Prognosis and treatment of metastatic prostate cancer

Abstract

Disclosed herein are methods, including methods for determining a response to treatment comprising ADT and a taxane compound, for example docetaxel, that a subject with metastatic prostate cancer is expected to have based on at least the expression level a plurality of targets in the sample from the subject. In some embodiments, the methods include administering or having administered to the subject with metastatic prostate cancer in a treatment selected from: a treatment comprising ADT and a taxane compound, for example docetaxel; or a treatment comprising ADT and not comprising a taxane compound, for example docetaxel, wherein the treatment is selected based on the expected response to treatment comprising ADT and the taxane compound, for example docetaxel. Also disclosed are kits and reagents used for performing the methods.

Description

GENDX.035WO PCT PROGNOSIS AND TREATMENT OF METASTATIC PROSTATE CANCER FIELD

[0001] The present disclosure pertains to the field of metastatic prostate cancer. BACKGROUND

[0002] Globally, prostate cancer accounts for a fifth of male cancer-related deaths. The majority of these deaths occur in patients who presented with advanced disease, including metastatic disease. Androgen deprivation therapy (ADT) in combination with docetaxel improves survival for some patients with metastatic prostate cancer. The treatment regime is, however, both physically and financially taxing. It would be beneficial to have a test for determining which patients are likely to benefit from being treated with a combination comprising androgen deprivation therapy (ADT) and docetaxel.

[0003] This background information is provided for the purpose of making known information believed by the applicant to be of possible relevance to the present disclosure. No admission is necessarily intended, nor should be construed, that any of the preceding information constitutes prior art against the present disclosure. SUMMARY

[0004] Provided herein are biomarkers for determining an expected response to treatment comprising ADT and docetaxel, or another taxane compound, in metastatic prostate cancer, methods of using the biomarkers including methods of treatment based on the expected response to treatment comprising ADT and docetaxel, or another taxane compound, determined using the biomarkers, as well as kits for detecting the biomarkers, and for use in the methods of determining the expected response.

[0005] Some embodiments provided herein are described by way of the following numbered embodiments: 1. A method comprising:(a) obtaining or having obtained an expression level of a plurality of targets in a sample obtained from a subject with metastatic prostate cancer, wherein the plurality of targets comprises or consists of at least one target nucleic acid sequence selected from each of at least five of: UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, GLYATL1, PCAT-32, DNAH5, S1PR4, NFIB, and EPPK1; the biomarkers / genes listed in Table 1; the biomarkers / genes listed in Table 2; or the biomarkers / genes listed in Table 3; and (b) determining a response to treatment comprising ADT and a taxane compound, optionally wherein the taxane compound is docetaxel, that the subject with metastatic prostate cancer is expected to have based on at least the expression level of each of the plurality of targets in the sample obtained in step (a). 2. A method comprising: (a) obtaining or having obtained an expression level of a plurality of targets in a sample obtained from a subject with metastatic prostate cancer, wherein the plurality of targets comprises or consists of at least one target nucleic acid sequence selected from each of at least five of: UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, GLYATL1, PCAT-32, DNAH5, S1PR4, NFIB, and EPPK1; the biomarkers / genes listed in Table 1; the biomarkers / genes listed in Table 2; or the biomarkers / genes listed in Table 3; (b) determining or having determined a response to treatment comprising ADT and a taxane compound, optionally wherein the taxane compound is docetaxel, that the subject with metastatic prostate cancer is expected to have based on at least the expression level of each of the plurality of targets in the sample obtained in step (a); and (c) administering or having administered to the subject with metastatic prostate cancer in (b) a treatment selected from: (i) a treatment comprising ADT and the taxane compound, optionally wherein the taxane compound is docetaxel; or(ii) a treatment comprising ADT and not comprising the taxane compound, optionally wherein the taxane compound is docetaxel, wherein the treatment is selected based on the expected response to treatment comprising ADT and the taxane compound, optionally wherein the taxane compound is docetaxel, determined in (b). 3. The method of embodiment 1 or 2, wherein the expected response to treatment comprising ADT and the taxane compound is one or more of the following: a) overall survival, metastasis-free survival, progression-free survival, and / or metastatic progression-free survival, b) overall survival, progression-free survival, and / or metastatic progression-free survival, c) overall survival at 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 years, or a range defined by any two of the preceding values, or d) overall survival at 3 years. 4. The method of embodiment 2 or 3, wherein the treatment (i) comprising ADT and the taxane compound further comprises an Androgen Receptor Pathway Inhibitor (ARPI), optionally wherein the ARPI is abiraterone, apalutamide, darolutamide, or enzalutamide. 5. The method of embodiment 4, wherein the treatment (i) comprising ADT and the taxane compound further comprises abiraterone and optionally a corticosteroid, optionally wherein the corticosteroid is prednisone or prednisolone. 6. The method of any one of embodiments 1-5, wherein the plurality of targets comprises or consists of 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 or 22 target nucleic acid sequences, optionally wherein each target nucleic acid sequence is selected from a different gene, and / or not more than 2 target nucleic acid sequences are from the same gene, optionally wherein not more than 3 genes have 2 target nucleic acid sequences. 7. The method of any one of embodiments 1-6, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, and TNFRSF19. 8. The method of any one of embodiments 1-7, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3 and ANO7.9. The method of any one of embodiments 1-8, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, PCAT-32, S1PR4, NFIB, and EPPK1. 10. The method of any one of embodiments 1-9, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of USAP1, PCDH7, THBS2, TNFRSF19, CAMK2N1, IQGAP3, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, PCAT-32, S1PR4, NFIB, and EPPK1, and two nucleic acid sequences of each of UBE2C, MYBPC1, and ANO7, . 11. The method of any one of embodiments 1-8, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1, DNAH5 S1PR4, NFIB, and EPPK1. 12. The method of any one of embodiments 1-8, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, GLYATL1, DNAH5, S1PR4, NFIB, and EPPK1, and two nucleic acid sequences of each of IQGAP3, ANO7 and LASP1. 13. The method of any one of embodiments 1-9, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, GLYATL1P4 / PCAT-80, PCAT-32, S1PR4, NFIB, EPPK1, and two nucleic acid sequences of each of IQGAP3, ANO7 and LASP1. 14. The method of any one of embodiments 1-13, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets. 15. The method of any one of embodiments 1-14, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and wherein said determining or havingdetermined comprises determining or having determined that the subject with metastatic prostate cancer: (i) is expected to respond better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being high; or (ii) is expected to respond less or only minimally better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being high being low. 16. The method of any one of embodiments 1-15, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and wherein said determining or having determined comprises determining or having determined that the subject with metastatic prostate cancer: (i) is expected to respond better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score of the sample being high; or (ii) is expected to respond less or only minimally better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score of the sample being low. 17. The method of any one of embodiments 2-16, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and wherein the method comprises: (i) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and the taxane compound based on the risk score for the sample being high; or(ii) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and not comprising the taxane compound based on the risk score being low. 18. The method of any one of embodiments 2-17, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and wherein the method comprises: (i) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and the taxane compound based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score for the sample being high; or (ii) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score for the sample being low. 19. The method of any one of embodiments 1-18, wherein the expected better response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of at least 10%, 20%, 30%, 40% or 45% as compared to a treatment comprising ADT and not comprising the taxane compound and the expected less or minimally better response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of not greater than 15%, 10% or 5% as compared to a treatment comprising ADT and not comprising the taxane compound, optionally wherein overall survival is at 1, 2, 3, 4 or 5 years. 20. The method of any one of embodiments 1-19, wherein the determined expected response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of at least 10%, 20%, 30%, 40% or 45% as compared to a treatment comprising ADT and not comprising the taxane compound, optionally wherein the increase in overall survival is at 1, 2, 3, 4 or 5 years, and / or optionally wherein the expected response is based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being high.21. The method of any one of embodiments 14-20, wherein calculated risk score for the sample is above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score is high. 22. The method of any one of embodiments 1-19, wherein the determined expected response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of not greater than 15%, 10% or 5% as compared to a treatment comprising ADT and not comprising the taxane compound, optionally wherein the increase in overall survival is at 1, 2, 3, 4 or 5 years, and / or optionally wherein the expected response is based on the risk score for the sample being below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being low. 23. The method of any one of embodiments 1-19, or 22, wherein calculated risk score for the sample is below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score is low. 24. The method of any one of embodiments 14-23, wherein the risk score is on a scale from 0 to 1, and wherein: the high score comprises or consists of risk scores > 0.80 or > 0.85 and the low score comprises or consists of risk scores ≤ 0.80 or ≤ 0.85, optionally wherein the high score comprises or consists of risk scores > 0.85 and the low score comprises or consists of risk scores ≤ 0.85. 25. The method of any one of embodiments 14-24, wherein the expected better response to, selecting for and / or administering treatment comprising ADT and the taxane compound is based on the risk score being equal to the median value of the risk score observed in a population of metastatic patients. 26. The method of any one of embodiments 14-24, wherein the expected less or minimally better response to treatment comprising ADT and the taxane compound, or selecting for and / or administering treatment comprising ADT and not comprising the taxane compound is based on the risk score being equal to the median value of the risk score observed in a population of metastatic patients. 27. The method of any one of embodiments 1-14, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and wherein said determining or havingdetermined comprises determining or having determined that the subject with metastatic prostate cancer: (i) is expected to respond better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being > 0.85 on a scale from 0 to 1, optionally wherein the expected better response to treatment comprising ADT and the taxane compound is an increase in overall survival of at least 10%, 20%, or 30% as compared to treatment comprising ADT and not comprising the taxane compound; or (ii) is expected to respond less or only minimally better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being equal to or below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being ≤ 0.85 on a scale of 0 to 1, optionally wherein the expected less or minimally better response to treatment comprising ADT and the taxane compound is an increase in overall survival not greater than 15%, 10%, or 5% as compared to treatment comprising ADT and not comprising the taxane compound, optionally docetaxel. 28. The method of any one of embodiments 2-14 or 27, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and wherein the method comprises: i) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and the taxane compound based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being > 0.85 on a scale from 0 to 1, optionally wherein the expected better response to treatment comprising ADT and the taxane compound is an increase in overall survival of at least 10%, 20%, or 30% as compared to treatment comprising ADT and not comprising the taxane compound; orii) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and not comprising the taxane compound based on the risk score being equal to or below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being ≤ 0.85 on a scale of 0 to 1, optionally wherein the expected less or minimally better response to treatment comprising ADT and the taxane compound is an increase in overall survival not greater than 15%, 10%, or 5% as compared to treatment comprising ADT and not comprising the taxane compound, optionally docetaxel. 29. The method of any one of embodiments 1-14 or 27-28, wherein the expected response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of at least 10%, 20%, or 30% as compared to ADT and not comprising the taxane compound, optionally measured at 3 years, and / or optionally wherein the expected response is based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being > 0.85 on a scale from 0 to 1. 30. The method of any one of embodiments 1-14 or 27-28, wherein the expected response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of not greater than 15%, 10% or 5% as compared to ADT treatment and not comprising the taxane compound, optionally measured at 3 years, and / or optionally wherein the expected response is based on the risk score for the sample being equal to or below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being ≤ 0.85 on a scale of 0 to 1. 31. The method of any one of the preceding embodiments, wherein said determining or having determined the expected response to treatment comprising ADT and the taxane compound is in comparison to a treatment comprising ADT and not comprising the taxane compound, optionally docetaxel. 32. The method of any one of the preceding embodiments, wherein said determining or having determined the expected response of the subject with metastatic prostate cancer to treatment comprising ADT and the taxane compound is not based on prognostic clinical variables, optionally wherein the prognostic clinical variables are tumor stage, nodalstage, metastatic tumor volume categorization, a Gleason score and / or a serum PSA level of the subject. 33. The method of any one of embodiments 1-31, wherein said determining or having determined the expected response of the subject with metastatic prostate cancer to treatment comprising ADT and the taxane compound is further based on one or more prognostic clinical variables, optionally wherein the prognostic clinical variables are tumor stage, nodal stage, metastatic tumor volume categorization, a Gleason score and / or a serum PSA level of the subject. 34. The method of any one of the preceding embodiments, wherein said obtaining or having obtained the expression level of the plurality of targets comprises utilizing a microarray to assess on the plurality of targets, performing qPCR on the plurality of targets, and / or sequencing the plurality of targets. 35. The method of any one of the preceding embodiments, wherein the metastatic prostate cancer is castration-sensitive prostate cancer. 36. The method of any one of embodiments 1-35, wherein the subject has low- volume metastatic cancer, optionally wherein the low-volume metastatic cancer subject does not have a visceral metastasis, and does not have ≥ 4 bone metastases with ≥ 1 outside the vertebral bodies or pelvis. 37. The method of any one of embodiments 1-35, wherein the subject has high- volume metastatic cancer, optionally wherein the high-volume metastatic cancer subject has a visceral metastasis, or has ≥ 4 bone metastases with ≥ 1 outside the vertebral bodies or pelvis. 38. The method of any one of the preceding embodiments, wherein the taxane compound is selected from docetaxel, paclitaxel, and cabazitaxel, optionally wherein the taxane compound is docetaxel. 39. The method of any one of the preceding embodiments, wherein the taxane compound is not docetaxel. 40. The method of any one of the preceding embodiments, wherein the taxane compound is paclitaxel. 41. The method of any one embodiments 1-39, wherein the taxane compound is cabazitaxel.42. The method of any one of the preceding embodiments, wherein the sample is from a radical prostatectomy, a resected specimen, optionally a transurethral resection of prostate (TURP) specimen, or a biopsy of the prostate cancer, optionally a needle biopsy. 43. The method of any one of the preceding embodiments, wherein the sample is from a primary prostate tumor. 44. The method of any one of the embodiments 16-43, wherein the population of metastatic patients comprises at least 10, 25, 50, 75 or 100 patients. 45. A kit for use in determining a response to treatment according to any one of the preceding methods. 46. The kit of embodiment 45, the kit comprising reagents for obtaining the expression level of biomarkers comprising or consisting of each of the plurality of targets. 47. The kit of embodiment 46, wherein the reagents comprise primer(s) and / or probe(s) for obtaining the expression level of each of the plurality of targets. INCORPORATION BY REFERENCE

[0006] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference for the disclosures referenced herein and in their entireties to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 is an embodiment of an experimental and analytical workflow diagram showing total eligible patients in full docetaxel and abiraterone trial cohorts and progress to the biomarker cohorts with breakdown of cases with quality-control (QC) passed expression data, Ki67 and PTEN immunohistochemistry and tumor infiltrating lymphocytes (TILs). Box-violin plots and stacked bar-plots comparing proportion or range of baseline clinical features of the biomarker cohorts that were adjusted for in prognostic analyses: age, serum prostate specific antigen (PSA) obtained prior to androgen deprivation therapy (ADT), World Health Organisation (WHO) performance status (PS), metastatic volume, Gleason score (GS) and tumor stage. Following pre-specified statistical analysis plans multivariable models were constructed with integration of transcriptome signatures, clinical variables, treatment armand long-term survival data to generate predictive and prognostic estimates. M0N0: non- metastatic node-negative, M0N1: non-metastatic with local lymph node involvement localized, M1LV: metastatic low-volume, M1HV: metastatic high-volume, M1X; Metastatic and disease volume unknown; RT: radiation therapy, Abi: abiraterone acetate and prednisolone; Doce: docetaxel

[0008] Figure 2 is an embodiment of a sample flow diagram depicting a docetaxel trial.

[0009] Figure 3 is an embodiment of a diagram depicting STAMPEDE platform protocol design.

[0010] Figure 4A is an embodiment of a box-plot and density plot of a distribution of Decipher® Prostate Gene Classifier (hereafter referred to as Decipher) scores across the STAMPEDE biomarker cohort (N=1523) and published cohorts of patients diagnosed with low to intermediate risk disease (N=81,594) (Weiner, et al., Cancer 129(14):2169-2178 (2023)) compared to Decipher across tumors from men (N=81,594). M0: non-metastatic; M1: Metastatic.

[0011] Figure 4B is an embodiment of box-violin plots of a distribution by metastatic volume of Decipher scores with p-values. M0: non-metastatic; M1: Metastatic.

[0012] Figure 5A is an embodiment of a Kaplan-Meier plot of overall survival in patients with metastatic disease (M1 All) in the STAMPEDE docetaxel trial (N=895) allocated to either androgen deprivation therapy (solid line) or androgen deprivation therapy with docetaxel + / - zoledronic acid (dashed line). Plot depicts pre-specified high Decipher. Hazard ratios and 95% confidence intervals included as insets.

