression levels of at least five genes are measured from each of the stromal response gene group and the cellular organization gene group. In yet a further embodiment, the expression levels of at least six genes are measured from each of the stromal response gene group and the cellular organization gene group.

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[0089] In another specific embodiment, the expression level of at least one gene from the stromal response gene group, or a co-expressed gene thereof, may be measured in addition to the expression level of at least one gene from an androgen gene group, or a co-expressed gene thereof. In a particular embodiment, the expression levels of at least three genes, or coexpressed genes thereof, from the stromal response gene group, and die expression level of at least one gene, or co-expressed gene thereof, from the androgen gene group may be measured.

[0090] In a further embodiment, the expression level of at least one gene each from the stromal response gene group, tire androgen gene group, and the cellular organization gene group, or co-expressed genes thereof, may be measured. In a particular embodiment, the level of at least three genes from the stromal resonse gene group, at least one gene from the androgen gene group, and at least three genes from the cellular organization gene group may be measured, In another embodiment, the expression level of at least one gene each from the stromal response gene group, the androgen gene group, and the proliferation gene group, or co-expressed genes thereof, may be measured. In a particular embodiment, the level of at least three genes from the stromal response gene group, at least one gene from the androgen gene group, and al least one gene from the proliferation gene group may be measured. In either of these combinations, at least two genes from the androgen gene group may also be measured. In any of the combinations, at least four genes from the androgen gene group may also be measured.

[0091] In another embodiment, the expression level of at least one gene each from the stromal response gene group, the androgen gene group, the cellular organization gene group, and the proliferation gene group, or co-expressed genes thereof, may be measured. In a particular embodiment, the level of at least three genes from the stromal response gene group, at least three genes from the cellular organization gene group, at least one gene from the proliferation gene group, and at least Iwo genes from the androgen gene group may be measured. In any of the embodiments, at least four genes from the androgen gene group may be measured.

[0092] Additionally, expression levels of one or more genes that do not fall within the gene subsets described herein may be measured with any of the combinations of the gene subsets described herein. Alternatively, any gene that falls within a gene subset may be analyzed separately from the gene subset, or in another gene subset. For example, the expression levels of at least one, at least two, at least three, or at least 4 genes may be measured in addition to the gene subsets described herein. In an embodiment of the invention, the 20

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WO 2013/116144 PCT/US2013/023409 additional geneis) are selected from STAT5B, NFAT5, AZGPl, ANPEP, 1GFBP2, SLC22A3, ERG, AR, SRD5A2, GSTM1, and GSTM2.

{0093] In a specific embodiment, the method of the invention comprises measuring the expression levels of the specific combinations of genes and gene subsets shown in Table 4, In a further embodiment, gene group score(s) and quantitative score(s) are calculated according to the algorithm(s) shown in Table 4,

[0094] Various technological approaches for determination of expression levels of the disclosed genes are set forth in this specification, including, without limitation, RT-PCR, microarrays, high-throughput sequencing, serial analysis of gene expression (SAGE) and Digital Gene Expression (DGE), which will be discussed in detail below. In particular aspects, the expression level of each gene may be determined in relation to various features of the expression products of the gene including exons, introns, protein epitopes and protein activity'.

[0095] The expression product that is assayed can be, for example, RNA or a polypeptide. 'Die expression product may be fragmented. For example, the assay may use primers that are complementary to target sequences of an expression product and could thus measure frill transcripts as well as those fragmented expression products containing the target sequence. Further information is provided in Table A.

[0096] The RNA expression product may be assayed directly or by detection of a cDN A product resulting from a PCR-bascd amplification method, e.g., quantitative reverse transcription polymerase chain reaction (qRT-PCR). (See e.g., U.S. Patent No. 7,587,279). Polypeptide expression product may be assayed using immunohistochemistry (IHC) by proteomics techniques. Further, both RNA and polypeptide expression products may also be assayed using microarrays.

Methods of assaying Expression Levels of a Gene Product

[0097] Methods of gene expression profiling include methods based on hybridization analysis of polynucleotides, methods based on sequencing of polynucleotides, and proteomics- based methods. Exemplary’ methods known in the art for the quantification of RNA expression in a sample include northern blotting and in situ hybridization (Parker & Barnes, Methods in Molecular Biology 106:247-283 (1999)); RNAse protection assays (Hod, Biotechniques 13:852-854 (1992)); and PCR-based methods, such as reverse transcription PCR (RT-PCR) (Weis et al., Trends in Genetics 8:263-264 (1992)). Antibodies may be employed that can recognize sequence-specific duplexes, including DNA duplexes, RNA duplexes, and DNA-RNA hybrid duplexes or DNA-protein duplexes. Representative methods

Λί I

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PCT/US2013/023409 for sequencing-based gene expression analysis include Serial Analysis of Gene Expression (SAGE), and gene expression analysis by massively parallel signature sequencing (MPSS). Other methods known in the art may be used.

Reverse Transcription PCR (RT-PCR)

[0098] Typically, mRNA is isolated from a test sample. The starting material is typically total RNA isolated from a human tumor, usually from a primary' tumor. Optionally, normal tissues from the same patient can be used as an internal control. Such normal tissue can be histologically-appearing normal tissue adjacent to a tumor. mRNA can be extracted from a tissue sample, e.g., from a sample that is fresh, frozen (e.g. fresh frozen), or paraffinembedded and fixed (e.g. formalin-fixed).

[0099] General methods for mRNA extraction are well known in the art and are disclosed in standard textbooks of molecular biology, including Ausubel et at, Current Protocols of Molecular Biology, John Wiley and Sons (1997). Methods for RNA extraction from paraffin embedded tissues are disclosed, for example, in Rupp and Locker, Lab Invest. 56:A67 (1987). and De Andrés et al., BioTechniques 18:42044 (1995). In particular, RNA isolation can be performed using a purification kit, buffer set and protease from commercial manufacturers, such as Qiagen, according to the manufacturer’s instructions. For example, total RNA from cells in culture can be isolated using Qiagen RNeasy mini-columns. Other commercially available RNA isolation kits include MasterPure™ Complete DNA and RNA Purification Kit (EPICENTRE®, Madison, WI), and Paraffin Block RNA Isolation Kit (Ambion. Inc.). Total RNA from tissue samples can be isolated using RNA Stat-60 (TelTest). RNA prepared from tumor can be isolated, for example, by cesium chloride density gradient centrifugation.

[00100] The sample containing the RNA is then subjected to reverse transcription to produce eDNA from the RNA template, followed by exponential amplification in a PCR reaction. The two most commonly used reverse transcriptases are avilo myeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murine leukemia virus reverse transcriptase (MMLVRT). The reverse transcription step is typically primed using specific primers, random hexamers, or oligo-dT primers, depending on the circumstances and the goal of expression profiling. For example, extracted RNA can be reverse-transcribed using a GeneAmp RNA PCR kit (Perkin Elmer, CA, USA), following the manufacturer’s instructions. The derived cDNA can then be used as a template in the subsequent PCR reaction.

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[00101 ] PCR-based methods use a thermostable DNA-dependent DNA polymerase, such as a Taq DNA polymerase. For example, TaqMan® PCR typically utilizes the 5’-nuclease activity of Taq or Tth polymerase to hydrolyze a hybridization probe bound to its target amplicon, but any enzyme with equivalent 5’ nuclease activity can be used. Two oligonucleotide primers are used to generate an amplicon typical of a PCR reaction product. A third oligonucleotide, or probe, can be designed to facilitate detection of a nucleotide sequence of the amplicon located between the hybridization sites the two PCR primers. The probe can be detectably labeled, e.g., with a reporter dye, and can further be provided with both a fluorescent dye, and a quencher fluorescent dye, as in a Taqman® probe configuration. Where a Taqman® probe is used, during the amplification reaction, the Taq DNA polymerase enzyme cleaves the probe in a template-dependent manner. The resultant probe fragments disassociate in solution, and signal from the released reporter dye is free from the quenching effect of the second fluorophore. One molecule of reporter dye is liberated for each new molecule synthesized, and detection of the unquenched reporter dye provides the basis for quantitative interpretation of (he data.

[001021 TaqMan® RT-PCR can be performed using commercially available equipment, such as, for example, high-throughput platforms such as the ABI PRISM 7700 Sequence Detection System® (Perkin-Elmer-Applied Biosystems, Foster City, CA, USA), or Lightcycier (Roche Molecular Biochemicals, Mannheim, Germany). In a preferred embodiment, the procedure is run on a LightCyclcr® 480 (Roche Diagnostics) real-time PCR system. which is a microwell plate-based cycler platform.

[00103J 5-Nuclease assay data are commonly initially expressed as a threshold cycle (“C”). Fluorescence values are recorded during every cycle and represent the amount of product amplified to that point in the amplification reaction. The threshold cycle (C_t) is generally described as the point when the fluorescent signal is first recorded as statistically significant. Alternatively, data may be expressed as a crossing point ( “Cp”). The Cp value is calculated by determining the second derivatives of entire qPCR amplification curves and their maximum value. The Cp value represents the cycle at which the increase of fluorescence is highest and where the logarithmic phase of a PCR begins.

[00104| To minimize errors and the effect of sampie-to-sample variation, RT-PCR is usually performed using an internal standard. The ideal internal standard gene (also referred to as a reference gene) is expressed at a quite constant level among cancerous and non-cancerous tissue of the same origin (i.e., a level that is not significantly different among normal and cancerous tissues), and is not significantly affected by the experimental treatment (Le., does 23

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WO 2013/116144 PCT/US2013/023409 not exhibit a significant difference in expression level in the relevant tissue as a result of exposure to chemotherapy), and expressed at a quite constant level among the same tissue taken from different patients. For example, reference genes useful in the methods disclosed herein should not exhibit significantly different expression levels in cancerous prostate as compared to normal prostate tissue. Exemplary reference genes used for normalization comprise one or more of the following genes: AAMP, ARF1, ATP5E, CLTC, GPS1, and PGK1. Gene expression measurements can be normalized relative to the mean of one or more (e.g., 2,3,4,5, or more) reference genes. Reference-normalized expression measurements can range from 2 to 15, where a one unit increase generally reflects a 2-fold increase in RNA quantity.

[00105] Real time PCR is compatible both with quantitative competitive PCR, where an internal competitor for each target sequence is used for normalization, and with quantitative comparative PCR using a normalization gene contained within the sample, or a housekeeping gene for RT-PCR. For further details see, e.g. Held et al., Genome Research 6:986-994 (1996).

[00i 06] The steps of a representative protocol for use in the methods of the present disclosure use fixed, paraffin-embedded tissues as the RNA source. For example, mRNA isolation, purification, primer extension and amplification can be performed according to methods available in the art. (see, e.g., Godfrey et ai. J. Molec. Diagnostics 2: 84-91 (2000); Specht et al.. Am. J. Pathol. 158:419-29 (2001)). Briefly, a representative process starts with, cutting about 10 gm thick sections of paraffin-embedded tumor tissue samples. The RNA is then extracted, and protein and DNA depleted from the RNA-containing sample. After analysis of the RNA concentration, RNA is reverse transcribed using gene-specific primers followed by RT-PCR to provide for cDNA amplification products.

Design of Intron-Based PCR Primers and Probes

[00107] PCR primers and probes can be designed based upon sxon or intron sequences present in (he mRNA transcript of the gene of interest. Primer/probe design can be performed using publicly available software, such as the DNA BLAT software developed by Kent, WJ., Genome Res. 12(4):656-64 (2002), or by the BLAST software including its variations.

[00108] Where necessary or desired, repetitive sequences of foe target sequence can be masked to mitigate non-specific signals. Exemplary tools to accomplish this include the Repeat Masker program available on-line through the Baylor College of Medicine, which screens DNA sequences against a library of repetitive elements and returns a query sequence in which the repetitive elements are masked. The masked intron sequences can then be used to design primer and probe sequences using any commercially or otherwise publicly available primer/probe design packages, such as Primer Express (Applied Biosystems); MGB assayby-design (Applied Biosystems); Primer3 (Steve Rozen and Helen J. Skaletsky (2000) Primer3 on the WWW for general users and for biologist programmers. See S, Rrawetz, S. Misener, Bioinformatics Methods and Protocols: Methods in Molecular Biology, pp. 365-386 (Humana Press).

100109] Other factors that can influence PCR primer design include primer length, melting temperature (Tm), and G/C content, specificity, complementary primer sequences, and 3 end sequence. In general, optimal PCR primers are generally 17-30 bases in length, and contain about 20-80%, such as, for example, about 50-60% G+C bases, and exhibit Tm’s between 50 and 80 0C, e.g. about 50 to 70 0C.

|00110] For further guidelines for PCR primer and probe design see, e.g. Dieffenbach. CW. et al, “General Concepts for PCR Primer Design” in: PCR Primer, A Laboratory Manual, Cold Spring Harbor Laboratory Press,. New York, 1995, pp. 133-155; Innis and Gelfand, “Optimization of PCRs” in: PCR Protocols, A Guide to Methods and Applications, CRC Press, London, 1994, pp. 5-11 ; and Plasterer, T.N. Primerselect: Primer and probe design. Methods Mol. Biol. 70:520-527 (1997).

[00111] Table A provides further information concerning the primer, probe, and amplicon sequences associated with the Examples disclosed herein.

MassARRAY® System (00112] In MassARRAY-based methods, such as the exemplary method developed by Scquenom, Inc. (San Diego, CA) following the isolation of RNA and reverse transcription, the obtained cDNA is spiked with a synthetic DNA molecule (competitor), which matches the targeted cDNA region in all positions, except a single base, and serves as an internal standard. The cDNA/competitor mixture is PCR amplified and is subjected to a post-PCR shrimp alkaline phosphatase (SAP) enzyme treatment, which results in the dephosphorylation of the remaining nucleotides. After inactivation of the alkaline phosphatase, the PCR products from the competitor and cDNA are subjected to primer extension, which generates distinct mass signals for the competitor- and cDNA-derives PCR products. After purification, these products are dispensed on a chip array, which is pre-loaded with components needed for analysis with matrix- assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis. The cDNA present in the reaction is then quantified by

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PCT/US2013/023409 analyzing the ratios of the peak areas in the mass spectrum generated. For further details see, e.g. Ding and Cantor, Proc. Natl Acad. Sci. USA 100:3059-3064 (20()3).

Other PCR-based Methods

[00113| Further PCR-based techniques that can find use in the methods disclosed herein include, for example, BeadArray® technology (Illumina, San Diego, CA; Oliphant et al., Discovery of Markers for Disease (Supplement to Biotechniques), June 2002; Ferguson et al., Analytical Chemistry 72:5618 (2000)); BeadsArray for Detection of Gene Expression® (BADGE), using the commercially available LuminexiOO LabMAP® system and multiple color-coded microspheres (Luminex Corp., Austin, TX) in a rapid assay for gene expression (Yang et ak. Genome Res. 11:1888-1898 (2001 )); and high coverage expression profiling (HiCEP) analysis (Fukumura et al., NucL Acids. Res. 31(16) e94 (2003).

Microarrays

[00114! Expression levels of a gene or microArray of interest can also be assessed using the microarray technique. In this method, polynucleotide sequences of interest (including cDNAs and oligonucleotides) are arrayed on a substrate. The arrayed sequences are then contacted under conditions suitable for specific hybridization with detectably labeled cDNA generated from RNA of a test sample. As in the RT-PCR method, the source of RNA typically is total RNA isolated from a tumor sample, and optionally from normal tissue of the same patient as an internal control or cell lines. RNA can be extracted, for example, from frozen or archived paraffin-embedded and fixed (e.g. formalin-fixed) tissue samples.

[00115 j For example, PCR amplified inserts of cDNA clones of a gene to be assayed are applied to a substrate in a dense array. Usually at least 10,000 nucleotide sequences are applied io the substrate. For example, the microarrayed genes, immobilized on the microchip at 10,000 elements each, are suitable for hybridization under stringent conditions.

Fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest. Labeled cDNA probes applied to die chip hybridize with specificity to each spot of DNA on the array. After washing under stringent conditions to remove non-specifically bound probes, the chip is scanned by confocal laser microscopy or by another detection method, such as a CCD camera. Quantitation.of hybridization of each arrayed element allows for assessment of corresponding RNA abundance.

[00116] With dual color fluorescence, separately labeled cDNA probes generated from two sources of RNA are hybridized pair wise to the array. The relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined 26

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PCT/US2013/023409 simultaneously. The miniaturized scale of the hybridization affords a convenient and rapid e valuation of the expression pattern for large numbers of genes. Such methods have been shown to have the sensitivity required to detect rare transcripts, which are expressed at a tew copies per cell, and to reproducibly detect at least approximately two-fold differences in the expression levels (Schenaet at, Proc. Natl. Acad. ScL USA 93(2):106-149 (1996)).

Microarray analysis can be performed by commercially available equipment, following manufacturer's protocols, such as by using the Affymetrix GenChip® technology, or Incyte's microarray technology.

Serial Analysis of Gene Expression (SAGE)

[00117] Serial analysis of gene expression (SAGE) is a method that allows the simultaneous and quantitative analysis of a large number of gene transcripts, without the need of providing an individual hybridization probe for each transcript. First, a short sequence tag (about 10-14 bp) is generated that contains sufficient information to uniquely identify a transcript, provided that the tag is obtained from a unique position within each transcript. Then, many transcripts are linked together to form long serial molecules, that can be sequenced, revealing the identity of the multiple tags simultaneously. The expression pattern of any population of transcripts can be quantitatively evaluated by determining the abundance of individual tags, and identifying the gene corresponding to each tag. For more details see, e.g. Velculescu et ah, Science 270:484-487 (1995); and Velculescu et al., Cell 88:243-51 (1997).

Gene Expression Analysis by Nucleic Add Sequencing

[00118] Nucleic acid sequencing technologies are suitable methods for analysis of gene expression. The principle underlying these methods is that the number of times a cDNA sequence is detected in a sample is directly related to tire relative expression of the RNA corresponding to that sequence. These methods are sometimes referred to by the term Digital Gene Expression (DGE) to reflect the discrete numeric property of the resulting data. Early methods applying this principle were Serial Analysis of Gene Expression (SAGE) and Massively Parallel Signature Sequencing (MPSS). See, e.g., S. Brenner, et ah, Nature Biotechnology i 8(6):630-634 (2000). More recently, the advent of next-generation” sequencing technologies has made DGE simpler, higher throughput, and more affordable. As a result, more laboratories are able to utilize DGE to screen the expression of more genes in more individual patient samples than previously possible. See, e.g., J. Marioni, Genome Research 18(9):1509-1517 (2008); R. Morin, Genome Research 18(4):610-621 (2008); A. Mortazavi, Nature Methods 5(7):621-628 (2008); N. Cloonan, Nature Methods 5(7):613-619 (2008).

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Isolating RNA from Body Fluids

[00119] Methods of isolating RNA for expression analysis from blood, plasma and serum (see. e.g., K. Enders, et al., Clin Chem 48,1647-53 (2002) (and references cited therein) and from urine (see, e.g., R. Boom, et al., J Clin Microbiol. 28,495-503 (1990) and references cited therein) have been described.

Immunohistochemistry

[00129] Immunohistochemistry methods are also suitable for detecting the expression levels of genes and applied to the method disclosed herein. Antibodies (e.g., monoclonal antibodies) that specifically bind a gene product of a gene cf interest can be used in such methods. The antibodies can be detected by direct labeling of the antibodies themselves, for example, with radioactive labels, fluorescent labels, hapten* labels such as, biotin, or an enzyme such as horse radish peroxidase or alkaline phosphatase. Alternatively, unlabeied primary antibody can be used in conjunction with a labeled secondary antibody specific for the primary antibody. Immunohistochemistry protocols and kits are well known in the art and are commercially available.

Proteomics

[0Ô121] The term “proteome” is defined as the totality of the proteins present in a sample (e,g. tissue, organism, or cell culture) at a certain point of time. Proteomics includes, among other things, study of the global changes of protein expression in a sample (also referred to as “expression proteomics”). Proteomics typically includes the following steps: (1) separation of individual proteins in a sample by 2-D gel electrophoresis (2-D PAGE); (2) identification of the individual proteins recovered from the gel, e.g. my mass spectrometry or N- terminal sequencing, and (3) analysis of the data using bioinformatics.

General Description of the mRNA Isolation, Purification and Amplification [00122] The steps of a representative protocol for profiling gene expression using fixed, paraffin-embedded tissues as the RNA source, including mRNA isolation, purification, primer extension and amplification are provided in various published journal articles. (See, e.g., T.E. Godfrey, et al,. J. Molec. Diagnostics 2:84-91 (2000); K. Specht et al., Am. J. Pathol. 158:419-29 (2001), M. Cronin, et al.. Am J Pathol 164:35-42 (2004)). Briefly, a representative process starts with cutting a tissue sample section (e.g.aboui 10 pm thick sections of a paraffin-embedded tumor tissue sample). The RNA is then extracted, and protein and DNA are removed. After analysis of the RNA concentration, RNA repair is performed if desired. The sample can then be subjected to analysis, e.g., by reverse transcribed using gene specific promoters followed by RT-PCR.

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Statistical Analysis Of Expression levels in Identification wmmvamonamnvtmivWTrawmwvmviwwwmwmwwwvvmmwvwwmtmvwmmwvnvvrnvmvmvvrm

[00123] One skilled in the art wi 11 recognize that there are many statistical methods that may be used to determine whether there is a significant relationship between a clinical outcome of interest (e.g,, recurrence) and expression levels of a marker gene as described here. In an exemplary embodiment, the present invention includes three studies. The first study is a stratified cohort sampling design (a form of case-control sampling) using tissue and data from prostate cancer patients. Selection of specimens was stratified by clinical T-stage (Tl, T2), year of surgery’ (<1993, >1993), and prostatectomy Gleason Score (low/intermediate, high). AH patients with clinical recurrence were selected and a stratified random sample of patients who did not experience a clinical recurrence was selected. For each patient, up to two enriched tumor specimens and one normal-appearing tissue sample were assayed. The second study used a subset of 70 patients from the first study from whom matched prostate biopsy tumor tissue was assayed. The third study includes all patients (170 evaluable patients) who had surgery for their prostate cancer between 1999 and 2010 at the Cleveland Clinic (CC) and had kw or Intermediate risk (by AHA) clinically localized prostate cancer who might have been reasonable candidates for active surveillance but who underwent RP at CC within 6 months of the diagnosis of prostate cancer by biopsy. Biopsy tumor tissue from these patients was assayed.

[ÛÔ124] Ail hypothesis tests were reported using two-sided p-values. To investigate if there is a significant relationship of outcomes (eg. clinical recurrence-free interval (cRFI), biochemical recurrence-free interval (bRFl), prostate cancer-specific survival (PCSS), overall survival (OS)) with individual genes, and demographic or clinical covariates), Cox Proportional Hazards (PH) models using maximum weighted pseudo partial-likelihood estimators were used and p-values from Wald tests of the null hypothesis that the hazard ratio (HR) is one are reported. To investigate if there is a significant relationship between individual genes and Gleason pattern of a particular sample, ordinal logistic regression models using maximum weighted pseudolikelihood methods were used and p-values from Wald teste of the null hypothesis that the odds ratio (OR) is one are reported. To investigate if there is a significant relationship between individual genes and upgrading and/or upstaging or adverse pathology at RP, logistic regression models using maximum weighted pseudo likelihood methods were used and p-values from Wald tests of the null hypothesis that the odds ratio (OR) is one are reported.

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Coexpression analysis

[00125] In an exemplary embodiment, the joint correlation of gene expression levels among prostate cancer specimens under study may be assessed. For tills purpose, the correlation structures among genes and specimens may be examined through hierarchical cluster methods. This information may be used to confirm that genes that are known to be highly correlated in prostate cancer specimens cluster together as expected. Only genes exhibiting a nominally significant (unadjusted p < 0.05) relationship with C.RFI in the univariate Cox PH regression analysis are included in these analyses.

[00126] One skilled in the art will recognize that many co-expression analysis methods now known or later developed will fall within the scope and spirit of the present invention. These methods may incorporate, for example, correlation coefficients, co-expression network analysis, clique analysis, etc., and may be based on expression data from RT-PCR, microarrays, sequencing, and other similar technologies. For example, gene expression clusters can be identified using pair-wise analysis of correlation based on Pearson or Spearman correlation coefficients. (See, e.g., Pearson K, and Lee A., Biometrika 2,357 (1902); C. Spearman, Amer, J. Psychol 15:72-101 (1904); J. Myers. A. Well, Research Design and Statistical Analysis, p. 508 (2nd Ed., 2003).) An exemplary method for identifying co-expressed genes is described in Example 3 below.

Normalization of Expression Levels

[00127] The expression data used in the methods disclosed herein can be normalized. Normalization refers to a process to correct for (normalize away), for example, differences in the amount of RNA assayed and variability in the quality of the RNA used, to remove unwanted sources of systematic variation in Ct or Cp measurements, and the like. With respect to RT-PCR experiments involving archived fixed paraffin embedded tissue samples, sources of systematic variation are known to include the degree of RNA degradation relative to the age of the patient sample and the type of fixative used to store the sample. Other sources of systematic variation are attributable to laboratory processing conditions.

[00128] Assays can provide for normalization by incorporating the expression of certain normalizing genes, which do not significantly differ in expression levels under the relevant conditions. Exemplary normalization genes disclosed herein include housekeeping genes. (See, e.g., E. Eisenberg, et al, Trends in Genetics 19(7):362-365 (2003).) Normalization can be based on the mean or median signal (Ct or Cp) of ail of the assayed genes or a large subset thereof (global normalization approach). In general, the normalizing genes, also referred to as reference genes, are typically genes that are known not to exhibit meaningfully different 30

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PCT/US2013/023409 expression in prostate cancer as compared to non-cancerous prostate tissue, and track with various sample and process conditions, thus provide for normalizing away extraneous effects. [00129] In exemplary embodiments, one or more of the following genes are used as references by which the mRNA expression data is normalized: A AMP, ARF1, ATP5E, CLTC. GPS1, and PGK1. The calibrated weighted average Ct or Cp measurements for each of the prognostic and predictive genes may be normalized relative to the mean of five or more reference genes.

100130] Those skilled in the art will recognize that normalization may be achieved in numerous ways, and the techniques described above are intended only to be exemplary, not exhaustive.

Standardization of Expression Levels

[00131] The expression data used in the methods disclosed herein can be standardized. Standardization refers to a process to effectively put all the genes on a comparable scale. This is performed because some genes will exhibit more variation (a broader range of expression) than others. Standardization is performed by dividing each expression value by its standard deviation across all samples for that gene. Hazard ratios are then interpreted as the proportional change in the hazard for the clinical endpoint (clinical recurrence, biological recurrence, death due to prostate cancer, or death due to any cause) per 1 standard deviation increase in expression.

Kits of the Invention

[60132] The materials for use in the methods of the present invention are suited for preparation of kits produced in accordance with well-known procedures. The present disclosure thus provides kits comprising agents, which may include gene-specific· or geneselective probes and/or primers, for quantifying the expression of the disclosed genes for predicting prognostic outcome or response to treatment. Such kits may optionally contain reagents for the extraction of RNA from tumor samples, in particular fixed paraffinembedded tissue samples and/or reagents for RNA amplification. In addition, the kits may optionally comprise the rcagent(s) with an identifying description or label or instructions relating to their use in the methods of the present invention. The kits may comprise containers (including microliter plates suitable for use in an automated implementation of the method), each with one or more of the various materials or reagents (typically in concentrated form) utilized in the methods, including, for example, chromatographic columns, pre-fabricated microarrays, buffers, the appropriate nucleotide triphosphates (e.g., dATP, dCTP, dGTP and dTTP; or rATP, rCTP, rGTP and DTP), reverse transcriptase, DNA polymerase, RNA

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PCT/US2013/023409 polymerase, and one or more probes and primers of the present invention (e.g., appropriate length poly(T) or random primers linked to a promoter reactive with the RNA polymerase). Mathematical algorithms used to estimate or quantify prognostic or predictive information are also properly potential components of kits.

Reports

[001331 The methods of this invention, when practiced for commercial diagnostic purposes, generally produce a report or summary of information obtained from the herein-described methods. For example, a report may include information concerning expression levels of one or more genes, classification of the tumor or the patient’s risk of recurrence, the patient’s likely prognosis or risk classification, clinical and pathologic factors, and/or other information. The methods and reports of this invention can further include storing the report in a database. Ilie method can create a record in a database for the subject and populate the record with data. The report may be a paper report, an auditory report, or an electronic record. The report may be displayed and/or stored on a computing device (e.g., handheld device, desktop computer, smart device, website, etc.). It is contemplated that the report is provided to a physician and/or the patient. The receiving of the report can further include establishing a network connection to a server computer that includes the data and report and requesting the data and report from the server computer.