[0013] Figure 5B is an embodiment of a Kaplan-Meier plot of overall survival in patients with metastatic disease (M1 All) in the STAMPEDE docetaxel trial (N=895) allocated to either androgen deprivation therapy (solid line) or androgen deprivation therapy with docetaxel + / - zoledronic acid (dashed line). Plot depicts pre-specified lower Decipher. Hazard ratios and 95% confidence intervals included as insets.

[0014] Figure 5C is an embodiment of a Kaplan-Meier plot of overall survival in patients with metastatic low volume (M1LV) disease in the STAMPEDE docetaxel trial (N=228) allocated to either androgen deprivation therapy (solid line) or androgen deprivationtherapy with docetaxel + / - zoledronic acid (dashed line). Plot depicts pre-specified high Decipher. Hazard ratios and 95% confidence intervals included as insets.

[0015] Figure 5D is an embodiment of a Kaplan-Meier plot of overall survival in patients with metastatic low volume (M1LV) disease in the STAMPEDE docetaxel trial (N=228) allocated to either androgen deprivation therapy (solid line) or androgen deprivation therapy with docetaxel + / - zoledronic acid (dashed line). Plot depicts pre-specified lower Decipher. Hazard ratios and 95% confidence intervals included as insets.

[0016] Figure 5E is an embodiment of a Kaplan-Meier plot of overall survival in patients with metastatic high volume (M1HV) disease in the STAMPEDE docetaxel trial (N=270) allocated to either androgen deprivation therapy (solid line) or androgen deprivation therapy with docetaxel + / - zoledronic acid (dashed line). Plot depicts pre-specified high Decipher. Hazard ratios and 95% confidence intervals included as insets.

[0017] Figure 5F is an embodiment of a Kaplan-Meier plot of overall survival in patients with metastatic high volume (M1HV) disease in the STAMPEDE docetaxel trial (N=270) allocated to either androgen deprivation therapy (solid line) or androgen deprivation therapy with docetaxel + / - zoledronic acid (dashed line). Plot depicts pre-specified lower Decipher. Hazard ratios and 95% confidence intervals included as insets.

[0018] Figure 5G is an embodiment of restricted mean survival time analyses demonstrating differences in survival over time by treatment allocation for patients split by Decipher high (dark dashed line) or lower (light solid line) in the docetaxel (N=895) trial.

[0019] Figure 6 is an embodiment of restricted mean survival time analyses demonstrating differences in survival over time by treatment allocation for patients with non- metastatic disease split by Decipher high or lower in the docetaxel (N=895) trial.

[0020] Figures 7A and 7B are an embodiment of an analysis of the association between docetaxel treatment and categorical Decipher score in metastatic subjects.

[0021] Figure 8 is an embodiment of a likelihood ratio test analysis of the association between docetaxel treatment and dichotomized Decipher score in metastatic subjects.

[0022] Figure 9 is an embodiment of a restricted mean survival time analysis of the association between docetaxel treatment and dichotomized Decipher score in metastatic subjects.DETAILED DESCRIPTION

[0023] Provided herein are biomarkers for determining an expected response to treatment comprising ADT and a taxane compound, for example docetaxel, in metastatic prostate cancer, methods of using the biomarkers including methods of treatment based on the expected response to treatment comprising ADT and a taxane compound, for example docetaxel, determined using the biomarkers, as well as kits for detecting the biomarkers, and for use in determining the expected response.

[0024] Some embodiments disclosed herein are a method comprising: (a) obtaining or having obtained an expression level of a plurality of targets in a sample obtained from a subject with metastatic prostate cancer, wherein the plurality of targets comprises or consists of at least one target nucleic acid sequence selected from each of at least five of the genes listed in Table 1, 2 and / or 3; and (b) determining a response to treatment comprising ADT and a taxane compound, for example docetaxel, that the subject with metastatic prostate cancer is expected to have based on at least the expression level of each of the plurality of targets in the sample obtained in step (a). Some embodiments disclosed herein are a method comprising: (a) obtaining or having obtained an expression level of a plurality of targets in a sample obtained from a subject with metastatic prostate cancer, wherein the plurality of targets comprises or consists of at least one target nucleic acid sequence selected from each of at least five of the genes listed in Table 1, 2 and / or 3; and (b) determining or having determined a response to treatment comprising ADT and a taxane compound, for example docetaxel, that the subject with metastatic prostate cancer is expected to have based on at least the expression level of each of the plurality of targets in the sample obtained in step (a); and (c) administering or having administered to the subject with metastatic prostate cancer in (b) a treatment selected from: (i) a treatment comprising ADT and a taxane compound, for example docetaxel; or (ii) a treatment comprising ADT and not comprising a taxane compound, for example docetaxel, wherein the treatment is selected based on the expected response to treatment comprising ADT and the taxane compound, for example docetaxel, determined in (b).Biomarkers / Genes for predicting response to treatment with ADT and a taxane compound, for example docetaxel

[0025] In some embodiments, Tables 1-3 are lists of biomarkers / genes for use in predicting the response of advanced prostate cancer (e.g., metastatic prostate cancer) to treatment comprising ADT and a taxane compound, for example docetaxel. In some embodiments, biomarkers / genes listed in Table 1, 2 or 3 are combined into a risk score using a GLMNet model. In some embodiments, the model is fitted and its mixing parameter are selected through 10-fold cross validation. In some embodiments, the coefficients of this model can have positive or negative weights. In some embodiments, the expression level is not relative to a matched control (e.g., a matched healthy tissue or low grade prostate cancer), but is an absolute expression level, optionally corrected for background noise of the measurement method or device (e.g., an array). In some embodiments, a variety of scales can be used for the expression level. In some embodiments, the expression level is in a logarithmic scale. In some embodiments, the expression level is in a scale other than logarithmic scale (e.g., in a scale starting from zero and increasing). In some embodiments, the expression level (e.g., for one or more of targets) is higher / above background noise. In some embodiments, the expression level (e.g., for one or more of targets) is lower / below background noise. In some embodiments, the expression level (e.g., for one or more of targets) is zero or a positive value. In some embodiments, the expression level for each of the target is either zero or a positive value. In some embodiments, an elevated expression level of the biomarkers / genes in Table 1, Table 2 or Table 3 with a positive coefficient value indicates that a subject is more likely to respond more to treatment comprising ADT and a taxane compound, for example docetaxel, and an elevated expression level of the target selected from a biomarker / gene with a negative coefficient value indicates that a subject is likely to experience less benefit from treatment comprising ADT and a taxane compound, for example docetaxel. In some embodiments, an elevated (e.g., relative to matched healthy tissue or low grade prostate cancer) expression level of the biomarkers / genes in Table 1, Table 2 or Table 3 with a positive coefficient value indicates that a subject is more likely to respond more to treatment comprising ADT and a taxane compound, for example docetaxel, and an elevated expression level of the target selected from a biomarker / gene with a negative coefficient value indicates that a subject is likely to experience less benefit from treatment comprising ADT and a taxane compound, forexample docetaxel. The greater the absolute value of the coefficient, the greater the relative predictive value of the biomarker / gene to the overall model. Table 1: Prostate Cancer Biomarker / Gene and Coefficients Biomarker / Gene Coefficient UBE2C 4.387Table 2: Prostate Cancer Biomarker / Gene and Coefficients Biomarker / Gene CoefficientPBX1 -0.724 TSBP1 aka C6orf10 -0.628oefficients Biomarker / Gene Coefficient UBE2C 4387

[0026] In some embodiments, a nucleic acid expression-based signature, (e.g., a signature including biomarkers selected from Tables 1, 2, or 3, Decipher, or a signature provided below and elsewhere herein) provide clinically-important information in advanced (e.g., metastatic) prostate cancer independent of prognostic clinical variables (e.g., Gleason score and metastatic burden). In some embodiments, the nucleic acid expression-based signature (e.g., a signature including biomarkers selected from Tables 1, 2, or 3, Decipher, orsignature provided below and elsewhere herein) provides a basis for selecting patients for treatment with a taxane compound, for example docetaxel, in addition to ADT treatment. In some embodiments, a nucleic acid expression-based signature, (e.g., a signature including biomarkers selected from Tables 1, 2, or 3, Decipher, or a signature provided below and elsewhere herein) measured at diagnosis from routinely-acquired primary tumors can classify advanced (e.g., metastatic) prostate cancers into clinically-useful groups that predict ADT + a taxane compound, for example docetaxel, treatment benefit. In some embodiments, the signature (e.g., the selected targets) is a signature disclosed in US Patent No.11,035,005, and PCT / US2013 / 055429, each of which is herein incorporated by reference in its entirety. In some embodiments, the signature (e.g., the selected targets) comprises or consists of those used in Decipher, disclosed for example in Erho, et al., PLoS One 8(6):e66855 (2013), which is herein incorporated by reference in its entirety. In some embodiments, the signature (e.g., the selected targets) comprises or consists of, or of at least, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22 or 23 of those used in Decipher. In some embodiments, the signature is Decipher.

[0027] In some embodiments, the method comprises: (a) obtaining or having obtained an expression level of a plurality of targets in a sample obtained from a subject with metastatic prostate cancer, wherein the plurality of targets comprises or consists of at least one target nucleic acid sequence selected from each of at least five of: UBE2C , NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, GLYATL1, PCAT-32, DNAH5 , S1PR4, NFIB, and EPPK1; the biomarkers / genes listed in Table 1; the biomarkers / genes listed in Table 2; or the biomarkers / genes listed in Table 3; and (b) determining a response to treatment comprising ADT and a taxane compound, for example docetaxel, that the subject with metastatic prostate cancer is expected to have based on at least the expression level of each of the plurality of targets in the sample obtained in step (a). In some embodiments, the method comprises: (a) obtaining or having obtained an expression level of a plurality of targets in a sample obtained from a subject with metastatic prostate cancer, wherein the plurality of targets comprises or consists of at least one target nucleic acid sequence selected from each of at least five of: UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10,RABGAP1, LASP1, GLYATL1P4 / PCAT-80, GLYATL1, PCAT-32, DNAH5, S1PR4, NFIB, and EPPK1; the biomarkers / genes listed in Table 1; the biomarkers / genes listed in Table 2; or the biomarkers / genes listed in Table 3; (b) determining or having determined a response to treatment comprising ADT and a taxane compound, for example docetaxel, that the subject with metastatic prostate cancer is expected to have based on at least the expression level of each of the plurality of targets in the sample obtained in step (a); and (c) administering or having administered to the subject with metastatic prostate cancer in (b) a treatment selected from: (i) a treatment comprising ADT and a taxane compound, for example docetaxel; or (ii) a treatment comprising ADT and not comprising a taxane compound, for example docetaxel, wherein the treatment is selected based on the expected response to treatment comprising ADT and the taxane compound, for example docetaxel determined in (b). In some embodiments, the expected response to treatment comprising ADT and the taxane compound, for example docetaxel, is one or more of the following: a) overall survival, metastasis-free survival, progression-free survival, and / or metastatic progression-free survival, b) overall survival, progression-free survival, and / or metastatic progression-free survival, c) overall survival at 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 years, or a range defined by any two of the preceding values, or d) optionally overall survival at 3 years. In some embodiments, the expected response to treatment comprising ADT and a taxane compound, for example docetaxel, is one or more of the following: overall survival, metastasis-free survival, progression-free survival, and / or metastatic progression-free survival. In some embodiments, the expected response to the treatment comprising ADT and a taxane compound, for example docetaxel, is overall survival at 3 years. In some embodiments, the expected better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or at least of, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45% or 50%, or a range defined by any two of the preceding values, for example, 5-50%, 5-35%, 30-50%, or 15-40% as compared to treatment comprising ADT and not comprising a taxane compound, for example docetaxel. In some embodiments, the expected better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or at least of 10%, 15%, 20%, 25%, or 30%. In some embodiments, the expected less or minimally better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or not greater than, 30%, 25%, 20%,15%, 10%, 5%, 0%, or a range defined by any two of the preceding values, for example, 30-0, 30-15% 15-0%, 15-5%, or 20-10%, as compared to treatment comprising ADT and not comprising a taxane compound, for example docetaxel. In some embodiments, the expected less or minimally better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or not greater than, 15%, 10%, 5% or 0% as compared to treatment comprising ADT and not comprising a taxane compound, for example docetaxel. In some embodiments, the treatment comprises ADT and a taxane compound, for example docetaxel. In some embodiments, the treatment further comprises an Androgen Receptor Pathway Inhibitor (ARPI). In some embodiments, the ARPI is abiraterone, apalutamide, darolutamide, or enzalutamide. In some embodiments, the treatment further comprises abiraterone. In some embodiments, the treatment comprises corticosteroid. In some embodiments, the corticosteroid is prednisone or prednisolone. In some embodiments, the plurality of targets comprises or consists of 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 or 22 target nucleic acid sequences, or a range defined by any two of the preceding values, for example, 5-22, 5-15, 10-22, 10-15, 14-22, or 18-22 target nucleic acid sequences. In some embodiments, each target nucleic acid sequence is selected from a different gene (biomarker). In some embodiments, not more than 1, 2, 3, 4, or 5 target nucleic acid sequences are from the same gene. In some embodiments, not more than 2 target nucleic acid sequences are from the same gene. In some embodiments, not more than 1, 2, 3, 4 or 5 genes have more than 1 target nucleic acid sequences. In some embodiments, not more than 1, 2, 3, 4 or 5 genes have more than 2 target nucleic acid sequences. In some embodiments, not more than 3 genes have 2 target nucleic acid sequences. In some embodiments, not more than 2 target nucleic acid sequences are from the same gene, and not more than 3 genes have 2 target nucleic acid sequences. In some embodiments, the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, and TNFRSF19. In some embodiments, the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3 and ANO7. In some embodiments, the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, PCAT-32, S1PR4, NFIB, and EPPK1. In some embodiments, theplurality of targets comprises or consists of a nucleic acid sequence of each of USAP1, PCDH7, THBS2, TNFRSF19, CAMK2N1, IQGAP3, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, PCAT-32, S1PR4, NFIB, and EPPK1, and two nucleic acid sequences of each of UBE2C, MYBPC1, and ANO7. In some embodiments, the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1, DNAH5 S1PR4, NFIB, and EPPK1. In some embodiments, the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, GLYATL1, DNAH5, S1PR4, NFIB, and EPPK1, and two nucleic acid sequences of each of IQGAP3, ANO7 and LASP1. In some embodiments, the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, GLYATL1P4 / PCAT-80, PCAT-32, S1PR4, NFIB, EPPK1, and two nucleic acid sequences of each of IQGAP3, ANO7 and LASP1. In some embodiments, the targets are selected from biomarkers / genes in Table 1, 2, or 3 that have coefficient values that are positive. In some embodiments, the targets are selected from biomarkers / genes in Table 1, 2, or 3 that have coefficient values that are negative. In some embodiments, the targets are selected from biomarkers / genes in Table 1, 2, or 3 that have coefficient values that are positive and negative. In some embodiments, the targets are selected from biomarkers / genes in Table 1, 2, or 3 that have an absolute coefficient value that is, or is at least, 0.03, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.5, 3.0, 3.5, 4.0, or 4.387, or a range defined by any two of the preceding values, for example, 0.03-4.387, 0.4- 4.387, or 1-4.387. In some embodiments, the targets are selected from biomarkers / genes in Table 1, 2, or 3 that have an absolute coefficient value that is, or is at least, 0.4. In some embodiments, the targets are selected from biomarkers / genes in Table 1, 2, or 3 that have an absolute coefficient value that is, or is at least, 1.0. In some embodiments, the targets are selected from biomarkers / genes in Table 1, 2, or 3 that have an absolute coefficient value that is, or is at least, 1.5. In some embodiments, the targets comprise or consist of at least one target nucleic acid from each of the biomarkers / genes in Table 1, 2, or 3. In some embodiments, the targets comprise or consist of at least one target nucleic acid from each of the biomarkers / genesin Table 1. In some embodiments, the targets comprise or consist of at least one target nucleic acid from each of the biomarkers / genes in Table 2. In some embodiments, the targets comprise or consist of at least one target nucleic acid from each of the biomarkers / genes in Table 3.

[0028] In some embodiments, the determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets. In some embodiments, the risk score is calculated using a GLMNet model. In some embodiments, the determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and the determining or having determined comprises determining or having determined that the subject with metastatic prostate cancer: (i) is expected to respond better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being high; or (ii) is expected to respond less or only minimally better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being high being low. In some embodiments, the determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and the determining or having determined comprises determining or having determined that the subject with metastatic prostate cancer: (i) is expected to respond better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score of the sample being high; or (ii) is expected to respond less or only minimally better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score of the sample being low. In some embodiments, the determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and the method comprises: (i) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and the taxane compound based on the risk score for the sample being high; or (ii) selecting for administration and / oradministering, or having administered, to the patient a treatment comprising ADT and not comprising the taxane compound based on the risk score being low. In some embodiments, the determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and the method comprises: (i) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and the taxane compound based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score for the sample being high; or (ii) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score for the sample being low. In some embodiments, the expected better response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of at least 10%, 20%, 30%, 40% or 45% as compared to a treatment comprising ADT and not comprising the taxane compound and the expected less or minimally better response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of not greater than 15%, 10% or 5% as compared to a treatment comprising ADT and not comprising the taxane compound. In some embodiments, the overall survival is at 1, 2, 3, 4 or 5 years. In some embodiments, the determined expected response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of at least 10%, 20%, 30%, 40% or 45% as compared to a treatment comprising ADT and not comprising the taxane compound. In some embodiments, the increase in overall survival is at 1, 2, 3, 4 or 5 years, and / or optionally wherein the expected response is based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being high. In some embodiments, the calculated risk score for the sample is above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score is high. In some embodiments, the determined expected response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of not greater than 15%, 10% or 5% as compared to a treatment comprising ADT and not comprising the taxane compound, optionally wherein the increase in overall survival is at 1, 2, 3, 4 or 5years, and / or optionally wherein the expected response is based on the risk score for the sample being below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being low. In some embodiments, the calculated risk score for the sample is below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score is low. In some embodiments, the risk score is on a scale from 0 to 1, and: the high score comprises or consists of risk scores > 0.80 or > 0.85 and the low score comprises or consists of risk scores ≤ 0.80 or ≤ 0.85, optionally wherein the high score comprises or consists of risk scores > 0.85 and the low score comprises or consists of risk scores ≤ 0.85. In some embodiments, the expected better response to, selecting for and / or administering treatment comprising ADT and the taxane compound is based on the risk score being equal to the median value of the risk score observed in a population of metastatic patients. In some embodiments, the expected less or minimally better response to treatment comprising ADT and the taxane compound, or selecting for and / or administering treatment comprising ADT and not comprising the taxane compound is based on the risk score being equal to the median value of the risk score observed in a population of metastatic patients. In some embodiments, the taxane compound is selected from docetaxel, paclitaxel, and cabazitaxel. In some embodiments, the taxane compound is docetaxel. In some embodiments, the taxane compound is not docetaxel. In some embodiments, the taxane compound is paclitaxel. In some embodiments, the taxane compound is cabazitaxel. In some embodiments, the determining or having determined that the subject with metastatic prostate cancer is expected to respond better to treatment comprising ADT and a taxane compound, for example docetaxel, than to treatment comprising ADT and not comprising a taxane compound, for example docetaxel, is based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients and / or the risk score being > 0.85 on a scale from 0 to 1. In some embodiments, the determining or having determined is based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients. In some embodiments, the determining or having determined that the subject with metastatic prostate cancer is expected to respond better to treatment comprising ADT and a taxane compound, for example docetaxel, than to treatment comprising ADT and not comprising a taxane compound, for example docetaxel, comprises the risk score being greater than, 0.7, 0.75, 0.8, 0.85, 0.9 or 0.95 on a scale from 0 to 1 or a range defined byany two of the preceding values, for example, 0.7-0.95, 0.7-0.85, 0.8-0.9, 0.8-0.95, 0.85-0.95, or 0.75-0.95. In some embodiments, the determining or having determined that the subject with metastatic prostate cancer is expected to respond better to treatment comprising ADT and a taxane compound, for example docetaxel, than to treatment comprising ADT and not comprising a taxane compound, for example docetaxel, comprises the risk score being > 0.85 on a scale from 0 to 1. In some embodiments, the determining or having determined that the subject with metastatic prostate cancer is expected to respond less or only minimally better to treatment comprising ADT and a taxane compound, for example docetaxel, than to treatment comprising ADT and not comprising a taxane compound, for example docetaxel, is based on the risk score for the sample being equal to or below the median value of the risk score observed in a population of metastatic patients and / or the risk score being ≤ 0.85 on a scale of 0 to 1. In some embodiments, the determining or having determined is based on the risk score for the sample being equal to or below the median value of the risk score observed in a population of metastatic patients. In some embodiments, the determining or having determined that the subject with metastatic prostate cancer is expected to respond less or only minimally better to treatment comprising ADT and a taxane compound, for example docetaxel, than to treatment comprising ADT and not comprising a taxane compound, for example docetaxel, comprises the risk score being, or not being greater than, 0.85, 0.80, 0.70, 0.60, 0.50, 0.40, 0.30.0.20, or 0.10 on a scale of 0 to 1, or a range defined by any two of the preceding values, for example, 0-0.85, 0.1-75.0.2-0.65, 0.3-0.85, 0-0.50, 0-35.0.1-0.60, 0.2-0.50, 0-0.40, 0.1-0.30.0-0.20, or 0-0.10. In some embodiments, the determining or having determined that the subject with metastatic prostate cancer is expected to respond less or only minimally better to treatment comprising ADT and a taxane compound, for example docetaxel, than to treatment comprising ADT and not comprising a taxane compound, for example docetaxel, is based on the risk score for the sample being ≤ 0.85 on a scale of 0 to 1. In some embodiments, the expected better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or at least of, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45% or 50%, or a range defined by any two of the preceding values, for example, 5-50%, 5-35%, 30-50%, or 15-40% as compared to treatment comprising ADT and not comprising a taxane compound, for example docetaxel. In some embodiments, the expected better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase inoverall survival of, or at least of 10%, 15%, 20%, 25%, or 30%. In some embodiments, the expected less or minimally better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or not greater than, 30%, 25%, 20%, 15%, 10%, 5%, 0%, or a range defined by any two of the preceding values, for example, 30-0, 30-15% 15-0%, 15-5%, or 20-10%, as compared to treatment comprising ADT and not comprising a taxane compound, for example docetaxel. In some embodiments, the expected less or minimally better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or not greater than, 15%, 10%, 5% or 0% as compared to treatment comprising ADT and not comprising a taxane compound, for example docetaxel. In some embodiments, the population of metastatic patients comprises, or comprises at least 10, 25, 50, 75 or 100 patients, or a range defined by any two of the preceding values, for example, 10-100, 75-100, 10-50, or 50-100.

[0029] In some embodiments, the method comprises selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and a taxane compound, for example docetaxel, based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients and / or the risk score being > 0.85 on a scale from 0 to 1. In some embodiments, the risk score is calculated using a GLMNet model. In some embodiments, the selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and a taxane compound, for example docetaxel, is based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients. In some embodiments, the selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and a taxane compound, for example docetaxel comprises the risk score being greater than, 0.7, 0.75, 0.8, 0.85, 0.9 or 0.95 on a scale from 0 to 1 or a range defined by any two of the preceding values, for example, 0.7-0.95, 0.7-0.85, 0.8-0.9, 0.8-0.95, 0.85-0.95, or 0.75-0.95. In some embodiments, the selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and a taxane compound, for example docetaxel, comprises the risk score being > 0.85 on a scale from 0 to 1. In some embodiments, selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and not comprising a taxane compound, for example docetaxel, is based on the risk score for the samplebeing equal to or below the median value of the risk score observed in a population of metastatic patients and / or the risk score being ≤ 0.85 on a scale of 0 to 1. In some embodiments, selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and not comprising a taxane compound, for example docetaxel, is based on the risk score for the sample being equal to or below the median value of the risk score observed in a population of metastatic patients. In some embodiments, selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and not comprising a taxane compound, for example docetaxel, comprises the risk score being, or not being greater than, 0.85, 0.80, 0.70, 0.60, 0.50, 0.40, 0.30.0.20, or 0.10 on a scale of 0 to 1, or a range defined by any two of the preceding values, for example, 0-0.85, 0.1-75. 0.2-0.65, 0.3-0.85, 0-0.50, 0-35. 0.1-0.60, 0.2-0.50, 0-0.40, 0.1- 0.30. 0-0.20, or 0-0.10. In some embodiments, selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and not comprising a taxane compound, for example docetaxel, is based on the risk score for the sample being ≤ 0.85 on a scale of 0 to 1. In some embodiments, the expected better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or at least of, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45% or 50%, or a range defined by any two of the preceding values, for example, 5-50%, 5-35%, 30-50%, or 15-40% as compared to treatment comprising ADT and not comprising a taxane compound, for example docetaxel. In some embodiments, the expected better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or at least of 10%, 15%, 20%, 25%, or 30%. In some embodiments, the expected less or minimally better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or not greater than, 30%, 25%, 20%, 15%, 10%, 5%, 0%, or a range defined by any two of the preceding values, for example, 30-0, 30-15% 15-0%, 15-5%, or 20-10%, as compared to treatment comprising ADT and not comprising a taxane compound, for example docetaxel. In some embodiments, the expected less or minimally better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or not greater than, 15%, 10%, 5% or 0% as compared to treatment comprising ADT and not comprising a taxane compound, for example docetaxel. In some embodiments, the population of metastatic patients comprises, orcomprises at least 10, 25, 50, 75 or 100 patients, or a range defined by any two of the preceding values, for example, 10-100, 75-100, 10-50, or 50-100.

[0030] In some embodiments, the subject has low-volume metastatic cancer. In some embodiments, the low-volume metastatic cancer subject does not have a visceral metastasis. In some embodiments, the low-volume metastatic cancer subject does not have a visceral metastasis and does not have ≥ 4 bone metastases with ≥ 1 outside the vertebral bodies or pelvis. In some embodiments, the low-volume metastatic cancer subject does not have ≥ 4 bone metastases with ≥ 1 outside the vertebral bodies or pelvis. In some embodiments, the subject has high-volume metastatic cancer. In some embodiments, the high-volume metastatic cancer subject has a visceral metastasis. In some embodiments, the high-volume metastatic cancer subject has ≥ 4 bone metastases with ≥ 1 outside the vertebral bodies or pelvis.

[0031] In some embodiments, the expected response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or at least of, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45% or 50%, or a range defined by any two of the preceding values, for example, 5-50%, 5-35%, 30-50%, or 15-40% as compared to treatment comprising ADT and not comprising a taxane compound, for example docetaxel. In some embodiments, the expected better response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or at least of 10%, 15%, 20%, 25%, or 30%. In some embodiments the response is measured at 3 years, e.g., post- treatment. In some embodiments, the expected response is based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and the risk score being > 0.85 on a scale from 0 to 1, for example, 0.87, 0.9.0.94, 0.97, 0.98, or 1, or a range defined by any two of the preceding values, for example, 0.87-1, 0.9-0.98, 0.94-0.97 or 0.97-1. In some embodiments, the expected response is based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients.

[0032] In some embodiments, the expected response is based on the risk score for the sample being > 0.85 on a scale from 0 to 1. In some embodiments, the expected response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or not greater than, 30%, 25%, 20%, 15%, 10%, 5%, 0%, or a range defined by any two of the preceding values, for example, 30-0, 30-15% 15-0%, 15-5%, or 20-10%, as compared to treatment comprising ADT and not comprising a taxane compound, for example docetaxel. In some embodiments, the expected response to treatment comprising ADT and a taxane compound, for example docetaxel, is an increase in overall survival of, or not greater than, 15%, 10%, 5% or 0% as compared to treatment comprising ADT and not comprising a taxane compound, for example docetaxel. In some embodiments the response is measured at 3 years, e.g., post-treatment. In some embodiments, the expected response is based on the risk score for the sample being equal to or below the median value of the risk score observed in a population of metastatic patients and the risk score being ≤ 0.85 on a scale of 0 to 1, for example 0, 0.1, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, or 0.85, or a range defined by any two of the preceding values, for example, 0-0.85, 0.1-75. 0.2-0.65, 0.3-0.85, 0-0.50, 0-35. 0.1-0.60, 0.2-0.50, 0- 0.40, 0.1-0.30. 0-0.20, or 0-0.10. In some embodiments, the expected response is based on the risk score for the sample being equal to or below the median value of the risk score observed in a population of metastatic patients. In some embodiments, the expected response is based on the risk score for the sample being ≤ 0.85 on a scale of 0 to 1.

[0033] In some embodiments, the determining or having determined the expected response to treatment comprising ADT and a taxane compound, for example docetaxel, is in comparison to a treatment comprising ADT without a taxane compound, for example docetaxel.

[0034] In some embodiments, the determining or having determined the expected response of the subject with metastatic prostate cancer to treatment comprising ADT and a taxane compound, for example docetaxel, is not based on prognostic clinical variables. In some embodiments, the prognostic clinical variables are tumor stage, nodal stage, metastatic tumor volume categorization, a Gleason score and a serum PSA level of the subject. In some embodiments, the prognostic clinical variables are tumor stage, nodal stage, metastatic tumor volume categorization, and a Gleason score. In some embodiments, the prognostic clinical variable is a serum PSA level of the subject. In some embodiments, the determining or having determined the expected response of the subject with metastatic prostate cancer to treatment comprising ADT and the taxane compound is further based on one or more prognostic clinical variables, optionally wherein the prognostic clinical variables are tumor stage, nodal stage,metastatic tumor volume categorization, a Gleason score and / or a serum PSA level of the subject.

[0035] In some embodiments, the metastatic prostate cancer is castration-sensitive prostate cancer.

[0036] In some embodiments, the taxane compound is selected from docetaxel, paclitaxel, and cabazitaxel. In some embodiments, the taxane compound is docetaxel. In some embodiments, the taxane compound is not docetaxel. In some embodiments, the taxane compound is paclitaxel. In some embodiments, the taxane compound is cabazitaxel.

[0037] In some embodiments, the obtaining or having obtained the expression level of the plurality of targets comprises utilizing a microarray to assess on the plurality of targets, performing qPCR on the plurality of targets, and / or sequencing the plurality of targets. In some embodiments, the sample is from a radical prostatectomy. In some embodiments, the sample is from a resected specimen. In some embodiments, the sample is from a transurethral resection of prostate (TURP) specimen. In some embodiments, the sample is from a biopsy of the prostate cancer. In some embodiments, the biopsy is a needle biopsy. In some embodiments, the sample is from a primary prostate tumor.

[0038] In some embodiments, the population of metastatic patients comprises, or comprises at least 10, 25, 50, 75 or 100 patients, or a range defined by any two of the preceding values, for example, 10-100, 75-100, 10-50, or 50-100. In some embodiments, the population of metastatic patients comprises at least 10, 25, 50, 75 or 100 patients.

[0039] Disclosed herein are kits for use in detecting and / or determining a response to treatment according to any one of the preceding methods, or methods disclosed elsewhere herein. In some embodiments, the kit comprises reagents for obtaining the expression level of biomarkers comprising or consisting of each of the plurality of targets. In some embodiments, the reagents comprise primer(s) and / or probe(s) for obtaining the expression level of each of the plurality of targets. Coding and Non-coding Targets

[0040] In some embodiments, the methods disclosed herein comprise assaying the expression level of a plurality of targets. The plurality of targets may comprise coding targets and / or non-coding targets of a protein-coding gene or a non protein-coding gene. A protein-coding gene structure may comprise an exon and an intron. The exon may further comprise a coding sequence (CDS) and an untranslated region (UTR). The protein-coding gene may be transcribed to produce a pre-mRNA and the pre-mRNA may be processed to produce a mature mRNA. The mature mRNA may be translated to produce a protein.

[0041] In some embodiments, a non protein-coding gene structure may comprise an exon and intron. In some embodiments, the exon region of a non protein-coding gene primarily contains a UTR. The non protein-coding gene may be transcribed to produce a pre- mRNA and the pre-mRNA may be processed to produce a non-coding RNA (ncRNA).

[0042] In some embodiments, a coding target may comprise a coding sequence of an exon. A non-coding target may comprise a UTR sequence of an exon, intron sequence, intergenic sequence, promoter sequence, non-coding transcript, CDS antisense, intronic antisense, UTR antisense, or non-coding transcript antisense. A non-coding transcript may comprise a non-coding RNA (ncRNA).