Computer program

[00134] The values from the assays described above, such as expression data, can be calculated and stored manually. Alternatively, the above-described steps can be completely or partially performed by a computer program product. The present invention thus provides a computer program product including a computer readable storage medium having a computer program stored on it. The program can, when read by a computer, execute relevant calculations based on values obtained from anaiysis of one or more biological samples from an individual (e.g., gene expression levels, normalization, standardization, thresholding, and conversion of values from assays to a score and/or text or graphical depiction of tumor stage and related information). The computer program product has stored therein a computer program for performing the calculation.

[00135] The present disclosure provides systems for executing the program described above, which system generally includes: a) a central computing environment; b) an input device, operatively connected to the computing environment to receive patient data, wherein the patient data can include, for example, expression level or other value obtained from an assay using a biological sample from the patient, or microarray data, as described in detail above;

¢) an output device, connected to the computing environment, to provide information to a user (e.g., medical personnel); and d) an algorithm executed by the central computing environment (e.g., a processor), where the algorithm is executed based on the data received by the input device, and wherein the algorithm calculates an expression score, thresholding, or other functions described herein. The methods provided by the present invention may also be automated in whole or in part.

[00136] Having described the invention, the same will be more readily understood through reference to the following Examples, which are provided by way of illustration, and are not intended to limit the invention in any way.

Examples

EXAMPLE 1: SELECTION OF 81 GENES FOR ALGORITHM DEVELOPMENT [00137] A gene identification study to identify genes associated with clinical recurrence, biochemical recurrence and/or death from prostate cancer is described in U.S. Provisional Application Nos. 61/368,217, filed July 27,2010; 61'414,310, filed November 16,2010; and 61/485,536, filed May 12,2011, and in U.S. Pub. No. 20120028264, filed July 25,2011, and published February 2,2012. RT-PCR analysis was used to determine RNA expression levels for 732 genes and reference genes in prostate cancer tissue and surrounding normal appearing tissue (NAT) in patients with early-stage prostate cancer treated with radical prostatectomy. Genes significantly associated (p<0.05) with clinical recurrence-free interval (cRFI), biochemical recurrence-free interval (bRFI), prostate cancer-specific survival (PCSS), and upgrading/upstaging were determined.

[00138] From the genes that were identified as being associated with outcome, 81 genes were selected for subsequent algorithm development. The primers, probes, and amplicon sequences of the 81 genes (and 5 reference genes) are listed in Table A. The genes selected were among the most prognostic with respect to cRFI and other properties and shown in Tables I A-IB. Other properties considered were: 1) Strongest genes with respect to the regression to the mean corrected standardized hazard ratio for the association of gene expression and cRFI in the primary Gleason pattern tumor; 2) Consistency in association (hazard ratio) with cRFI using the highest Gleason pattern tumor; 3) Associated with prostate-cancer specific survival (PCSS); 4) Strong hazard ratio after adjustment for The University of San Francisco Cancer of the Prostate Risk Assessment (CAPRA) (Cooperberg étal., J. Urol. 173:1983-1942,2005); 5) Statistically significant odds ratio for the association between gene expression and surgical Gleason pattern of the tumor; 6) Large overall

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PCT/US2013/023409 variability with greater between-patient variability than within-patiem variability preferable; and 7) Highly expressed.

[00139] The true discovery rate degree of association (TDRDA) method (Crager, Stat Med. 2010 Jan 15;29(l ):33-45.) was used in the analysis of gene expression and cRFl and results are shown in Table 1 A. The true discovery rate is the counterpart to the false discovery rate. Univariate Cox PH regression models were fit and the TDRDA method was used to correct estimated standardized hazard ratios for regression to the mean (RM) and and assess false discovery rates for identification of genes with absolute standardized hazard ratio of at least a specified level. The false discovery rates were controlled at 10%. The TDRDA method identifies sets of genes among which a specified proportion are expected to have an absolute association (here, the absolute standardized hazard ratio) of a specified degree or more. This leads to a gene ranking method that uses the maximum lower bound (MLS) degree of association for which each gene belongs to a TDRDA set. Estimates of each gene’s actual degree of association with approximate correction for “selection bias” due to regression to the mean can be derived using simple bivariate norma! theory and Efron and Tibshirani’s empirical Bayes approach. Efron, Annals of Applied Statistics 2:197-223 (2008); Efron and Tibshirani. Genetic Epidemiology 23: 70-86. Table IA shows the RM-corrected estimate of the standardized hazard ratio and the MLB for each gene using either the primary Gleason pattern (PGP) or highest Gleason pattern (HGP) sample gene expression. Genes marked with a direction of association of -I are associated with a reduced likelihood of clinical recurrence, while those marked with a direction of association of 1 are associated with an increased likelihood of clinical recurrence.

[00140] Within patient and between patient variance components were estimated using a mixed model treating the patient effect as random. The overall mean and standard deviation of normalized gene expression as well as within- and between-patient components of variance are shown in Table I A.

[00141] Univariate Cox PH regression models using maximum weighted partial pseudolikelihood estimation were used to estimate the association between gens expression and prostate cancer specific-survival (PCSS). The standardized hazard ratio (HR), p-value and q-value using Storey’s FDR method are reported in Table IB. Storey, Journal of the Royal Statistical Society, Scries B 64:479-498 (2002). The q- va lue can be interpreted as the empirical Bayes posterior probability given the data that the gene identified is a false discovery', that is, the probability that it has no association with clinical recurrence.

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[00142] Univariate ordinaf logistic regression models were used to estimate the association between gene expression and tire Gleason pattern of the primary Gleason pattern tumor (3,4, 5), The standardized odds ratio (OR), p-value and q-value using Storey’s FDR method are reported in Table IB.

[00143] Figure 1 shows an example of a dendrogram depicting the association of die 81 genes. The y-axis corresponds to the average distance between clusters measured as 1Pearson r. The smaller the number (distance measure), the more highly correlated the genes. The amalgamation method is weighted pair-group average. Genes that were co-expressed were identified from the dendrogram and are grouped into gene groups. Based on Figure I, the genes from the Gene Identification study were formed into the following gene groups or subsets:

[00144] Cellular organization gene group (BINI; IGF1; C7; GSN; DES; TGFBill; TPM2; VCL; FLNC; 1TGA7; COL6A1; PPP1R12A: GSTM1; GSTM2: PAGE4; PPAP2B;

SRD5A2; PRKCA; IGFBP6; GPM6B; OLFML3; HLF)

[00145] Basal epithelia gene group (CYP3A5; KRT15; KRT5; LAMB3; SDCI) ]00146] Stress response gene group ( DUSPI ; EGR1 ; FOS; JUN; EGR3; GADD45B;

ZFP36)

[00147] Androgen gene group (FAMI3C; KLK2; AZGP1; SRD5A2)

[00148] Stromal gene group (ASPN; SFRP4; BGN; THBS2; 1NHBA; COL1A1; COL3A1;

COL1A2; SPARC; COL8AI; COL4A1; FN1; FAP; COL5A2)

[00149] Proliferation gene group (CDC20; TPX2; UBE2T; MYBL2; CDKN2C)

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EXAMPLE 2; ALGORITHM DEVELOPMENT BASED ON DATA FROM A

COMPANION STUDY

[00150] The Cleveland Clinic (“CC”) Companion study consists of three patient cohorts and separate analyses for each cohort as described in Table 2, The first cohort (Table 2) includes men with low to high risk (based on AUA criteria) prostate cancer from Gene ID study 09002 who underwent RP at CC between 1987 and 2004 and had diagnostic biopsy tissue available at CC. Cohorts 2 and 3 include men with clinically localized Low and Intermediate Risk (based on AUA criteria) prostate cancer, respectively, who might have been reasonable candidates for active surveillance but who underwent radical prostatectomy (RP) within 6 months of the diagnosis of prostate cancer by biopsy. The main objective of Cohort I was to compare the molecular profile from biopsy tissue with that from radical prostatectomy tissue. The main objective of Cohorts 2 and 3 was to develop a multigene predictor of upgrading/upstaging at RP using biopsy tissue in low to intermediate risk patients at diagnosis.

[00151] Matched biopsy samples were obtained for a subset of the patients (70 patients) from the gene identification study. Gene expression of the 81 selected genes and the 5 reference genes (ARFl, ATP5E, CLTC, GPSi, PGK1) were compared in the RP specimens and the biopsy tissue obtained from these 70 patients.

[00152] The 81 genes were evaluated in Cohorts 2 and 3 for association with upgrading and upstaging. The association between these 81 genes and upgrading and upstaging in Cohorts 2 and 3 are shown in Table 3. P values and standardized odds ratio are provided.

[00153] In this context, “upgrade” refers to an increase in Gleason grade from 3+3 or 3+4 at. the time of biopsy to greater than or equal to 3+4 at the time of RP. “UpgradeZ” refers to an increase in Gleason grade from 3+3 or 3+4 at the time of biopsy to greater than or equal to 4+3 at the time ofRP.

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TABLE 2

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<td> t</td><td> Subset of patients from Gene ID study 09-002 who underwent RP at CC between 1987 and 2(X)4 and had diagnostic biopsy tissue available at CC. PatienU from the original strati (led «short sample with available biopsy tissue blocks</td><td> 70</td><td> • Comparison of gene expression from : biopsy sample wuh gene expression । from RP specimen (Co-Primary Objective) • Explore association of risk of recurrence after RI’ with gene expression from biopsy sample and gene expression from RP sample • Explore association of risk of recurrence after RP with gene expression from RP samples</td>

<td> n</td><td> Low Risk Patients from CC database of patients who were biopsied, and then underwent RP atCC between ’.999 and 2010 All patients in database who meet minimum tumor tissue criteria</td><td> 92</td><td> • Association between gene expsession from biopsy sample· and likelihood of upgradingAipst aging in tissue obtained at prostatectomy • (Co-Primary Objective)</td>

<td> 3</td><td> Intermediate Risk Patients from CC database of patients who were biopsied, and then underwent RP at CC between 1999 and 2010 All patients in database who meet minimum tumor tissue criteria__________</td><td> 75</td><td> ♦ Association between gene expression from biopsy sample and likelihood of upgrading/upstaging in tissue obtained at prostatectomy I-.-.-.-.- - - ------------------------.6666 6 66 .IIIHIH</td>

|001S4] Several different models were explored to compare expression between the RP and biopsy specimens. Genes were chosen based on consistency of expression between the RP and biopsy specimens. Figures 2A-2E are the scatter plots showing the comparison of normalized gene expression (Cp) for matched samples from each patient where the x-axis is the normalized gene expression from the PGP RP sample (PGP) and the y-axis is the normalized gene expression from the biopsy sample (BX). Figures 3A-3D show range plots of gene expression of individual genes within each gene group in the biopsy (BX) and PGP RP samples.

[00155] After evaluating the concordance of gene expression in biopsy and RP samples, the following algorithms (RS models) shown in Table 4 were developed where the weights are determined using non-standardized, but normalized data. Some genes, such as SRD5A2 and GSTM2, which fall within the cellular organization gene group, were also evaluated separately and independent coefficients were assigned (see the “other” category in Table 4), In other instances, GSTM1 and GSMT2 were grouped as an oxidative “stress” group and a

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PCT/US2013/023409 coefficient was assigned to this “stress” group (see RS20 and RS22 models). Other genes, such as AZGP1 and SLC22A3, which did not fall within any of the gene groups, were also included in certain algorithms (see the “other” category in Tabic 4). Furthermore, the androgen gene group was established to include FAM13C, KLK2, AZGP1, and SRD5A2. Some genes such as BGN, SPARC, FLNC, GSN, TPX2 and SRD5A2 were thresholded before being evaluated in models. For example, normalized expression values below 4.5 were set to 4.5 for TPX2 and normalized expression values below 5.5 were set to 5.5 for SRD5A2.

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<td> RS Model</td><td> RS25</td><td> RS26</td><td> 5}</td>

CA 02863040 2014-07-28

WO 2013/116144 PCT/US2013/023409 (00156] Table 5A shows the standardized odds ratio of each of the RS models using the data from the original Gene ID study described in Example I for time to cR and for upgrading and upstaging and the combination of significant upgrading and upstaging. Table 5B shows the performance of each of the RS models using the data from the CC Companion (Cohorts 2 and 3) study for upgrading and upstaging and the combination of significant upgrading and upstaging. In this context “upgrading” refers to an increase in Gleason grade from 3+3 or 3+4 at biopsy to greater than or equal to 3+4 at radical prostatectomy. “Significant upgrading” in this context refers to upgrading from Gleason grade 3+3 or 3+4 at biopsy to equal to or greater than 4+3 at radical prostatectomy.

(80157] In addition, the gene groups used in the RS25 model were evaluated alone and in various combinations. Table 6A shows the results of this analysis using the data from the Gene Identification study and Table 6B shows the results of this analysis using the data from Cohorts 2 and 3 of the CC Companion Study.

[00158] The gene expression for some genes may be thresholded, for example SRD5A2 Thresh = 5.5 if SRD5A2 &lt;5.5 or SRD5A2 if SRD5A2 &gt;5.5 and TPX2 Thresh = 5.0 if TPX2 &lt;5.0 or TPX2 if TPX2 &gt;5.0, wherein the gene symbols represent normalized gene expression values.

[80159] The unsealed RS scores derived from Table 4 can also be rescaled to be between 0 and 100. For example, RS27 can be rescaled to be between 0 and 100 as follows: [00160] RS (scaled) «0 if 13.4 x(RSu+10.5)O; 13.4 x (RSu+10.5) if 0&lt;13.4x(RSu+W.5)&lt;100; or 100 if 13.4 x (RSu+10.5)&gt;100.

[00161] Using the scaled RS, patients can be classified into low, intermediate, and high RS groups using pre-specified cut-points defined below in Table B. These cut-points define the boundaries between low and intermediate RS groups and between intermediate and high RS groups. The cutpoints were derived from the discovery study with the intent of identifying substantial proportions of patients who on average had clinically meaningful low or high risk of aggressive disease. The scaled RS is rounded to the nearest integer before the cut-points defining RS groups are applied.

TABLE B.

[ RS Group ____» Risk Score _______

I____Low___________________I_______Less than 16

Intermediate I Greater than or equal to 16 and less than 30

......... «..μ..».........................

[__High__ϊ Greater than or equal to 30

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Example 3; Clique Stack Analysis to Identify Co-Expressep Genes [00162] The purpose of the gene clique stacks method described in this Example was to find a set of co-expressed (or surrogate) biomarkers that can be used to reliably predict outcome as well or better titan the genes disclosed above. The method used to identify the coexpressed markers is illustrated in Figure 4. The set of co-expressed biomarkers were obtained by seeding the maximal clique enumeration (MCE) with curated biomarkers extracted from the scientific literature. The maximal clique enumeration (MCE) method [Bron et al. 1973] aggregates genes into tightly co-expressed groups such that all of the genes in the group have a similar expression profile. When all of the genes in a group satisfy a minimal similarity condition, the group is called a clique. When a clique is as large as possible without admitting any ‘dissimilar’ genes into the clique, then the clique is said to be maximal. Using the MCE method, all maximal cliques are searched within a dataset. Using this method, almost any degree of overlap between the maximal cliques can be found, as long as the overlap is supported by the data. Maximal clique enumeration has been shown [Borate et al, 2009] to be an effective way of identifying co-expressed gene modules (CGMs).

1. Definitions

[00163] The following table defines a few terms commonly used in the gene clique stack analyses.

Table 7

<td> Term</td><td> Definition</td>

<td> Node</td><td> The abundance of a gene (for the purposes of CGM analysis)__</td>

<td> Edge</td><td> A line connecting two nodes, indicating co-expression of the two nodes</td>

<td> Graph</td><td> À collection of nodes and edges</td>

<td> Clique</td><td> A graph with an edge connecting all pair-wise combinations of nodes in the graph</td>

<td> maximal clique __ Stack</td><td> A clique that is not contained in any other clique ___________ A graph obtained by merging at least two cliques or stacks such that the overlap between the two cliques or stacks exceeds some user-</td>

<td></td><td> defined threshold.</td>

<td> gene expression profile</td><td> A two-dimensional matrix, with genes listed down the rows and samples listed across the columns. Each (i j) entry in the matrix corresponds to relative mRNA abundance for gene i and sample]. _</td>

2, Examples of clignes and stacks

[00164] Figure 5 shows a family of three different graphs. A graph consists of nodes (numbered) and connecting edges (lines). Figure 5(a) is not a clique because there is no edge connecting nodes 3 and 4. Figure 5(b) is a clique because there is an edge connecting all pair

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PCT/US2013/023409 wise combinations of nodes in the graph. Figure 5(c) is a clique, but not a maximai clique because it is contained in clique (b). Given a graph with connecting edges, the MCE algorithm will systematically list all of maximal cliques with 3 or more nodes. For example, the graph in Figure 6 has two maximal cliques: 1-2-3-4-5 and 1-2-3-4-6.

[00165] When based on gene expression data, there are typically large numbers of maximal cliques that are very' similar to one another. These maximal cliques can be merged into stacks of maxima! cliques. The stacks are the final gene modules of interest and generally are far fewer in number than are the maximal cliques. Figure 7 schematically illustrates stacking of two maximal cliques.

3. Seeding

[00166] For the purposes of finding surrogate co-expressed markers, biomarkers from the literature can be identified and then used to seed the MCE and stacking algorithms. The basic idea is as fellows: for each seed, compute a set of maximal cliques (using the parallel MCE algorithm). Then stack the maximal cliques obtained for each seed, yielding a set of seeded stacks. Finally, stack the seeded stacks to obtain a “stack of seeded stacks.” lite stack of seeded stacks is an approximation to the stacks that would be obtained by using the conventional (i.e. unseeded) MCE/stacking algorithms.The method used to identify genes that co-express with the genes disclosed above illustrated in Figure 4 and is described in more detail below.

3.1 Seeded MCE algorithm (steps 1-4) (00167] 1. The process begins by identifying an appropriate set, S_s, of seeding genes. In the instant case, the seeding genes were selected from ths gene subsets disclosed above.

[00168] 2. With the seeding genes specified, select a measure of correlation, R(gi,g2), between the gene expression profiles of any two genes, along with a correlation threshold below which g},g2, can be considered uncorrelated. For each seeding gene s in the seeding set S_s, find all gene pairs (s,g) in the dataset such that R(s,g) is greater than or equal to the correlation threshold. Let G_s be die union of s and the set of all genes correlated with s. For the instant study, the Spearman coefficient was used as the measure of correlation and 0.7 as the correlation threshold.

[00169] 3. Compute the correlation coefficient for each pair-wise combination of genes (gi,gj) in G₅. Let X_s be the set of all gene pairs for which R(g&gt;,gj) is greater than or equal to the correlation threshold. If the genes were plotted as in Figure 5, there would be an edge (line) between each pair of genes in X_s.

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[00170] 4. Run the MCE algorithm, as described in Schmidt et ai (J. Parallel Distrib. Comput. 69 (2009) 417-428) on the gene pairs X_s lor each seeding gene.

3.2 Seeded stacking algorithm (steps 5-6)

[00171] The purpose of stacking is to reduce the number of cliques down to a manageable number of gene modules (stacks). Continuing with steps 5 and 6 of Figure 4:

[00172] 5. For each seeding gene, sort cliques from largest to smallest, i.e. most number of nodes to smallest number of nodes. From the remaining cliques, find the clique with the greatest overlap. If the overlap exceeds a user-specified threshold T, merge the two cliques together to form the first stack. Resort the cliques and stack(s) from largest to smallest and repeat the overlap test and merging. Repeat the process until no new merges occur.

[00173] 6. One now has a set of stacks for each seeding gene. In the final step, all of the seeded stacks are combined into one set of stacks, σ. As the final computation, all of the stacks in σ are stacked, just as in step 5. This stack of stacks is the set of gene modules used for the instant study.

[00174] Genes that were shown to co-express with genes identified by this method are shown in Tables 8-11. “Stack ID” in the Tables is simply an index to enumerate the stacks and “probe Wt” refers to the probe weight, or the number of times a probe (gene) appears in the stack.

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<td> Coexpressed ί Gene ξ ProbeWt</td><td> PPAP28 I IS794</td><td> VWA5A Ϊ 12616</td><td> SPON1 I 12395</td><td> ί 8ΪΖΖΤ I V1V3</td><td> SSPN | 12126 \</td><td> MKXj 11S52 j</td><td> PRRX1 I 11061</td><td> 0Q © çn ιΛ 3 Ο</td><td> 1 SYNM | 10654 j</td><td> | ANXA6 j 10330 j</td><td> | PDE5A________]___10011 !</td><td> 1 T5HZ3 | 9588 j</td><td> 1 SOS 6 ] NS9 1</td><td> eose 1 ZG1N i</td><td> j ClU__________j____9304</td><td> [ TPM2 1 8659 |</td><td> I FBLN1 | 8068 |</td><td> PARVA______________ 7949</td><td> | SP0CK3 I 7772 j</td><td> VlCL..........| StHCDd |</td>

<td> : StackiD</td><td></td><td></td><td> τΉ</td><td></td><td></td><td></td><td></td><td> r-4</td><td> «~4</td><td></td><td> 7—4</td><td></td><td></td><td> «-4</td><td> r*i</td><td></td><td> r-4</td><td></td><td></td><td> |</td>

<td> Seeding PrabeWt Gene__</td><td> 168 | GSTM2 ]</td><td> 163 | GSTM2 j</td><td rowspan="2"> 1 RBMS3 £ 162 | GSTM2 j</td><td> 161 ! GSTM2 J</td><td rowspan="2"> [1 | MYLK ______L 158 | GSTM2 |</td><td> 155 | GSTM2 J</td><td> 1 154 j GSTM2 j</td><td> ______152 ί GSTM2 1</td><td> 1 147 i GSTM2 j</td><td> | 142 ί GSTM2 j</td><td> [ 141 | GSTM2 j</td><td> [ 132 | GSTM2___</td><td> i ¹³⁰ GSTM7 1</td><td> ί 127 j G5TM2___J</td><td> i 125 : GSTM2 j</td><td> 118 i GSTM2 j</td><td> i 101 ! GSTM2 __1</td><td> ί 72 î GSTM2 j</td><td> | 66 ί GSTM2 1</td><td> _______60 1 GSTM2____j</td>

<td rowspan="2"> ; [ Coexpressed 1 ί Seeding | Coexpressed i ; Stack» Gene ProbeWt I Gene | StackiD Gene</td><td rowspan="2"> [ 1 î OOR2 î 26870 i C7 [1 [ MYH11________|</td><td> £2 CÛ 2</td><td> ί 1 1 FHU</td><td> [1 {CACHOI ____</td><td> 1 1 ! TIMP3 I</td><td> ί 1 [ SYNM ____]</td><td> 1 1 | NEXN j</td><td> î 1 . j MYL9______________j</td><td> ________3 WAP 1 τ 1</td><td> i 1 | VWA5A</td><td> 1 1 j AOX1 _______I</td><td> «j Z &lt;4</td><td> Γ1 | PPAP2B</td><td> | 1 ] GSTM2</td><td> 1 1 î C21orf63</td><td> 1 1 P0P0C2 ί</td><td colspan="2"> 1 j TPM2_________j J________î CDC42EP3____</td>

<td> r-------— ................................i.............. i 1 SPARCLl 25953 I C7</td><td> I 1 FAT4 24985 | C7 !</td><td> | 1 SYNE1 ! 24825 | C7 |</td><td> | 1 SLC8A1 1 24327 | C7</td><td> ί 1 MEIS1 23197 1 C7 1</td><td> ί ί 1 PRRX1 ί 2284 7 | C7 1</td><td> [ 1 î CACHDl I 22236 J C7 Ί</td><td> ί 1 OPYSL3 \ 20623 | C7 ί</td><td> 1 1 1 LTBPS 1 20345 1 C7 j</td><td> ί i iSGK269 19461 | C7</td><td> i 1 I EDNRA 19280 1 C7 i</td><td> 1 ] TRPC4 i 18689 l C7 1</td><td> 1 1 ί T1MP3 | 18674 ί C7</td><td> 1 î TGF8R3 18367 ί C7</td><td> I 1 î ZEB1 1 18355 = C7 I</td><td> [ 1 Î CIS 16871 i C7 ]</td><td> Γϊ 1 ABCC9 16562 [ C7</td><td> j 1 î PCDH18 S 14936 i C7 I</td><td> ...........................j....... i 1 — -1 1_______[C7____________i 14789 ! C7_________</td>

CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

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Applicant Refi 09042.8-304 / GHÎ-052PCT rd cm φ ç Ο Φ W Φ

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CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 0904?.. $-304 ! GHI-O52PCT

<td> C &amp; «</td><td> Gene</td><td> SRD5A2____ i</td><td> SRD5A2 ____|</td><td> zvsaSs</td><td> SRD5A2 j</td><td> zwaus</td><td> SRD5A2</td><td> SRD5A2</td><td> SRDSA2 ΐ</td><td> SRO5A2</td><td> SRD5A2 ί</td><td> SRD5A2 1</td><td> SRD5A2 ί</td><td> SRD5A2\</td><td> SRD5A2 j</td><td> SRD5A2______</td><td> 5RD5A2 i</td><td> ί SVSQHS</td><td> £ o or &lt;n</td><td> SRD5A2 |</td><td> SRO5A2 j</td><td> SRD5A2_________</td><td> 5RO5A2 I</td><td> SRDSA2 |</td><td> SRD5A2 |</td><td> SRD5A2 j</td><td> SRD5A2______1</td><td> | SRD5A2_________ί</td>

<td></td><td> §</td><td> 1300 !</td><td></td><td> 1202 1</td><td> »*)ί Φ: vH ; :</td><td> © 3:</td><td> 1.107 j</td><td> 987 !</td><td> 930</td><td> 793J</td><td> 77S |</td><td> 733 j</td><td> .....673</td><td> I 899</td><td> 61.1 \</td><td> 519 i</td><td> 505 \</td><td> 493 j</td><td> o</td><td> 428 I</td><td> 9 07</td><td> 383</td><td> 322</td><td> 314</td><td> 278</td><td> 219 !</td><td> ! 66X I</td><td> ____1.74 ]</td>

<td></td><td> 2</td><td></td><td></td><td></td><td> :</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> Coexpressed 1</td><td> Gene |</td><td> a 2 SC</td><td> SCN7A j</td><td> GPM6B j</td><td> ARHGAP20________</td><td> PDZRN4 j</td><td> ' PCM i</td><td> : ANO5 I</td><td> © 0Ç Ç G 6© u</td><td> ARHGAP10</td><td> CUP4______</td><td> | 693033</td><td> co « xr g &lt;Λ</td><td> ACSS3__</td><td> IL33 1</td><td> ID IN &amp; s &lt; Q</td><td> &lt; swl Ë</td><td> aî 2 UI Lk LU</td><td> 1 kit §</td><td> [ODZ3 ;</td><td> u. CC A. £ s</td><td> C21orf63 ί</td><td> ί CRISPLD2</td><td> I MYADM</td><td> D</td><td> \ PDGFRA</td><td> EYAI .,.,...........</td><td> | ATP1A2__</td>

<td></td><td> Û 2 u co</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> 1½</td><td> v·»</td><td> T“l</td><td> TH</td><td> tH</td><td> TM</td><td> ▼H</td><td></td><td> th</td><td> •Ή</td><td> ♦**</td><td> &lt;H</td><td> Ή</td><td> &lt;H</td><td> »H</td><td> tH</td><td> xH</td><td> vH</td><td> »H</td><td></td><td></td><td> fH</td><td></td><td></td><td> tH</td><td> rH</td><td> rH</td><td> rH</td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> 1</td><td></td>

<td> &amp; c</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> Φ V VJ</td><td> Gene</td><td> IGFl</td><td> Ua £</td><td> Ui 2</td><td> IGFl</td><td> (GF1</td><td> IGFl</td><td> IGFl</td><td> IGFl</td><td> a</td><td> IGFl.</td><td> IGFl</td><td> IGFl</td><td> tH 2</td><td> IGFl</td><td></td><td> Γ IGFl</td><td> IGFl</td><td> tH</td><td> 1 IGFl</td><td> ! IGFl</td><td> I IGFl</td><td> ! IGFl</td><td> | IGFl</td><td> IGFl</td><td> è</td><td> ! IGFl</td><td> ί IGFl</td>