[0043] In some embodiments, the plurality of targets are differentially expressed. In some embodiments, a plurality of probe selection regions (PSRs) is differentially expressed.

[0044] In some embodiments, the plurality of targets comprises one or more targets selected from Tables 1, 2, or 3. In some embodiments, the plurality of targets comprises at least about 2, at least about 3, at least about 4, at least about 5, at least about 6, at least about 7, at least about 8, at least about 9, or at least about 10 targets selected from Tables 1, 2, or 3. In some embodiments, the plurality of targets comprises at least about 12, at least about 15, at least about 17, at least about 20, at least about 22, at least about 25, at least about 27, at least about 30, at least about 32, at least about 35, at least about 37, or at least about 40 targets selected from Tables 1, 2, or 3. In some embodiments, the targets are selected from Table 1. In some embodiments, the targets are selected from Table 2. In some embodiments, the targets are selected from Table 3. In some embodiments, the plurality of targets comprises a coding target, non-coding target, or any combination thereof. In some embodiments, the coding target comprises an exonic sequence. In some embodiments, the non-coding target comprises a non- exonic sequence. In some embodiments, a non-coding target comprises a UTR sequence, an intronic sequence, or a non-coding RNA transcript. In some embodiments, a non-coding target comprises sequences which partially overlap with a UTR sequence or an intronic sequence. A non-coding target also includes non-exonic transcripts. Exonic sequences may compriseregions on a protein-coding gene, such as an exon, UTR, or a portion thereof. Non-exonic sequences may comprise regions on a protein-coding, non protein-coding gene, or a portion thereof. For example, non-exonic sequences may comprise intronic regions, promoter regions, intergenic regions, a non-coding transcript, an exon anti-sense region, an intronic anti-sense region, UTR anti-sense region, non-coding transcript anti-sense region, or a portion thereof. In some embodiments, the plurality of targets comprises a non-coding RNA transcript. Probes / Primers

[0045] The present disclosure provides for a probe set (e.g., in a kit) for predicting a response to treatment in metastatic prostate cancer in a subject comprising a plurality of probes. In some embodiments, the probe set may comprise one or more polynucleotide probes. In some embodiments, individual polynucleotide probes comprise a nucleotide sequence derived from the nucleotide sequence of the target sequences or complementary sequences thereof. The nucleotide sequence of the polynucleotide probe is designed such that it corresponds to, or is complementary to the target sequences. In some embodiments the polynucleotide probe can hybridize under either stringent or lowered stringency hybridization conditions to a region of the target sequences, to the complement thereof, or to a nucleic acid sequence (such as a cDNA) derived therefrom. In some embodiments, the selection of the polynucleotide probe sequences and determination of their uniqueness is carried out in silico using suitable techniques known in the art, for example, based on a BLASTN search of the polynucleotide sequence in question against gene sequence databases, such as the Human Genome Sequence, UniGene, dbEST or the non-redundant database at NCBI. In some embodiments, the polynucleotide probe is complementary to a region of a target mRNA derived from a target sequence in the probe set. In some embodiments, computer programs can also be employed to select probe sequences that may not cross hybridize or may not hybridize non-specifically.

[0046] One skilled in the art understands that the nucleotide sequence of the polynucleotide probe need not be identical to its target sequence in order to hybridize thereto. The polynucleotide probes of the present disclosure, therefore, comprise a nucleotide sequence that is at least about 65% identical to a region of the coding target or non-coding target selected from Tables 1, 2, or 3. In some embodiments, the nucleotide sequence of the polynucleotideprobe is at least about 70% identical a region of the coding target or non-coding target from Tables 1, 2, or 3. In some embodiments, the nucleotide sequence of the polynucleotide probe is at least about 75% identical a region of the coding target or non-coding target from Tables 1, 2, or 3. In some embodiments, the nucleotide sequence of the polynucleotide probe is at least about 80% identical a region of the coding target or non-coding target from Tables 1, 2, or 3. In some embodiments, the nucleotide sequence of the polynucleotide probe is at least about 85% identical a region of the coding target or non-coding target from Tables 1, 2, or 3. In some embodiments, the nucleotide sequence of the polynucleotide probe is at least about 90% identical a region of the coding target or non-coding target from Tables 1, 2, or 3. In some embodiments, the nucleotide sequence of the polynucleotide probe is at least about 95% identical to a region of the coding target or non-coding target from Tables 1, 2, or 3. In some embodiments, the targets are selected from Table 1. In some embodiments, the targets are selected from Table 2. In some embodiments, the targets are selected from Table 3.

[0047] Suitable methods of determining sequence identity are known in the art. In some embodiments, identity is determined, for example, by using the BLASTN program of the University of Wisconsin Computer Group (GCG) software or provided on the NCBI website. The nucleotide sequence of the polynucleotide probes of the present disclosure may exhibit variability by differing (e.g. by nucleotide substitution, including transition or transversion) at one, two, three, four or more nucleotides from the sequence of the coding target or non-coding target.

[0048] In some embodiments, other suitable criteria known in the art are employed in the design of the polynucleotide probes of the present disclosure. For example, the probes can be designed to have <50% G content and / or between about 25% and about 70% G+C content. Strategies to optimize probe hybridization to the target nucleic acid sequence can also be included in the process of probe selection.

[0049] In some embodiments, hybridization under particular pH, salt, and temperature conditions are optimized by taking into account melting temperatures and by using empirical rules that correlate with desired hybridization behaviors. Computer models may be used for predicting the intensity and concentration-dependence of probe hybridization.

[0050] In some embodiments, the polynucleotide probes of the present disclosure range in length from about 15 nucleotides to the full length of the coding target or non-codingtarget. In some embodiments, the polynucleotide probes are at least about 15 nucleotides in length. In some embodiments, the polynucleotide probes are at least about 20 nucleotides in length. In some embodiments, the polynucleotide probes are at least about 25 nucleotides in length. In some embodiments, the polynucleotide probes are between about 15 nucleotides and about 500 nucleotides in length. In some embodiments, the polynucleotide probes are between about 15 nucleotides and about 450 nucleotides, about 15 nucleotides and about 400 nucleotides, about 15 nucleotides and about 350 nucleotides, about 15 nucleotides and about 300 nucleotides, about 15 nucleotides and about 250 nucleotides, about 15 nucleotides and about 200 nucleotides in length. In some embodiments, the probes are at least 15 nucleotides in length. In some embodiments, the probes are at least 15 nucleotides in length. In some embodiments, the probes are at least 20 nucleotides, at least 25 nucleotides, at least 50 nucleotides, at least 75 nucleotides, at least 100 nucleotides, at least 125 nucleotides, at least 150 nucleotides, at least 200 nucleotides, at least 225 nucleotides, at least 250 nucleotides, at least 275 nucleotides, at least 300 nucleotides, at least 325 nucleotides, at least 350 nucleotides, at least 375 nucleotides in length.

[0051] In some embodiments the polynucleotide probes of a probe set can comprise RNA, DNA, RNA or DNA mimetics, or combinations thereof, and can be single-stranded or double-stranded. In some embodiments, the polynucleotide probes are composed of naturally- occurring nucleobases, sugars and covalent internucleoside (backbone) linkages as well as polynucleotide probes having non-naturally-occurring portions which function similarly. Such modified or substituted polynucleotide probes may provide desirable properties such as, for example, enhanced affinity for a target gene and increased stability. The probe set may comprise a coding target and / or a non-coding target. In some embodiments, the probe set comprises a combination of a coding target and non-coding target.

[0052] In some embodiments, the probe set comprises a plurality of target sequences that hybridize to at least about 5 coding targets and / or non-coding targets selected from Tables 1, 2, or 3. In some embodiments, the probe set comprises a plurality of target sequences that hybridize to at least about 10 coding targets and / or non-coding targets selected from Tables 1, 2, or 3. In some embodiments, the probe set comprises a plurality of target sequences that hybridize to at least about 15 coding targets and / or non-coding targets selected from Tables 1, 2, or 3. In some embodiments, the probe set comprises a plurality of targetsequences that hybridize to at least about 20 coding targets and / or non-coding targets selected from Tables 1, 2, or 3. In some embodiments, the probe set comprises a plurality of target sequences that hybridize to at least about 30 coding targets and / or non-coding targets selected from Tables 1, 2, or 3. In some embodiments, the targets are selected from Table 1. In some embodiments, the targets are selected from Table 2. In some embodiments, the targets are selected from Table 3.

[0053] In some embodiments, the probe set comprises a plurality of target sequences that hybridize to a plurality of targets, wherein the at least about 20% of the plurality of targets are targets selected from Tables 1, 2, or 3. In some embodiments, the probe set comprises a plurality of target sequences that hybridize to a plurality of targets, wherein the at least about 25% of the plurality of targets are targets selected from Tables 1, 2, or 3. In some embodiments, the probe set comprises a plurality of target sequences that hybridize to a plurality of targets, wherein the at least about 30% of the plurality of targets are targets selected from Tables 1, 2, or 3. In some embodiments, the probe set comprises a plurality of target sequences that hybridize to a plurality of targets, wherein the at least about 35% of the plurality of targets are targets selected from Tables 1, 2, or 3. In some embodiments, the probe set comprises a plurality of target sequences that hybridize to a plurality of targets, wherein the at least about 40% of the plurality of targets are targets selected from Tables 1, 2, or 3. In some embodiments, the probe set comprises a plurality of target sequences that hybridize to a plurality of targets, wherein the at least about 45% of the plurality of targets are targets selected from Tables 1, 2, or 3. In some embodiments, the probe set comprises a plurality of target sequences that hybridize to a plurality of targets, wherein the at least about 50% of the plurality of targets are targets selected from Tables 1, 2, or 3. In some embodiments, the probe set comprises a plurality of target sequences that hybridize to a plurality of targets, wherein the at least about 60% of the plurality of targets are targets selected from Tables 1, 2, or 3. In some embodiments, the probe set comprises a plurality of target sequences that hybridize to a plurality of targets, wherein the at least about 70% of the plurality of targets are targets selected from Tables 1, 2, or 3. In some embodiments, the targets are selected from Table 1. In some embodiments, the targets are selected from Table 2. In some embodiments, the targets are selected from Table 3.

[0054] In some embodiments, the system of the present disclosure further provides for primers and primer pairs capable of amplifying target sequences defined by the probe set, or fragments or subsequences or complements thereof. The nucleotide sequences of the probe set may be provided in computer-readable media for in silico applications and as a basis for the design of appropriate primers for amplification of one or more target sequences of the probe set.

[0055] In some embodiments, primers based on the nucleotide sequences of target sequences are designed for use in amplification of the target sequences. In some embodiments, for use in amplification reactions such as PCR, a pair of primers are used. In some embodiments, the primers may hybridize to specific sequences of the probe set under stringent conditions. In some embodiments, the conditions are of high stringency, as known in the art. In some embodiments, the pairs of primers are chosen so as to generate an amplification product of at least about 50 nucleotides. In some embodiments, the amplification product is at least about 100 nucleotides. In some embodiments, algorithms for the selection of primer sequences are known, and are available in commercial software packages. These primers may be used in standard quantitative or qualitative PCR-based assays to assess transcript expression levels of RNAs defined by the probe set. In some embodiments, these primers are used in combination with probes, such as molecular beacons in amplifications using real-time PCR.

[0056] In some embodiments, the primers or primer pairs, when used in an amplification reaction. In some embodiments, the primers or primer pairs amplify at least a portion of a nucleic acid sequence of a target selected from any of Tables 1, 2, or 3 (or subgroups thereof as set forth herein), an RNA form thereof, or a complement to either thereof. In some embodiments, the targets are selected from Table 1. In some embodiments, the targets are selected from Table 2. In some embodiments, the targets are selected from Table 3.

[0057] As is known in the art, a nucleoside is a base-sugar combination, and a nucleotide is a nucleoside that further includes a phosphate group covalently linked to the sugar portion of the nucleoside. In forming oligonucleotides, the phosphate groups covalently link adjacent nucleosides to one another to form a linear polymeric compound, with the normal linkage or backbone of RNA and DNA being a 3' to 5' phosphodiester linkage. In some embodiments, polynucleotide probes or primers useful in this disclosure include oligonucleotides containing modified backbones or non-natural internucleoside linkages. Insome embodiments, oligonucleotides having modified backbones include both those that retain a phosphorus atom in the backbone and those that lack a phosphorus atom in the backbone. In some embodiments, modified oligonucleotides that do not have a phosphorus atom in their internucleoside backbone can also be considered to be oligonucleotides.

[0058] In some embodiments, the nucleotide sequence of the entire length of the polynucleotide probe or primer does not need to be derived from the target sequence. In some embodiments, for example, the polynucleotide probe may comprise nucleotide sequences at the 5' and / or 3' termini that are not derived from the target sequences. In some embodiments, nucleotide sequences which are not derived from the nucleotide sequence of the target sequence may provide additional functionality to the polynucleotide probe. In some embodiments, for example, they may provide a restriction enzyme recognition sequence or a "tag" that facilitates detection, isolation, purification or immobilization onto a solid support. In some embodiments, the additional nucleotides may provide a self-complementary sequence that allows the primer / probe to adopt a hairpin configuration. Such configurations are necessary for certain probes, for example, molecular beacon and Scorpion probes, which can be used in solution hybridization techniques.

[0059] In some embodiments, the polynucleotide probes or primers incorporate moieties useful in detection, isolation, purification, or immobilization, if desired. Such moieties are well-known in the art (see, for example, Ausubel et al., (1997 & updates) Current Protocols in Molecular Biology, Wiley & Sons, New York) and are chosen such that the ability of the probe to hybridize with its target sequence is not affected. In some embodiments, examples of suitable moieties are detectable labels, such as radioisotopes, fluorophores, chemiluminophores, enzymes, colloidal particles, and fluorescent microparticles, as well as antigens, antibodies, haptens, avidin / streptavidin, biotin, haptens, enzyme cofactors / substrates, enzymes, and the like. In some embodiments, a label is attached to or incorporated into a probe or primer polynucleotide to allow detection and / or quantitation of a target polynucleotide representing the target sequence of interest. In some embodiments, the target polynucleotide is the expressed target sequence RNA itself, a cDNA copy thereof, or an amplification product derived therefrom, and may be the positive or negative strand, so long as it can be specifically detected in the assay being used. In some embodiments, an antibody is labeled.

[0060] In some embodiments, for certain multiplex formats, labels used for detecting different targets are distinguishable. In some embodiments, the label is attached directly (e.g., via covalent linkage) or indirectly, e.g., via a bridging molecule or series of molecules (e.g., a molecule or complex that can bind to an assay component, or via members of a binding pair that can be incorporated into assay components, e.g. biotin-avidin or streptavidin). Many labels are commercially available in activated forms which can readily be used for such conjugation (for example through amine acylation), or labels may be attached through suitable known or determinable conjugation schemes, many of which are known in the art.

[0061] Labels useful in some embodiments disclosed herein include a substance which can be detected when bound to or incorporated into the biomolecule of interest. In some embodiments, an appropriate detection method is used, including for example, optical, spectroscopic, electrical, piezoelectrical, magnetic, Raman scattering, surface plasmon resonance, colorimetric, calorimetric, etc. In some embodiments, the label is selected from a chromophore, a lumiphore, a fluorophore, one member of a quenching system, a chromogen, a hapten, an antigen, a magnetic particle, a material exhibiting nonlinear optics, a semiconductor nanocrystal, a metal nanoparticle, an enzyme, an antibody or binding portion or equivalent thereof, an aptamer, and one member of a binding pair, and combinations thereof. In some embodiments, a quenching scheme is used, wherein a quencher and a fluorophore as members of a quenching pair are used on a probe, such that a change in optical parameters occurs upon binding to the target introduce or quench the signal from the fluorophore. One example of such a system is a molecular beacon. Suitable quencher / fluorophore systems are known in the art. In some embodiments, the label is bound through a variety of intermediate linkages. In some embodiments, for example, a polynucleotide may comprise a biotin-binding species, and an optically detectable label is conjugated to biotin and then bound to the labeled polynucleotide. In some embodiments, a polynucleotide sensor may comprise an immunological species such as an antibody or fragment, and a secondary antibody containing an optically detectable label may be added.

[0062] Chromophores useful in some embodiments disclosed herein include any suitable substance which can absorb energy and emit light. In some embodiments of multiplexed assays, a plurality of different signaling chromophores are used with detectablydifferent emission spectra. In some embodiments, the chromophore is a lumophore or a fluorophore. In some embodiments, the fluorophores includes fluorescent dyes, semiconductor nanocrystals, lanthanide chelates, polynucleotide-specific dyes and green fluorescent protein.

[0063] In some embodiments, coding schemes are used, comprising encoded particles and / or encoded tags associated with different polynucleotides of the disclosure. A variety of different suitable coding schemes are known in the art, including fluorophores, including SCNCs, deposited metals, and RF tags.

[0064] In some embodiments, polynucleotides from the described target sequences are employed as probes for detecting target sequences expression, for ligation amplification schemes, or used as primers for amplification schemes of all or a portion of a target sequences. When amplified, either strand produced by amplification may be provided in purified and / or isolated form.

[0065] In some embodiments, complements may take any polymeric form capable of base pairing, including nucleic acid such as RNA or DNA, or may be a neutral polymer such as a peptide nucleic acid. Polynucleotides of the disclosure can be selected from the subsets of the recited nucleic acids described herein, as well as their complements.

[0066] In some embodiments, polynucleotides of the disclosure comprise at least 20 consecutive bases of the nucleic acid sequence of a target selected from any of Tables 1, 2, or 3 or a complement thereto. The polynucleotides may comprise at least 21, 22, 23, 24, 25, 27, 30, 32, 35 or more consecutive bases of the nucleic acids sequence of a target selected from any of Tables 1, 2, or 3, as applicable. In some embodiments, the targets are selected from Table 1. In some embodiments, the targets are selected from Table 2. In some embodiments, the targets are selected from Table 3.

[0067] In some embodiments, the polynucleotides are provided in a variety of formats, including as solids, in solution, or in an array. In some embodiments, the polynucleotides comprise one or more labels, which may be chemically and / or enzymatically incorporated into the polynucleotide.

[0068] In some embodiments, solutions comprising polynucleotide and a solvent are also provided. In some embodiments, the solvent is water or is predominantly aqueous. In some embodiments, the solution may comprise at least two, three, four, five, six, seven, eight, nine, ten, twelve, fifteen, seventeen, twenty or more different polynucleotides, includingprimers and primer pairs, of the disclosure. In some embodiments, additional substances are included in the solution, alone or in combination, including one or more labels, additional solvents, buffers, biomolecules, polynucleotides, and one or more enzymes useful for performing methods described herein, including polymerases and ligases. The solution may further comprise a primer or primer pair capable of amplifying a polynucleotide of the disclosure present in the solution.

[0069] In some embodiments, one or more polynucleotides provided herein are provided on a substrate. The substrate can comprise a wide range of material, either biological, nonbiological, organic, inorganic, or a combination of any of these. For example, the substrate may be a polymerized Langmuir Blodgett film, functionalized glass, Si, Ge, GaAs, GaP, SiO2, SiN4, modified silicon, or any one of a wide variety of gels or polymers such as (poly)tetrafluoroethylene, (poly)vinylidenedifluoride, polystyrene, cross-linked polystyrene, polyacrylic, polylactic acid, polyglycolic acid, poly(lactide coglycolide), polyanhydrides, poly(methyl methacrylate), poly(ethylene-co-vinyl acetate), polysiloxanes, polymeric silica, latexes, dextran polymers, epoxies, polycarbonates, or combinations thereof. Conducting polymers and photoconductive materials can be used.

[0070] In some embodiments, substrates are planar crystalline substrates such as silica based substrates (e.g. glass, quartz, or the like), or crystalline substrates used in, e.g., the semiconductor and microprocessor industries, such as silicon, gallium arsenide, indium doped GaN and the like, and include semiconductor nanocrystals.

[0071] In some embodiments, the substrate can take the form of an array, a photodiode, an optoelectronic sensor such as an optoelectronic semiconductor chip or optoelectronic thin-film semiconductor, or a biochip. The location(s) of probe(s) on the substrate can be addressable; this can be done in highly dense formats, and the location(s) can be microaddressable or nanoaddressable.

[0072] In some embodiments, silica aerogels can also be used as substrates, and can be prepared by suitable methods known in the art. Aerogel substrates may be used as free standing substrates or as a surface coating for another substrate material.

[0073] In some embodiments, the substrate can take any form and typically is a plate, slide, bead, pellet, disk, particle, microparticle, nanoparticle, strand, precipitate, optionally porous gel, sheets, tube, sphere, container, capillary, pad, slice, film, chip, multiwellplate or dish, optical fiber, etc. The substrate can be any form that is rigid or semi-rigid. The substrate may contain raised or depressed regions on which an assay component is located. The surface of the substrate can be etched using known techniques to provide for desired surface features, for example trenches, v-grooves, mesa structures, or the like.

[0074] In some embodiments, surfaces on the substrate are composed of the same material as the substrate or can be made from a different material, and can be coupled to the substrate by chemical or physical means. Such coupled surfaces may be composed of any of a wide variety of materials, for example, polymers, plastics, resins, polysaccharides, silica or silica-based materials, carbon, metals, inorganic glasses, membranes, or any of the above-listed substrate materials. The surface can be optically transparent and can have surface Si-OH functionalities, such as those found on silica surfaces.

[0075] In some embodiments, the substrate and / or its optional surface is chosen to provide appropriate characteristics for the synthetic and / or detection methods used. The substrate and / or surface can be transparent to allow the exposure of the substrate by light applied from multiple directions. The substrate and / or surface may be provided with reflective "mirror" structures to increase the recovery of light.

[0076] In some embodiments, the substrate and / or its surface is generally resistant to, or is treated to resist, the conditions to which it is to be exposed in use, and can be optionally treated to remove any resistant material after exposure to such conditions.

[0077] In some embodiments, the substrate or a region thereof is encoded so that the identity of the sensor located in the substrate or region being queried may be determined. Any suitable coding scheme can be used, for example optical codes, RFID tags, magnetic codes, physical codes, fluorescent codes, and combinations of codes. Samples

[0078] In some embodiments, samples for use in the present disclosure comprise nucleic acids suitable for providing RNA expression information. In some embodiments, the biological sample from which the expressed RNA is obtained and analyzed for target sequence expression can be any material suspected of comprising cancer tissue or cells. In some embodiments, the sample is a biological sample used directly in a method of the disclosure. In some embodiments, the sample is a sample prepared from a biological sample.

[0079] In some embodiments, the sample or portion of the sample comprising or suspected of comprising cancer tissue or cells is any source of biological material, including cells, tissue or fluid, including bodily fluids. Non-limiting examples of the source of the sample include an aspirate, a needle biopsy, a cytology pellet, a bulk tissue preparation or a section thereof obtained for example by surgery or autopsy, lymph fluid, blood, plasma, serum, tumors, and organs. In some embodiments, the sample is from urine. In some embodiments, the sample is from blood, plasma or serum. In some embodiments, the sample is from saliva.

[0080] In some embodiments, the samples are archival samples, having a known and documented medical outcome, or are samples from current patients whose ultimate medical outcome is not yet known.

[0081] In some embodiments, the sample are dissected prior to molecular analysis. The sample may be prepared via macrodissection of a bulk tumor specimen or portion thereof, or may be treated via microdissection, for example via Laser Capture Microdissection (LCM).

[0082] In some embodiments, the sample may initially be provided in a variety of states, as fresh tissue, fresh frozen tissue, fine needle aspirates, and may be fixed or unfixed. In some embodiments, medical laboratories routinely prepare medical samples in a fixed state, which facilitates tissue storage. A variety of fixatives can be used to fix tissue to stabilize the morphology of cells, and may be used alone or in combination with other agents. In some embodiments, fixatives include crosslinking agents, alcohols, acetone, Bouin's solution, Zenker solution, Hely solution, osmic acid solution and Carnoy solution.

[0083] In some embodiments, crosslinking fixatives can comprise any agent suitable for forming two or more covalent bonds, for example an aldehyde. In some embodiments, sources of aldehydes used for fixation include formaldehyde, paraformaldehyde, glutaraldehyde and formalin. In some embodiments, the crosslinking agent comprises formaldehyde, which may be included in its native form or in the form of paraformaldehyde or formalin. One of skill in the art would appreciate that for samples in which crosslinking fixatives have been used special preparatory steps may be necessary including for example heating steps and proteinase-k digestion.

[0084] In some embodiments, one or more alcohols are used to fix tissue, alone or in combination with other fixatives. In some embodiments, alcohols used for fixation include methanol, ethanol and isopropanol.

[0085] In some embodiments, formalin, which comprises both an alcohol, for example methanol, and formaldehyde, both of which can act to fix a biological sample, is used.

[0086] In some embodiments, the biological sample, which may be fixed or unfixed, is embedded in an embedding medium. In some embodiments, the embedding media used in histology is paraffin, Tissue-Tek® V.I.P.TM, Paramat, Paramat Extra, Paraplast, Paraplast X-tra, Paraplast Plus, Peel Away Paraffin Embedding Wax, Polyester Wax, Carbowax Polyethylene Glycol, PolyfinTM, Tissue Freezing Medium TFMFM, Cryo-GefTM, and OCT Compound (Electron Microscopy Sciences, Hatfield, PA). Prior to molecular analysis, the embedding material may be removed via any suitable techniques, as known in the art. For example, where the sample is embedded in wax, the embedding material may be removed by extraction with organic solvent(s), for example xylenes. Kits are commercially available for removing embedding media from tissues. Samples or sections thereof may be subjected to further processing steps as needed, for example serial hydration or dehydration steps.

[0087] In some embodiments, the sample is a fixed, wax-embedded biological sample. Frequently, samples from medical laboratories are provided as fixed, wax-embedded samples, most commonly as formalin-fixed, paraffin embedded (FFPE) tissues.

[0088] In some embodiments, the target polynucleotide that is assayed is prepared synthetically (e.g. in the case of control sequences). In some embodiments, the target polynucleotide that is assayed is purified from the biological source and subjected to one or more preparative steps. The RNA may be purified to remove or diminish one or more undesired components from the biological sample or to concentrate it. In some embodiments, where the RNA is too concentrated for the particular assay, it may be diluted. RNA Extraction

[0089] In some embodiments, RNA is extracted and purified from biological samples using any suitable technique. A number of suitable techniques are known in the art, and several are commercially available (e.g., FormaPure nucleic acid extraction kit, Agencourt Biosciences, Beverly MA, High Pure FFPE RNA Micro Kit, Roche Applied Science, Indianapolis, IN). RNA can be extracted from frozen tissue sections using TRIzol (Invitrogen, Carlsbad, CA) and purified using RNeasy Protect kit (Qiagen, Valencia, CA). RNA can befurther purified using DNAse I treatment (Ambion, Austin, TX) to eliminate any contaminating DNA. RNA concentrations can be made using a Nanodrop ND-1000 spectrophotometer (Nanodrop Technologies, Rockland, DE). RNA can be further purified to eliminate contaminants that interfere with cDNA synthesis by cold sodium acetate precipitation. RNA integrity can be evaluated by running electropherograms, and RNA integrity number (RIN, a correlative measure that indicates intactness of mRNA) can be determined using the RNA 6000 PicoAssay for the Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA). Kits

[0090] In some embodiments, kits for performing a method disclosed herein are provided. In some embodiments, the kit comprise a container or housing for holding the components of the kit, one or more vessels containing one or more nucleic acid(s). In some embodiments, one or more vessels contain one or more reagents. In some embodiments, the reagents include those described herein (e.g., primers, probes, etc.). In some embodiments, the reagents include those useful for performing a methods disclosed herein, for example, amplification reagents, primers, probes, etc. In some embodiments, the reagents include one or more probes, primers or primer pairs, enzymes (including polymerases and ligases), intercalating dyes, labeled probes, and labels that can be incorporated into amplification products.

[0091] In some embodiments, the kit comprises primers or primer pairs specific for those subsets and combinations of target sequences described herein. In some embodiments, at least two, three, four or five primers or pairs of primers suitable for selectively amplifying the same number of target sequence-specific polynucleotides can be provided in kit form. In some embodiments, the kit comprises from five to fifty primers or pairs of primers suitable for amplifying the same number of target sequence-representative polynucleotides of interest.

[0092] In some embodiments, the primers or primer pairs of the kit, when used in an amplification reaction, specifically amplify a non-coding target, coding target, or non- exonic target described herein, for example a nucleic acid sequence corresponding to a target selected from Tables 1, 2, or 3, an RNA form thereof, or a complement to either thereof. In some embodiments, the kit may include a plurality of such primers or primer pairs which canspecifically amplify a corresponding plurality of different amplify a non-coding target, coding target, or non-exonic transcript described herein, a nucleic acid sequence corresponding to a target selected from Tables 1, 2, or 3, RNA forms thereof, or complements thereto. In some embodiments, at least two, three, four or five primers or pairs of primers suitable for selectively amplifying the same number of target sequence-specific polynucleotides can be provided in kit form. In some embodiments, the kit comprises from five to fifty primers or pairs of primers suitable for amplifying the same number of target sequence-representative polynucleotides of interest. In some embodiments, the targets are selected from Table 1. In some embodiments, the targets are selected from Table 2. In some embodiments, the targets are selected from Table 3.

[0093] In some embodiments, the reagents may independently be provided in liquid or solid form. In some embodiments, the reagents are provided in mixtures. In some embodiments, control samples and / or nucleic acids are provided in the kit. Control samples may include tissue and / or nucleic acids obtained from or representative of tumor samples from patients showing no evidence of disease, as well as tissue and / or nucleic acids obtained from or representative of tumor samples from patients that develop systemic cancer.

[0094] In some embodiments, the nucleic acids are provided in an array format, and thus an array or microarray may be included in the kit. In some embodiments, the kit is certified by a government agency for use in prognosing the disease outcome of cancer patients and / or for designating a treatment modality.

[0095] In some embodiments, instructions for using the kit to perform one or more methods of the disclosure is provided with the container, and can be provided in any fixed medium. The instructions may be located inside or outside the container or housing, and / or may be printed on the interior or exterior of any surface thereof. A kit may be in multiplex form for concurrently detecting and / or quantitating one or more different target polynucleotides representing the expressed target sequences. Amplification and Hybridization

[0096] In some embodiments, following sample collection and nucleic acid extraction, the nucleic acid portion of the sample comprising RNA that is or can be used to prepare the target polynucleotide(s) of interest can be subjected to one or more preparativereactions. These preparative reactions can include in vitro transcription (IVT), labeling, fragmentation, amplification and other reactions. mRNA can first be treated with reverse transcriptase and a primer to create cDNA prior to detection, quantitation and / or amplification; this can be done in vitro with purified mRNA or in situ, e.g., in cells or tissues affixed to a slide. "Amplification" has its plain and ordinary meaning as understood in light of the specification, and refers to any process of producing at least one copy of a nucleic acid, in this case an expressed RNA, and in many cases produces multiple copies. An amplification product can be RNA or DNA, and may include a complementary strand to the expressed target sequence. DNA amplification products can be produced initially through reverse translation and then from further amplification reactions. The amplification product may include all or a portion of a target sequence. In some embodiments, the amplification reaction may result in the amplification product being labeled. A variety of amplification methods are suitable for use, including polymerase-based methods and ligation-based methods. In some embodiments, amplification techniques include the polymerase chain reaction method (PCR), the lipase chain reaction (LCR), ribozyme-based methods, self sustained sequence replication (3SR), nucleic acid sequence-based amplification (NASBA), the use of Q Beta replicase, reverse transcription, nick translation, and the like.

[0097] In some embodiments, asymmetric amplification reactions are used to amplify one strand representing the target sequence that is used for detection of the target polynucleotide. In some embodiments, the presence and / or amount of the amplification product itself is used to determine the expression level of a given target sequence. In some embodiments, the amplification product is used to hybridize to an array or other substrate comprising sensor polynucleotides which are used to detect and / or quantitate target sequence expression.

[0098] In some embodiments, the first cycle of amplification in polymerase-based methods forms a primer extension product complementary to the template strand. If the template is single-stranded RNA, a polymerase with reverse transcriptase activity is used in the first amplification to reverse transcribe the RNA to DNA, and additional amplification cycles can be performed to copy the primer extension products. In some embodiments, the primers for a PCR are designed to hybridize to regions in their corresponding template that canproduce an amplifiable segment. In some embodiments, each primer hybridizes so that its 3' nucleotide is paired to a nucleotide in its complementary template strand that is located 3' from the 3' nucleotide of the primer used to replicate that complementary template strand in the PCR reaction.