<td colspan="2"> w 5</td><td> 14</td><td> en «Μ</td><td> cn *H</td><td></td><td> tn</td><td></td><td> oo</td><td> 00</td><td> r&lt;</td><td> rx</td><td> ©</td><td> tn</td><td> 4</td><td> 4</td><td> KT</td><td> 4</td><td> KT</td><td> 4</td><td> 4</td><td> X?</td><td> 4</td><td> xr</td><td> XT</td><td> «T</td><td> XT</td><td> 4 :</td><td> 4</td>

<td> 1</td><td> £ g</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> ί</td><td></td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> *····*</td><td></td><td></td><td> .......</td><td></td><td></td><td></td><td></td>

<td> •8 Ώ V) 0» a δ δ</td><td> Gene______</td><td> SPRYD4</td><td> SGCB</td><td> IN MT</td><td> IGFl_________</td><td> ARPP19</td><td> M0CS3</td><td> « Z</td><td> εεμοεο</td><td> &lt; © y iA</td><td> OI3</td><td> X z «Λ</td><td> C1.orf5S</td><td> Clorfl74</td><td> MIKS</td><td> MCART6</td><td> OW03</td><td> ADAMTS4</td><td> FEZ1</td><td> SPATA5</td><td> £ CC z fN</td><td> σι ΓΗ CM X Q</td><td> STX2</td><td> PURB</td><td> BVES</td><td> DTX3L</td><td> : -1</td><td> St a</td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> :</td><td></td>

<td></td><td> Ω 5</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> Stas</td><td> PM</td><td> CM</td><td> OJ</td><td> IN</td><td> CM</td><td> (N</td><td> ΓΜ</td><td> CM</td><td> CM</td><td> IN</td><td> (N</td><td> CM</td><td> &lt;N</td><td> IN</td><td> ; &lt;n</td><td> ΓΜ</td><td> CM</td><td> &lt;N</td><td> (N</td><td> &lt;N</td><td> n</td><td> CM</td><td> &lt;N</td><td> : FM</td><td> CM</td><td> &lt;N</td><td> iM</td>

<td> Seeding |</td><td> Gene I</td><td> C7 1</td><td> C7 j</td><td> I ⁴³</td><td> 0</td><td> C7 j</td><td> C7 1</td><td></td><td></td><td> ΰ</td><td> c</td><td> ΰ</td><td> L ⁴³</td><td> C7 I</td><td> 1 ⁴³</td><td> 1 £3</td><td> C7 I</td><td> C7 i</td><td> G</td><td> 0</td><td></td><td> D</td><td> C7 1</td><td> C7</td><td> r. O</td><td> C7 I</td><td> 0</td><td> C7 1</td>

<td></td><td></td><td></td><td></td><td></td><td> UUlt</td><td></td><td> lUSISI</td><td> IUIU</td><td></td><td> IIIIWI</td><td></td><td></td><td></td><td></td><td> wnrtv</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> nnw</td>

<td></td><td> £</td><td> 6219</td><td> 6151</td><td> σι ω 4Λ</td><td> CM oo tn</td><td> o 0Ô un</td><td> 00 to</td><td> § Ui</td><td> 5063</td><td> 00 CM ¢0</td><td> 4825</td><td> 60 *</td><td> 00 xr •t TJ</td><td> 4329</td><td> ΙΛ CM</td><td> 3798</td><td> 3679</td><td> 3678</td><td> 3671</td><td> 02 Τ'! cn</td><td> iïï ♦H</td><td> 3126</td><td> rn © Ch (N</td><td> 2925</td><td> rH PM</td><td> 2609</td><td> 2519</td><td> &lt;0 1Λ ΓΜ</td>

<td></td><td> a</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td></td><td></td><td></td><td> ......</td><td> .......</td><td> .......</td><td></td><td></td><td></td><td></td><td> vwrt*</td><td></td><td> ......</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> ......</td><td colspan="2"> :—*......</td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> -a 0) V)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> l·</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> g CL X 03 o u</td><td> : Gene</td><td> î TIMP2</td><td> δ U</td><td> 1 ATP2B4</td><td> 1-1 LO g J τ'*</td><td> PDGFRA</td><td> 4 ë</td><td> Q X a</td><td> ICOL14A1</td><td> T CALD1</td><td> z Q</td><td> I</td><td> I MATN2</td><td> I KIT</td><td> NX3N ;</td><td> IM SÛ UI N</td><td> COL6A3</td><td> M o 2</td><td> Ï</td><td> 2 O</td><td> i V)</td><td> rH © o un</td><td> s U» Q</td><td> ΓΜ 03 o</td><td> ΓΜ X</td><td> &lt;N M O.</td><td> i § i H</td><td> ] ANXA6</td>

<td></td><td> Û $ 5 1A</td><td> :</td><td></td><td> rH</td><td> 1 rt</td><td> i</td><td></td><td></td><td> 1..7.</td><td> ! 1</td><td> ♦M</td><td> *&lt;</td><td> rH</td><td> 1</td><td></td><td> i 1</td><td> 4*t</td><td></td><td></td><td></td><td></td><td></td><td> 71</td><td> «4</td><td> «f4</td><td></td><td></td><td> ..7.</td>

CA 02863040 2014-07-20

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-304 / ÜH1-O52PC1’

<td> ......—T i i M ! E s » s g Λ ©</td><td colspan="2"> .....1......1 Oil Oli &lt;1 &lt; ml in Q □« ac a: VH V)</td><td rowspan="2"> 166 ] SRD5A2 j</td><td> SRD5A2__________j</td><td> SRD5A2_____</td><td rowspan="2"> ICO j SRD5A2 j</td><td rowspan="2"> ZVSOHS 1 Z6</td><td rowspan="2"> 90 SRD5A2____________</td><td rowspan="2"> 82 j SRD5A2 |</td><td rowspan="2"> 70 j SRDSA2_____</td><td> SRD5A2 1</td><td> 5RD5A2...........\</td><td> SRD5A2 \</td><td> SRD5A2 {</td><td> SRD5A2 ;</td><td> SRD5A2___\</td><td> SRD5A2 i</td><td rowspan="2"> 15 \ SRD5A2 |</td><td rowspan="3"> I ZV5GH5 i 8 1 W®S0 j</td><td> SRD5A2</td><td> SRD5A2_____</td><td rowspan="3"> P0K4 î_______2 j SRD5A2_____</td><td rowspan="2"> [______________2 i5RD5A2</td><td> SRO5A2</td><td colspan="2"> £$[ SÎ £ 2 U U £1 g</td><td> I TGFB.ltl___j</td>

<td colspan="2"> ProbeWt 173</td><td> 89V</td><td colspan="2"> .............165 1.23</td><td> ........._ 63 i</td><td> j 62</td><td> 51 \</td><td rowspan="2"> PAK3 1 38 j</td><td> -K ___ a5 j</td><td> 27 |</td><td> ! i____________________________</td><td rowspan="2"> GSTMSP1_____4</td><td rowspan="2"> i GSTM4 | 3 ;</td><td></td><td colspan="2" rowspan="2"> LOC728846 1 CLIP3 1</td><td rowspan="2"> | EWHLIM1 ! 1</td>

<td> Coexpressed Gene ____</td><td> ACAC8____</td><td> NT5E I</td><td> Λ. ο</td><td> en Oi o: m 9</td><td> LRCH2 1</td><td> S O Sx</td><td> GSTM2 j</td><td> KCNAB1 1</td><td> HHIP i</td><td> ALDH1A2 i</td><td> PRDM5 !</td><td> I 8V98V</td><td> MAML2 !</td><td> SNAÎ2 !</td><td> i UST ;</td><td> UJ x S</td><td> i ACTCl ______</td><td> 1 TGFB3___</td><td> I ίΛ 13</td>

<td> | Stack! D</td><td></td><td></td><td></td><td></td><td> PM</td><td> «U</td><td></td><td> d</td><td> ......</td><td></td><td></td><td> rf</td><td></td><td></td><td> 7*4</td><td></td><td> w</td><td></td><td></td><td></td><td> r-4</td><td> H</td><td></td><td></td><td> : </td><td></td><td> ♦-4</td>

<td rowspan="2"> Coexpressed Seeding Gene ProbeWt Gene</td><td rowspan="2"> SLC35F1 [ 4j IGFl |</td><td rowspan="2"> C22orf25 1 ^\ IGFl j</td><td rowspan="2"> STK4 _________j 4 [iGFl__I</td><td rowspan="2"> E1FSA2 1 4 1 IGF! j</td><td rowspan="2"> SUPT7L 1 4 ί K5F1 |</td><td rowspan="2"> i 1391 j P [ W°0O</td><td rowspan="2"> H s &amp;Û m &lt;</td><td rowspan="2"> ClorflSl ! ____4j IGFl j</td><td rowspan="2"> RPL32P3 1_______4JJGF1</td><td rowspan="2"> SEC62 j________4 j IGFl J</td><td rowspan="2"> s &lt;r 5 m a</td><td rowspan="2"> FU39639 ] 4 \ IGFl \</td><td rowspan="2"> ZNF543 | 4 j IGFl ____j</td><td> [ 1391 1 t?</td><td> 4 j IGFl j</td><td rowspan="2"> WDRS5 ! 4 j IGFl j</td><td> _______ 4 | IGFl</td><td> 4 1 IGFl</td><td> Ή 2 «t</td><td> 2</td><td> H U. 2 «î</td><td> ri 2</td><td> 1 4 1 IGFl</td><td> a! O M·</td><td> i 4 | IGFl.</td><td> i 4 i IGFl</td><td> i 4 | IGFl.</td>

<td> FRRS1 1</td><td> TATDN3______</td><td> j KÎAA1737</td><td> δ kU ao 0 a. &lt;</td><td> 1 RNF7 1</td><td> I SIKE1 |</td><td> | HSP90B3P______1</td><td> 1 GNS _:|</td><td> fN O» X Q ^4 o</td><td> © z N</td><td> ] TMEM127</td><td> ALDH1S1 1</td><td> ffl a. CÛ o. T</td>

<td> ·*...... 'η StacMD j</td><td> OJ</td><td> 04</td><td> Oj</td><td> 04</td><td></td><td> i</td><td> oi</td><td> 04</td><td> 04</td><td> Ol</td><td> OI</td><td> rs</td><td> : Oi</td><td> n</td><td> 04</td><td> N</td><td rowspan="2"> Γ1 ί GPM6B 993 Cl ί 2</td><td> Oi</td><td> Ol</td><td> Ol</td><td> Ol</td><td> «N</td><td> 04</td><td> 04</td><td> : 04</td><td> Ol</td><td> Ot</td>

<td> i j Coexpressed j 1 Seeding i StacklD Gene \ ProbeWt Gene</td><td> i 1 ί SPON1 I 2278 1 C7j</td><td> 1 491 cm \ smtu j t i</td><td> !-------------------------------------------------------------------!-----------------------------------------------------------! ! 1 CHRÜL1 ί 1936 Cl</td><td> il MEF2C i 1980 C7</td><td> ί 1 EFEMP1 ; 1939 | c7</td><td> 1 1 JAZF1 ί 1748 f Cl</td><td> i 1 DNAJBd i 1636 Cl j</td><td> i 1 ARHGEF6 i 1594 ί Cl |</td><td> £3 ί £051 } VAViVi j ï 1</td><td> Γΐ i 100552799 l 1470 i C7</td><td> !--------------------------------------------------------------------------------⁵---------------------------i 1 1 PREX2 1.464 i Cl</td><td> | 1 i MANIAI \ 1433 î C7 !</td><td> δ «e *4 04 U» M i™™</td><td> 1. i CRIM1 1181 î C7</td><td> 1 \ A2M I 1168 î Cl 1</td><td> 1 ; DPVSL2 1029 | C7</td><td> a en Z ml a</td><td> i 1 51.33 | 942 C7 1</td><td> Ο 1 688 i 080099 T i ________________i-------------L-------------------------------i</td><td> ί 1 ! 1MO3 î 852 C7</td><td> î 1 SEC23A î 765 Cl i</td><td> î 1 MOXOÎ ; 708 I C7</td><td> i 1 SPOCK3 i 622 | Cl</td><td> i 1 HEGl i 608 I C7 j</td><td> ί 1 Î.UM i 589 I C7 i</td><td> [ 1 C7orf58__566 ί C7___</td>

CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-304 / GHÏ-0S2PCT

<td> π $ s « 5» u</td><td> TGFBlil__ί</td><td> TGFB1I1 I ............</td><td> TGFB1I1 \</td><td> i W£H91</td><td> TGFBlil !</td><td> ri 03 £</td><td> ......| Su S «&gt; Ue g</td><td> TGFBlil \</td><td> rt 03 U. a r“</td><td> S U. o h*</td><td> TGFBlil_____j</td><td> TGFBlil_____</td><td> | TGFBlil</td><td> rl| H | îû M</td><td> ί TGFBlil_____j</td><td> ï TGFBlil _____j</td><td> ri rî CO $5 r-</td><td> TGFBlil i</td><td> 1 TGFBlil_____[</td><td> I TGFBlil i</td><td> TGF81I1 j</td><td> TGF B1H</td><td> ΰΤίΰίλΠ</td><td> TGFBlil___!</td><td> U19391 î</td><td> j TGFBlil_____</td><td> I 1118191 !</td>

<td> Coexpressed ; | Gene____j ProbeWt i</td><td> CLIPS______________Ϊ__________1 j</td><td> ri D cc Σ</td><td> Γ | £93W</td><td> MRÇ2________I L i</td><td> LCAT I 1 j</td><td> ï 1 E93FM</td><td> st earn</td><td> 1 TGFBlil____i 15</td><td> ASB2 .1 11</td><td> CUP3_______ï____11</td><td> JTGA7_______________j____10 J</td><td> hpH2__________j...........10</td><td> ί RUSC2__________j 10 </td><td> HRNBP3 8</td><td> UMS2 ï 8</td><td> ί CSPG4 ...............£__Ί_</td><td> ί NLGN3 | 5</td><td> m en i Q «</td><td> j NH5L2___________3.</td><td> i SVOE1 ί 2</td><td> ] RASL12 1 2</td><td> cm] mU «j uni © &lt;n U S|</td><td> i G N AZ_______1.</td><td> T i SEW3W1 ί</td><td> i LCAT i 1</td><td> § « 00 cj r* o</td><td> j SLC24A3______£ ___1_</td>

<td> StackID</td><td></td><td> cM</td><td> PI</td><td> M</td><td> M</td><td> Cô</td><td> S'</td><td> «4</td><td> et</td><td> : s</td><td> S</td><td> Mf;</td><td> «2</td><td> «i</td><td> «ï</td><td></td><td> «t</td><td> «t</td><td> s-</td><td> ef</td><td> «r</td><td> ΐΓ</td><td></td><td></td><td> S'</td><td> s</td><td> «</td>

<td> Seeding Gene_____</td><td> IGFl 1</td><td> §</td><td> ri U. Φ</td><td> IG Fl________</td><td> rf ©</td><td> IGFl</td><td> IGFl 1</td><td> IGF!_____</td><td> IGFl_____</td><td> IGFl j</td><td> JGF1</td><td> S</td><td> | IGF1</td><td> 1 IGFl i</td><td> i «91 j</td><td> ί IGFl</td><td> ! »GF1 J</td><td> IGF!</td><td> £ 2</td><td> 0</td><td> l’gfi_______________</td><td> IGFl__</td><td> 1 IGFl</td><td> £ g</td><td> j IGFl</td><td> ! 1GF1</td><td> F IGFl .....</td>

<td> ProbeWt Î</td><td></td><td> s</td><td> «t</td><td> «r</td><td> S'</td><td> «T</td><td> S</td><td> S'</td><td></td><td> «t</td><td> s·</td><td> •tf</td><td> «</td><td> S</td><td> •st</td><td> S-</td><td> S</td><td> S·</td><td> ’t</td><td> S'</td><td> s-</td><td> -t</td><td> -t</td><td></td><td> •r</td><td></td><td> S</td>

<td> Coexpressed Gene</td><td> APOL6]</td><td> MAU.____ 1</td><td> ΐ ο ri Q</td><td> LOC729199 !</td><td> ri -J Cm tt</td><td> PEL.il</td><td> ASB6 ______î</td><td> « ? Q PI V</td><td> CM eu CL h» v&gt; CL</td><td> &lt; D a U</td><td> RAB22A ____i</td><td> L0C643770 i</td><td> LOC1OO129SO2 !</td><td> ZCCHC4</td><td> i PNMA2</td><td> PIGW</td><td> I SLC25A32 §</td><td> § d</td><td> m un 3 S</td><td> ! SS18</td><td> CECR1</td><td> !.............................. j ZNF490</td><td> I PDE12</td><td> 9IP00T0 j</td><td> A ΰ</td><td> RRN3P1</td><td> un CM Ch CM s rM Q 5</td>

<td> StackID</td><td> PI</td><td></td><td> CM</td><td> n</td><td> i ft</td><td> PI</td><td> CM</td><td> CM</td><td> CM</td><td> ft</td><td> ! Al</td><td> CM</td><td> PI</td><td> CM</td><td> CM</td><td> CM</td><td> PI</td><td> CM</td><td> Al</td><td> CM</td><td> rl</td><td> PI</td><td> Pi</td><td> PI</td><td> PI</td><td> PJ</td><td> CM</td>

<td> Seeding Ï Gene I</td><td> U</td><td> C7 1</td><td> 2</td><td> U</td><td> 1 ^a</td><td> 23</td><td> C7</td><td> U</td><td> ï ^zo</td><td> b</td><td> C7 I</td><td> i ......&amp;</td><td> b</td><td> b</td><td> 1 ^a</td><td> b</td><td> î ù</td><td> C7</td><td> b</td><td> 1 C7</td><td> ! $</td><td> C7</td><td> S3G |</td><td> S3 Q</td><td> 115 Q</td><td> ί DES</td><td> î DES</td>

<td> 4-4 3 « â 2 &amp;</td><td> mw σ» en ιΛ</td><td> 524 1</td><td> CM «</td><td> 417 I</td><td> _</td><td> 322</td><td colspan="2"> FF **1! 301 \</td><td> r..... «M «h PI</td><td> N PI :</td><td> 1 SW</td><td> tA s</td><td> --- 169 i</td><td> 166</td><td> ζττ</td><td> ; Oïï</td><td> O O i</td><td> 56 ;</td><td> PJ «4</td><td> 12!</td><td> : «e</td><td> rt</td><td></td><td> r*</td><td></td><td> r&lt;</td><td> ri</td>

<td> TS » V) U) £ X «</td><td> en Ui cm δ o u</td><td> &gt; a. V</td><td> CPA3 1</td><td> ΓΜ P □ un</td><td> L 1</td><td> j U; i x</td><td> ------1 PLXDC2 1</td><td> ZdV3</td><td> s &amp; w-</td><td> ECM2 ΐ</td><td> 1 cvsaas i----</td><td> MBNtï</td><td> LAMA2 î</td><td> IL6ST 1</td><td> POON</td><td> ATRNL1</td><td> I r· • u 18</td><td> ί Π91</td><td> (Λ</td><td> i--------------------------------------------------------------------------------------------------1 OLFML1 1</td><td> r· tt a Ul z</td><td> ! IGFBP5</td><td> ί SORBS 1</td><td> U——.............. — ! CACNA1C</td><td> DES</td><td> SH 111</td><td> ANXA6_____</td>

<td> Q 3E u a V</td><td> j rt</td><td> ♦*</td><td> Γ</td><td></td><td> • r«</td><td> Ê ***</td><td></td><td> ri</td><td> ri</td><td></td><td> rl</td><td> ei</td><td> i i r</td><td colspan="2"> ! : { ri ! r</td><td> : î : cm</td><td> ri</td><td> ri</td><td></td><td> en</td><td> i</td><td> ri</td><td></td><td> r-¹</td><td> CM</td><td> î d</td><td> L</td>

CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-304 / GHI-052PCT

<td colspan="2" rowspan="2"> £ Ό «</td><td rowspan="3"> S LL</td><td rowspan="3"> TS CS LL</td><td rowspan="3"> tgfbiîi i</td><td rowspan="3"> È I VÎ g</td><td rowspan="3"> TGFBIII</td><td rowspan="3"> rl ÎÛ Wr P P</td><td rowspan="3"> œ Ur g</td><td rowspan="3"> TGFBlil_____</td><td rowspan="3"> TGFBIII_____</td><td colspan="2" rowspan="3"> nraJDl j miHai</td><td rowspan="3"> H £Û q</td><td rowspan="3"> TGFBIII j</td><td rowspan="3"> I TGFBIII....... |</td><td rowspan="3"> U. g</td><td rowspan="3"> ri U. S</td><td rowspan="3"> j TGFB1I1 1</td><td rowspan="3"> i wsii&amp;EI</td><td rowspan="3"> i madai</td><td rowspan="3"> j TGF81I1_____ί</td><td rowspan="3"> &lt;*i j Ή &lt;Û $</td><td rowspan="3"> j TGF Bill_______ί</td><td rowspan="3"> TGFBlil_______|</td><td colspan="2"></td><td rowspan="3"> : CO IL* g</td><td rowspan="3"> .TGFBlil_____|</td>

<td rowspan="2"> CQ g</td><td rowspan="2"> s g</td>

<td> 01</td><td> «3</td>

<td></td><td> 1</td><td> 381</td><td> 362</td><td> 321</td><td> Wï</td><td> 306</td><td> d σι</td><td> 287 j</td><td> 1 S/.Z</td><td> 253 !</td><td> 222. !</td><td> d</td><td> ΐ VIZ</td><td> 206 J</td><td> 184</td><td> (A S</td><td> 3 «M</td><td> 163</td><td> 7sï'</td><td> d&gt; 2</td><td> en</td><td> 127</td><td> M· d r»</td><td> ÎZT</td><td> τζτ</td><td> d;</td><td> 111</td><td> 108</td>

<td></td><td> Æî pî</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> α.</td><td></td><td></td><td></td><td> mxv.</td><td></td><td></td><td></td><td></td><td> .......</td><td></td><td> ......</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> .......</td><td></td>

<td> $ ίΛ</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> !</td><td></td><td></td><td></td><td></td><td> 1</td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> ii h» &amp; g U</td><td> 1 Gene</td><td> | MRGPRF</td><td> 1 g</td><td> j AOC3</td><td> ! APCYS</td><td> d x Z</td><td> m &lt; «y d y v6</td><td> 2 S</td><td> i FLNC</td><td> ! TGFBIII</td><td> ITGA7</td><td> IA D</td><td> FLNA k&gt; . — —</td><td> EFEMP2</td><td> z 1</td><td> i RASL12</td><td> j GAS6</td><td> s z &amp;</td><td> z S Λ</td><td> 3 X CL o</td><td> St o u</td><td> ΙΛ « &lt; Z CS</td><td> [ COL6A2</td><td> I TPM2</td><td> [ WF PCI</td><td> ♦* &lt;A Z 1*</td><td> j DKK3</td><td> HSPB8</td>

<td></td><td> Û S w</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> 43 CA</td><td> Ut</td><td> *A</td><td> 1A</td><td> lA</td><td> &lt;A</td><td> iA</td><td> IA</td><td> IA</td><td> *A</td><td> IA</td><td> IA</td><td> iA</td><td> in</td><td> 1Λ</td><td> IA</td><td> m</td><td> m</td><td> m</td><td> IA</td><td> ut</td><td> ut</td><td> in</td><td> LA</td><td> «A</td><td> LA</td><td> &lt;n</td><td> in</td>

<td> ng ]</td><td></td><td></td><td></td><td></td><td></td><td></td><td> “A</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> 1 &amp; 4Λ</td><td> Gene</td><td> IG Fl</td><td> §</td><td> IGFl</td><td> ri g</td><td> IGFl</td><td> IGF!</td><td> IGFl</td><td> IGFl</td><td> 0</td><td> IGFl</td><td> 0</td><td> S</td><td> w u. g</td><td> S? S</td><td> IGFl</td><td> 0</td><td> IGFl</td><td> IGFl</td><td> IGFl</td><td> v»i</td><td> 0</td><td> IGFl</td><td> ilGFl</td><td> flGFl</td><td> L»</td><td> ri U. 2</td><td> ε</td>

<td colspan="2"></td><td></td><td></td><td> U·».·</td><td> &gt;**·*«*</td><td> —</td><td></td><td></td><td> nnr</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> 3</td><td> «r</td><td> KT</td><td> Xt</td><td> «J</td><td> ’«r</td><td> VT</td><td> xr</td><td> Xf</td><td> xt</td><td> sf·</td><td> •it</td><td> xf</td><td> ·*</td><td> «r</td><td> V</td><td> St</td><td> «r</td><td> V</td><td> «t</td><td> «S</td><td> •«r</td><td> ««r</td><td> «e</td><td> M-</td><td></td><td> M·</td><td> Xf</td>

<td></td><td> p</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> &amp;</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td rowspan="2"> [ MOAP1 i</td><td></td><td></td><td></td>

<td> Coexpressed |</td><td> Gene</td><td> o 2 xr w v&gt;</td><td> LU Σ &lt;</td><td> APOLO1 j</td><td> ARSB</td><td> ! VSCdNZ L......i.______~~</td><td> SLC30A6</td><td> ; METTL7A i</td><td> PARD6B j</td><td> STOM</td><td> rvordÂO</td><td> N</td><td> i ATP1S4</td><td> SCD5</td><td> CEP170L</td><td> [ NU DTI9</td><td> CQ S z X &gt;*·</td><td> | APPL1</td><td> i OS&amp;PL2</td><td> d i &gt;</td><td> d U. Z</td><td> [ZNF772</td><td> [ LOC646973____</td><td> [ LOC10012.8096</td><td> î HIGD1A</td><td> j DISC2</td><td> CYCS_________</td>

<td colspan="2" rowspan="2"> Q 3 S w</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> :</td><td></td>

<td> d</td><td> N</td><td> Ci</td><td> d</td><td> d</td><td> d</td><td> d</td><td> d</td><td> d</td><td> d</td><td> d</td><td> et</td><td> d</td><td></td><td> d</td><td> d</td><td> d</td><td></td><td> d</td><td> d</td><td> d</td><td> N</td><td> N</td><td> d</td><td> N</td><td> d</td><td> d</td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> :</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> r~ 1</td><td></td><td></td><td> :</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> w c 1 Λ</td><td> Gene</td><td> □ES</td><td> □ES</td><td> DES</td><td> DES</td><td> sao</td><td> DES</td><td> DES</td><td> SBO</td><td> LÔ LU O</td><td> DES</td><td> tZ LU o</td><td> DES</td><td> DES</td><td> L</td><td> DES</td><td> DES</td><td> DES</td><td> DES</td><td> □ES</td><td> DES</td><td>_: DES</td><td> DES</td><td> DES</td><td> DES</td><td> O</td><td> DES</td><td> S3G</td>

<td></td><td></td><td> Mem </td><td> mm</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> *******</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> 1 JO ο</td><td> mH</td><td> «-»</td><td></td><td></td><td> : r!</td><td> 0-4</td><td> V-!</td><td> 72309</td><td> 72305</td><td> σι 4j» O</td><td> ifc 00 en w</td><td> 68389</td><td> 6772S</td><td> 67225</td><td> «3 LC LO</td><td> 1 LA 10</td><td> 9*4 ch d IA «</td><td> 65217</td><td> 65097</td><td> X d s</td><td> 64293</td><td> m XT so</td><td> m &lt;A en en sc</td><td> 61499</td><td> 60803</td><td> 59947</td><td> Q S s</td>

<td></td><td> £</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> •</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td colspan="2"> Coexpressed Gene ;</td><td> ATP1A2</td><td> m X E</td><td> O</td><td> AMXAG 1</td><td> TIAMJ.</td><td> DES</td><td> CES1</td><td> TAGLN [</td><td> : &lt; : Z «ni U.</td><td> TNS1</td><td> CNN1</td><td> ACTA2</td><td> CHRDL1</td><td> ; DPVS13 ]</td><td> _</td><td> «U</td><td> CCNO2 1</td><td> i Î.V8DIS !</td><td> MEIS1 i</td><td> ΓαΤΡ2Β4 1</td><td> DDR2</td><td> Q O s</td><td> i SORBS 1</td><td> I KCNMB1</td><td> ! PGR</td><td> i R8PMS</td><td> ί Ft.NC</td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> !</td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> ώ</td><td></td><td></td><td> *</td><td></td><td></td><td> t</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> 1</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> X U (9</td><td></td><td></td><td></td><td> l</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> !</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> &amp;</td><td> s d</td><td> ! M</td><td> Μ</td><td> | «</td><td> «e</td><td> i *</td><td> «r</td><td> in</td><td> IA</td><td> lA</td><td> IA</td><td> ;</td><td> LT</td><td> Λ</td><td> iA</td><td> tn</td><td> : LA</td><td> m</td><td> LA</td><td> m</td><td> iA</td><td> LA</td><td> IA</td><td> VI</td><td> IA</td><td> m</td><td> IA</td>

CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-301 ! GH1-O52PCT

<td rowspan="7"> Ceexpressed Seeding ; StackID Gene___ ProbeWt Gene &gt;</td><td rowspan="6"> 5 ί TSPAN18 j 103 j TGFBlil_____j</td><td colspan="2"></td><td colspan="3"> t I</td><td rowspan="7"> 1 5 1 MRVI1 1 75 | TGFBlil |</td><td rowspan="7"> [ 5_____ j MYLK_________L ⁶⁸ i TGFBlil ί</td><td rowspan="7"> j 5 1 CNN1_____ I 63 I TGFBlil ___J</td><td colspan="3" rowspan="2"> H: w| ri ud I Mdf mi</td><td rowspan="7"> 1 5 { ÎM0D1 j 56 1 TGFBlil____1</td><td rowspan="3"> w ri £û g §</td><td rowspan="3"> 43 1 TGFBlil_____1</td><td rowspan="5"> s u. g 5</td><td colspan="2"> .....&gt;»»»»»»</td><td rowspan="7"> 1 5 1 AS82 ________1 36 I TGFBlil J</td><td colspan="2"></td><td rowspan="7"> 1 5 | DBNDO2 i 20 j TGFBlil I</td><td rowspan="7"> [ 5_____ ÎRUSC2 ______ i 19 I TGFBlil 1</td><td colspan="2"></td><td colspan="2"></td>

<td rowspan="5"> 5 1 MYH11 ______ | 102 j TGFBlil</td><td rowspan="6"> | 5 j SEPT ________[ 90 j TGFBlil</td><td rowspan="6"> \ 5___ j fTIHS _____ 1 81 | TGFBlil</td><td rowspan="6"> 1 5 ! PYGM_________1 81 ί TGFBlil</td><td rowspan="6"> L· | MCAM j______78 1 TGFBlil</td><td rowspan="4"> 1 39 1 TGFBlil</td><td rowspan="6"> [5 j HRNBP3 j 38 | TGFBlil</td><td rowspan="6"> [ 5 1 CLIP3 I 25 j TGFBlil</td><td rowspan="6"> ί 5 j C16orf45 j 22 | TGFBlil</td><td rowspan="2"> ë LU £ œ rS</td><td rowspan="2"> __18 I TGFBlil</td><td rowspan="6"> [5 j TINAGL1_______I_______17 j TGFBl.il</td><td rowspan="6"> j 5_________________i_______1? TGFBlil</td>

<td rowspan="5"> \ 5 I R8PMS2 1 63 \ TGFB</td><td colspan="2" rowspan="3"> I 58 ί TGFB: j 58 j TGFB:</td>

<td colspan="2"></td><td colspan="2"></td>

<td rowspan="3"> 1 5 1 GNAO1 j</td><td rowspan="3"> 1 ⁵ 1 16ALS1 j</td><td rowspan="3"> \ 5 ] RARRES2__1</td><td rowspan="3"> Is IADRA1A_______j</td>

<td rowspan="2"> I 5 [ ATP1A2</td><td rowspan="2"> 15 1 UMS2 ____</td><td colspan="2" rowspan="2"> 5 I DAAM2________ 5_____j MRC2_______</td>

<td colspan="2"></td>

<td> I Seeding ! Gene</td><td> 1 IGF1 1</td><td> ri u. g</td><td> IGF1 I</td><td> IGF1 |</td><td> IGF1</td><td> ί IGF! ________</td><td> IGF!__i</td><td> IGF1</td><td> IGF1</td><td> 2</td><td> 1GF1 |</td><td> ; «91</td><td> IGÎ1 ____J</td><td> [ «91</td><td> ri Ur g</td><td> I6F1 I</td><td> I W9t</td><td> : IGF1 _______1</td><td> 2</td><td> IGF1 1</td><td> IGF1</td><td> iGFl Î</td><td> I «91 :</td><td> ri 2</td><td> IGF1 |</td><td> IGF1 _____ 1</td><td> [____»^M</td>

<td> 4&lt;» 3 I g &amp;</td><td> xr</td><td> &lt;7</td><td> xr</td><td> xt</td><td> xf</td><td> &lt;7</td><td> «7</td><td> kt</td><td> «t</td><td> KT</td><td> χτ</td><td></td><td> Kt</td><td> ·*</td><td> «3*</td><td> «T</td><td></td><td> XT</td><td></td><td> Xt</td><td> «t</td><td> tf</td><td> O’</td><td> &lt;»</td><td> «r</td><td></td><td> «Γ</td>

<td> Coexpressed | StacicID Gene _________</td><td> m g u</td><td> [2 Τΐθ«46127 J</td><td> tn Ή oi QC &lt;N</td><td> |2 î 10000130357</td><td> [ ÏS3A ί ______Z j</td><td> 1 2 I MTFMT i</td><td> EOSOfT Zj</td><td> j 2__L^rHOF 1</td><td> K? A g</td><td> [ 2 I LOC729142 ]</td><td> [2 j GMG4 |</td><td> [2 1 H6PD j</td><td> [ 2 [ FBXW2 ]</td><td> j SIMON J Z j</td><td> © in Oi Q &lt;N</td><td> ί ΖΠ39ΝΥ I Z j</td><td> 1 2 I SGTB j</td><td> [2 1 MAPK1IP1L 1</td><td> z δ in N PM</td><td> 2 1FXC1 i</td><td> \ 2______InQOI· J</td><td> &lt; tt CÛ O Σ</td><td> 1 2 [ ANAPC16 1</td><td> m Φ X o M2 &lt;N</td><td> | 2 I TBCCO1 ]</td><td> 1 2 i DLEU2</td><td> f 2 1 CAROS i</td>

<td> Seeding j Gene i</td><td> 1 DES________J</td><td> | DES J</td><td> I_______________</td><td> Loes______________|</td><td> ΐ ⁵³⁰ Ϊ</td><td> 1 DES ί</td><td> ΐ OES 1</td><td> i OES________________I</td><td> 1 des j</td><td> 1 DES ______I</td><td> &lt;a Ui O</td><td> LA 0</td><td> [des___________1</td><td> 1 DES i</td><td> ί DES j</td><td> DES________1</td><td> ; DES j</td><td> L.......</td><td> 1 S3O</td><td> ! DES _________1</td><td> | DES ]</td><td> IA LU ^Q</td><td> Ides 1</td><td> L__^S30l</td><td> [ S3G i</td><td> DES 1</td><td> 1 DES J</td>

<td> ProbeWt</td><td> 00 uh</td><td> [ 58303 1</td><td> 56889 ]</td><td> [ 0Z99S</td><td> 3 m IC m</td><td> 54990</td><td> ___54713</td><td> 53979</td><td> 53386</td><td> 00 N m m</td><td> 52082 :</td><td> 1 51S56 j</td><td> s « in</td><td> Uh 5 O if</td><td> © PM cn</td><td> i 5</td><td> j 06191?</td><td> 44926 ;</td><td> O CM 3</td><td> VZ9EV</td><td> 43602</td><td> 42715</td><td> 42364</td><td> 41435 j</td><td> p9PZ£</td><td> j 008SE</td><td> 33287</td>

<td> Coexpressed Gene !</td><td> Imylk</td><td> j FHL1 |</td><td> a</td><td> Î EDNRA___ !</td><td> i DKK3 j</td><td> IS 0</td><td> LpSM5_________□</td><td> j LOC729468 J</td><td> s z lA</td><td> ί PGM5P2 i</td><td> 1 SPARCL1 :</td><td> I ACTG2 _____</td><td> I TRPC4</td><td> ! CAV1 I</td><td> —1 &lt; Z 0</td><td> 1 TIMP3 J</td><td> ί ABCC9 1</td><td> i MRVI1 j</td><td> ÏN13VJ</td><td> Q</td><td> TdNld83S ]</td><td> JAZF1</td><td> | KANK2______ i</td><td> I SOdSH j</td><td> 3 &gt; S</td><td> ! PRNP |</td><td> 1 TSPAM18 I</td>

<td> I StacicID</td><td> in</td><td></td><td> tn</td><td> 1 5</td><td></td><td> tn</td><td> in</td><td></td><td></td><td> in</td><td> m</td><td> in</td><td> tn</td><td> m</td><td> in</td><td></td><td></td><td> Uh</td><td> tn</td><td> m</td><td> in</td><td></td><td></td><td></td><td> m</td><td></td><td> 22</td>

CA 02863040 2014-07-20

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-304 / GHI-O52FCT

<td rowspan="4"> ί Coexpressed i \ Seeding StackID ! Gene 1 ProbeWt i Gene________j</td><td rowspan="3"> TMEM3S ! 34 ! TGFBlll ί</td><td rowspan="2"> 12 i TGF81I1 =</td><td rowspan="2"> 12 î TGFBlll__j</td><td rowspan="2"> _____11 TGFBlll J</td><td rowspan="2"> Γ CltSdOt CT</td><td rowspan="2"> 11 TGFBlll \</td><td rowspan="2"> 10 TGFBlll i</td><td rowspan="2"> ! 1118391 8</td><td rowspan="2"> 7 TGFBlll</td><td> TGFBlll</td><td> TGFBlll__________J</td><td rowspan="2"> S TGFBlll_____</td><td rowspan="2"> 4 j TGFBlll |</td><td rowspan="2"> __4 i TGFBlll j</td><td rowspan="2"> 3 I TGFBlll 1</td><td> -TGFBlll_____l</td><td> ri CD U. £</td><td rowspan="3"> 1 SMOC1 î 2 j TGFBlll ;</td><td rowspan="3"> Alt so U* il N ?</td><td rowspan="3"> MiCALLl ........ 1__1 TGFBlil........\</td><td rowspan="3"> j LCAT_________ I 1 TGFBlll \</td><td rowspan="3"> \ iiiâdàÎ ï 1 9adSH 1</td><td rowspan="3"> i FIN A 1 33418 j TPM2</td><td rowspan="3"> TAGLN j 33391 TPM2</td><td> N 5 a</td><td> ί TPM2</td><td> ί TPM2______j</td>

<td> 1</td><td> to</td><td rowspan="2"> ί SYDE1_________ j ____2</td><td> Cî</td><td rowspan="2"> ίTM5132975</td><td> 1 32489 i</td><td> j 3176S</td>

<td> COPZ2 _____ i</td><td> LTBP4</td><td> SCARA3______!</td><td> 2 2</td><td> PCOHIO j</td><td> RAB34_____</td><td> roxFi_______j</td><td></td><td> ί KIRREL |</td><td> ! PACT!__________|</td><td> ta 2 z CM</td><td> Z I Ul</td><td> ί DCHS1 j</td><td> ! E1C43H3 ;</td><td> 1 PPP1R14A______</td><td> jCNN1________</td><td> S a: x U</td>

<td> in</td><td> tn</td><td> in</td><td> 1Λ·</td><td> m</td><td> UT</td><td> m</td><td> m</td><td> tn</td><td> tn</td><td> »n</td><td> m</td><td></td><td> 1Λ</td><td> ιΛ</td><td> tn</td><td> Λ</td><td> tn</td><td> iA</td><td> i tn</td><td> ΙΛ</td><td> m</td><td> i</td><td></td><td> Ή</td><td rowspan="4"> î [ U9I \ P j________ NXN j</td><td rowspan="3"> 1 4 i IGFl 1 1</td>

<td> Seeding * Gene i</td><td> | IGFl I</td><td> [ 1391 1</td><td> 0</td><td> ik: a</td><td> IGFl________1</td><td> ί IGFl_____1</td><td> a</td><td> j cjsf j</td><td> IGFl_______</td><td> s</td><td rowspan="2"> ί ί V ί ........t____________1</td><td rowspan="2"> ! 4 ] IG Fl j</td><td rowspan="2"> 4 | IG Fl i</td><td rowspan="2"> [ 4 | IGF1__</td><td rowspan="2"> 4 I IGF1 ____ΐ</td><td rowspan="2"> _____ 4 | IGF1</td><td rowspan="2"> ui a MJ</td><td rowspan="2"> 1______ 4 i IGFl________j</td><td rowspan="2"> ί 4 I IGFl</td><td rowspan="2"> 0 SJ</td><td rowspan="2"> ί 4 1 IGFl</td><td rowspan="2"> j 4 j IGFl</td><td rowspan="2"> !4 1IGFl ________</td><td> 1 IGFl__________</td><td> C39I l</td>

<td> ProbeWt</td><td> sr</td><td> e</td><td> e</td><td> «</td><td> 4'</td><td> «t</td><td></td><td></td><td> «î</td><td> CT</td><td> •sf</td><td rowspan="2"> 1 CCDC122 i __4</td>

<td rowspan="2"> i Coexpressed StackID ’ Gene</td><td rowspan="2"> rn s Λ O s u 2 rs</td><td rowspan="2"> 1 ζιζίοετοοιοοΊ i z</td><td> 2 u</td><td> ZBTB3______ I</td><td> ZNF445 J</td><td> CASP8 1</td><td> FN ta &lt;</td><td> m</td><td> SC5D1.</td><td> KILLIN I</td><td> MTX3__j</td><td> IP z U</td><td> GM2A ]</td><td> I.OC401588</td><td> C8orf79</td><td> KIAA0754</td><td> I SMUl________</td><td> Ï IAdSl i</td><td> SPRED1</td><td> ί L0C100128997</td><td> Ζ596ΖΖ90Ί j</td><td> 1 TRAPPC.2</td><td> 1 KCTD10</td><td> en s. m 0</td><td> ......¹................... E8Z3NZ</td>

<td> ΓΝ</td><td> cm</td><td> CM</td><td> CM</td><td colspan="2"> rii CM</td><td> CM</td><td> CM</td><td> CS</td><td> CM</td><td> CM</td><td rowspan="2"> _______Z | S3G 1 ZZESZ ________TMIND</td><td rowspan="2"> FERMT2 25146 1 DES i 2 J</td><td> CM</td><td></td><td> &lt;N</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> PM</td><td> CM</td><td> «N</td>

<td rowspan="2"> .....— ......................................y—a......'·.............. j Coexpressed | | Seeding StackID ί Gene ί ProbeWt Gene</td><td> FRMD6 1 32935 \ DES I</td><td> CSRPl j 32471 \ DES</td><td> V) U4 P rn » AT 04 PC T &amp; r</td><td> NEXN 29867 DES</td><td rowspan="2"> i S PRICK1E2 29746 I DES 1</td><td rowspan="2"> 1 S PPAP2B \ 28983 I DES</td><td rowspan="2"> ! S MYH11 ί 28923 1 DES</td><td rowspan="2"> i S PDGFC Î 287321 DES 1</td><td> TPMl I 27766 = DES</td><td> SVIl 1 27S21 | DES Ί</td><td rowspan="2"> 5 ί LOC732446 27335 ί DES</td><td> î--------1--- MEIS2 25944 | DES</td><td> ...----_------M------1........... 9 CALDl 25386 1 DES</td><td> Cl.U 24888 1 DES |</td><td> SPON1 23171 1 DES</td><td> TGFBR3 23018 ! DES Ί</td><td> ίΰ O U5 S PM CM «H n X ω &lt; V</td><td> ί TPM2 ί 22108 î DES</td><td> GSN ! 22102 ! DES</td><td> ! NID2 21240 DES 1</td><td> MYOCD 21178 DES i</td><td> MKX 20028 DES</td><td> EYA4 19967 DES</td><td> I LOC100127983 18208 DES</td><td> ANXA6___L_____16600 l DES</td>

<td> «</td><td></td><td colspan="2"> ιΛ ; ιΛ</td><td> ΐ 1Λ</td><td> *Λ</td><td> &lt;n</td><td> i i m</td><td> î 1 ^w</td><td> w*</td><td colspan="2"> Γ5___ j i S</td><td> m</td><td> « tn</td><td> 01</td><td> 1Λ</td><td> î ^1/5</td><td> 1</td><td> tn</td><td> Λ</td><td> 1 tn .i.....</td><td> Ul</td>

CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-304 / Gœ-OSZÎ’CT

<td colspan="2"> I Seeding I Gene _____</td><td> n Ê</td><td> I TPM2_______j</td><td> ί TPM2 i</td><td> CN</td><td> CN s fc</td><td> i TPM2 _____</td><td> CN s &amp;</td><td> CM 5 £</td><td> 1 TPM2_______</td><td> ί rpM2 i</td><td> | TPM2</td><td> ZiAdlJ</td><td> ΤΡΜ2 [</td><td> CN 5 &amp;</td><td> TPM2 __J</td><td> CN Σ û_ μ-</td><td> TPM2 |</td><td> - CM S £</td><td> TPM2 j</td><td> i mai</td><td> Γ &lt;N J·*·</td><td> i mai |</td><td> ne s &amp;</td><td> [ TPM2 1</td><td> «N 2</td><td> TPM2 j</td><td> j m&lt;.u</td>

<td></td><td> 4* δ λ ο</td><td> CO IC tA CQ</td><td> 31444</td><td> ί οτετε</td><td> 30665</td><td> 30331 ί</td><td> N 8 Q m</td><td> 29926</td><td> 29802</td><td> 29158 ;</td><td> 29088 j</td><td> 29075 1</td><td> 28780 |</td><td> 28764 1</td><td> 28584 j</td><td> 28495 j</td><td> pozsz</td><td> 28101 !</td><td> 27926 I</td><td> 27789</td><td> 27438 ί</td><td> 26679J</td><td> 26409 j</td><td> 25979J</td><td> 25603 |</td><td> 24576J</td><td> 24353]</td><td> 24298 j</td>

<td></td><td> £</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> Φ s 2 a X Φ 9 W</td><td> 1 Gene________</td><td> r&lt; a o S</td><td> ΧΙΛΙΑ j</td><td> LACTA2</td><td> j ACTG2</td><td> \ KCNMB3 i</td><td> ί MSR83 j</td><td> \ S0R6S1 J</td><td> | DPYSL3 I</td><td> in UJ a</td><td> &gt;</td><td> [SLCSAl j</td><td> [ zaiwj</td><td> MHS1 1</td><td> 1 PG MS________ !</td><td> ί ATP2B4 |</td><td> 1OC729468 '</td><td> fl X Mr μ...</td><td> FLNC__]</td><td> ri a. m S o a</td><td> H5PB8___ j</td><td> (N cd û O</td><td> O£ g</td><td> ··&lt; g</td><td> \ EXW !</td><td> RBPMS ]</td><td> MYH11 i</td><td> : FZD7 !</td>

<td></td><td> StackJD</td><td> T-C</td><td> vi</td><td></td><td rowspan="2"></td><td rowspan="2"> «ΜΚΜΛ</td><td rowspan="2"> MW</td><td></td><td> w</td><td> c-f</td><td></td><td> w&lt;</td><td> Ç-J</td><td></td><td> »&lt;</td><td></td><td></td><td></td><td> 4*4</td><td> fl</td><td> rH</td><td> w</td><td> Ή</td><td></td><td> «M</td><td> ft</td><td> fl</td><td> ft 1</td>

<td></td><td></td><td></td><td></td><td></td><td> ......</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> M β</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> ό φ »</td><td> e φ Φ</td><td> n ». Si</td><td> ft We 2</td><td> rt Ue Q</td><td> U.</td><td> FlGFl</td><td> 2 52</td><td> 2 2</td><td> rS è</td><td> «91</td><td> u! g</td><td> 2</td><td> C39I</td><td> 2</td><td> | IGF!</td><td> 2 52</td><td> IGFl</td><td> ts</td><td> IGF1</td><td> ul 52</td><td> 2</td><td> IGF1</td><td> ; IGF!</td><td> IGF1</td><td> IGF1</td><td> IGF1</td><td> IdSH</td><td> IGF1</td>

<td></td><td> §</td><td> ’C?</td><td> «r</td><td></td><td> n</td><td></td><td></td><td> 'ey</td><td> tr</td><td> &lt;y</td><td> sr</td><td></td><td> Ν’</td><td> N·</td><td> N</td><td> e</td><td> -e</td><td> N</td><td> ef</td><td> «</td><td> t?</td><td> N·</td><td> &lt;?</td><td> «</td><td></td><td> m</td><td> m</td><td> en</td>

<td></td><td> φ 42 Ο</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> a?</td><td></td><td></td><td></td><td></td><td></td><td colspan="2"> ?</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td rowspan="2"> LRTOMT______i</td><td></td><td></td><td></td>

<td colspan="2"> Coexpressed Gene</td><td> SPAÎS2L Î</td><td> TRIMS_________1</td><td> HAUS3 ____]</td><td> UTPllt 1</td><td> o u tn</td><td> MBOAT1</td><td> Ζ3Η3ί-</td><td> VPS33A _J</td><td> SENP5 Π</td><td> V, §</td><td> NDUFC2 1</td><td> ZBTB8A ____ί</td><td> ST8SIA4 I</td><td> •e e t: o D</td><td> MEDIS =</td><td> MPV17L</td><td> E OTZPOID</td><td> LIM7C ]</td><td></td><td> COX18________1</td><td> PCBD2 1</td><td> SPAST___ 1</td><td> ί ZAI?d/O L------------------</td><td> fl Q &lt; a» 1</td><td> i δΖΝΧ8Π</td><td> n £2 b ΰ</td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> Q ?</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> «</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td> in</td><td> CN</td><td> CN</td><td> CN</td><td> (N</td><td> CN</td><td> &lt;N</td><td> CN</td><td> &lt;N</td><td> iN</td><td> (N</td><td> rs</td><td> CN</td><td> CN</td><td> CN</td><td> CN</td><td> CN</td><td> CN</td><td> CN</td><td> CN</td><td> CN</td><td> CN</td><td> CN</td><td> ΓΜ</td><td> CN</td><td> CN</td><td> CN</td><td> «N</td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> g ? 4» &amp;</td><td> ; Gene</td><td rowspan="2"> 16262 ί DES</td><td rowspan="2"> 16175 ] DES</td><td> Ώ a</td><td> &lt;a Ui a</td><td> CA s</td><td> tA UJ Q</td><td> cn UJ</td><td> ul a</td><td> tA UJ Q</td><td> lA s</td><td> ça O</td><td> «A UJ Q</td><td> en UJ a</td><td> &lt;Λ O</td><td> t/) UJ C</td><td> en UJ O</td><td> ΙΛ ui a</td><td> ΙΛ UJ Ω</td><td rowspan="2"> 7000 1 DES</td><td rowspan="2"> 6648 î DES</td><td rowspan="2"> 5948 î DES</td><td rowspan="2"> 5715 j DES</td><td> en LU O</td><td> UJ O</td><td> ΰ a</td><td> ÇA a</td><td> Ώ a</td>

<td></td><td> I o</td><td> ΙΛ 3</td><td> 15943 ί</td><td> 14001j</td><td> CO m rt</td><td> 13760 1</td><td> 13444 1</td><td> $»EEl</td><td> id id AJ m Ft</td><td> 12617</td><td> 12259</td><td> M CN FÎ</td><td> 11490</td><td> 10S95 j</td><td> S v*4 O</td><td> 86.71.</td><td> 8478 ]</td><td> !n φ m</td><td> 5611 ί</td><td> S55sJ</td><td> 4795J</td><td> 4611 1</td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> F”............................. i Coexpressed ;</td><td> ! Gene ]</td><td> u.</td><td> &lt; in 1</td><td> SRD5A2 J</td><td> 5 z v&gt;</td><td> no a. u; δ © u</td><td> ί AOC3 _______I</td><td> I TJMP2 i</td><td></td><td> ADCY5____</td><td> PARVA ____i</td><td> I INW</td><td> nin σι v) S ο 2</td><td> FAT4 ί</td><td> 5TIH5__1</td><td> 3 2 s</td><td> en N X</td><td> MCAM 1</td><td> eû i</td><td> T3Q3AA</td><td> PDE.5A_____ |</td><td> z</td><td> ) ZiAHOd</td><td> 5POCK3_______1</td><td> BOC 1</td><td> CBYAB J</td><td> ί PMP22 |</td><td> ί ADRA1A____ί</td>

<td colspan="2"> ώ</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> !</td><td> Λ V</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> ! ί ...</td><td> in</td><td> ΙΛ</td><td> tn</td><td> in</td><td> tn</td><td> m</td><td> IT.</td><td> l</td><td> in</td><td> m</td><td></td><td> tn</td><td> m</td><td> in</td><td> m</td><td> in</td><td> in</td><td> tn</td><td> in</td><td> m</td><td> &lt;n</td><td> in</td><td> m</td><td> tn</td><td> in</td><td> in</td><td> m</td><td> in</td>

CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-30-1 / GHI-O52PCT

<td colspan="14"> —---,1 ·***·*’ ΑΑΑΑΑΑ^Ααααααα AAAAAA* maa,ΜΜ,,Μ, W,,-.wa*v maaaa SSSSW .sksasa^askasv, : * : t ί :</td><td rowspan="5"> Γ 17793 i TPM2 |</td><td rowspan="5"> 17659 ’ 7PM2 |</td><td rowspan="5"> ------------------.------------------------; 17306 ί 7PM2 I</td><td colspan="2" rowspan="3"> t rsJ CN</td><td rowspan="5"> 15853 I TPM2</td><td rowspan="5"> 14646 ί 7PM2</td><td rowspan="5"> —........—----------j 13548 ί 7PM2 I</td><td rowspan="5"> Σ Ck r S m</td><td rowspan="5"> 13043 l ΪΡΜ2 I</td><td rowspan="5"> 12988 Î 7PM2</td><td rowspan="5"> 12.334 ί 7PM2 i</td><td colspan="2" rowspan="2"> ! I</td><td rowspan="5"> 11833 TPM2___________</td>

<td rowspan="4"> [ ; Seeding</td><td rowspan="4"> ! ProbeWt 1 Gene</td><td rowspan="4"> ί 23458 = TPM2</td><td rowspan="4"> i 23091 I TPM2</td><td rowspan="4"> \ 22987 ! 7PM2</td><td rowspan="4"> \ 21665 ί TPM2</td><td rowspan="4"> ί 21569 | TPM2</td><td rowspan="4"> 0i s H s t0 &lt;4 04</td><td rowspan="4"> ί 20876 ΐ 7PM2</td><td rowspan="4"> | 20468 ί 7PM2</td><td rowspan="4"> CM Σ 0» 09 O ιΰ es</td><td rowspan="4"> ZWdl j E9Z87 ’</td><td colspan="2" rowspan="3"> 284 Î 7PM2 017 7PM2</td>

<td rowspan="3"> 12112 i TPM2</td><td rowspan="3"> 01 2 &amp; 04 Ι Ή</td>

<td rowspan="2"> 16659 Î 1PM</td><td rowspan="2"> INdL j 0ZS91</td>

<td> 18</td><td> Γ 18</td>

<td> I Coexpressed</td><td> Gene</td><td> [ TPM2</td><td> I GNAL</td><td> ί MYL9</td><td></td><td> i CAV1</td><td> I KANK2</td><td> ΐ EDNRA</td><td> I SPARCL1</td><td> TRPC4 ί</td><td> oO z « Cu ί</td><td> *4 g &lt;</td><td> Γ0 a* s r*</td><td> § co «</td><td> j T3NAS i</td><td> u Z è LU 40</td><td> Q &lt; a.</td><td> 0J J u 2 &amp;</td><td> CSRP1</td><td> HEPH 1</td><td> NEXN 1</td><td> I MYOCD</td><td> 04 10 tu s</td><td> TPM1 1</td><td> z O a. &lt;Z!</td><td> EYA4 |</td><td> T</td><td> SYNM ]</td>

<td colspan="2"> Q</td><td> ΓΊ</td><td></td><td> Fl</td><td></td><td></td><td></td><td> yn</td><td> &lt;•4</td><td></td><td> fM</td><td> w</td><td></td><td></td><td></td><td> r*</td><td></td><td></td><td></td><td> **&lt;</td><td></td><td> ed</td><td></td><td> 7—1</td><td> ♦4</td><td></td><td> &lt;4</td><td> v4</td>