[0099] In some embodiments the target polynucleotide is amplified by contacting one or more strands of the target polynucleotide with a primer and a polymerase having suitable activity to extend the primer and copy the target polynucleotide to produce a full-length complementary polynucleotide or a smaller portion thereof. Any enzyme having a polymerase activity that can copy the target polynucleotide can be used, including DNA polymerases, RNA polymerases, reverse transcriptases, enzymes having more than one type of polymerase or enzyme activity. The enzyme can be thermolabile or thermostable. Mixtures of enzymes can also be used. In some embodiments the enzymes used can include: DNA polymerases such as DNA Polymerase I ("Pol I"), the Klenow fragment of Pol I, T4, T7, Sequenase® T7, Sequenase® Version 2.0 T7, Tub, Taq, Tth, Pfic, Pfu, Tsp, Tfl, Tli and Pyrococcus sp GB-D DNA polymerases; RNA polymerases such as E. coil, SP6, T3 and T7 RNA polymerases; and reverse transcriptases such as AMV, M-MuLV, MMLV, RNAse H MMLV (SuperScript®), SuperScript® II, ThermoScript®, HIV-1, and RAV2 reverse transcriptases. All of these enzymes are commercially available. In some embodiments, polymerases with multiple specificities include RAV2 and Tli (exo-) polymerases. In some embodiments, thermostable polymerases include Tub, Taq, Tth, Pfic, Pfu, Tsp, Tf1, Tli and Pyrococcus sp. GB-D DNA polymerases.

[0100] In some embodiments, suitable reaction conditions are chosen to permit amplification of the target polynucleotide and can include pH, buffer, ionic strength, presence and concentration of one or more salts, presence and concentration of reactants and cofactors such as nucleotides and magnesium and / or other metal ions (e.g., manganese). optional In some embodiments, cosolvents, temperature, thermal cycling profiles for polymerase chain reaction amplification schemes may depend in part on the polymerase being used as well as the nature of the sample. In some embodiments, cosolvents can include formamide (e.g., from about 2 to about 10 %), glycerol (e.g., from about 5 to about 10 %), and DMSO (e.g., from about 0.9 to about 10 %). Techniques may be used in the amplification scheme in order to minimize the production of false positives or artifacts produced during amplification. These include"touchdown" PCR, hot-start techniques, use of nested primers, or designing PCR primers so that they form stem-loop structures in the event of primer-dimer formation and thus are not amplified. Techniques to accelerate PCR can be used, for example centrifugal PCR, which allows for greater convection within the sample, and comprising infrared heating steps for rapid heating and cooling of the sample. One or more cycles of amplification can be performed. An excess of one primer can be used to produce an excess of one primer extension product during PCR. In some embodiments, the primer extension product produced in excess is the amplification product to be detected. A plurality of different primers may be used to amplify different target polynucleotides or different regions of a particular target polynucleotide within the sample.

[0101] In some embodiments, an amplification reaction is performed under conditions which allow a labeled sensor polynucleotide to hybridize to the amplification product during at least part of an amplification cycle. In some embodiments, when the assay is performed in this manner, real-time detection of this hybridization event can take place by monitoring for light emission or fluorescence during amplification, as known in the art.

[0102] In some embodiments, where the amplification product is to be used for hybridization to an array or microarray, a number of suitable commercially available amplification products are available. These include amplification kits available from NuGEN, Inc. (San Carlos, CA), including the WT-OvationTm System, WT-OvationTm System v2, WT-OvationTm Pico System, WT-Ovation'm FFPE Exon Module, WT-OvationTm FFPE Exon Module RiboAmp and RiboAmpPlusRNA Amplification Kits (MDS Analytical Technologies (formerly Arcturus) (Mountain View, CA), Genisphere, Inc. (Hatfield, PA), including the RampUp PlusTM and SenseAmpTM RNA Amplification kits, alone or in combination. Amplified nucleic acids may be subjected to one or more purification reactions after amplification and labeling, for example using magnetic beads (e.g., RNAC1ean magnetic beads, Agencourt Biosciences).

[0103] In some embodiments, multiple RNA biomarkers are analyzed using real- time quantitative multiplex RT-PCR platforms and other multiplexing technologies such as GenomeLab GeXP Genetic Analysis System (Beckman Coulter, Foster City, CA), SmartCycler® 9600 or GeneXpert(R) Systems (Cepheid, Sunnyvale, CA), ABI 7900 HT Fast Real Time PCR system (Applied Biosystems, Foster City, CA), LightCycler® 480 System(Roche Molecular Systems, Pleasanton, CA), xMAP 100 System (Luminex, Austin, TX) Solexa Genome Analysis System (Illumina, Hayward, CA), OpenArray Real Time qPCR (BioTrove, Woburn, MA) and BeadXpress System (Illumina, Hayward, CA). Detection and / or Quantification of Target Sequences

[0104] In some embodiments, any suitable method of detecting and / or quantitating the expression of the encoded target sequences is used. In some embodiments, the expressed target sequences is directly detected and / or quantitated, or may be copied and / or amplified to allow detection of amplified copies of the expressed target sequences or its complement.

[0105] In some embodiments, methods for detecting and / or quantifying a target can include Northern blotting, sequencing, array or microarray hybridization, by enzymatic cleavage of specific structures (e.g., an Invader® assay, Third Wave Technologies, e.g. as described in U.S. Pat. Nos. 5,846,717, 6,090,543; 6,001,567; 5,985,557; and 5,994,069) and amplification methods, e.g. RT-PCR, including in a TaqMan® assay (PE Biosystems, Foster City, Calif., e.g. as described in U.S. Pat. Nos. 5,962,233 and 5,538,848), and may be quantitative or semi-quantitative, and may vary depending on the origin, amount and condition of the available biological sample. In some embodiments, combinations of these methods may also be used. In some embodiments, for example, nucleic acids are amplified, labeled and subjected to microarray analysis.

[0106] In some embodiments, target sequences are detected by sequencing. In some embodiments, sequencing methods comprise whole genome sequencing or exome sequencing. In some embodiments, sequencing methods such as Maxim-Gilbert, chain- termination, or high-throughput systems are used. In some embodiments, suitable sequencing techniques include classic dideoxy sequencing reactions (e.g., Sanger method) using labeled terminators or primers and gel separation in slab or capillary, sequencing by synthesis using reversibly terminated labeled nucleotides, pyrosequencing, 454 sequencing, allele specific hybridization to a library of labeled oligonucleotide probes, sequencing by synthesis using allele specific hybridization to a library of labeled clones that is followed by ligation, real time monitoring of the incorporation of labeled nucleotides during a polymerization step, and SOLiD sequencing.

[0107] In some embodiments, methods for detecting and / or quantifying a target include single-molecule sequencing (e.g., Helicos, PacBio), sequencing by synthesis (e.g., Illumina, Ion Torrent), sequencing by ligation (e.g., ABI SOLID), sequencing by hybridization (e.g., Complete Genomics), in situ hybridization, bead-array technologies (e.g., Luminex xMAP, Illumina BeadChips), branched DNA technology (e.g., Panomics, Genisphere). In some embodiments, sequencing methods use fluorescent (e.g., Illumina) or electronic (e.g., Ion Torrent, Oxford Nanopore) methods of detecting nucleotides. Reverse Transcription for QRT-PCR Analysis

[0108] In some embodiments, reverse transcription is be performed by any suitable method known in the art. In some embodiments, for example, reverse transcription is performed using the Omniscript kit (Qiagen, Valencia, CA), Superscript III kit (Invitrogen, Carlsbad, CA), for RT-PCR. In some embodiments, target-specific priming is performed in order to increase the sensitivity of detection of target sequences and generate target-specific cDNA. TaqMan®Gene Expression Analysis

[0109] In some embodiments, TaqMan®RT-PCR is performed using Applied Biosystems Prism (ABI) 7900 HT instruments in a 51.11 volume with target sequence-specific cDNA equivalent to 1 ng total RNA.

[0110] In some embodiments, primer and probe concentrations for TaqMan analysis are added to amplify fluorescent amplicons using PCR cycling conditions such as 95°C for 10 minutes for one cycle, 95°C for 20 seconds, and 60°C for 45 seconds for 40 cycles. In some embodiments, a reference sample is assayed to ensure reagent and process stability. In some embodiments, negative controls (e.g., no template) are assayed to monitor any exogenous nucleic acid contamination. Classification Arrays

[0111] In some embodiments, a probe set or probes derived therefrom is provided in an array format. In the context of the present disclosure, an "array" has its plain and ordinary meaning as understood in light of the specification, and refers to a spatially or logicallyorganized collection of polynucleotide probes. In some embodiments, an array comprising probes specific for a coding target, non-coding target, or a combination thereof is used. In some embodiments, an array comprising probes specific for two or more of transcripts of a target selected from any of Tables 1, 2, or 3 or a product derived thereof is used. In some embodiments, an array is specific for 5, 10, 15, 20, 25, 30, 50, 75, 100, 150, 200 or more of transcripts of a target selected from any of Tables 1, 2, or 3. In some embodiments, the targets are selected from Table 1. In some embodiments, the targets are selected from Table 2. In some embodiments, the targets are selected from Table 3. In some embodiments, expression of these sequences is detected alone or in combination with other transcripts. In some embodiments, an array is used which comprises a wide range of sensor probes for prostate-specific expression products, along with appropriate control sequences. In some embodiments, the array may comprise the Human Exon 1.0 ST Array (HuEx 1.0 ST, Affymetrix, Inc., Santa Clara, CA.).

[0112] In some embodiments, the polynucleotide probes are attached to a solid substrate and are ordered so that the location (e.g., on the substrate) and the identity of each are known. In some embodiments, the polynucleotide probes are attached to one of a variety of solid substrates capable of withstanding the reagents and conditions necessary for use of the array. In some embodiments, examples include, but are not limited to, polymers, such as (poly)tetrafluoroethylene, (poly)vinylidenedifluoride, polystyrene, polycarbonate, polypropylene and polystyrene; ceramic; silicon; silicon dioxide; modified silicon; (fused) silica, quartz or glass; functionalized glass; paper, such as filter paper; diazotized cellulose; nitrocellulose filter; nylon membrane; and polyacrylamide gel pad. In some embodiments, substrates that are transparent to light are useful for arrays that are used in an assay that involves optical detection. In some embodiments, examples of array formats include membrane or filter arrays (for example, nitrocellulose, nylon arrays), plate arrays (for example, multi-well, such as a 24-, 96-, 256-, 384-, 864- or 1536-well, microtitre plate arrays), pin arrays, and bead arrays (for example, in a liquid "slurry"). In some embodiments, arrays on substrates such as glass or ceramic slides, often referred to as chip arrays or "chips," are well known in the art and are used in the assays disclosed herein.Data Analysis

[0113] In some embodiments, one or more pattern recognition methods is used in analyzing the expression level of target sequences. In some embodiments, the pattern recognition method comprises a linear combination of expression levels, or a nonlinear combination of expression levels. In some embodiments, expression measurements for RNA transcripts or combinations of RNA transcript levels are formulated into linear or non-linear models or algorithms (e.g., an 'expression signature') and converted into a likelihood score. In some embodiments, this likelihood score indicates the probability that a biological sample is from a patient who will respond to treatment with a taxane compound, for example docetaxel. In some embodiments, the likelihood score is used to distinguish these disease states. In some embodiments, the models and / or algorithms are provided in machine readable format, and may be used to correlate expression levels or an expression profile with a response to a taxane compound, for example docetaxel treatment for a patient or class of patients.

[0114] In some embodiments, assaying the expression level for a plurality of targets comprises the use of an algorithm or classifier. Array data can be managed, classified, and analyzed using suitable techniques known in the art. In some embodiments, assaying the expression level for a plurality of targets comprises probe set modeling and data pre- processing. In some embodiments, probe set modeling and data pre-processing is derived using the Robust Multi-Array (RMA) algorithm or variants GC-RMA, fRMA, Probe Logarithmic Intensity Error (PLIER) algorithm or variant iterPLIER. In some embodiments, variance or intensity filters are applied to pre-process data using the RMA algorithm, for example by removing target sequences with a standard deviation of < 10 or a mean intensity of < 100 intensity units of a normalized data range, respectively.

[0115] In some embodiments, assaying the expression level for a plurality of targets may comprise the use of a machine learning algorithm. In some embodiments, the machine learning algorithm comprises a supervised learning algorithm. In some embodiments, examples of supervised learning algorithms include Average One-Dependence Estimators (AODE), Artificial neural network (e.g., Backpropagation), Bayesian statistics (e.g., Naive Bayes classifier, Bayesian network, Bayesian knowledge base), Case-based reasoning, Decision trees, Inductive logic programming, Gaussian process regression, Group method of data handling (GMDH), Learning Automata, Learning Vector Quantization, Minimummessage length (e.g., decision trees, decision graphs, etc.), Lazy learning, Instance-based learning Nearest Neighbor Algorithm, Analogical modeling, Probably approximately correct learning (PAC) learning, Ripple down rules, a knowledge acquisition methodology, Symbolic machine learning algorithms, Subsymbolic machine learning algorithms, Support vector machines, Random Forests, Ensembles of classifiers, Bootstrap aggregating (bagging), and Boosting. Supervised learning may comprise ordinal classification such as regression analysis and Information fuzzy networks (IFN). In some embodiments, supervised learning methods comprise statistical classification, such as AODE, Linear classifiers (e.g., Fisher's linear discriminant, Logistic regression, Naive Bayes classifier, Perceptron, and Support vector machine), quadratic classifiers, k-nearest neighbor, Boosting, Decision trees (e.g., C4.5, Random forests), Bayesian networks, and Hidden Markov models.

[0116] In some embodiments, the machine learning algorithms also comprise an unsupervised learning algorithm. In some embodiments, examples of unsupervised learning algorithms include artificial neural network, Data clustering, Expectation-maximization algorithm, Self-organizing map, Radial basis function network, Vector Quantization, Generative topographic map, Information bottleneck method, and IBSEAD. In some embodiments, unsupervised learning comprises association rule learning algorithms such as Apriori algorithm, Eclat algorithm and FP-growth algorithm. Hierarchical clustering, such as Single-linkage clustering and Conceptual clustering, and is also used. In some embodiments, unsupervised learning comprises partitional clustering such as K-means algorithm and Fuzzy clustering.

[0117] In some embodiments, the machine learning algorithms comprise a reinforcement learning algorithm. Examples of reinforcement learning algorithms include, but are not limited to, temporal difference learning, Q-learning and Learning Automata. In some embodiments, the machine learning algorithm comprises Data Pre-processing.

[0118] In some embodiments, the machine learning algorithms includes, but are not limited to, Average One-Dependence Estimators (AODE), Fisher's linear discriminant, Logistic regression, , Perceptron, Multilayer Perceptron, Artificial Neural Networks, Support vector machines, Quadratic classifiers, Boosting, Decision trees, C4.5, Bayesian networks, Hidden Markov models, High-Dimensional Discriminant Analysis, and Gaussian Mixture Models. In some embodiments, the machine learning algorithm comprises support vectormachines, Naïve Bayes classifier, k-nearest neighbor, high-dimensional discriminant analysis, or Gaussian mixture models. In some embodiments, the machine learning algorithm comprises Random Forests. Additional Techniques and Tests

[0119] In some embodiments, suitable factors known in the art for diagnosing and / or suggesting, selecting, designating, recommending or otherwise determining a course of treatment for a patient or class of patients having or suspected of having prostate cancer can be employed in combination with measurements of the target sequence expression. In some embodiments, the methods disclosed herein may include additional techniques such as cytology, histology, ultrasound analysis, MRI results, CT scan results, and measurements of PSA levels.

[0120] In some embodiments, certified tests for classifying disease status and / or designating treatment modalities are also used in diagnosing, predicting, and / or monitoring the status or outcome of a cancer in a subject. In some embodiments, a certified test comprises a means for characterizing the expression levels of one or more of the target sequences of interest, and a certification from a government regulatory agency endorsing use of the test for classifying the disease status of a biological sample, e.g., response to treatment with a taxane compound, for example docetaxel.

[0121] In some embodiments, the certified test comprises reagents for amplification reactions used to detect and / or quantitate expression of the target sequences to be characterized in the test. In some embodiments, an array of probe nucleic acids is used, with or without prior target amplification, for use in measuring target sequence expression.

[0122] In some embodiments, the test is submitted to an agency having authority to certify the test for use in distinguishing disease status and / or outcome. In some embodiments, results of detection of expression levels of the target sequences used in the test and correlation with disease status and / or outcome are submitted to the agency. In some embodiments, a certification authorizing the diagnostic and / or prognostic use of the test is obtained.

[0123] In some embodiments, also provided are portfolios of expression levels comprising a plurality of normalized expression levels of the targets selected from any ofTables 1, 2, or 3. In some embodiments, the targets are selected from Table 1. In some embodiments, the targets are selected from Table 2. In some embodiments, the targets are selected from Table 3. Such portfolios may be provided by performing the methods described herein to obtain expression levels from an individual patient or from a group of patients. In some embodiments, the expression levels are normalized by any suitable method known in the art. In some embodiments, normalization methods that are used include Robust Multichip Average (RMA), probe logarithmic intensity error estimation (PLIER), non-linear fit (NLFIT) quantile-based and nonlinear normalization, and combinations thereof. In some embodiments, background correction can also be performed on the expression data. In some embodiments, techniques useful for background correction include mode of intensities, normalized using median polish probe modeling and sketch-normalization.

[0124] In some embodiments, portfolios are established such that the combination of targets in the portfolio exhibit improved sensitivity and specificity relative to known methods. In some embodiments, a group of targets are selected for inclusion in a portfolio based on a small standard deviation in expression measurements correlating with greater specificity. Other measurements of variation such as correlation coefficients can also be used in this capacity. The disclosure also encompasses the above methods where the expression level determines the status or outcome (e.g., response to treatment with a taxane compound, for example docetaxel) of a prostate cancer in the subject with at least about 45% specificity, at least about 50% specificity, at least about 55% specificity, at least about 60% specificity, at least about 65% specificity, at least about 70% specificity, at least about 75% specificity, at least about 80% specificity. In some embodiments, t the expression level determines the status or outcome of a cancer in the subject with at least about 85% specificity, at least about 90% specificity, or at least about 95% specificity.

[0125] The disclosure also encompasses the any of the methods disclosed herein where the accuracy of diagnosing, monitoring, and / or predicting a status or outcome (e.g., response to treatment with a taxane compound, for example docetaxel) of a prostate cancer is at least about 45%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, or at least about 95%.

[0126] In some embodiments, the accuracy of a classifier or biomarker (e.g., signature) is determined by the 95% confidence interval (CI). In some embodiments, a classifier or biomarker is considered to have good accuracy if the 95% CI does not overlap 1. In some embodiments, the 95% CI of a classifier or biomarker is at least about 1.08, 1.10, 1.12, 1.14, 1.15, 1.16, 1.17, 1.18, 1.19, 1.20, 1.21, 1.22, 1.23, 1.24, 1.25, 1.26, 1.27, 1.28, 1.29, 1.30, 1.31, 1.32, 1.33, 1.34, or 1.35 or more. In some embodiments, the 95% CI of a classifier or biomarker is at least about 1.14, 1.15, 1.16, 1.20, 1.21, 1.26, or 1.28. In some embodiments, the 95% CI of a classifier or biomarker is less than about 1.75, 1.74, 1.73, 1.72, 1.71, 1.70, 1.69, 1.68, 1.67, 1.66, 1.65, 1.64, 1.63, 1.62, 1.61, 1.60, 1.59, 1.58, 1.57, 1.56, 1.55, 1.54, 1.53, 1.52, 1.51, 1.50 or less. In some embodiments, the 95% CI of a classifier or biomarker is less than about 1.61, 1.60, 1.59, 1.58, 1.56, 1.55, or 1.53. In some embodiments, the 95% CI of a classifier or biomarker is between about 1.10 to 1.70, between about 1.12 to about 1.68, between about 1.14 to about 1.62, between about 1.15 to about 1.61, between about 1.15 to about 1.59, between about 1.16 to about 1.160, between about 1.19 to about 1.55, between about 1.20 to about 1.54, between about 1.21 to about 1.53, between about 1.26 to about 1.63, between about 1.27 to about 1.61, or between about 1.28 to about 1.60.

[0127] In some embodiments, the accuracy of a biomarker or classifier is dependent on the difference in range of the 95% CI (e.g., difference in the high value and low value of the 95% CI interval). In some embodiments, biomarkers or classifiers with large differences in the range of the 95% CI interval have greater variability and are considered less accurate than biomarkers or classifiers with small differences in the range of the 95% CI intervals. In some embodiments, a biomarker or classifier is considered more accurate if the difference in the range of the 95% CI is less than about 0.60, 0.55, 0.50, 0.49, 0.48, 0.47, 0.46, 0.45, 0.44, 0.43, 0.42, 0.41, 0.40, 0.39, 0.38, 0.37, 0.36, 0.35, 0.34, 0.33, 0.32, 0.31, 0.30, 0.29, 0.28, 0.27, 0.26, 0.25 or less. In some embodiments, the difference in the range of the 95% CI of a biomarker or classifier is less than about 0.48, 0.45, 0.44, 0.42, 0.40, 0.37, 0.35, 0.33, or 0.32. In some embodiments, the difference in the range of the 95% CI for a biomarker or classifier is between about 0.25 to about 0.50, between about 0.27 to about 0.47, or between about 0.30 to about 0.45.

[0128] In some embodiments of the methods disclosed herein, the sensitivity is at least about 45%, at least about 50%, at least about 55%, at least about 60%, at least about 65%,at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, or at least about 95%.

[0129] In some embodiments, the classifiers or biomarkers disclosed herein are clinically significant. In some embodiments, the clinical significance of the classifiers or biomarkers is determined by the AUC value. In order to be clinically significant, the AUC value is at least about 0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.85, 0.9, or 0.95. In some embodiments, the clinical significance of the classifiers or biomarkers is determined by the percent accuracy. For example, in some embodiments, a classifier or biomarker is determined to be clinically significant if the accuracy of the classifier or biomarker is at least about 50%, 55%, 60%, 65%, 70%, 72%, 75%, 77%, 80%, 82%, 84%, 86%, 88%, 90%, 92%, 94%, 96%, or 98%.

[0130] In some embodiments, the clinical significance of the classifiers or biomarkers is determined by the median fold difference (MDF) value. In some embodiments, in order to be clinically significant, the MDF value is at least about 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.9, or 2.0. In some embodiments, the MDF value is greater than or equal to 1.1. In some embodiments, the MDF value is greater than or equal to 1.2. In some embodiments, alternatively, or additionally, the clinical significance of the classifiers or biomarkers is determined by the t-test P-value. In some embodiments, in order to be clinically significant, the t-test P-value is less than about 0.070, 0.065, 0.060, 0.055, 0.050, 0.045, 0.040, 0.035, 0.030, 0.025, 0.020, 0.015, 0.010, 0.005, 0.004, or 0.003. The t-test P-value can be less than about 0.050. In some embodiments, the t-test P-value is less than about 0.010.

[0131] In some embodiments, the clinical significance of the classifiers or biomarkers is determined by the clinical outcome. For example, in some embodiments, different clinical outcomes can have different minimum or maximum thresholds for AUC values, MDF values, t-test P-values, and accuracy values that determine whether the classifier or biomarker is clinically significant. In some embodiments, a classifier or biomarker is considered clinically significant if the P-value of the t-test is less than about 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01, 0.005, 0.004, 0.003, 0.002, or 0.001. In some embodiments, the P- value is based on any of the following comparisons: BCR vs non-BCR, CP vs non-CP, PCSM vs non-PCSM. For example, in some embodiments, a classifier or biomarker is determined to be clinically significant if the P-values of the differences between the KM curves for BCR vsnon-BCR, CP vs non-CP, PCSM vs non-PCSM is lower than about 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01, 0.005, 0.004, 0.003, 0.002, or 0.001.

[0132] In some embodiments, the performance of the classifier or biomarker is based on the odds ratio. In some embodiments, a classifier or biomarker is considered to have good performance if the odds ratio is at least about 1.30, 1.31, 1.32, 1.33, 1.34, 1.35, 1.36, 1.37, 1.38, 1.39, 1.40, 1.41, 1.42, 1.43, 1.44, 1.45, 1.46, 1.47, 1.48, 1.49, 1.50, 1.52, 1.55, 1.57, 1.60, 1.62, 1.65, 1.67, 1.70 or more. In some embodiments, the odds ratio of a classifier or biomarker is at least about 1.33.

[0133] In some embodiments, the clinical significance of the classifiers and / or biomarkers is based on Univariable Analysis Odds Ratio P-value (uvaORPval ). In some embodiments, the Univariable Analysis Odds Ratio P-value (uvaORPval ) of the classifier and / or biomarker is between about 0-0.4. In some embodiments, the Univariable Analysis Odds Ratio P-value (uvaORPval ) of the classifier and / or biomarker is between about 0-0.3. In some embodiments, the Univariable Analysis Odds Ratio P-value (uvaORPval ) of the classifier and / or biomarker is between about 0-0.2. In some embodiments, the Univariable Analysis Odds Ratio P-value (uvaORPval ) of the classifier and / or biomarker is less than or equal to 0.25, 0.22, 0.21, 0.20, 0.19, 0.18, 0.17, 0.16, 0.15, 0.14, 0.13, 0.12, 0.11. In some embodiments, the Univariable Analysis Odds Ratio P-value (uvaORPval ) of the classifier and / or biomarker is less than or equal to 0.10, 0.09, 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01. In some embodiments, the Univariable Analysis Odds Ratio P-value (uvaORPval ) of the classifier and / or biomarker is less than or equal to 0.009, 0.008, 0.007, 0.006, 0.005, 0.004, 0.003, 0.002, 0.001.

[0134] In some embodiments, the clinical significance of the classifiers and / or biomarkers (e.g., signature) is based on multivariable analysis Odds Ratio P-value (mvaORPval ). In some embodiments, the multivariable analysis Odds Ratio P-value (mvaORPval ) of the classifier and / or biomarker is between about 0-1. In some embodiments, the multivariable analysis Odds Ratio P-value (mvaORPval ) of the classifier and / or biomarker is between about 0-0.9. In some embodiments, the multivariable analysis Odds Ratio P-value (mvaORPval ) of the classifier and / or biomarker is between about 0-0.8. In some embodiments, the multivariable analysis Odds Ratio P-value (mvaORPval ) of the classifier and / or biomarker is less than or equal to 0.90, 0.88, 0.86, 0.84, 0.82, 0.80. In some embodiments, themultivariable analysis Odds Ratio P-value (mvaORPval ) of the classifier and / or biomarker is less than or equal to 0.78, 0.76, 0.74, 0.72, 0.70, 0.68, 0.66, 0.64, 0.62, 0.60, 0.58, 0.56, 0.54, 0.52, 0.50. In some embodiments, the multivariable analysis Odds Ratio P-value (mvaORPval ) of the classifier and / or biomarker is less than or equal to 0.48, 0.46, 0.44, 0.42, 0.40, 0.38, 0.36, 0.34, 0.32, 0.30, 0.28, 0.26, 0.25, 0.22, 0.21, 0.20, 0.19, 0.18, 0.17, 0.16, 0.15, 0.14, 0.13, 0.12, 0.11. In some embodiments, the multivariable analysis Odds Ratio P-value (mvaORPval ) of the classifier and / or biomarker is less than or equal to 0.10, 0.09, 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01. In some embodiments, the multivariable analysis Odds Ratio P-value (mvaORPval ) of the classifier and / or biomarker is less than or equal to 0.009, 0.008, 0.007, 0.006, 0.005, 0.004, 0.003, 0.002, 0.001.

[0135] In some embodiments, the clinical significance of the classifiers and / or biomarkers is based on the Kaplan Meier P-value (KM P-value). In some embodiments, the Kaplan Meier P-value (KM P-value) of the classifier and / or biomarker is between about 0-0.8. In some embodiments, the Kaplan Meier P-value (KM P-value) of the classifier and / or biomarker is between about 0-0.7. In some embodiments, the Kaplan Meier P-value (KM P- value) of the classifier and / or biomarker is less than or equal to 0.80, 0.78, 0.76, 0.74, 0.72, 0.70, 0.68, 0.66, 0.64, 0.62, 0.60, 0.58, 0.56, 0.54, 0.52, 0.50. In some embodiments, the Kaplan Meier P-value (KM P-value) of the classifier and / or biomarker is less than or equal to 0.48, 0.46, 0.44, 0.42, 0.40, 0.38, 0.36, 0.34, 0.32, 0.30, 0.28, 0.26, 0.25, 0.22, 0.21, 0.20, 0.19, 0.18, 0.17, 0.16, 0.15, 0.14, 0.13, 0.12, 0.11. In some embodiments, the Kaplan Meier P-value (KM P-value) of the classifier and / or biomarker is less than or equal to 0.10, 0.09, 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01. In some embodiments, the Kaplan Meier P-value (KM P- value) of the classifier and / or biomarker is less than or equal to 0.009, 0.008, 0.007, 0.006, 0.005, 0.004, 0.003, 0.002, 0.001.

[0136] In some embodiments, the clinical significance of the classifiers and / or biomarkers is based on the survival AUC value (survAUC). In some embodiments, the survival AUC value (survAUC) of the classifier and / or biomarker is between about 0-1. In some embodiments, the survival AUC value (survAUC) of the classifier and / or biomarker is between about 0-0.9. In some embodiments, the survival AUC value (survAUC) of the classifier and / or biomarker is less than or equal to 1, 0.98, 0.96, 0.94, 0.92, 0.90, 0.88, 0.86, 0.84, 0.82, 0.80. In some embodiments, the survival AUC value (survAUC) of the classifier and / or biomarker isless than or equal to 0.80, 0.78, 0.76, 0.74, 0.72, 0.70, 0.68, 0.66, 0.64, 0.62, 0.60, 0.58, 0.56, 0.54, 0.52, 0.50. In some embodiments, the survival AUC value (survAUC) of the classifier and / or biomarker is less than or equal to 0.48, 0.46, 0.44, 0.42, 0.40, 0.38, 0.36, 0.34, 0.32, 0.30, 0.28, 0.26, 0.25, 0.22, 0.21, 0.20, 0.19, 0.18, 0.17, 0.16, 0.15, 0.14, 0.13, 0.12, 0.11. In some embodiments, the survival AUC value (survAUC) of the classifier and / or biomarker is less than or equal to 0.10, 0.09, 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01. In some embodiments, the survival AUC value (survAUC) of the classifier and / or biomarker is less than or equal to 0.009, 0.008, 0.007, 0.006, 0.005, 0.004, 0.003, 0.002, 0.001.

[0137] In some embodiments, the clinical significance of the classifiers and / or biomarkers is based on the Univariable Analysis Hazard Ratio P-value (uvaHRPval). In some embodiments, the Univariable Analysis Hazard Ratio P-value (uvaHRPval) of the classifier and / or biomarker is between about 0-0.4. In some embodiments, the Univariable Analysis Hazard Ratio P-value (uvaHRPval) of the classifier and / or biomarker is between about 0-0.3. In some embodiments, the Univariable Analysis Hazard Ratio P-value (uvaHRPval) of the classifier and / or biomarker is less than or equal to 0.40, 0.38, 0.36, 0.34, 0.32. In some embodiments, the Univariable Analysis Hazard Ratio P-value (uvaHRPval) of the classifier and / or biomarker is less than or equal to 0.30, 0.29, 0.28, 0.27, 0.26, 0.25, 0.24, 0.23, 0.22, 0.21, 0.20. In some embodiments, the Univariable Analysis Hazard Ratio P-value (uvaHRPval) of the classifier and / or biomarker is less than or equal to 0.19, 0.18, 0.17, 0.16, 0.15, 0.14, 0.13, 0.12, 0.11. In some embodiments, the Univariable Analysis Hazard Ratio P-value (uvaHRPval) of the classifier and / or biomarker is less than or equal to 0.10, 0.09, 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01. In some embodiments, the Univariable Analysis Hazard Ratio P-value (uvaHRPval) of the classifier and / or biomarker is less than or equal to 0.009, 0.008, 0.007, 0.006, 0.005, 0.004, 0.003, 0.002, 0.001.