<td colspan="2"> ί Seeding I Gene :</td><td> ί IGFl</td><td> £ g</td><td> ί IGFl I</td><td> i IGFl :</td><td> j IGFl j</td><td> I IGFl ί</td><td> ! IGFl ί</td><td> 1391 |</td><td> [ 1GF1</td><td> 1 ITGA7 ί</td><td> 5 g</td><td> f ITGA7 ΐ</td><td> [ ITGA7 1</td><td> | ITGA7______]</td><td> 5 g</td><td> &lt; g</td><td> 1 ITGA7 \</td><td> ITGA7 I</td><td> ITGA7 1</td><td> ITGA7 |</td><td> I7GA7 |</td><td> ITGA7 1</td><td> ITGA7 1</td><td> ITGA7 |</td><td> | zvau</td><td> ITGA7 1</td><td> 17GA7 I</td>

<td></td><td> j ProbeWt</td><td> tn</td><td> en</td><td> CM</td><td> CM</td><td> iN</td><td> 0i</td><td> CM</td><td> 04</td><td> Ή</td><td></td><td> V*</td><td></td><td> 5</td><td> Γ</td><td> en</td><td> L 627 1</td><td> ! 624 j</td><td> 611 j</td><td> 602 !</td><td> 540 I</td><td> ΓΜ in</td><td> 04 eg</td><td> 491 I</td><td> 1 ISP</td><td> 434 I</td><td> m η</td><td> 364 j</td>

<td colspan="2"> i Coexpressed ϊ Gene</td><td> ί FOXJ3 ______</td><td> Γ PPP1R158</td><td> eft &lt; z u?</td><td> SARI 8</td><td> ' SERPINB9</td><td> SI91d i ___________ 1</td><td> 0ZPOS3 i 1</td><td> δ Q Z D at</td><td> ί srai</td><td> [ CPXM2</td><td> â 5</td><td> HTGA7</td><td> j ADCYS ]</td><td> j MRGPRF______|</td><td> ! PDLIM7 |</td><td> w z -2</td><td> 04 Z g</td><td> 1 MYL9 I</td><td> |aOC3__Ί</td><td> j FLNA j</td><td> | TAG IN j</td><td> [ T3WN3X j</td><td> | DES |</td><td> 1 IIGA7</td><td> ί SLC24A3 I</td><td> J^SI____________________</td><td> TSPAN18 j</td>

<td></td><td> | StackID</td><td> 1*4</td><td> 0«</td><td> 04</td><td> 04</td><td> 0)</td><td> 01 —mJ</td><td> 04 —</td><td> 04</td><td> 01</td><td> ·-·</td><td> 7-4</td><td> e*4</td><td> 01</td><td></td><td> A4</td><td> 0!</td><td> &lt;N</td><td> 04</td><td> 0*</td><td> 0«</td><td> 01</td><td> 01</td><td> (N</td><td> 01</td><td> 04</td><td> 0!</td><td> 04</td>

<td> [ Seeding</td><td> tt &amp; tt a</td><td> DES 23Ί</td><td> I DES ._____1</td><td> ί DES</td><td> [ DES</td><td> [des________ί</td><td> [DES</td><td> i DES</td><td> 10 Ui Q</td><td> I DES</td><td> : DES</td><td> DES j</td><td> a</td><td> DES j</td><td> DES I</td><td> DES j</td><td> DES j</td><td> DES [</td><td> DES j</td><td> I S3Q</td><td> DES J</td><td> DES i</td><td> Γ S3Q</td><td> DES___ ]</td><td> [ S3G</td><td> DES j</td><td> DES |</td><td> DES 1</td>

<td></td><td> j ProbeWt</td><td> ___4439</td><td> | 4392</td><td> 1 4243</td><td> | 3966</td><td> | 3592</td><td> | 3236</td><td> | 3165</td><td> 3042</td><td> [ 3011 !</td><td> : 2881 j</td><td> [ 2851 j</td><td> ί 2724 ]</td><td> I ΡΟΖΕ</td><td> 2404 j</td><td> 2374 j</td><td> 2253</td><td> 2088 j</td><td> § 8</td><td> W9 10 σι</td><td> 1851 i</td><td> j 0ES1</td><td> 1830 j</td><td> 179?</td><td> r&gt;</td><td> 1682 1</td><td> 1596 |</td><td> in cH</td>

<td> Î Coexpressed</td><td> ; Gene</td><td> δ u.</td><td> CELF2</td><td> i MMP2</td><td> i WW7R1</td><td> j CAP2___________j</td><td> î LOC.a00129846 |</td><td> RBMS3 j</td><td> AOX1 j</td><td> i MFAP4</td><td> ΐ TCF21 j</td><td> 1 MA7N2 1</td><td> 1 MRGPRF 1</td><td> I POPDC2 |</td><td> 1 CFL2</td><td> j LOC2839O4 j</td><td> i PRELP</td><td> | CCDC69</td><td> I WM j</td><td> [ DNAJB5 j</td><td> I tZIMdD r......... i</td><td> GASS i</td><td> TSPAM2 j</td><td> ANGPT1______</td><td> MFGE8 |</td><td> ITGA1 [</td><td> GSTM5 f</td><td> MYADM I</td>

<td></td><td> □ 5 u rat w &lt;0</td><td> m</td><td> in</td><td> 10</td><td> tn</td><td> : 10’ 1</td><td></td><td> 60! :</td><td> 10</td><td> 10</td><td> 40</td><td> IF.</td><td> 10</td><td> un ......</td><td> 10</td><td> »0</td><td> in</td><td> 1 ! ί «ni !</td><td> 10</td><td> in</td><td> 10|</td><td> in</td><td> .r.</td><td></td><td> i s 1</td><td> j 5</td><td> Ll„.</td><td></td>

CA 02863040 2014-07-28

WO 2013/116144

PCT/LS2Ü13/023409

Applicant Ref. 09042.8-304 / GHI-052PCT

<td> w c ό ÿ s « Λ 19</td><td> 1 TPM 2 _______I</td><td> CM s Q. H</td><td> i TPM2 I</td><td colspan="2"> i ZWd2 i j zwdi. j</td><td> | TPM2</td><td> i TPM2</td><td> LTPM2 i</td><td> 1 TPM2_______;</td><td> | TPM2</td><td> CM S CL H</td><td> 1 ÏPM2</td><td> CM 2 Pr</td><td> | TPM2 !</td><td> ' TPM2_______i</td><td> es S £</td><td> CM 2 &amp;</td><td> TPM2 j</td><td> CM S &amp;</td><td> N S &amp;</td><td> ni 5 &amp; &gt;-</td><td> CM S</td><td> ni S &amp;</td><td> CM 5 Ê</td><td> CM Σ &amp;</td><td> TPM2 |</td><td> TPM2 :</td>

<td> I 2 a</td><td> cn</td><td> δ 2</td><td> •o S 2</td><td> B g</td><td> CM eo m 2</td><td> 09 «J O 2</td><td> m Q σ» Çh</td><td> CM S en</td><td> m m ch</td><td> 8 g</td><td> ω m σι a&gt;</td><td> σ» rM 00</td><td> «n s 09</td><td> S w</td><td> OC &lt;n Mi «</td><td> δ ΙΛ 09</td><td> tn rM 99</td><td> R</td><td> § en MJ</td><td> δ CM U?</td><td> m «r ΓΜ KD</td><td> 00 T*t N IH</td><td> 3 va m</td><td> 00 δ va</td><td> m CM oa</td><td> CM CM §</td><td> s î</td>

<td rowspan="2"> y Coexpressed Stack! D j Gene</td><td> &gt;</td><td> KO ω Σ as u.</td><td> «4 z h» Z u</td><td> d</td><td> M 00 01 r&gt; CM 0 _s</td><td> Cl Z ce a.</td><td> X x: S</td><td> a δ</td><td> P s ti w U.</td><td> ni O Z</td><td> E</td><td> U LL Φ O Q,</td><td> Φ 5 ri m o O</td><td> XT m tft m u&gt; Q 9</td><td> tn δ a &lt;</td><td> fô U S</td><td> CM &lt; £ a a</td><td> z va &lt;2</td><td> y«I g 3</td><td> 4 i &gt;</td><td></td><td> en QC Cû LU g</td><td> m &amp; uj CM δ ô a</td><td> X</td><td> Μί §</td><td> i i</td><td> Σ 4 U Σ</td>

<td></td><td> νΐ</td><td> ,-1</td><td> rH</td><td> rl</td><td> «M</td><td> r*t</td><td> H</td><td></td><td></td><td></td><td> rM</td><td></td><td> «U</td><td> w-i</td><td></td><td> cM</td><td></td><td></td><td></td><td> r4</td><td></td><td> r*4</td><td> τ*ΐ</td><td></td><td> ♦M</td><td></td>

<td> : Seeding 1 Gene</td><td> 4</td><td> 4 £</td><td> 4 g H</td><td> 4 P H</td><td> 4 g</td><td> 4 g</td><td> 4 g h</td><td> 5 g</td><td> 4 ë</td><td> 4 g</td><td> g</td><td> 5 g</td><td></td><td> &lt; £</td><td> 5 g</td><td> g</td><td> 5 o</td><td> 4 g</td><td> 4 P c:</td><td colspan="2"> 4 4 P P HI H</td><td></td><td> 4 g</td><td> 4 g</td><td> 4 g</td><td> 4 g</td><td> |</td>

<td> ProbeWt</td><td> ri in rc</td><td> CM CM m</td><td> CM CM ca</td><td> q m</td><td> Si</td><td> s m</td><td> n o en</td><td> 00 00 CM</td><td> r* 00 CM</td><td> CM oo CM</td><td> S CM</td><td> KO in CM</td><td> ch ne CM</td><td> oc m CM</td><td> w m Cm</td><td> Ol CM</td><td> O CM ΓΜ</td><td> © O (N</td><td> •ï o CM</td><td> δ *4</td><td> ai 00</td><td> s ·«</td><td> &lt;T CO</td><td> î? ri</td><td> CM ïM</td><td> b», ua m</td><td> KO tn rM</td>

<td> i Coexpressed 1 Gene____</td><td> 2 δ 5</td><td> η σ âx H*</td><td></td><td> w i» a. va X</td><td> JH 5 Σ</td><td> i s</td><td> s o 1</td><td> z z y</td><td> in X</td><td> VI « 5 z o</td><td> Ω OC X Q</td><td> CM CL Σ ω i</td><td> H û. &lt;</td><td> z g ta</td><td> KP ©</td><td rowspan="2"> 3 Q U. ?</td><td> 2 U. g</td><td> CM £É Q. &lt;5</td><td> CM 2 Z</td><td> &lt; W &lt; OC o</td><td> 2 o &amp;</td><td> ....... CM «H va â</td><td> U o CO</td><td> r» O e</td><td> CM Q S</td><td> JM « y S</td><td> UJ y?</td>

<td> StackID</td><td> (N</td><td> CM</td><td> CM</td><td colspan="2"> n&gt;! ni</td><td> CM</td><td> CM</td><td> CM</td><td> FM</td><td> CM</td><td> &lt;N</td><td> CM</td><td> CM</td><td> &lt;N</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> ni</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td>

<td> [seeding i Gene</td><td> a 3</td><td> ft o</td><td> ιΛ ω Ω</td><td> va LU Ω</td><td> C</td><td> LÔ LU o</td><td> &lt;Λ UJ Ω</td><td> ίβ O</td><td> ta LU Ω</td><td> va LU O</td><td> q Q</td><td> ΙΛ Ω</td><td> ft Q</td><td> LH Ut O</td><td> va UJ O</td><td> ta U! Ω</td><td> ft a</td><td> va U! es</td><td> va Ω</td><td> ft n</td><td> va LU Ω</td><td> Ω Ω</td><td> Ώ Q</td><td> va UJ Ω</td><td> îu Ω</td><td> va UJ Q</td><td> va LJ Ω</td>

<td> i i ProbeWt</td><td> w 2</td><td> m in 2</td><td> S 2</td><td> S CM F&lt;</td><td> IA •M «M</td><td> s S</td><td> KO 00</td><td> δ 00</td><td> H *9 00</td><td> &lt;0 M 00</td><td> LO CM CO</td><td> CM g</td><td> CM</td><td> g Φ</td><td> «3 ΚΛ</td><td> ¢0 ΙΛ LÔ</td><td> δ ΙΛ</td><td> ch «s *</td><td> 1Λ</td><td> h* s</td><td> 00 i</td><td> eh « en</td><td> lO KD ca</td><td> LO M</td><td> O ΙΛ no</td><td> ra M ?û</td><td> e N m</td>

<td> i Coexpressed ; Gene</td><td> 5» d</td><td> o 2 5 _δ</td><td> ? k?</td><td> M &lt; S ta</td><td rowspan="2"> Z « Ai _____ G</td><td> &lt; 5 z U ta</td><td> «t z û£ fM o Cl.</td><td> o « tp X âi „5</td><td> S ç o to &lt;J</td><td> o CM CL δ x ta &lt;</td><td> L» g</td><td> CM âi £! £</td><td> cj « P ç !Λ</td><td> r&lt; a z</td><td> S g</td><td> z S ΙΛ</td><td> P s £</td><td> YM &lt; !S o V</td><td> 4 P</td><td> 3 B</td><td> ‘Π « O «N Q</td><td> CM 1 LU LL UJ</td><td> 3 a. t</td><td> P ta</td><td> fA S 4</td><td> 4</td><td> a. a»</td>

<td> ! \ StackIO</td><td> Λ</td><td></td><td> ©</td><td> 1 ©</td><td> ©</td><td> G</td><td> 1Λ</td><td> m</td><td> in</td><td> m</td><td> m</td><td> m _____</td><td> m</td><td> LH</td><td> m</td><td> m ~x~xJ</td><td> m _</td><td> G</td><td> in</td><td></td><td> IH</td><td> LJ</td><td></td><td> m</td><td> en</td><td> LH</td>

CA 02863040 2014-07-28

WO 2013/116144

PCT/LS2Ü13/023409

Applicant Ret. O9042.8-3O4 / GH1-052PCT

<td colspan="2"></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>^.......</td><td></td><td></td><td></td><td></td><td></td><td></td><td> ··*···*</td><td></td><td></td>

<td> fseeding</td><td> 1 Gene</td><td> 1 TPM 2</td><td> TPM 2</td><td> ] TPM2</td><td> \ TPM2</td><td> 5 à</td><td> rt 2 &amp;</td><td> rt 2 H</td><td> ί TPM2</td><td> s rt</td><td> TPM2</td><td> CM 5 &amp;</td><td> TPM2</td><td> CM S £L &gt;—</td><td> 1 TPM2</td><td> î TPM2</td><td> TPM2</td><td> TPM2</td><td> TPM2</td><td> I TPM2</td><td> S t—</td><td> TPM2</td><td> TPM2</td><td> CM 2 Ê</td><td> TPM2</td><td> : CM 5 au</td><td> CM S</td><td> CM 5</td>

<td colspan="2"> ? £ 0 a</td><td> Γ 4753</td><td> OPSV ]</td><td> [ 4499</td><td> 1 4133</td><td> ί 3515</td><td> 3490</td><td> «3 m en</td><td> 3141 1</td><td> 2530</td><td> 2406</td><td> 2375</td><td> n en N</td><td> 2029</td><td> : 2029 ί</td><td> 2007 i</td><td> 1965 j</td><td> 1785 |</td><td> 1720 1</td><td> 1700 1</td><td> 1459 ]</td><td> 1296 j</td><td> .1287 ]</td><td> 1256 1</td><td> 1226 \</td><td> 1170 1</td><td> 1069 j</td><td> 1065 ]</td>

<td> Fcoexpressed</td><td> o c Φ 0</td><td> 1 PDUM7 j</td><td> I ADRA1A ______j</td><td> 1 ANXA6</td><td> | FB1N1 ]</td><td> BOC J</td><td> cn &lt; o o</td><td> I CRYAB Ί</td><td> m Q O Q*</td><td> PDE5A i</td><td> MAP1B j</td><td> FGF2 I</td><td> § m rt § V 9</td><td> MRGPRF</td><td> S8WN0</td><td> &lt;T O 3ï en so CM V 9</td><td> POPDC2 j</td><td>^; TCF21</td><td> TLN1</td><td> CM Uj M U</td><td> AOX1 ______|</td><td> m $ CM ΪΛ</td><td> 0) δ Q $</td><td> k· 0 I</td><td> j WDd</td><td> L ^23NS</td><td> «t a o; N Q Or</td><td> RGN ί</td>

<td colspan="2"> । StackiD j</td><td></td><td></td><td></td><td></td><td> ri</td><td> rd</td><td> ri</td><td></td><td> ri</td><td></td><td></td><td> ri</td><td></td><td> ri</td><td> r&lt;</td><td> ^4</td><td></td><td></td><td></td><td> r&lt;</td><td> ri</td><td> •“t</td><td> r4</td><td></td><td></td><td> ri</td><td> ri-</td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> MMW</td><td></td><td></td><td></td><td></td><td></td><td></td><td> WWW»</td><td></td><td></td>

<td> w E Ό Φ Λ Ul</td><td> ί Gene</td><td> Γ ΠΌΑ7</td><td> g</td><td> ITGA7</td><td> ITGA7</td><td> ITGA7</td><td> ί ITGA7</td><td> ί ITGA7</td><td> ί ΠΌΑ 7</td><td> | ITGA7</td><td> | ITGA7</td><td> πόα 7</td><td> &lt; g</td><td> j ΠΌΑ7</td><td> ! ITGA7</td><td> I ITGA7</td><td> LiJGA7</td><td> 1 ΠΌΑ7</td><td> i</td><td> ITGA7</td><td> ITSA7</td><td> ?</td><td> ! ITGA7</td><td> ITGA7</td><td> ITGA7</td><td> ITGA7</td><td> ITGA7</td><td> ; ITGA7</td>

<td></td><td> eWt</td><td> zvt</td><td> 133</td><td> ΓΜ CO</td><td> 126</td><td> CM ri</td><td> 110</td><td> 109</td><td> 101</td><td> 66</td><td> CS ω</td><td> en ut</td><td> UT</td><td> 3</td><td> 43 !</td><td> 41 j</td><td> S</td><td> 34 J</td><td> 33 |</td><td> 30 i</td><td> CO CM</td><td> CM</td><td> N N</td><td> ZZ</td><td> σι «M</td><td> 3</td><td> 19j</td><td> Rl...</td>

<td></td><td> s έ</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td colspan="2"></td><td></td><td></td>

<td> I Coexpressed</td><td> [ Gene</td><td> © O V</td><td> Ï----------------- I PG MS</td><td> [ SYNM</td><td> d X IX.</td><td> | HEPH</td><td> 1 COL6A2</td><td> [1OC729468</td><td> 1 MYOCD</td><td> | ACTA2</td><td> ! RBPMS2</td><td> 1.1 MS2</td><td> ί GNAO1</td><td> i A5B2</td><td> | HRNBP3</td><td> 1 POPDC2</td><td> [ DAAM2____</td><td> Q O</td><td> PDZRN4</td><td> UJ «5 ç o « u</td><td> S g</td><td> ταΐΝ</td><td> MÎ ? s u</td><td> ZOSfîM</td><td> m m 2 UJ Σ H</td><td> CLIP3</td><td> M s</td><td> ' TINAGLl</td>

<td colspan="2"> 1 StackiD</td><td> rJ</td><td> *N</td><td> CM</td><td> CM</td><td> &lt;s</td><td> CM</td><td> CM</td><td> CM</td><td> n</td><td> rs</td><td> rt</td><td> rt</td><td> CM</td><td> CM</td><td> rs</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> rt</td><td> rt</td><td> CM</td><td></td><td></td><td> CM</td>

<td> ue s</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> ί Seed</td><td> j ProbeWt J Gem</td><td> | 302 ] DES</td><td> 1 294 1 DES</td><td> i 266 J DES</td><td> | 249 1 DES</td><td> __239] DES</td><td> «Λ ω Ο « m cm</td><td> j - --j------------ i 232 ί DES</td><td> 1 221 l DES</td><td> 1 . 213 1 DES</td><td> ' 182 1 DES</td><td> ! 181 ? DES</td><td colspan="2"> 176 ί DES 173] DES</td><td> | 166 î DES</td><td> en ÜJ CS T Φ ri</td><td> I 156 | DES</td><td> j 133 | DES</td><td> 132 1 DES</td><td> ί 126 | DES</td><td> S3G ] 56</td><td> 94 f DES</td><td> l 91 i DES</td><td> \_______SI 1 DES</td><td> 49 j D ES</td><td> 48 ί DES</td><td> 45 1 DES</td><td> ί_______40 [ DES</td>

<td> I Coexpressed</td><td> Gene _____</td><td> ί CO16A2</td><td> 1 ODZ3____</td><td> ! PLEKHO1</td><td> ί PYGM</td><td> Z P</td><td> X o V</td><td> j P N MAI</td><td> j ACAC8</td><td> 1 RASL12 _______</td><td> 3 DH VI j</td><td> L· LU Φ</td><td> i NCS1</td><td> ί TRANK1 ]</td><td> I FGFR1 ______j</td><td> I AHNAK2 1</td><td> 1GAIS1_______</td><td> ï BRAS j</td><td> Q ξ S V</td><td> j TGFBltl ί</td><td> RAB34_______]</td><td> PrRF__J</td><td> ; SCHÎP1 ]</td><td> GSTM2</td><td> S3 O s</td><td> MASP1 |</td><td> TRÎP10 ____|</td><td> K UJ o; CK. â</td>

<td colspan="2"> Γ ! StackiD</td><td> m</td><td> m</td><td> in</td><td> 1/)</td><td> -Ί</td><td> &lt;n</td><td> UT</td><td> m</td><td> m</td><td> m</td><td> LO</td><td> UT</td><td> ©</td><td> ©</td><td> un</td><td> UT</td><td> m</td><td> 4Π</td><td> Is i</td><td> en:</td><td> in</td><td> ©</td><td> ir.</td><td> un</td><td> m</td><td> UT</td><td> in</td>

CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-304 ! GHI-052PCT

<td colspan="2"> j Seeding i 1 Gene i t-----i = TPM2 1</td><td rowspan="4"> I 1 ΐ GPR124 | 917 î TPM2 Î</td><td> CM s</td><td rowspan="4"> Ϊ a I CFL2 ( 871 ! TPM2</td><td> CM s</td><td> 1 ZWdX » ? :</td><td> i i ___________</td><td> i TPM2</td><td rowspan="2"> WL I £69 i L____s_____4</td><td rowspan="2"> 1 540 i TPM2 J</td><td> [ TPM2 Î</td><td> ί TPM2 :</td><td> | TPM2 I</td><td> ί TPM2 1</td><td> : 2</td><td> ZiAJdJL \</td><td> § £</td><td> j ZlAIdl j</td><td> rd</td><td> cv 5 Sb</td><td> f ZWdL 1</td><td></td><td> I ?WdJL |</td><td> j TPM2</td><td> r^- CM 2 X k*</td><td> 7PM2</td><td> : TPM2_______</td>

<td rowspan="3"> i Coexpressed 1 StacHD ] Gene ProbeWt</td><td rowspan="3"> Ll \ CESl ΐ 1050</td><td></td><td rowspan="3"> H CAMK2G ] 869</td><td> 0S8</td><td> 794</td><td> 752</td><td> 1 533</td><td> 500</td><td> : ¢9 : !</td><td> ! i 429</td><td> :___ί</td><td> C4 §</td><td> s m</td><td> | 354</td><td> Γ 339</td><td> I 327 1</td><td> 325 j</td><td></td><td> | 300 1</td><td> r~</td><td> ! 254 1</td><td> i 248</td><td> CZZ</td>

<td rowspan="2"> I 1 | GAS6</td><td rowspan="2"> ! 1 1 ARHGAP20</td><td rowspan="2"> tn 5 &amp; Φ pd</td><td> CAP2</td><td rowspan="2"> 1 i PRELP</td><td> z tn</td><td rowspan="2"> 9&lt;3AXd T I ______J...............</td><td rowspan="2"> I 1 ] TSPAN2</td><td> KCNMA1</td><td> 1 PTGER2</td><td rowspan="2"> [ 1 \ TCEAL2</td><td rowspan="2"> 5 a I</td><td> cn s «C</td><td> I COL&amp;A1</td><td> 1 ATP1A2</td><td> I SLC12A4 !</td><td> 1 ITGA5 j</td><td> !σΰΑ9 j</td><td> j 1TGA7 1</td><td> PM 2 u&lt; &amp;</td><td> : PYGM 1</td><td> COL6A2. I</td><td> OldVSHVV ;</td>

<td> &lt;·&lt;</td><td></td><td></td><td> rd</td><td></td><td></td><td></td><td> 4**</td><td rowspan="2"> SRDSA2 11</td><td rowspan="2"> SRD5A2 | 1_______ί</td><td rowspan="2"> SRD5A2 I 1 1</td><td rowspan="2"> SRDSA2 1 1 1</td><td rowspan="2"> SRD5A2 11 j</td><td rowspan="4"> TAGIN ! 46404 j SRDSA2 1 1 ί</td><td rowspan="3"> 46365 SRD5A2 [ 1_______§</td>

<td> r Seeding j £ Gene_______i</td><td rowspan="2"> | 17 1 WGA7i</td><td rowspan="2"> i _____11 ? iTGA7 J</td><td> j HGA7</td><td> &lt; t</td><td> «</td><td> i ITGA7 \</td><td> «</td><td> |jTGA7 I</td><td> i ZVDH |</td><td> | FFGA7 1</td><td> &lt; £</td><td> &lt;</td><td> « g t=</td><td> [ zv&amp;it :</td><td> ! ZV91I</td><td> 1 iV&amp;ll</td><td> SRDSA2 |</td><td> SRD5A2 1</td><td> SRD5A2 1</td><td> SRD5A2 |</td>

<td> 1 ProbeWt</td><td></td><td> o&gt;</td><td> ¢1</td><td> 0C</td><td></td><td> &lt;6</td><td></td><td></td><td> cn</td><td> rn</td><td> CM</td><td> ri</td><td> n</td><td> ri</td><td> 1 47139 J</td><td> 470561</td><td> 47002</td><td> 46967 1</td><td> ___46874</td><td> H r* OQ t£&gt;</td><td> o 4g</td><td> C» © M? IO *?*</td><td> 46428 j</td>

<td> Coexpressed Gene</td><td> | DBNDD2</td><td> 1 ÎTGB3</td><td> LL0B3</td><td> | ITGAS</td><td> ISDN</td><td> FOXF1</td><td> OACTl________j</td><td> tOdSO i</td><td> ΐ JPH2 1</td><td> i 9TS3NZ</td><td> a: cc X</td><td> i HSHN</td><td> LCAÏ 1</td><td> I £&lt;J8Vd j</td><td> GNAZ j</td><td> s CM ft.</td><td> s 3 «Λ</td><td> OS © Φ CM f*. o 2</td><td> DPYSW______ I</td><td> ACTA2 \</td><td> | SW9d</td><td> MEiSl |</td><td> ACTG2 ί</td><td> n û. m 2 © A,</td><td> MSRB3</td><td> FLNA ί</td>

<td> | StacMD</td><td> CM</td><td> Ci</td><td> PM</td><td rowspan="2"> z | saa j</td><td> CM</td><td> CM</td><td> IM</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> PM</td><td> CM</td><td> CM</td><td> PM</td><td rowspan="2"> ! DES | 2 _____|</td><td rowspan="2"> ! DES 11 j</td><td rowspan="2"> I_______τ I $30 )</td><td rowspan="2"> i DES_______]1__________</td><td rowspan="2"> GSTM1 I 1</td><td rowspan="2"> 1 1 ] ÎIAI.I.S9</td><td rowspan="2"> GSTMl | 1 j</td><td rowspan="4"> GSTM5 j ___4 j GSTM1 | 1 |</td><td rowspan="2"> I t | rmss ί</td><td rowspan="2"> GSTMl | 1 ί</td><td rowspan="2"> GSTM1 ___[1 I</td><td rowspan="2"> GSTMl | 1 i</td>

<td rowspan="3"> —........................................................................... Coexpressed ; t Seeding ; Gene j ProbeWt j Gene j</td><td rowspan="3"> [ RBPMS2 j 37 ‘ DES ]</td><td> \ DES |</td><td> ί DES 1</td><td> I DES</td><td> i S30</td><td> ί DES ]</td><td> I DES__________I</td><td> iû a</td><td> [ DES j</td><td> Ldes ___J</td><td> ifl a</td><td> i DES !</td><td> L_...... ^S30^</td><td> 1 DES j</td>

<td rowspan="2"> i APO8EC3C | 30</td><td> 29</td><td> Ic ]</td><td> ί 16</td><td> CM</td><td> zr l _____________1</td><td> TT</td><td> ϊΐ</td><td> j</td><td> Cl</td><td> 10</td><td> ιΛ</td><td></td><td> cn</td><td> en</td><td> PM</td><td> CM</td><td> ♦d</td><td> &lt;F</td><td> MJ</td><td rowspan="2"> GSTM4_______j 4</td><td rowspan="2"> SP0CK3 1 3i</td><td rowspan="2"> PGM5 [ 3 Î</td><td rowspan="2"> i £ ί 88dSH</td><td rowspan="3"> 1 jAOX1 } .2 j</td>

<td> [ C0PZ2</td><td> j CACNA1C</td><td> ί GNAO1</td><td rowspan="2"> ±sn ! s I</td><td rowspan="2"> 1 s ί Acrci</td><td> CES4 j</td><td> ÎD4</td><td> I Sn»9TD ί</td><td> CM m 1</td><td> I GSTM5P1 1</td><td> i GSTM4</td><td> i CBX7 . |</td><td> _________1</td><td> ï FABP3___________ί</td><td> GSTM3 t</td><td> SSTM2P1 ï</td><td> HSPB6 j</td><td> GSTMSPl_____i</td><td> GSTM2 Î</td>

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CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-304 f GHI-052PCT d

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CA 02861040 2014-07-28

WO 2013/116144

PCT/US2013/023409

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Appli-cant.Ref. 09042.8-304 !GHÎ-052PCT ee

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CA 02863040 2014-07-20

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-304 ! GHHW2PCT

<td> I Seeding i Gene</td><td></td><td colspan="2"> E I i</td>

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<td> Coexpres! Gene___</td><td> X S</td><td> KANK2</td><td> a. UU § o Q</td>

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<img file="CA2863040C_D0022.tif" />

<td> I ; i</td><td> Seeding Gene</td><td> 3 CO s</td><td> | MYBL2 |</td><td colspan="2"> MYBL2 MYBL2</td><td> 2</td><td colspan="2"> MYBL2___ MYBL2</td><td> I MYBL2 i</td><td> [ MYBL2 J</td><td> 04 ce</td><td> ! MYBL2 j</td><td> 3 CO 5</td><td> i MYBL2 i</td><td> | Π8ΑΑΙ |</td><td> I ΖΊ8ΛΙΛΙ |</td><td colspan="2"> MYBL2 1 MYBL2 j</td>

<td></td><td> I i Co-expressed I | StacklD ; Gene I ProbeWt</td><td> | 1 î SÜSD2 i 3824</td><td> 1 1 î TGM6 ΐ 3767</td><td> j 1________i CDCA3 ί 3765 1</td><td> j 1 \ C20orfl51 3706 |</td><td> Γ1 î CllorfAl ί 3650</td><td colspan="2"> 1 I C9orf98 î 3636 1 î KRT24____________Î 3589</td><td> i 1 Ξ ABCC12 Î 3582</td><td> j 1 = B3GNT4__; 3569</td><td> | 9SS£ ; ÏIZV ; il</td><td> ΟΝ m QC c. ci</td><td> j 1 i KIF24 i 3264 |</td><td> | 1 î DERL3 î 3232 |</td><td> | 1 l LIRE î 3221 |</td><td> i 1 î mis _________i 3196 |</td><td> [ 1__ί SEC1 i 3196 1</td><td> ί 1 ί ADAMS i 3185</td>

<td rowspan="6"> Table 10</td><td> Seeding Gene</td><td> CDC20 |</td><td colspan="2"> CDC20________ CDC20</td><td> CDC20 ί</td><td> CDC20 ;</td><td colspan="2"> CDC20 1 CDC20 1</td><td> CDC20 ί</td><td> Q D Q U</td><td> Q ü Q U</td><td> CDC20 1</td><td> Q 0 Q U</td><td rowspan="2"> ί C6orf25 1 1765 j CDC20 j</td><td> CDC20____j</td><td rowspan="2"> AGXT j 1529 ί CDC20 ί</td><td> Ο 0 Q U</td><td> CDC20 I</td>

<td> Coexpressed ί Gene 1 ProbeWt</td><td> | GPAT2 ____ ] 1997</td><td> j AVPR1B I 1991</td><td> 1 MGCS0722 1990</td><td> j AQP12A Î 1983 |</td><td> Γ C6orf222 | 1965</td><td> j PRAMEF19 I .1965 j</td><td> | PRAMS Fl 8 ____ί 1965</td><td> 1 StCSA9 I 1965</td><td> ί FCN3 1955</td><td> I GCM2 | 1910</td><td> 1 AD0RA3 1 1862 !</td><td> j PLA2G2F 1 1821</td><td> ί CDC45 i 1681</td><td> ! KIF25 i 1507</td><td> ZDHHC19 J _____1507</td>

<td rowspan="2"> 1 Seeding | ProbeWt ί Gene 1 StacklD</td><td rowspan="2"> 9758 f CDC20 1 1</td><td rowspan="2"> 1 I 0Z3G0 î 8SZ6</td><td rowspan="2"> o a g 0Ô m n G*</td><td rowspan="2"> I ¢2903 1 VZ96</td><td rowspan="2"> 9571î CDC20 I 1</td><td rowspan="2"> T f 0Z3Q3 ί ΪΖ96</td><td rowspan="2"> 9328 CDC20 I 1</td><td> rd</td><td> «H</td><td> V-l</td><td></td><td colspan="2"> j H! **&lt;</td><td> n</td><td> «Μ</td><td> t»l</td><td></td>

<td> e 8 o o Ιώ Λ σι</td><td> 9178 1 CDC20____!</td><td> 8987 ί COC20</td><td> 887S î CDC20____J</td><td> 8875 I CDC20 |</td><td> 8554 j CDC20 I</td><td> 8346 i CDC20 I</td><td> 8322 I CDC20 |</td><td> 8135 î CDC20 i</td><td> O N O U e» σ&gt; m</td>

<td> Coexpressed Gene</td><td> NCAPH i</td><td> CDC20 j</td><td> IQGAP3 |</td><td> δί in</td><td> &lt; ο. z w V</td><td> o</td><td> CO oo &lt;“4 £</td><td> 1 Z9WGM</td><td> ^_RoAp</td><td> ί ADAMTS7 i</td><td> E s Sw.</td><td> 3 g v&gt;</td><td> I FNDCl i</td><td> &lt;S e © ί</td><td> aû T~i s ί</td><td> I PNLDC1 j</td><td> K1FC1 ____________</td>

<td colspan="2"> ; 1 StacklD \ 1</td><td> w|</td><td></td><td> Ή</td><td> -4</td><td> ¢-4</td><td> *4</td><td> «Μ</td><td></td><td> Μ</td><td> «M</td><td> H</td><td> •w</td><td> «M</td><td> *4</td><td> M</td><td> t~i</td>

CA 02863040 2014-07-20

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-304 / OHJ-052PCT

<td rowspan="2"> | Seeding ProbeWt I Gene</td><td rowspan="2"> 3136 MYBL2</td><td rowspan="2"> | 3136 ; MYBL2</td><td rowspan="2"> [ 3094 1 MYBL2</td><td rowspan="2"> i 3034 ί MYBL2</td><td rowspan="2"> 2.936 ί MYBL2</td><td rowspan="2"> ! 2936 I MYBL2 !</td><td rowspan="2"> | 2915 ί MYBL2 |</td><td rowspan="2"> 1 2868 MYBI.2 i</td><td rowspan="2"> f 2862 MYBL2 ί</td><td rowspan="3"> ; 1________1 REM2_____________1..........2832 I MY8L2 j</td><td rowspan="2"> -T ©! w 0 co Cd</td><td rowspan="3"> J j TSNAXiPl ί 2799 MY8L2 i</td><td> MYBL2__</td><td> □ co S</td><td rowspan="3"> i 1 j WDR16___ 2723 ί MYBL2 1</td><td rowspan="3"> il______ACR____________l 2710 MYBL2.......]</td><td rowspan="3"> [ 1 1 TMPRSS13____1 2672 j MYBL2</td><td rowspan="3"> 1 1 i C15orf42 | 2659 i MYBL2</td><td rowspan="3"> * CT8AW ΐ 6P9Z 1 8£1WMG 1</td><td rowspan="3"> 1 ___[uNC13D________1 _____2610 i MYB12_____j</td><td rowspan="3"> 1______ i SYT5 ; 2544 1 MYBL2</td><td colspan="3"> J d| d g g g 5| S: SI</td><td> MYBL2 i</td><td> MYBL2 ........... •’’♦i</td><td rowspan="3"> 1 1 i LAI R 2 1 2233 j MYBL2____|</td>

<td colspan="2"> ί 2767 j 2762 J</td><td rowspan="2"> 1 1 i PAX2 ________J 2462 j</td><td rowspan="2"> L· î PRCD___j___2426 j</td><td rowspan="2"> 1 1 i PPFÎA3 i 2421 j</td><td rowspan="2"> j 1 I GCGR î 2338 !</td><td rowspan="2"> | 1_______I CACNG3_______1 2289 î</td>

<td> Co-expressed Stack! D Gene________</td><td> 1 j SLC25A19 j</td><td> 1 1 PRSS27 j</td><td> 1 | ODF3L2 1</td><td> 1 | 0024____</td><td rowspan="3"> 990 j CDC20 I 1_______ί RAD54L__________j</td><td> 1 | KCNE1L ;</td><td> 1 ______| SBF1P1___</td><td> 1______j AIPL1 ......... i</td><td> i VEONH i T !</td><td> ; rod IX ; Ï</td><td> e &lt;o o cn cn u O «j ri</td><td> 1 1 SLC6A12</td>

<td rowspan="2"> ; Seeding ProbeWt I Gene</td><td rowspan="2"> 1374 i CDC20 \</td><td> 1...... 0003</td><td rowspan="2"> 1063 îCDC20____</td><td rowspan="2"> 1052 j CDC20 ]</td><td rowspan="2"> 932 | coao I</td><td rowspan="2"> 1 757 | CDC20 ___</td><td rowspan="2"> Γ_____748] CDC20 1</td><td> CDC20 |</td><td> CDC20 j</td><td> CDC20 I</td><td> CDC20____</td><td> CDC20_________</td><td> CDC20 |</td><td> CDC20 j</td><td> CDC20 j</td><td> CDC20 i</td><td> : CDC20</td><td> CPC20 j</td><td> CDC20 |</td><td> I CDC20_____1</td><td> CDC20 i</td><td> CDC20</td><td> CDC20 !</td><td> ί COC20 i</td><td> ΐ CDC20</td><td> O 0 a u</td>

<td> 1220 I</td><td> 687J</td><td> j 632 |</td><td> 1 621 ί</td><td> Γ 601 j</td><td> co tn</td><td> 566 |</td><td rowspan="3"> \ 1 î CDCA3 i 442 |</td><td rowspan="2"> ! CLSPN I 381 |</td><td rowspan="2"> ESYT3_______ i__356 J</td><td rowspan="2"> ce r* ΓΜ C x U-</td><td rowspan="2"> I CDCA2 |________186 i</td><td rowspan="2"> | CKAP21 1 159 j</td><td> ÎS uh wi</td><td> ΐ________136J</td><td rowspan="2"> I UHRF1 j_________125 j</td><td rowspan="2"> j KIF20A 1 110 j</td><td rowspan="2"> I ESCO2_____ ! 107</td><td> 001 \</td><td rowspan="2"> pua_________1_____84</td>

<td> Coexpressed Gene</td><td> a Z &lt;</td><td> TACC3 |</td><td> 781 I</td><td> C15orf42</td><td> 3 2 « u-</td><td> VJ z 5</td><td> © o S</td><td> o ri Uh «fi c</td><td> FUT5 __ΐ</td><td> FOLD</td><td> 1 LOC643988</td><td> RAD51___</td><td> a</td><td rowspan="2"> ί 1 î KIF24</td><td> FOXMl______</td><td> 2 U.</td><td> g</td>

<td> StackID</td><td></td><td></td><td> *4</td><td></td><td></td><td> i ri</td><td></td><td> ri</td><td> ri</td><td> ti</td><td></td><td> ;</td><td> ri</td><td> ri</td><td rowspan="2"> CDC20 î 1</td><td> ri</td><td></td><td> ri</td><td> : :</td><td> ri</td><td> ci</td><td> Li ________</td><td> ri</td><td></td><td> ci</td>

<td> Seeding | Gene I</td><td> COC2O</td><td> CDC20</td><td> CDC20 I</td><td> C0C20 1</td><td> CDC20</td><td> CDC20</td><td> COC20</td><td> CDC20</td><td> I CDC20</td><td> CDC20</td><td> o c o u</td><td> c s Q</td><td> I CDC20</td><td> I CDC20 I</td><td> ΓCDC20</td><td> © a a u</td><td> o 3 Q U</td><td> — CDC20 i</td><td> Q y U</td><td> Q Q W</td><td> © g U</td><td> ! CDC20</td><td rowspan="2"> BIRCS ί 6278 i CDC20</td><td rowspan="2"> AQP10 6251 i CDC20</td><td> ο g U</td><td rowspan="2"> [ TFR2___ 6181 CDC20</td>

<td> I © ! $ c © CA g c X s u</td><td rowspan="2"> 1 \ C9orfl00 7547 I</td><td rowspan="2"> ------j........-....... ?.............. ! 1 ί RPS6KU 7527 i</td><td rowspan="2"> 1 Î WRAP 7521 1</td><td rowspan="2"> 1 AURKB 7224 1</td><td rowspan="2"> © s 1 * £ P</td><td> TMEM163 6853</td><td> KRBA1 6S46 !</td><td> ZMYND10 I 6825</td><td> LOC541473 ί 6824</td><td> 5LC6A1 i 6669</td><td> ci © ID Φ ci δ c</td><td> BAI2 I 6583</td><td> EM El 1 6533</td><td> CICP3 ί 6481</td><td> PPFIA4 1 6480</td><td> 8SP9 j____________</td><td> i SSPO f 6431</td><td> m m KT î ΓΜ © CE œ &lt;</td><td> IRF5 ; 6399</td><td> i NXPH1 î 6399</td><td> ZIC1 i 6346</td><td> SLC6A20 ! 6336</td><td> PKD1L1 ? 6281</td><td> AEICA4 6216</td>

<td> Q 2 u e $</td><td></td><td> * t i</td><td> ri</td><td> r»</td><td> î</td><td> ri</td><td colspan="2"> ri I *6</td><td> ; W</td><td> ***</td><td> r·</td><td> e*4</td><td> ri</td><td></td><td> Τ’</td><td> i 3____</td><td> ci</td><td> ti</td><td> ; 4 1 1 ci</td><td> M</td><td> i</td><td> ri</td>

CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

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Applicant Ref. 09042.8-304 ! GHI-052PCT

ΙΛ Ul tt w « &lt;r&gt; 09 z

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CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

<td> Seeding 1 Gene.......J</td><td> 3 » 2</td><td> 1 MYBL2 ί</td><td> Mvau i</td><td> MYSL2 1</td><td> U ωί 2</td><td> 3 ta 2</td><td> Z1SAIAI [</td><td> a OÛ s</td><td> MYBL2</td><td> } rtaÀw</td><td> ί MYBL2</td><td> a «û i</td><td> MYBL2</td><td> îj| ω 2</td><td> \ MYBL2 j</td><td> &gt; MYBL2i</td><td> ί MYBL2 i</td><td> j a CÛ s</td><td> œ 2</td><td> a » s|</td><td> a &lt;0 &gt; 2È</td><td> a es S</td><td> [ MYBL2____</td><td> a £0 S</td><td colspan="2"> I MYBL2 Γ MYBL2</td><td> i MYBL2 I</td>

<td> ProbeWt</td><td> _____?3eJ</td><td> ΙΠ Λ w</td><td> ......... 780</td><td> 733 j</td><td> ['2X9</td><td> rt r&gt;</td><td> : ¢47 |</td><td> ______548 i</td><td> ______523 !</td><td> Λ î$</td><td> Q î?</td><td> j______406</td><td> ZOt j</td><td> 61E j</td><td> zû i</td><td> i 284</td><td> [____137</td><td> i__115</td><td> 114</td><td> [_________112</td><td> 107 F———..............</td><td> 94</td><td> m 03</td><td> 1_____________68</td><td> ΙΠϊ</td><td> m</td><td> |__________31</td>

<td> | I Co-expressed i StacklD Gene____________</td><td> ί 1 ! UHRF1 j</td><td> 1 | ENO4</td><td> 1 ! ClOorflOS</td><td> .1. ί NEIL3______________</td><td> £Û CL CL ri</td><td> 1 j PROCA1_________1</td><td> 1_____1 TMEM132A.......J</td><td> \ ZSBHG \ τ</td><td> 1 ______[pLKl __________i</td><td> trSNfâ 1 T</td><td> it 1 gel ..........J</td><td> | «£JNZ i Tj</td><td> Il j FOXM1_______ !</td><td> j mod | τ</td><td> | 1 | ADAM12</td><td> ! 1 i SEMA7A J</td><td> | 1 ! HOXBS !</td><td> 11 i Exoi !</td><td> 1 1_____ 1 K1F4A .........</td><td> [ 1 ! FEN1</td><td> Z o. υ ©</td><td> t U r»</td><td> fl j CDCA2 ______</td><td> 8MÎX I ï |</td><td> 1 1 | PIK3RS___</td><td> |1 ί KÎF20A</td><td> | 1 ί ZWiNT</td>

<td> Seeding Gene</td><td> I Z18AW</td><td colspan="2"> J al a aa! œ sis</td><td> 1 Z18AW</td><td> MYBUj</td><td> J s</td><td> [___nsAW</td><td> | Π8ΛΜ</td><td> 2 CÛ 1</td><td> [ Ζ19ΛΙΑΙ</td><td> a as S</td><td> MYBL2</td><td> [ nSAW</td><td> MYBL2 |</td><td> Lmyblz._______1</td><td> a £Q S</td><td> a CO &gt; 2</td><td> a « s</td><td> ί MYBL2 j</td><td> ΖΊ8ΛΙΑΙ !</td><td> I MYBL2</td><td> a 03 5</td><td> ! MVBL2</td><td> fM Φ S</td><td> 1 MYBE2</td><td> I MYBL2</td><td> MYBL2 ______</td>

<td> ProbeWt</td><td> cr&gt; δ S</td><td> 9961 ]</td><td> •e is &lt;Λ</td><td> 9313 1</td><td> r“ 04 10 w en</td><td> CT ΙΛ es</td><td> 8537 |</td><td> 8619</td><td> CM « m 00</td><td> 6858</td><td> E ZSf 8</td><td> i______ 8273j</td><td> 1 8245 |</td><td> [61Z8 |</td><td> [1518 |</td><td> 1 8037 ]</td><td> 1 7868 1</td><td> ί 7731</td><td> I 7603 i</td><td> [ 7590</td><td> ί 7465</td><td> WEZ.</td><td> 7024</td><td> i 6981</td><td> | 6896</td><td> δ co</td><td> 6725</td>

<td> Coexpressed ! Gene !</td><td> ABCB9 1</td><td> | ziwdnaM</td><td> AOAMTS7 ]</td><td> MAST3</td><td> GABBR2</td><td> g &gt; S</td><td> DNAH3</td><td> ττω</td><td> ZFHX2 |</td><td> CDC20 ]</td><td> RASAL1</td><td> HdVON '</td><td> IQGAP3</td><td> ONAH2</td><td> LOC400499</td><td> I CHSTl</td><td> ί ATP4A</td><td> Hl 1</td><td> — EX0C3L</td><td> 00 Ur rt u/</td><td> XïdWW j ..................... î</td><td> Î5 IA3 U</td><td> i COCA5</td><td> î FAM131B</td><td> ÇZiBOtIO i ...... 4</td><td> 1 FBXW9</td><td> Φ U SI</td>

<td> St ack ID</td><td> rt</td><td> ri</td><td> n</td><td> ri</td><td></td><td> ri</td><td colspan="2"> r» î ri</td><td> r&lt;</td><td> ri</td><td></td><td> Ή</td><td> n</td><td> T*i</td><td> ri</td><td> rt</td><td> •H</td><td> ri</td><td> ri</td><td> K</td><td> ri</td><td> rt</td><td></td><td> : ri</td><td></td><td></td><td> ri</td>

<td> Seeding Gene</td><td> C0C20 I</td><td> CDC2O</td><td> CDC20 |</td><td> C0C20 Ί</td><td> CDC20</td><td> CDC20</td><td> CDC20</td><td> C0C20 1</td><td> o g U</td><td> COC2O i</td><td> 8 o U</td><td> CDC20 !</td><td> COC2Ü i</td><td> COC2O ί</td><td> I CDC20</td><td> CDC20 i</td><td> 0Z303j</td><td> CDC20</td><td> ί ° S o U</td><td> O a δ</td><td> I CDC20</td><td> i C0C20</td><td> CDC20</td><td> C0C20</td><td> Q g U</td><td> COC20</td><td> CDC20</td>

<td> ibeWt</td><td> 5491!</td><td> I6US</td><td> ri S</td><td> 5491</td><td> Λ</td><td> S S</td><td> i wt?s</td><td> 5439 î</td><td> t m î en t ** in</td><td> 5435 !</td><td> 5368</td><td> 5291</td><td> ri 00 ΓΜ U7</td><td> 5275;</td><td> 5275</td><td> ”~5217!</td><td> 5166 I</td><td> 8815'</td><td> 5114</td><td> $095</td><td> 5078</td><td> 4946</td><td> m 90 SO ’T</td><td> 4673</td><td> 4633</td><td> 90 O</td><td> 4528</td>

<img file="CA2863040C_D0024.tif" />

Li u

Applicant Ref. Ü9Ü42.8-3Ü4 I GHf“052PC’i si $ Si il Q

CA 02063040 2014-07-20

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-304 ! GHI-052PCT

<td rowspan="7"> Co-expressed ί Seeding Gene__ProbeWt | Gene</td><td rowspan="7"> SPAG5 ' 19 I MYBL2 |</td><td rowspan="7"> ERCC6L _____ j 17 ί MY8L2 j</td><td rowspan="7"> TPX2 j 11 I TPX2 [</td><td colspan="3" rowspan="6"> __11 I TPX2 10 1 TPX2 7|TPX2</td><td rowspan="7"> RACGAP1 | 6 I TPX2 [</td><td rowspan="7"> NCAPG__________________4 I. TPX2 1</td><td rowspan="7"> | MKI67 | 4 I TPX2 |</td><td colspan="2" rowspan="2"> 4 j TPX2 4 I TPX2</td><td colspan="2"> | TPX2 I TPX2</td><td colspan="2" rowspan="4"> 3 ] TPX2 2 I TPX2</td><td rowspan="7"> ί RRM2___________________1 ] TPX2 j</td><td rowspan="7"> ί KIF11_____________I________ 1 j TPX2 j</td><td rowspan="7"> j PRR11 |_________1 j TPX2 1</td><td rowspan="7"> i CM Xi &amp; ri Ur CL Z u; Q</td><td rowspan="7"> ί MKI67 ] 41 j TPX2 |</td><td rowspan="7"> CASCS [ 39 ί TPX2 |</td><td colspan="3"> 1 * CM IN; CM X X; X O.E CL; ftJ μ</td><td rowspan="2"> Î6 j TPX2_____</td><td rowspan="7"> TPX2_____________[ 33 ΐ TPX2 ____|</td><td rowspan="7"> KIF14 | 31 ΐ TPX2 [</td>

<td rowspan="2"> tr&gt;</td><td rowspan="2"> m</td><td rowspan="4"> «ο</td><td colspan="2"> m*</td>

<td rowspan="5"> | CDKN3 1..............</td><td rowspan="5"> 1 PRC1__I________</td><td colspan="3" rowspan="3"> j î ? ; । |</td>

<td colspan="2" rowspan="3"> I Î</td>

<td rowspan="3"> ; AN LN___________________j__</td><td rowspan="3"> i FAM 1118 J</td>

<td colspan="4"> i </td>

<td> 1 TOP2A_____________________j</td><td colspan="2"> NUSAP1 MELK</td><td> j ARHGAP11B |</td><td> ί KIAA0101 |</td><td> ASPM 1</td><td> KIF4A |</td><td> OLGAP5 ]</td><td> CO ί £</td>

<td> ώ S S ΙΛ</td><td> ri</td><td></td><td> ri</td><td> ri</td><td> ri</td><td> ri</td><td></td><td> ri</td><td></td><td> ri</td><td> ri</td><td> r)</td><td> ri wmn</td><td></td><td> ri</td><td> ri</td><td> ri</td><td> ri</td><td> ri</td><td> CM</td><td> &lt;M</td><td> ÎM</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> Seed in. Gene</td><td> MYBL2</td><td> 2 5</td><td> MYBL2</td><td> 2 CD ?</td><td> MYBL2</td><td> n; s ?</td><td> MYBL2</td><td> MYBL2</td><td> MYBL2</td><td> MYBL2</td><td> □ co £</td><td> MYBL2</td><td> 2 S3 £</td><td> g</td><td></td><td> MYBL2</td><td> MYBL2</td><td> g 5</td><td> g €0</td><td> MŸBL2</td><td> □ CD 2</td><td> CD 5</td><td> MYBL2</td><td> □ CS s</td><td> MY812</td><td> MYB12</td><td> MYB12</td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> 1 tu Λ</td><td> 6720 I</td><td> 6515</td><td> 6413 I</td><td> CM O tr to</td><td> 6382 ί</td><td> 6360 ί</td><td> 6312</td><td> 8 CM SC</td><td> to CM O «</td><td> 6020</td><td> o 3 SP</td><td> 5896</td><td> 5896 i</td><td> o tT GO tn</td><td> 5838 ί</td><td> 5659</td><td> 5593</td><td> ri In tn</td><td> 5337</td><td> 5286</td><td> 9PTS</td><td> 5123</td><td> 5068</td><td> n s m</td><td> O en §</td><td> «M Q §</td><td> __4901</td>

<td> 0 w &amp;</td><td></td><td></td><td></td><td></td><td></td><td></td><td> —</td><td> ......</td><td></td><td> ......</td><td></td><td></td><td> .......</td><td> ___</td><td> ......</td><td> .......</td><td></td><td> ......</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> XI</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> Φ V»</td><td></td><td></td><td></td><td></td><td></td><td></td><td> Q tn</td><td></td><td></td><td></td><td></td><td> m</td><td> m</td><td></td><td></td><td> o</td><td></td><td> ΤΓ</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> Coexpres Gene</td><td> FNDC1</td><td> 9Z3S</td><td> FCHO1</td><td> APLNR</td><td> ALAS2</td><td> VSX1</td><td> en σ&gt; U 2</td><td> 0PF1</td><td> CDC45</td><td> Cllorf9</td><td> CM El</td><td> ADAMTS:</td><td> TMEM14</td><td> &lt;9 «0</td><td> CBX2</td><td> r* CM g 2</td><td> CCOC135</td><td> ADAMTS:</td><td> 6Û 5! ë</td><td> q c a.</td><td> o •u z &amp;</td><td> UCP3</td><td> FANCA</td><td> | M5LNL</td><td> CL Q- £</td><td> | LRRC168</td><td> CACNA1F</td>

<td> o « β</td><td></td><td></td><td></td><td></td><td></td><td></td><td> n</td><td> ri</td><td> ri</td><td> r&lt;</td><td></td><td> ri</td><td></td><td> ri</td><td> rc</td><td> r&lt;</td><td></td><td> ri</td><td> r&lt;</td><td></td><td></td><td></td><td> n</td><td> r&lt;</td><td></td><td></td><td> ri</td>

<td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> ........</td><td></td><td></td><td></td><td></td>

<td> \ ί Seeding ! ί ProbeWt ί Gene</td><td> 4497 1 CDC2O ]</td><td> ! 4475 î COC20_____|</td><td> \ 4451 = CDC20 |</td><td> 1 02^03 : 6m i___________________________________________i ........&lt;</td><td> I 4299 ΐ COC20 ]</td><td> I 4297 j COC20 1</td><td> | 4272 I CDC20 |</td><td> 4211 i CDC20 1</td><td> 4155 î C0C20 1</td><td> 4113 \ CDC20 I</td><td> 1 4063 ί C0C20 |</td><td> j 4059 I CDC20</td><td> 1 3913 î CDC2Ü j</td><td> ---,---------- -i 1 3743 1 CDC20</td><td> ÎRXO 1 1898 |</td><td> | 3665 1 C0C20 1</td><td> I 3638 I CDC20</td><td> 1 3589 I COC20 1</td><td> I 3573 I CDC2.0 J</td><td> ï 3S51 I CDC20 I</td><td> ί 35SI I CDC20</td><td> 1 orxn 1 tsse i i I 1</td><td rowspan="2"> | KIF2C 3541 i C0C20 ]</td><td> ! 3426 1 COC20 ]</td><td rowspan="2"> | NUDT17 ί 3399 j CDC20 i</td><td rowspan="2"> 1 UL8P2 ί 3395 1 CDC20 ί</td><td> i 3341 | CDC20 ί</td>

<td> Coexpressed Gene ί</td><td> ri V at O</td><td> SI XIA ;</td><td> MFSD2A</td><td> BEST4 |</td><td> CACNA1F j</td><td> KLHDC7A</td><td> MAPK15 1</td><td> GHRHR j</td><td> KEI.</td><td> C2orf62 1</td><td> s z &lt;</td><td> RAET1G I</td><td> i GPR88</td><td> 1 F12 1</td><td> LYPD1</td><td> o t 0 M u</td><td> ABCB9 1</td><td> . Z 2</td><td> Γ CDC25C I</td><td> jC6LA3A ί</td><td> I AQP12B</td><td> «r □ z</td><td> i £ΊΪ3Ν j</td><td> : ri 2</td>

<td> StackID</td><td> ri</td><td></td><td> rt</td><td> ri</td><td colspan="2"> l 1 n</td><td></td><td> r*</td><td> n</td><td> ri</td><td> r&lt;</td><td> ri</td><td> ί Ή _</td><td> Ή</td><td> ri</td><td> ri</td><td> rt</td><td></td><td> rl</td><td> r|</td><td> ri</td><td></td><td> r| .....</td><td> H</td><td> ri</td><td> T |</td><td> J ri]</td>

CA 02863040 2014-07-20

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09C42..8-3041GHI-Û52PCT

<td> Seeding Gene______</td><td> TPX2</td><td> TPX2</td><td> 5 Cl</td><td> TPX2</td><td> TPX2</td><td> TPX2.__</td><td> TPX2</td><td> TPX2 j</td><td> EXdl</td><td> ΪΝ X a·</td><td> TPX2__________|</td><td> CH; X Q,</td><td> ί TPX2 j</td><td> TPX2 i</td><td> 5 ZXdl</td><td> I EXdl</td><td> ΓΗ X fc</td><td> TPX2</td><td> TPX2__</td><td> j TPX2</td><td> 1 TPX2</td><td> TPX2</td><td> TPX2 ;</td><td> i TPX2</td><td> ΓΜ g r*</td><td> ï EXdi :</td><td> • i TPX2</td>

<td> §</td><td> pF</td><td> 30</td><td> 27</td><td> 27 j</td><td> 2.5 j</td><td> 9E</td><td> m ΓΗ</td><td> o CM</td><td> I 6T</td><td> 18 ------</td><td> 17 !</td><td> U? d</td><td> 51</td><td> al</td><td> S</td><td> 13</td><td> 13</td><td> 13</td><td> 0Ϊ</td><td> ©</td><td> ©</td><td> d</td><td> CM</td><td> CM</td><td> d</td><td> CM</td><td> d</td>

<td colspan="2"> Λ ί C CÛ|</td><td> —</td><td> ......</td><td> —</td><td> —</td><td> .......</td><td></td><td></td><td> j i</td><td> 1</td><td> —</td><td></td><td> -....4</td><td></td><td></td><td></td><td></td><td></td><td></td><td> ......</td><td> i</td><td></td><td></td><td></td><td> 6WM</td><td></td><td></td>

<td> Co-expressed Gene ............</td><td> « o X</td><td> SKA3</td><td> SPAG5</td><td> CiT____</td><td> Kana</td><td> tn Z X Q &lt;J</td><td> CENPF_______</td><td> ; ME1K ____________</td><td> z z &lt;</td><td> 8Ϊ8Π8 !</td><td> ! U8E2C</td><td> ss&lt;œ i</td><td> &lt; Q fN X</td><td> DEPDC1.B</td><td> DTL</td><td> \ UBE2T________</td><td> NCAPG</td><td> j PBK_______</td><td> ! 0ÎAPH3</td><td> 2 X</td><td> j FOXM1________________</td><td> ! RRM2</td><td> \ SGO11_____</td><td> Ûv</td><td> EVN03</td><td> TXG^ i</td><td> | z</td>

<td> StacklD i</td><td> rM</td><td> : IN</td><td> CM</td><td> CM</td><td></td><td> CM</td><td> 04</td><td> 04</td><td> CM</td><td> M</td><td> CM</td><td> CM</td><td> CM</td><td> fM</td><td> IN</td><td> 04</td><td> ΓΗ</td><td> CM</td><td> fN</td><td> Pm</td><td> ΓΜ</td><td> ΓΜ</td><td> ΓΜ</td><td> CM</td><td> CM</td><td> M</td><td> ni</td>

<td></td><td></td><td></td><td></td><td> www</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> Seeding Gene</td><td> MYBL2</td><td> MYBL2</td><td> MYBL2</td><td> MYBL2</td><td> MYBL2</td><td> MYBL2</td><td> MYBL2</td><td> if 0) &gt; S</td><td> MYBL2</td><td> MYBL2</td><td> 1 MYBL2</td><td> « s</td><td> MY8L2</td><td> ¢9 5</td><td> 1 MYB12</td><td> 21 CÛ 5</td><td> i MYBL2</td><td> 1 MYBL2</td><td> i MYBL2</td><td> ί MYB12</td><td> MYBL2</td><td> j ΜΥΒ12</td><td> |MYBL2</td><td> I MYSL2</td><td> £0 S</td><td></td><td></td>

<td> 4* ?</td><td> eO $</td><td> 4851 1</td><td> ***** *4* ce</td><td> 4847 ί</td><td> σ o §</td><td> 4720 ΐ</td><td> 4720</td><td> 4717</td><td> 4713 ί</td><td> a w</td><td> 4661 j</td><td> 4629 I</td><td> σ fC</td><td> 4360J</td><td> © HI eo</td><td> 4308</td><td> 4283</td><td> 4276</td><td> 4111</td><td> 4107</td><td> 3984</td><td> 3977</td><td> 3973</td><td> 8986</td><td> 3833</td><td></td><td></td>

<td> w Λ O £</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> Coexpressed i Gene______ j</td><td> m ¢0 z u. ω</td><td> MYBPC2 ]</td><td> FUT6 1</td><td> CDH15</td><td> HAL ____I</td><td> PGA3 ________i</td><td> PGA4</td><td> C17orfS3</td><td> 3 O O s 3</td><td> OTOG</td><td> H8G !</td><td> § d M d 2 Φ a.</td><td> 1 ONAJB13_____</td><td> I TK1 ______</td><td> 5 Ç Q Ch Q</td><td> ) RH8DL1</td><td> MUC5B</td><td> $</td><td> &lt; G «</td><td> ί APOB48R</td><td> i iqco__________</td><td> ί FUTS</td><td> [~AIFM3</td><td> I LOC390595</td><td> CD en a. ΰ</td><td></td><td> :</td>

<td> StadklO</td><td> d</td><td></td><td> d</td><td> d</td><td> d</td><td> rt</td><td> rd</td><td> ri</td><td> r</td><td> d</td><td> «Η</td><td></td><td> ci</td><td></td><td> d</td><td> ci</td><td></td><td> L·</td><td> d</td><td> f-l</td><td></td><td> d</td><td> d</td><td> d</td><td> d</td><td></td><td> L</td>

<td> Seeding Gene</td><td> CDC20</td><td> o G Q W</td><td> O G a u</td><td> C0C20</td><td> CDC20 I</td><td> o G o o</td><td> C0C20</td><td> i o !g t^υ</td><td> ............... 1 CDC20</td><td> C0C20</td><td> o tv u G U</td><td> C 0 c u</td><td> — CDC20</td><td> o s u</td><td> CDC20</td><td> o ΰ G U</td><td> CDC20 1</td><td> \ CDC20 j</td><td> CDC20 I</td><td> i CDC20</td><td> CDC20</td><td> o a G U</td><td> [ COC20</td><td> i CDC20</td><td></td><td></td><td> i</td>

<td> Probe Wt</td><td> 33401</td><td> 3317</td><td> s m</td><td> 3311 I</td><td> 3219 !</td><td> xr Gt d m</td><td> 3109!</td><td> 2984 i</td><td> 2936</td><td> 2809 ί</td><td> o tn η» CM</td><td> 2653 !</td><td> 2641</td><td> 2534</td><td> 2499</td><td> 2497</td><td></td><td> 2313</td><td> 2258</td><td> 2232</td><td> 2199</td><td> 2174</td><td> 2130</td><td> O 00 © ΓΜ</td><td></td><td></td><td></td>

<td> Coexpressed Gene ;</td><td> ARHGEF19 Î</td><td> CYP4A22 1</td><td> i &lt; U</td><td> SCNN10 I</td><td> FRMO1 I</td><td> FAM179A ί</td><td> 3 At □ Q Z</td><td> Q s</td><td> OD24 Î</td><td> A8CC12 !</td><td> d u. CL Q</td><td> CDH24 ί</td><td> smsxooi</td><td> KIF21B</td><td> SEMA5S \</td><td> PSORS1C2 !</td><td> FCRL4 ί</td><td> L...................</td><td> TRAIP i</td><td> OC d u:</td><td> ί PC s y &lt;Λ</td><td> CBX2</td><td> i CDCA5 !</td><td> i DUSP5P ;</td><td> 5</td><td></td><td> ί î</td>

<td> | GPP83S I ' i</td><td> 1</td><td></td><td> wi</td><td> d</td><td> ci</td><td> d</td><td> fl</td><td> Ή</td><td> d</td><td> j d</td><td></td><td> r·</td><td></td><td></td><td> {</td><td></td><td> μ</td><td></td><td> * d</td><td> i</td><td> d</td><td> d</td><td> 1.7</td><td> et</td><td></td><td></td><td></td>

CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

Applicant Ref. ¢9042. g-304 / GHM152PC

<td> Seeding Gene</td><td> “1 to in xr a a « o</td><td> [ GADD45B |</td><td> 1 GADD45B |</td><td> 1 GADD45B ]</td><td colspan="2"> , GADD45B '----[ GADD45B</td><td> GADD45B|</td><td> 1 GADD45B j</td><td colspan="2"> ! GADD45B_ [GADD4SB</td><td> Φ a. N</td><td> Φ a. LU NI</td><td> Γ oëdïz]</td><td> Φ en U. N</td><td> Φ m eu u Ni</td><td> Mr en CL N</td><td> i m fc</td><td> s N</td><td colspan="2"> i A ΦΪ Φ £L; LL: LU N? NI</td><td colspan="2"> | ZFP36 |zFP36 J</td><td> | ZFP36 i</td><td> [ ZFP36_____j</td>

<td> -------4 j ProbeWt</td><td> e·</td><td></td><td></td><td></td><td> Cl:</td><td> ...... Ni ί</td><td> IN</td><td> ci</td><td colspan="2"> &lt;-11 »4</td><td> c4</td><td> *4</td><td> H</td><td> &lt;4</td><td> χ4</td><td> t4</td><td> ! 53 j</td><td> 1 49 j</td><td> fN</td><td> φ (N</td><td colspan="2"> 24 24</td><td> ______20</td><td> L___18.J</td>

<td> Γ Coexpressed Ί StackiD ! Gene________</td><td> R . ί ZFP36 |</td><td> | 3 i SOCS3 j</td><td> | 3_______[rhob j</td><td> o s 3 X SC en</td><td> ί 3 fos</td><td> i 3 j FOSI.2 j</td><td> R | BTG2</td><td> en « 2 Z</td><td colspan="2"> R__FOSB______ [ 3 ÊRF1</td><td> N 10 O U</td><td> LL w QQ X</td><td> 1 1 j BHIHE40</td><td> [ 2________1 H REGF J</td><td> [2 | NR4A3 1</td><td> [ 2 j BH1HE4O</td><td> R i CSRNPl</td><td> tt en CL LU NI M</td><td> ca Z¹3 «7</td><td> R I fos</td><td colspan="2"> 3______1 BHLHE40 ί 3 1 BTG2 i</td><td> * ί H_____pose !</td><td> [ 3 \ NR4A3</td>

<td> Coexpressed j | Seeding Gene j ProbeWt ί Gene</td><td> FOS j 14 | FOS_________1</td><td> BTG2 j 14 I FOS________|</td><td> CSRNP1 | 13 j FOS _______ί</td><td> ZFP36 | 13 j FOS 1</td><td> JUNB ί 9 MOS |</td><td> £ SOd 1 L £Vt?HN I ί ! . ........:______</td><td> FOSE i 7 j FOS_________l</td><td> SiKl i 6 I FOS__________\</td><td> [ BHLHE40 j_________&amp; FOS \</td><td> i RHOB 1 s ] FOS j</td><td> i TIPARP_________î___________5 i FOS 1</td><td> i KLF6 _______ ί S Î FOS___________1</td><td> i MCL1 i 5 ί FOS i</td><td> O «t H « s z</td><td> 1 EGR1 \ 4 j FOS ί</td><td> I NR4A2 \ 4 ; FOS j</td><td> GADD45B J_____ 3 MOS i</td><td> ί SOCS3 j 2 î FOS</td><td> 1 NFKBIZ________j ¹ ï ^FOS</td><td rowspan="2"> 1 2 j FOS 1 24 ί FOS__________</td><td rowspan="2"> | 2__1 FOSB |_________22 ί FOS</td><td rowspan="2"> R 1 EGRl !______ 20 ] FOS</td><td rowspan="2"> 1 2 [ NR4A1________j 19 1 FOS_________</td><td rowspan="2"> 2_______ BTG2_______j________1S ] FOS____</td>

<td rowspan="2"> Coexpressed i \ Seeding 1 Gene i ProbeWt \ Gene | StackiD</td><td rowspan="2"> NNT 1 I OUSP1 1 1 j</td><td rowspan="2"> RNF180 ί 1 I DUSPl | 1 i</td><td rowspan="2"> PCDH18 1 î DUSPl | 1 i</td><td rowspan="2"> RNF180 1 ; DUSPl 1 1 j</td><td rowspan="2"> DUSPl I 1 ; DUSPl__________| 1 |</td><td colspan="2"></td><td> Ή</td><td></td><td> 4</td><td colspan="2"> î «4? ri</td><td></td><td> &lt;4</td><td> *4</td><td> *4</td><td> *4</td><td> r4</td><td> r*t</td>

<td> PCDH18 t \ DUSPl J</td><td> ACTE î 1 i DUSPl !</td><td> RHOB 1 ί DUSPl ]</td><td> DUSPl \ 1 j DUSPl j</td><td> ! ACTE ; i î DUSPl</td><td> i DUSPl ί 1 ; DUSPl 1</td><td> CRTAP i ί ί DUSPl ]</td><td> I RNF1SO 1 1 ί DUSPl j</td><td> । ïdsna i ï \ td$na |</td><td> I CRTAP 1 1 i DUSPl 1</td><td> PAM \ 1 \ DUSPl ]</td><td> I DUSPl ί 8 \ DUSPl [</td><td> I NR4A1 1 7 \ DUSPl 1</td><td> I FOS ί 7 1 DUSPl</td><td> 1 EGR1 5 ί DUSPl {</td><td> [ BTG2 | S l DUSPl__________1</td><td> FOSB 1 5 | DUSPl j</td><td> ί JUN 4 j DUSPl</td><td rowspan="2"> [β î NR4A2 [ 3 DUSPl</td>

<td> QPP^S j</td><td> &lt;•4</td><td></td><td> — ; *4</td><td> ί : N</td><td> ni</td><td> ni</td><td></td><td colspan="2"> .t : Mî M</td><td></td><td> «t</td><td> *0-</td><td> iC</td><td> 10</td><td> (Λ</td><td> 1Λ</td><td colspan="2"> 1 us ; tt</td><td colspan="2"> tti φ</td><td> tt</td><td colspan="2"> T : tt: tt 1.</td>

CA 02863040 2014-07-28

WO 2013/116144

PCT/US2013/023409

Applicant Ref. 09042.8-304 ! GHb0S2«:F

<td rowspan="2"> ! ] Seeding ! ProbeWt | Gene______j</td><td> i ZFP36 j</td><td> LD m &amp; IX. d</td><td> ZFP36</td><td> ZFP36</td><td> 10 2: u.</td><td> | ZFP36 j</td><td> ZFP36_____1</td><td> ZFP3C</td><td> ZFP36__</td><td> ZFP36</td><td> ! «sî m? ai n|</td><td> ZFP36</td><td> | ZFP36 î</td><td> LO m a| nÎ</td><td> | ZFP36</td><td> « CO &amp;</td><td> ZFP36____</td><td> S0 CO au» Si</td><td> m· u. :</td><td> Γ 9ediz j</td><td> SO co CL ft</td><td> ro £L N</td><td rowspan="2"> __________4 | ZFP36</td><td rowspan="4"> 1 3 _____j SRF_______________3 ZFP36 j</td><td rowspan="4"> 1 3 j ERRFIj _________2 j ZFP36 |</td><td rowspan="4"> Φ co X N N 1A N «Λ1 y (A (O</td><td rowspan="2"> I__________2 1 ZFP36 j</td>

<td> 90</td><td> y</td><td> JO</td><td> m;</td><td> Mt rW</td><td> ©</td><td> ©</td><td> eûi</td><td> GÛ</td><td> 00</td><td></td><td> t</td><td> s-</td><td> S* :</td><td> M5</td><td></td><td> LD</td><td> iA</td><td rowspan="3"> S 1 EB3Î j « 1</td><td rowspan="3"> 1 3 ί IER2__________ i . 5</td><td rowspan="2"> j MAFF_____________4</td><td> xr</td>

<td> S Coexpressed I Gene I</td><td> SOCS3 j</td><td> EG Ri j</td><td> I RHOB ]</td><td> O u.</td><td> &lt; it « z</td><td> GADD45B |</td><td> 1 MYADM i</td><td> 1 KtF6</td><td> | CYR6L</td><td> ί EGR3</td><td> \ EMP1</td><td rowspan="2"> _3__ | tMNA______</td><td> i TIPARP____________</td><td rowspan="2"> ΐ3 ; NR4A2</td><td rowspan="2"> row i s i</td><td rowspan="2"> i 3 SI Kl__</td><td rowspan="2"> ί 3______I ATF3__________</td><td rowspan="2"> | 3 i CEBPD</td><td> j IRFl___</td><td rowspan="2"> | 3 1 PH Fl 2 2</td><td rowspan="2"> 5 K si O U ©</td>

<td> StackID</td><td> *0</td><td> &lt;n</td><td> ΓΛ</td><td></td><td></td><td> en</td><td> en</td><td> m</td><td> m</td><td></td><td> m</td><td> m</td><td colspan="2"> t coi co</td>

<td rowspan="2"> Coexpressed I Seeding Gene ___; ProbeWt Gene______</td><td rowspan="2"> ZFP36_____ ί 12 i FOS</td><td rowspan="2"> CSRNP1 | 11J FOS________I</td><td rowspan="2"> CYR61 I 10 1 FOS__|</td><td rowspan="2"> DUSPI 1 _______8 j FOS |</td><td rowspan="2"> ATF3 i__________8 j FOS j</td><td rowspan="2"> 8 LU d QC LU</td><td rowspan="2"> RHOB________i 6 ί FOS 1</td><td rowspan="2"> TIPARP î__________6 1 FOS_________I</td><td rowspan="2"> 8 L£? B ec Z</td><td> SO3 i 9</td><td> ί SO4 i 9</td><td> ___________5 î FOS 1</td><td> 1 4 i FOS__________</td><td> __________3 î FOS</td><td> ! 2 1 FOS j</td><td> «A O u. d</td><td rowspan="2"> i KLF4 i___________2 ] FOS J</td><td> ί ² 1 ^pos 1</td><td> ______i Iras î</td><td> ί 7 1 GADD45B</td><td> _________7 ] GADD45B |</td><td> 7 | GADD4SB |</td><td> ί________4 1 GADD4SB__</td><td rowspan="2"> [ F0SL2 j________ 3 [ GADD45B </td><td rowspan="2"> j GADD45B |________3 | GADD4SB</td><td rowspan="2"> Λ in s a « «&gt; σΐ d d Z oc</td><td rowspan="2"> ί KLF10 | 3 ! GADD4SB ?</td>

<td> z ©</td><td> JUNB ]</td><td> EGR3 ]</td><td> : NR4A3 1</td><td> £</td><td> PPP1R1SA</td><td> ai Q Q IU Z</td><td> ZU93</td><td> 3 u 2</td><td> 1 EM Pl</td><td> o U! X ί â</td><td> 1 SOCS3____</td><td> ί NR4A3</td>

<td> StackID</td><td> d</td><td rowspan="2"> CYR61 3 I DUSPI 12 j</td><td rowspan="2"> ATF3 2 ’ DUSPI | 2</td><td> Cl</td><td> d</td><td> d</td><td> d</td><td> d</td><td> d</td><td> d</td><td> d</td><td> d</td><td> N</td><td> d</td><td> d</td><td> d</td><td> d</td><td> d</td><td> d</td><td> ri</td><td> ri</td><td rowspan="2"> --------------------------------------------------------j------------------------------------------------------------------------------------------------------------------ NR4A1 \ 25 1 EGRl I 1</td><td rowspan="2"> FOSB ί 23 i EGRl Γ1 _Z</td><td> ri</td><td> ri</td><td> «H</td><td> «*4</td>

<td> Coexpressed i Î Seeding I Gene 1 ProbeWt i Gene s</td><td> TIPARP 1 3 î DUSPi</td><td> RHOB 2 i DUSPI !</td><td> &amp; □ Q i-..... !Ί σι Q α w Z</td><td> si ÎA g 3 u 2</td><td> RA501 ί 1 ! DUSPI |</td><td> JUNB 1 1 \ EGRl</td><td> S u CL a: « CL</td><td> BTG2 1 1 \ EGR1</td><td> JUNB 1 1 EGRl</td><td> I TB93 1 T________1 ZD18</td><td> EGRl i 1 EGRl j</td><td> f ÏH93 1 ï J____________WT&lt;_</td><td> FOSB 1 1 1 EGRl |</td><td> EGRl ; 1 ί EGRl |</td><td rowspan="2"> ! 4 I FOSB \ .11 EGRl 1</td><td> CSRNPl \ 1 \ EGRl 1</td><td> EGRl ί 1 l EGRl Ί</td><td> EGRl î 3S î EGRl 1</td><td> FOS i 30 | EGRl 1</td><td> 5 ω 1X1 d d d k :</td><td> CYR61 \ 20 \ EGRl</td><td> ZFP36 1S \ EGRl</td><td> CSRNPl j 17 j EGRl</td>

<td> StackID ;</td><td></td><td> ld</td><td> LO</td><td> LD</td><td> LD</td><td> LD</td><td> î i LD</td><td> î i</td><td> «H</td><td> t-4</td><td> d</td><td> d</td><td> d</td><td> : m 1......</td><td> ΓΟ</td><td> CO</td><td> &lt;T</td><td> i «t</td><td> ιΑ</td><td> ï tA</td><td> iA</td><td> «Λ</td><td> j 1</td><td></td><td></td><td> ΙΛ</td>

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App) leant itef. 09042.8-304 ! GHI-052PCT

<td> bd c « * * £</td><td> ID g N</td><td> ZFP36</td><td></td><td> J</td><td> .....T</td><td></td><td></td><td> I j</td><td></td><td> t</td><td></td><td> î</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> ProbeWt 1</td><td> ri</td><td> rt</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td> l t</td><td></td><td> 1</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td>

<td> • Coex pressed StackiD j Gene_______</td><td> A! Q£ 19 UJ m</td><td> 5 : m</td><td></td><td></td><td></td><td></td><td></td><td></td><td> —</td><td></td><td></td><td> —</td><td></td><td> !</td><td> ......</td><td> ......</td><td> .....</td><td></td><td></td>

<td> .......’auas ___guipaas</td><td> CÛ UT s a &lt; 0</td><td> œ in Û C 4 *</td><td> co Ml &lt;? § 0</td><td> CÛ s ds § 0</td><td> Cû 3 CS Q &lt; 0</td><td> co © kt a &lt; 0</td><td> ce © Û O « 0</td><td> as © 4 Cs CS &lt; 0</td><td> SO s o 4 0</td><td> cc MT S § 0</td><td> ai © a Q «t 0</td><td rowspan="2"> i 2 \ GADD4SB |</td><td> sa MT o û &lt; 0</td><td> cO © •ίΟ ώ &lt;ί 0</td><td> cû 3 Q CS 4 0</td><td> | GADD4SB__</td><td> aû $ a Cs &lt; 0</td><td> SJ uT M? O, O &lt; 0</td><td> i GADO45B</td>

<td> ProbeWt ί</td><td> tn</td><td> rt</td><td></td><td></td><td> «N</td><td> CM •</td><td> CM</td><td> CM</td><td> Ci</td><td> CM</td><td rowspan="2"> CM ..HW « 0 W</td><td> IN</td><td> rt</td><td> ri</td><td></td><td></td><td> 4</td><td> «t</td>

<td> Coexpressed ; Gene________|</td><td> ri Z « ΰ</td><td> 3 g V)</td><td> tn &lt;K u. N</td><td> CÛ ΙΛ Ο</td><td> S or z</td><td> ut g</td><td> S3 UT O □ &lt; &lt;9</td><td> rt 1? es</td><td> en i£ Z</td><td> 05 Z □</td><td> &amp; z UT U</td><td> S M» N</td><td> aû O X ÛS</td><td> m es □ LU</td><td> en LL 3</td><td> ω WT â CS &lt; a</td><td> 03 z 3 T</td><td> £ z « u</td>

<td> StackiD j</td><td> ri</td><td> ri</td><td> ri</td><td> CM</td><td> CM</td><td> cm</td><td> ΓΜ</td><td> CM</td><td></td><td> rt</td><td> rt</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> CM</td><td> &lt;n</td><td> ©</td><td> m</td>

<td> Coexpressed 1 ί Seeding 1 Gene i ProbeWt I Gene</td><td> NR4A3 i 13 1 EGR1 !</td><td> EGR3 1 13 EGR1</td><td> KI.F6 1 12 EGR1 |</td><td> RHOB : 11 EGR1</td><td> 2 S * &amp; v&gt; î □ î °</td><td> ATF3 ί 9 ΐ EGR1 i</td><td> s g &lt;3* i Z 0 rt</td><td> TIPARP l S 5 EGR1</td><td> Γ NFKSIZ \ 7 ] EGR1</td><td> NR4A2 \ 7 ί EGR1 j</td><td> 2 0 LU CO Z □ rt</td><td> ί EER2 ! 7 ί EGR1</td><td> MCI! 4 ί EGR1</td><td> i KI.F4 l 4 j EGR1</td><td> i EGR2 \ 4 î EGR1</td><td> NEDD9 2 EGR1</td><td> ÎSRF S 2 | EGR1</td><td> TM93 j T ; SSVaGVD</td><td> IRiBl 1 î EGR1</td>

<td> a ? 3 ©</td><td> «&gt;</td><td> m</td><td></td><td> ί I ΐ ©</td><td> 1</td><td> m</td><td> ut</td><td> UT</td><td> i 41</td><td> UT</td><td> ï m</td><td> t j l·</td><td> i</td><td> MT</td><td> i { ! t : MT</td><td> MT</td><td> î UT 1</td><td> WT</td><td> UT </td>

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Example 4; Prospective Validation Study of RS27

Study Design and Statistical Methods

[00175] The algorithm RS27 in Table 4 was tested in a prospective clinical validation study that included 395 evaluable patients who had surgery for their prostate cancer between 1997 and 2010 at the University of California, San Francisco (UCSF). The patients had Low or Intermediate risk (by CAPRA) for clinically localized prostate cancer who might have been reasonable candidates for active surveillance but underwent RP at UCSF within 6 months of the diagnosis of prostate cancer by biopsy. No randomization for patient selection was performed. For each patient, prostate biopsy samples from one fixed, paraffin-embedded tissue (FPET) block containing one or more tumor-containing needle cores was evaluated. [00176] To investigate if there is a significant relationship between RS27 or any component of RS27 and adverse pathology at RP, multivariable and univariable multinomial logistic regression models were used and p-values from likelihood-ratio (LR) tests of the null hypothesis that the odds ratio (OR) is one were reported. The multinomial logistic model was also used to calculate estimates with 95% confidence intervals of die probability of high’ grade or non-organ confined disease. To evaluate the relationship between RS27, baseline covariates, and combinations of these factors with high grade or non-organ confined disease, multivariable and univariable binary logistic regression models were used and p-vaiues from likelihood-ratio tests of the null hypothesis that the odds ratio (OR) is one were reported.

[00177] Hie primary endpoint was formulated as follows:

Table 12: Clinical Endpoint - RP Grade and Stage

<td> RP Gleason Score</td><td> Pathologic T2 Stage</td><td> Pathologic T3 Stage</td><td> j</td>

<td> &lt;3+3</td><td> 1</td><td> 2</td><td></td>

<td> — -</td><td> 3</td><td> 1</td><td> i .......i</td>

<td> Major pattern 4 or minor pattern 5, or</td><td> 5</td><td> 6</td><td> ? 1</td>

<td> tertiary pattern 5</td><td></td><td></td><td> ____J</td>

where Gleason Score &lt;3+3 and pT2 (denoted “1”) is the reference category and all other categories (2-6) are compared to the reference category.

[00178] Cell combinations of Table 12 evaluated in binary logistic regression models include the following:

Cells 2,4,6 vs. 1,3,5: Non-organ-confmeddisease

Cells 5,6 vs. 1,2,3,4; High-grade disease

Ceils 2,4,5, 6 vs. I and 3: High-grade or non-organ-confined disease

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RS27 Algorithm

[1)0179] RS27 on a scale from 0 to 100 was derived from reference-normalized gene expression measurements as follows.

[00180] Unsealed RS27 (RS27u) was defined as in Table 4:

[00181] RS27u = 0.735*ECM (Stromal Response) group -0.368*Migration (Cellular

Organization) group -0.352*PSA (Androgen) group +0.095*Proliferation (TPX2)

[00182] Where:

[00183] ECM (Stromal Response) group score = 0.527*BGN + 0.457*COL1 Al +

0.156*SFRP4

[Ô0184J Migration (Cellular Organization) group score “ 0.163*FLNC * 0.504*GSN +

0.421*TPM2 + 0.394*GSTM2

[00185] PSA (Androgen) group score = 0.634*FAM13C + 1.079*KLK2 + O.642*AZGP1 + 0.997*SRD5A2 Thresh

[00186] Proliferation (TPX2) score - TPX2 Thresh

[001871 where the tnresholded gene scores for SRD5A2 and TPX2 are calculated as follows:

(5.5 ifSRD5A2&lt;5.5

[00188] SRD5A2 Thresh = &lt;

ISRD5/X2 otherwise

[00189] TPX2 Thresh = '5.0

TPX2 ifTPX2&lt;5.0 otherwise

[00190] RS27u is then rescaled to be between 0 and 100 as follows:

I 0 if 13.4 χ (RS27u+lO.5)&lt;0

[00191] RS27(scaled)“^ 13.4 x (RS27u+10.5) if 0 &lt; 13.4 x (RS27u+10.5) &lt; 100

I 100 if 13.4 x (RS27u+l 0.5) &gt; 100

[00192] Patients were classified into low, intermediate, and high RS27 groups using prespecified cut-points defined in Table 13 below. These cut-points defined foe boundaries between low and intermediate RS27 groups and between intermediate and high RS27 groups. The cutpoints were derived from the discovery' study with the intent of identifying substantial proportions of patients who on average had clinically meaningful low or high risk of adverse pathology. The RS27 was rounded to the nearest integer before the cut-points defining the RS27 grouops were applied.

Table 13 ] ~ ~ score^- ” ””i

Low Less than 16 [

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High

Greater than or equal to 16 and less than 30

Greater than or equal to 30

Assay Methods (00193} Paraffin from the samples was removed with Shandon Xylene substitute (Thermo Scientific, Kalamazoo, Ml). Nucleic acids were isolated using the Agencourt® FormaPure® XP kit (Beckman Coulter, Beverly, MA).

[00194] The amount of RNA was determined using the Quant-iT™ RiboGreen® RNA Assay kit (Invitrogen™, Carlsbad, CA). Quantitated RNA was convereted to complementary DNA using the Omniscript® RT kit (Qiagen. Valencia, CA) and combined with the reverse primers for the 12 genes of RS27 and 5 normalization genes (ARFL ATP5E, CLTC, GPS1, PGK1) as shown in Table A. The reaction was incubated at 37^ for 60 minutes and then inactivated at 93°€ for 5 minutes.

[00195] The eDNA was preampiified using a custom TaqMan® PreAmp Master Mix made for Genomic Health, Inc. by Life Technologies (Carlsbad, CA) and the forward and reverseprimers for all targets as shown in Table A. The reaction was placed in a thermocycler (DNA Engine® PTC 2ÔÔG, Bio-Rad, Hercules, CA) and incubated under the following conditions: A) 95°C for 15 sec; B) 60°C for 4 min: C) 95°C for 15 sec; and D) steps B and C were repeated 8 times. The amplified product was then mixed with the forward and reverse primers and probes for each of foe targets as shown in Table A and the QuantiTect® Primer Assay master mix (Qiagen, Valencia, CA) and amplified for 45 cycles in a LightCycler® 480 (Roche Applied Science, Indianapolis, IN). The level of expression was calculated using the crossing-point (Cp) method.

Results

[00196] RS27 significantly predicted for adverse pathology, non-organ-confmed disease, high-grade disease, and high-grade or non-organ-confined disease, and adds value beyond biopsy Gleason Score as shown in Tables 14,15,16, and 17, respectively.

Table 14 Prediction of Adverse Pathology

<td></td><td></td><td> « I? »</td><td> w β</td><td> NW</td><td></td><td></td><td></td>

<td colspan="2"> RS27 Score</td><td colspan="3"> 19.31</td><td colspan="2"></td><td> 0.002</td>

<td colspan="2"> Central Biopsy Gleason Score 3+4 vs 3+3</td><td colspan="3"> 32.86</td><td colspan="2"> 5</td><td> &lt;0.001</td>

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Results obtained from the multivariable multinomial logistic model for cells 2.3,4,5, and 6 vs 1 in Table 12.

DF - degrees of freedom

Table 15 Prediction of Non-organ-confined disease

<td></td><td></td><td></td><td></td><td></td><td> w</td><td colspan="2"> ®ί·</td><td> β ||||</td>

<td colspan="2"></td><td></td><td></td><td></td><td colspan="2"> .5:¾¾¾¾¾.¾¾¾¾½. V Ml,</td><td> x- V</td><td> “-X</td>

<td colspan="2"> |RS27</td><td> 2.20</td><td> (1.46,3.3 i)</td><td> i</td><td colspan="2"> 14.44</td><td colspan="2"> &lt;0.001</td>

<td colspan="2"></td><td></td><td> X - -- . , s</td><td></td><td colspan="2"></td><td colspan="2"></td>

<td></td><td> RS27......................</td><td> 1.93</td><td> (1.25,2.96)</td><td> I</td><td colspan="2"> 8.97</td><td colspan="2"> 0.003</td>

<td></td><td> Central Biopsy Gleason Score 34 vs 3+3</td><td> Ï.79</td><td> (1.04,3.10)</td><td> l</td><td colspan="2"> 4.23</td><td colspan="2"> 0.040</td>

Results obtained from univariable and multivariable binary logistic regression models for cells 2,4.6 vs. 1,3,5 in Table 12

Odds ratio for RS27 was per 20 unit increase

Table 16 Prediction of high-grade disease

<td></td><td> yjaWttjiSÇM ySSwfJ^ — /:.2...: .ύ.*.y a.?.</td><td> MM ·· ·· Λ. .. .....................</td><td> »</td><td> 81¾¾¾ η· ·'</td><td> ι |Ι|||® ·</td>

<td> RS27</td><td> 2.48</td><td> (1.60,3.85)</td><td> 1</td><td> 16,78</td><td> &lt;0.001</td>

<td></td><td></td><td> X ·1 ίί ' ί S 1</td><td></td><td></td><td> ί kl· 3 · « l· j Hi ‘ Η *&gt;»*&gt;»</td>

<td> RS27</td><td> 2.32</td><td> (1.46,3.67)</td><td> 1</td><td> 12.92</td><td> &lt;0.00!</td>

<td> Central Biopsy Gleason Score 3+-4 vs 3+3</td><td> 1.36</td><td> (0.75,2.47)</td><td> 1</td><td> 0.98</td><td> 0.322</td>

Results obtained from univariable and multivariable binary' logistic regression models for cells 5,6 vs. 1-4 in Table 12

Odds ratio for RS27 was per 20 unit increase

Table 17 Prediction of high-grade or non-organ-confined disease

<td> ΙΜΜ|ΙΒ8^ 8^1¾¾¾¾¾¾^^</td><td></td><td colspan="2"> SliM sSS?S§g$S$gÿg^^^</td><td></td><td> sasKmaaaw O®</td>

<td></td><td></td><td></td><td> ' %</td><td></td><td></td>

<td> |rS27</td><td> 2.23</td><td> (1.52,3.27)</td><td> 1 A</td><td> Î7.77</td><td> &lt;o.ooi</td>

<td></td><td> .. , .. J. ,&gt;..._v^&gt;..</td><td></td><td></td><td> ’ T* ï '” ’</td><td></td>

<td> RS27</td><td> 1,93</td><td> &lt;1.30,2.88)</td><td> ]</td><td> 10.70</td><td> 0.001</td>

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<td> i Central Biopsy Gleason | Score 3 +4 vs 3+3</td><td> 1.94</td><td> (1.17,3.21)</td><td> 1</td><td> 6.45</td>

0.011 ♦Results obtained from univariable and multivariable binary logistic regression models for ceils 2,4,5,6 vs. 1,3 in Table 12

Odds ratio for RS 17 was per 20 unit increase

[00197] In addition, RS27 predicted adverse pathology beyond conventional clinicaVpathology treatment factors as shown in Table 18.

Table 18 Prediction of Adverse Pathology Beyond Conventional CiinicaVPathology Treatment Factors

<td></td><td></td><td></td><td></td>

<td> RS27</td><td> 21.46</td><td> 5</td><td> &lt;0.001</td>

<td> Original Biopsy Gleason Score</td><td> 22.77</td><td> 5</td><td> &lt;0.001</td>

<td></td><td></td><td></td><td></td>

<td> RS27</td><td> 19.31</td><td> 5</td><td> 0.002</td>

<td> Central Biopsy Gleason Score</td><td> 32.86</td><td> 5</td><td> &lt;0.001</td>

<td> —-</td><td> 30.09 ' ”</td><td> 5 „ ,</td><td> &lt;0.00!</td>

<td> ClinT2 v.Tl</td><td> 11.94</td><td> 5</td><td> 0.036</td>

<td></td><td></td><td></td><td></td>

<td> RS27</td><td> 30.17</td><td> 5</td><td> &lt;0.001</td>

<td> Baseline PSA (ng/ml) &lt;10 v. &gt;=i0</td><td> 10.44</td><td> 5</td><td> 0.064</td>

<td></td><td></td><td></td><td></td>

<td> RS27</td><td> 30.75</td><td> 5</td><td> &lt;0.001</td>

<td> Continuous PSA</td><td> 15.17</td><td> 5</td><td> 0.010</td>

<td></td><td></td><td></td><td></td>

<td> RS27</td><td> 26.36</td><td> 5</td><td> &lt;0.001</td>

<td> Age</td><td> 19.05</td><td> 5</td><td> 0.002</td>

<td></td><td></td><td></td><td></td>

<td> RS27</td><td> 29.20</td><td> 5</td><td> &lt;0.001</td>

<td> Pct Core Positive</td><td></td><td> 5</td><td> 0447</td>

[00198] When added to conventional clinical/pathology tools such as CAPRA, RS27 further refined the risk of high grade or non-organ-confined disease. Using CAPRA alone, 5% of patients were identified as having greater than 85% probability of being free from high-grade 92

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PCT/US2013/023409 or non-organ-confined disease compared to 22% of patients identified of being free from high-grade or non-organ-confmed disease using RS27 in addition to CAPRA (Figure 8). [00199] When added to conventional clmical/pathology tools such as AUA (D’Amico et al, JAMA 280:969-974,1998), RS27 further refined the risk of high grade or non-organ-confined disease. As shown in Figure 9, using AUA alone, 0% of patients are identified as having greater than 80% probability of being free from high-grade or non-organ-confined disease compared to 27% of patients identified of being free from high-grade or non-organ-confined disease using GPS in addition to AUA.

[00200] individual genes and gene groups of RS27 were also associated with adverse pathology, high-grade disease, non-organ-confined disease, and high-grade or non-organconfined disease, in univariable analyses as shown in Tables 19,20,21, and 22, respectively.

Table 19 Association of Genes and Gene Groups with Adverse Pathology, Univariable

Analyses

<td> unes am ant</td><td></td><td> MM lllBM</td><td></td>

<td> BGN</td><td> 7,11</td><td> 5</td><td> 0,213</td>

<td> COIJAt</td><td> 7.88</td><td> 5</td><td> 0.163</td>

<td> SFRP4</td><td> 8.87</td><td> 5</td><td> 0.114</td>

<td> FLNC</td><td> 12.26</td><td> 5</td><td> 0.031</td>

<td> GSN</td><td> 5.73</td><td> 5</td><td> 0.333</td>

<td> GSTM2</td><td> 1.84</td><td> 5</td><td> 0.870</td>

<td> TPM2 AZGP1</td><td> 18.33 22.87</td><td> (Λ j Ul</td><td> 0.003 &lt;0,001</td>

<td> KLK2</td><td> 5.97</td><td> 5</td><td> 0.309</td>

<td> FAM13C1</td><td> 21.55</td><td> 5</td><td> &lt;9.001</td>

<td> SRD5A2</td><td> 9.10</td><td> 5</td><td> 0.105</td>

<td> SRD5A2 Thresholded</td><td> 9.25</td><td> 5</td><td> 0.099</td>

<td> TPX2</td><td> 14.26</td><td> 5</td><td> 0.014</td>

<td> TPX2 Thresholded</td><td> 23.34</td><td> 5</td><td> &lt;0.001</td>

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<td> Ref Gene Average</td><td> 3.27</td><td> S</td><td> 0.659</td>

<td> Stromal Group Score</td><td> 9.84</td><td> 5</td><td> 0.080</td>

<td> Cellular Organization Group Score</td><td> 8.04</td><td> 5</td><td> 0.154</td>

<td> Androgen Group Score</td><td> 29.46</td><td> §</td><td> &lt;0.001</td>

<td> Proliferation Group Score</td><td> 23.34</td><td> 5</td><td> &lt;0.001</td>

<td> GPS</td><td> 29.98</td><td> 5</td><td> &lt;0.001</td>

Table 20 Association of Genes and Gene Groups with High-Grade Disease, Uni variable

Analyses

<td></td><td> Chi Equate</td><td></td><td></td><td></td><td> IB·^</td>

<td> BGN</td><td> 3.67</td><td> 1</td><td> 0.055</td><td> 1.46</td><td> (0.99,2.15)</td>

<td> COL1AI</td><td> 2.33</td><td> 1</td><td> 0.127</td><td> 1.32</td><td> (0.93,1.87)</td>

<td> SFRP4</td><td> 6.08</td><td> 1</td><td> 0.014</td><td> 1.33</td><td> (1.06,1.67)</td>

<td> FLNC</td><td> 3.04</td><td> 1</td><td> 0.081</td><td> 0.77</td><td> (0.57,1.03)</td>

<td> GSN</td><td> 0.14</td><td> 1</td><td> 0.710</td><td> 0.94</td><td> (0.67, 132)</td>

<td> GSTM2 TPM2 AZGP1</td><td> 0.03 •mm ·»··*«· &lt;««*«· lUMiiituim· 2.85 12.69</td><td> 1 τ,ιπγη'η.κι'ίτ.τΜ 1 1</td><td> 0.870 ivrtrtiwr/nwMwnwrtt 0.091 &lt;0.001</td><td> 0.97 0.76 0.58</td><td> (0.69,1.37) (0.56,1.04) (0.42,0.79)</td>

<td> KLK2</td><td> 3.50</td><td> 1</td><td> 0.061</td><td> 0.62</td><td> (0.38,1.02)</td>

<td> FAM13C1</td><td> 9.29</td><td> 1</td><td> 0.002</td><td> 0.51</td><td> (033,0.79)</td>

<td> SRDSA2</td><td> 3.26</td><td> 1</td><td> 0.071</td><td> 0.76</td><td> (0.56,1.02)</td>

<td> SRD5A2 Threshvided</td><td> 2.70</td><td> 1</td><td> 0.100</td><td> 0.75</td><td> (0.53,1.06)</td>

<td> TPX2</td><td> 1.72</td><td> 1</td><td> 0.190</td><td> 1.21</td><td> (0.91,1.59)</td>

<td> TPX2 Thresholded</td><td> 7.38</td><td> 1</td><td> 0.007</td><td> 1.93</td><td> (1.20,3.11)</td>

<td> Ref Gene Average</td><td> 1.18</td><td> 1</td><td> 0.277</td><td> 0.86</td><td> (0.65,1.14)</td>

<td> Stromal Response Group Score</td><td> 4.92</td><td> 1</td><td> 0.027</td><td> 1.49</td><td> (1.05,2.12)</td>

<td> Cellular Organization Group Score</td><td> 1.12</td><td> 1</td><td> 0.290</td><td> 0.87</td><td> (0.66,1.13)</td>

<td> Androgen Group Score</td><td> 15.07</td><td> 1</td><td> &lt;0.001</td><td> 0.69</td><td> (0.58,0.83)</td>

<td> Proliferation Group Score</td><td> 7.38</td><td> 1</td><td> 0.007</td><td> 1.93</td><td> (1.20,3.11)</td>

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Table 21 Association of Genes and Gene Groups with Non-Organ-Confined Disease, Univariable Analyses

<td></td><td></td><td> Ugg</td><td> Mggjj</td><td> SUSP</td><td></td>

<td> BGN</td><td> 2.58</td><td> 1</td><td> 0.109</td><td> 134</td><td> (0.94,1.91)</td>

<td> COL1A1</td><td> 2.90</td><td> 1</td><td> 0.089</td><td> 133</td><td> (0.96,1.83)</td>

<td> SFRP4</td><td> 4.39</td><td> 1</td><td> 0.036</td><td> 1.25</td><td> (1.01,1.54)</td>

<td> FLNC</td><td> 0.34</td><td> 1</td><td> 0.560</td><td> 0-92</td><td> (0.70,1.21)</td>

<td> GSN</td><td> 0.27</td><td> 1</td><td> 0.603</td><td> 6.92</td><td> (0.67,1.26)</td>

<td> GSTM2</td><td> o.u</td><td> 1</td><td> 0.693</td><td> 0.94</td><td> (0.68,1.29)</td>

<td> TPM2</td><td> 0.5!</td><td> 1</td><td> 0.473</td><td> 0.9</td><td> (0.67,1.20)</td>

<td> AZGP1</td><td> 12.48</td><td> 1</td><td> &lt;0.001</td><td> 0.59</td><td> (0.44,0.80)</td>

<td> KLK2</td><td> 2.10</td><td> 1</td><td> 0.148</td><td> 0.71</td><td> (0.45,1.12)</td>

<td> FAM13C1</td><td> 12.42</td><td> 1</td><td> 0.000</td><td> 0.48</td><td> (032,0.73)</td>

<td> SRD5A2</td><td> 2.42</td><td> 1</td><td> 0.120</td><td> 0.8</td><td> (0.60,1.06)</td>

<td> SRDSA2 Thresholded</td><td> 2.6S</td><td> 1</td><td> 0.103</td><td> 0.77</td><td> (0.56,1.06)</td>

<td> TPX2</td><td> 6.38</td><td> 1</td><td> 0.012</td><td> 139</td><td> (1.08,1.81)</td>

<td> TPX2 Thresholded</td><td> 6.51</td><td> 1</td><td> 0.011</td><td> 1.82</td><td> (1.14,2.89)</td>

<td> Ref Gene Average______________</td><td> _________0.33</td><td> _________1</td><td> 0.563</td><td> 0.93</td><td> (0.73,1,19)</td>

<td> Stromal Response Group Score</td><td> 4.24</td><td> 1</td><td> 0.040</td><td> 1.41</td><td> (1.02,1.95)</td>

<td> Cellular Organization Group Score</td><td> 0.4S</td><td> 1</td><td> 0.504</td><td> 0.92</td><td> (0.72,1.18)</td>

<td> Androgen Group Score</td><td> 14.64</td><td> 1</td><td> &lt;0.001</td><td> 0.71</td><td> (0.60,0.85)</td>

<td> Proliferation Group Score</td><td> 6.51</td><td> 1</td><td> 0.011</td><td> 1.82</td><td> (1.14,2.89)</td>

Table 22 Association of Genes and Gene Groups with High-Grade or Non-Organ-Confined Disease, Univariable Analyses

<td> . $..........A. '</td><td> S—</td><td> g» -S'</td><td> MM lOlO nMB</td><td> mmMI</td><td> 5¼ .^^5! A</td>

<td> BGN</td><td> 3.15</td><td> 1</td><td> 0.076</td><td> 133</td><td> (0.97,1.84)</td>

<td> COL1A1</td><td> 1.96</td><td> 1</td><td> 0.162</td><td> 1.23</td><td> (0.92,1.65)</td>

<td> SFRP4</td><td> 7.08</td><td> 1</td><td> 0.008</td><td> 1.29</td><td> (1.07,1.55)</td>

<td> FLNC</td><td> 236</td><td> 1</td><td> 0.125</td><td> 0.83</td><td> (0.65,1.06)</td>

<td> GSN___________________ GSTM2</td><td> 0.45 «vrnwMWwrtxvrvmwwHV 0.49</td><td> __________1 1</td><td> 0.503 0.484</td><td> 0.91 iiuwnwnwnwnnvrii 0.9</td><td> (0.68,1.20) (0.68,1.20)</td>

<td> TPM2 -----------------------------------............................. AZGPl</td><td> 2.24 12.20</td><td> __1 1</td><td> 0.135 0.001</td><td> 0.82 0.61</td><td> (0.63,1.06) (0.46,0.82)</td>

<td> KLK2</td><td> 2.18</td><td> 1</td><td> 0.140</td><td> 0.73</td><td> (0.48,1.11)</td>

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<td></td><td> HSlS</td><td></td><td></td><td></td><td></td>

<td> FAM13C1</td><td> 11.13</td><td> 1</td><td> 0.001</td><td> 0.53</td><td> (0.37,0.78)</td>

<td> SRD5A2</td><td> 4.36</td><td> 1</td><td> 0.037</td><td> 0.76</td><td> (8.59,0.98)</td>

<td> SRD5A2 ThreshoMed</td><td> 4.63</td><td> 1</td><td> 0.032</td><td> 0.73</td><td> (0.55,0.98)</td>

<td> TPX2</td><td> 3.50</td><td> 1</td><td> 0,062</td><td> 1.25</td><td> (0.99,1.58)</td>

<td> TPX2 Thresholded</td><td> 5.86</td><td> 1</td><td> 0.016</td><td> 1.73</td><td> (1.09,2.74)</td>

<td> Ref Gene Average</td><td> 0.68</td><td> 1</td><td> ¢.041</td><td> 0.91</td><td> (8.73,1.14)</td>

<td> Stromal Response Group Score</td><td> 4.59</td><td> 1</td><td> 0.032</td><td> 1.37</td><td> (1.03,1.84)</td>

<td> Cellular Organization Group Score</td><td> 1.54</td><td> 1</td><td> 0.215</td><td> 0.87</td><td> (0.70,1.08)</td>

<td> Androgen Group Score</td><td> 16.56</td><td> 1</td><td> &lt;0.081</td><td> 0.72</td><td> (0.61,0.84)</td>

<td> Proliferation Group Score</td><td> 5.86</td><td> I</td><td> 0.016</td><td> 1.73</td><td> (1.09,2.74)</td>

Example 5: RS27 Adds Value Beyond PTEN/TMPRSS2-ERG Status in Predicting Clinical Recurrence

[00201] PTEN mutation and TMPRSS2-ERG fusion genes are commonly associated with poor prognosis in prostate cancer. Here, RS27 was analyzed to determine whether it can provide value beyond PTEN/TMPRSS2-ERG status in predicting clinical recurrence.

[00202] PTEN and TMPRSS2-ERG fusion expression levels obtained in the gene identification study described in Example 1 above and in U.S. Pub. No. 20120028264 were used to stratify patients into PTEN low and PTEN normal groups, PTEN and TMPRSS2ERG (“T2-ERG”) status of the patients were found as follows:

Table 23. Distribution of ΡΓΕΝ Expression by T2-ERG Status

[..................................................j T2¥l^ f2-ERG Positive (47%)

..................................................................-...........-........._

[00203] A cutpoint for “PTEN low” was made at &lt;~8,5, which included approximately 13% of T2-ERG negative patients and 28% of T2-ERG positive patients. PTEN normal was defined as &gt;8.5.

[00204] Univaraiblc Cox Proportional Hazards was applied to evaluate the association between PTEN status and time to clinical recurrence (cR). Figure 10 and Table 24 show that PTEN low patients have a higher risk of recurrence compared to PTEN normal patients, [00205]

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Table 24.

' ChiSq P-value ' , . ' HR ' „ 95%CI

12.44 ” ’ .........3 &lt;0.001 ' ” 0.38 ’ (0.22,0.65) ’

[00296J When the patients were further stratified into Pl EN low/T2-ERG negative (“category 0”), PTEN îowÆ2-ERG positive (“category 1”), PTEN normai/T2-ERG negative (“category 2”), and PTEN normal/T2-ERG positive (“category 3”), both PTEN low categories had the lowest recurrence rates compared to PTEN normal patients as shown in

Figure 11 and Tabic 25.

Table 25.

PTEN/TZ-ERG categories CHISQ...... ί P-VALUE·· ·. 85% Cl „· ' 7- Cat1 v0 ’ ,.......3 ’ 0.93 ; ’^; / ΰ.34 ’I.....” (0.28,1.55)

- , Cat2vO . -11.80 ..... &lt;0.01.....(0.12,0.56)

Gat3vO ......... 7.05 ........... O.01 - ·· (0.18,0.76) .

[00207] The tables below summarize the results of a multivariable model with PTEN/T2ERG status (Table 26) or PTEN status (Table 27), RS27, and biopsy Gleason Score (Bx GS), demonstrating that RS27 adds value beyond PTEN and T2-ERG markers and Biopsy GS in predicting clinical recurrence.

Table 26.

<td> 1 VARIABLE 1</td><td> DF</td><td> CHISQ</td><td> P-VALUE</td><td> HR</td><td> 95% C! |</td>

<td> β§27 |</td><td></td><td> 6413</td><td> &lt;Ôôî</td><td> __</td><td></td>

<td> PTÉN/T2-ËRG Status i</td><td> 3</td><td> 1.58</td><td> 0.66</td><td></td><td></td>

<td> jpTEWT2-ERG (Cat 1 v. 0)</td><td> 1</td><td> 0.06</td><td> 0.80</td><td> 0.91</td><td> (0,41.198) | J</td>

<td></td><td> 1</td><td> 1.17</td><td> 0.28 ;</td><td> Ô65</td><td> (0.28,1.42)</td>

<td> FTEhlTZ-ERG (Cat 3 v. 0)</td><td> 1</td><td> Ô.Î4</td><td> 0.71</td><td> 0.86</td><td> (Ô’.39,î.69)|</td>

<td> LlWWWMOWOKOWWWWWWWMMWMWW»......»l»fcl»lM fetGS I</td><td></td><td> 7.19 '</td><td> 0Ό3</td><td></td><td> ΜΜ»»ί»««ηυ···’·”’”*ι</td>

<td> BxGS(7v. 6) j</td><td> 1</td><td> 6.86</td><td> 0 Cl</td><td> 0.40</td><td> (0.20,079) j</td>

<td> feGS(8+v.6) j</td><td> Ï</td><td> 1.35</td><td> 0.24 .........</td><td> 0.69</td><td> (0.36,1.29) 1</td>

Table 27.

<td> VARIABLE</td><td> DF</td><td> ! CHISQ</td><td> P-VALUE</td><td> HR I</td><td> 85% Ci</td>

<td> GPS</td><td> 1</td><td> | 6667</td><td> &lt;0.01</td><td> 1.07 :</td><td> (1.05,1.09) 1 I</td>

<td> PTEN Status</td><td> 1</td><td> ~ | ~ 0.86</td><td> 0.35</td><td> 0.78</td><td> (0.46,1.32) 1</td>

<td> BXGS</td><td> .........2.....</td><td> 't......5.43.......</td><td> ..........0.04</td><td> „ L.</td><td></td>

<td></td><td> .........</td><td> 6.Ϊ2^-</td><td> ÔÔÎ</td><td></td><td> (0.21,0.84)</td>

<td> Bx GS (8+ v. 6)</td><td> 1</td><td> ί 1.15</td><td> 0.28</td><td> 0.71</td><td> (0.37,1.33)</td>

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