[0138] In some embodiments, the clinical significance of the classifiers and / or biomarkers is based on the Multivariable Analysis Hazard Ratio P-value (mvaHRPval)mva HRPval. In some embodiments, the Multivariable Analysis Hazard Ratio P-value (mvaHRPval)mva HRPval of the classifier and / or biomarker is between about 0-1. In some embodiments, the Multivariable Analysis Hazard Ratio P-value (mvaHRPval)mva HRPval of the classifier and / or biomarker is between about 0-0.9. In some embodiments, the Multivariable Analysis Hazard Ratio P-value (mvaHRPval)mva HRPval of the classifierand / or biomarker is less than or equal to 1, 0.98, 0.96, 0.94, 0.92, 0.90, 0.88, 0.86, 0.84, 0.82, 0.80. In some embodiments, the Multivariable Analysis Hazard Ratio P-value (mvaHRPval)mva HRPval of the classifier and / or biomarker is less than or equal to 0.80, 0.78, 0.76, 0.74, 0.72, 0.70, 0.68, 0.66, 0.64, 0.62, 0.60, 0.58, 0.56, 0.54, 0.52, 0.50. In some embodiments, the Multivariable Analysis Hazard Ratio P-value (mvaHRPval)mva HRPval of the classifier and / or biomarker is less than or equal to 0.48, 0.46, 0.44, 0.42, 0.40, 0.38, 0.36, 0.34, 0.32, 0.30, 0.28, 0.26, 0.25, 0.22, 0.21, 0.20, 0.19, 0.18, 0.17, 0.16, 0.15, 0.14, 0.13, 0.12, 0.11. In some embodiments, the Multivariable Analysis Hazard Ratio P-value (mvaHRPval)mva HRPval of the classifier and / or biomarker is less than or equal to 0.10, 0.09, 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01. In some embodiments, the Multivariable Analysis Hazard Ratio P-value (mvaHRPval)mva HRPval of the classifier and / or biomarker is less than or equal to 0.009, 0.008, 0.007, 0.006, 0.005, 0.004, 0.003, 0.002, 0.001.

[0139] In some embodiments, the clinical significance of the classifiers and / or biomarkers is based on the Multivariable Analysis Hazard Ratio P-value (mvaHRPval). In some embodiments, the Multivariable Analysis Hazard Ratio P-value (mvaHRPval) of the classifier and / or biomarker is between about 0 to about 0.60. significance of the classifier and / or biomarker is based on the Multivariable Analysis Hazard Ratio P-value (mvaHRPval). In some embodiments, the Multivariable Analysis Hazard Ratio P-value (mvaHRPval) of the classifier and / or biomarker is between about 0 to about 0.50. significance of the classifier and / or biomarker is based on the Multivariable Analysis Hazard Ratio P-value (mvaHRPval). In some embodiments, the Multivariable Analysis Hazard Ratio P-value (mvaHRPval) of the classifier and / or biomarker is less than or equal to 0.50, 0.47, 0.45, 0.43, 0.40, 0.38, 0.35, 0.33, 0.30, 0.28, 0.25, 0.22, 0.20, 0.18, 0.16, 0.15, 0.14, 0.13, 0.12, 0.11, 0.10. In some embodiments, the Multivariable Analysis Hazard Ratio P-value (mvaHRPval) of the classifier and / or biomarker is less than or equal to 0.10, 0.09, 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01. In some embodiments, the Multivariable Analysis Hazard Ratio P-value (mvaHRPval) of the classifier and / or biomarker is less than or equal to 0.01, 0.009, 0.008, 0.007, 0.006, 0.005, 0.004, 0.003, 0.002, 0.001.

[0140] In some embodiments, the classifiers and / or biomarkers disclosed herein outperform current classifiers or clinical variables in providing clinically relevant analysis of a sample from a subject. In some embodiments, the classifiers or biomarkers more accuratelypredict a clinical outcome or status as compared to current classifiers or clinical variables. For example, in some embodiments, a classifier or biomarker may more accurately predict response of metastatic disease to treatment with a taxane compound, for example docetaxel. In some embodiments, the performance of a classifier or biomarker disclosed herein is based on the AUC value, odds ratio, 95% CI, difference in range of the 95% CI, p-value or any combination thereof.

[0141] In some embodiments, the performance of the classifiers and / or biomarkers disclosed herein is determined by AUC values and an improvement in performance is determined by the difference in the AUC value of the classifier or biomarker disclosed herein and the AUC value of current classifiers or clinical variables. In some embodiments, a classifier and / or biomarker disclosed herein outperforms current classifiers or clinical variables when the AUC value of the classifier and / or or biomarker disclosed herein is greater than the AUC value of the current classifiers or clinical variables by at least about 0.05, 0.06, 0.07, 0.08, 0.09, 0.10, 0.11, 0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, 0.19, 0.20, 0.022, 0.25, 0.27, 0.30, 0.32, 0.35, 0.37, 0.40, 0.42, 0.45, 0.47, 0.50 or more. In some embodiments, the AUC value of the classifier and / or or biomarker disclosed herein is greater than the AUC value of the current classifiers or clinical variables by at least about 0.10. In some embodiments, the AUC value of the classifier and / or or biomarker disclosed herein is greater than the AUC value of the current classifiers or clinical variables by at least about 0.13. In some embodiments, the AUC value of the classifier and / or or biomarker disclosed herein is greater than the AUC value of the current classifiers or clinical variables by at least about 0.18.

[0142] In some embodiments, the performance of the classifiers and / or biomarkers disclosed herein is determined by the odds ratios and an improvement in performance may be determined by comparing the odds ratio of the classifier or biomarker disclosed herein and the odds ratio of current classifiers or clinical variables. In some embodiments, comparison of the performance of two or more classifiers, biomarkers, and / or clinical variables is based on the comparison of the absolute value of (1-odds ratio) of a first classifier, biomarker or clinical variable to the absolute value of (1-odds ratio) of a second classifier, biomarker or clinical variable. In some embodiments, the classifier, biomarker or clinical variable with the greater absolute value of (1-odds ratio) is considered to have better performance as compared to the classifier, biomarker or clinical variable with a smaller absolute value of (1-odds ratio).

[0143] In some embodiments, the performance of a classifier, biomarker or clinical variable is based on the comparison of the odds ratio and the 95% confidence interval (CI). In some embodiments, for example, a first classifier, biomarker or clinical variable may have a greater absolute value of (1-odds ratio) than a second classifier, biomarker or clinical variable, however, the 95% CI of the first classifier, biomarker or clinical variable may overlap 1 (e.g., poor accuracy), whereas the 95% CI of the second classifier, biomarker or clinical variable does not overlap 1. In this instance, the second classifier, biomarker or clinical variable is considered to outperform the first classifier, biomarker or clinical variable because the accuracy of the first classifier, biomarker or clinical variable is less than the accuracy of the second classifier, biomarker or clinical variable. In another example, a first classifier, biomarker or clinical variable may outperform a second classifier, biomarker or clinical variable based on a comparison of the odds ratio; however, the difference in the 95% CI of the first classifier, biomarker or clinical variable is at least about 2 times greater than the 95% CI of the second classifier, biomarker or clinical variable. In this instance, the second classifier, biomarker or clinical variable is considered to outperform the first classifier.

[0144] In some embodiments, a classifier or biomarker disclosed herein is more accurate than a current classifier or clinical variable. In some embodiments, the classifier or biomarker disclosed herein is more accurate than a current classifier or clinical variable if the range of 95% CI of the classifier or biomarker disclosed herein does not span or overlap 1 and the range of the 95% CI of the current classifier or clinical variable spans or overlaps 1.

[0145] In some embodiments, a classifier or biomarker disclosed herein is more accurate than a current classifier or clinical variable. In some embodiments, the classifier or biomarker disclosed herein is more accurate than a current classifier or clinical variable when difference in range of the 95% CI of the classifier or biomarker disclosed herein is about 0.70, 0.60, 0.50, 0.40, 0.30, 0.20, 0.15, 0.14, 0.13, 0.12, 0.10, 0.09, 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02 times less than the difference in range of the 95% CI of the current classifier or clinical variable. In some embodiments, the classifier or biomarker disclosed herein is more accurate than a current classifier or clinical variable when difference in range of the 95% CI of the classifier or biomarker disclosed herein between about 0.20 to about 0.04 times less than the difference in range of the 95% CI of the current classifier or clinical variable.

[0146] In some embodiments, the methods disclosed herein may comprise the use of a genomic classifier (GC) model. In some embodiments, a general method for developing a GC model may comprise (a) providing a sample from a subject suffering from a cancer; (b) assaying the expression level for a plurality of targets; (c) generating a model by using a machine learning algorithm. In some embodiments, the machine learning algorithm comprises Random Forests. In some embodiments, a GC model is developed by using a machine learning algorithm to analyze and rank genomic features. In some embodiments, analyzing the genomic features comprises classifying one or more genomic features. In some embodiments, the method further comprise validating the classifier and / or refining the classifier by using a machine learning algorithm.

[0147] In some embodiments, the methods disclosed herein may comprise the use of a genomic-clinical classifier (GCC) model. In some embodiments, a general method for developing a GCC model comprises (a) providing a sample from a subject suffering from a cancer; (b) assaying the expression level for a plurality of targets; (c) generating a model by using a machine learning algorithm. In some embodiments, the machine learning algorithm comprises Random Forests. Embodiments

[0148] Some embodiments provided herein are described by way of the following numbered embodiments: 1. A method comprising: (a) obtaining or having obtained an expression level of a plurality of targets in a sample obtained from a subject with metastatic prostate cancer, wherein the plurality of targets comprises or consists of at least one target nucleic acid sequence selected from each of at least five of: UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, GLYATL1, PCAT-32, DNAH5, S1PR4, NFIB, and EPPK1; the biomarkers / genes listed in Table 1; the biomarkers / genes listed in Table 2; or the biomarkers / genes listed in Table 3; and (b) determining a response to treatment comprising ADT and docetaxel that the subject with metastatic prostate cancer is expected to have based on at least the expression level of each of the plurality of targets in the sample obtained in step (a).2. A method comprising: (a) obtaining or having obtained an expression level of a plurality of targets in a sample obtained from a subject with metastatic prostate cancer, wherein the plurality of targets comprises or consists of at least one target nucleic acid sequence selected from each of at least five of: UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, GLYATL1, PCAT-32, DNAH5, S1PR4, NFIB, and EPPK1; the biomarkers / genes listed in Table 1; the biomarkers / genes listed in Table 2; or the biomarkers / genes listed in Table 3; (b) determining or having determined a response to treatment comprising ADT and docetaxel that the subject with metastatic prostate cancer is expected to have based on at least the expression level of each of the plurality of targets in the sample obtained in step (a); and (c) administering or having administered to the subject with metastatic prostate cancer in (b) a treatment selected from: (i) a treatment comprising ADT and docetaxel ; or (ii) a treatment comprising ADT and not docetaxel, wherein the treatment is selected based on the expected response to treatment comprising ADT and docetaxel determined in (b). 3. The method of embodiment 1 or 2, wherein the expected response to treatment comprising ADT and docetaxel is one or more of the following: overall survival, metastasis- free survival, progression-free survival, and / or metastatic progression-free survival, optionally overall survival at 3 years. 4. The method of embodiment 2 or 3, wherein the treatment (i) comprising ADT and docetaxel further comprises an Androgen Receptor Pathway Inhibitor (ARPI), optionally wherein the ARPI is abiraterone, apalutamide, darolutamide, or enzalutamide. 5. The method of embodiment 4, wherein the treatment (i) comprising ADT and docetaxel further comprises abiraterone and optionally a corticosteroid, optionally wherein the corticosteroid is prednisone or prednisolone. 6. The method of any one of embodiments 1-5, wherein the plurality of targets comprises or consists of 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 or 22 target nucleic acid sequences, optionally wherein each target nucleic acid sequence is selected froma different gene, and / or not more than 2 target nucleic acid sequences are from the same gene, optionally wherein not more than 3 genes have 2 target nucleic acid sequences. 7. The method of any one of embodiments 1-6, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, and TNFRSF19. 8. The method of any one of embodiments 1-7, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3 and ANO7. 9. The method of any one of embodiments 1-8, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, PCAT-32, S1PR4, NFIB, and EPPK1. 10. The method of any one of embodiments 1-9, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of USAP1, PCDH7, THBS2, TNFRSF19, CAMK2N1, IQGAP3, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, PCAT-32, S1PR4, NFIB, and EPPK1, and two nucleic acid sequences of each of UBE2C, MYBPC1, and ANO7, . 11. The method of any one of embodiments 1-8, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1, DNAH5 S1PR4, NFIB, and EPPK1. 12. The method of any one of embodiments 1-8, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, GLYATL1, DNAH5, S1PR4, NFIB, and EPPK1, and two nucleic acid sequences of each of IQGAP3, ANO7 and LASP1. 13. The method of any one of embodiments 1-9, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1,GLYATL1P4 / PCAT-80, PCAT-32, S1PR4, NFIB, EPPK1, and two nucleic acid sequences of each of IQGAP3, ANO7 and LASP1. 14. The method of any one of embodiments 1-13, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets. 15. The method of any one of embodiments 1-14, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and wherein said determining or having determined that the subject with metastatic prostate cancer: (i) is expected to respond better to treatment comprising ADT and docetaxel than to treatment comprising ADT and not docetaxel based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being > 0.85 on a scale from 0 to 1, optionally wherein the expected better response to treatment comprising ADT and docetaxel is an increase in overall survival of at least 10%, 20%, or 30% as compared to treatment comprising ADT and not docetaxel; or (ii) is expected to respond less or only minimally better to treatment comprising ADT and docetaxel than to treatment comprising ADT and not docetaxel based on the risk score for the sample being equal to or below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being ≤ 0.85 on a scale of 0 to 1, optionally wherein the expected less or minimally better response to treatment comprising ADT and docetaxel is an increase in overall survival not greater than 15%, 10%, or 5% as compared to treatment comprising ADT and not docetaxel. 16. The method of any one of embodiments 2-15, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and wherein the method comprises: i) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and docetaxel based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being > 0.85 on a scale from 0 to 1, optionally wherein the expected better response to treatment comprising ADT and docetaxel is an increase in overall survival of at least 10%, 20%, or 30% as compared to treatment comprising ADT and not docetaxel; orii) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and not docetaxel based on the risk score being equal to or below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being ≤ 0.85 on a scale of 0 to 1, optionally wherein the expected less or minimally better response to treatment comprising ADT and docetaxel is an increase in overall survival not greater than 15%, 10%, or 5% as compared to treatment comprising ADT and not docetaxel. 17. The method of any one of embodiments 1-16, wherein the subject has low- volume metastatic cancer, optionally wherein the low-volume metastatic cancer subject does not have a visceral metastasis, and does not have ≥ 4 bone metastases with ≥ 1 outside the vertebral bodies or pelvis. 18. The method of any one of embodiments 1-16, wherein the subject has high- volume metastatic cancer, optionally wherein the high-volume metastatic cancer subject has a visceral metastasis, or has ≥ 4 bone metastases with ≥ 1 outside the vertebral bodies or pelvis. 19. The method of any one of embodiments 1-18, wherein the expected response to treatment comprising ADT and docetaxel in the subject comprises an increase in overall survival of at least 10%, 20%, or 30% as compared to ADT without docetaxel, optionally measured at 3 years, and / or optionally wherein the expected response is based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being > 0.85 on a scale from 0 to 1. 20. The method of any one of embodiments 1-18, wherein the expected response to treatment comprising ADT and docetaxel in the subject comprises an increase in overall survival of not greater than 15%, 10% or 5% as compared to ADT treatment without docetaxel, optionally measured at 3 years, and / or optionally wherein the expected response is based on the risk score for the sample being equal to or below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being ≤ 0.85 on a scale of 0 to 1. 21. The method of any one of the preceding embodiments, wherein said determining or having determined the expected response to treatment comprising ADT and docetaxel is in comparison to a treatment comprising ADT without docetaxel.22. The method of any one of the preceding embodiments, wherein said determining or having determined the expected response of the subject with metastatic prostate cancer to treatment comprising ADT and docetaxel is not based on prognostic clinical variables, optionally wherein the prognostic clinical variables are tumor stage, nodal stage, metastatic tumor volume categorization, a Gleason score and / or a serum PSA level of the subject. 23. The method of any one of the preceding embodiments, wherein said obtaining or having obtained the expression level of the plurality of targets comprises utilizing a microarray to assess on the plurality of targets, performing qPCR on the plurality of targets, and / or sequencing the plurality of targets. 24. The method of any one of the preceding embodiments, wherein the sample is from a radical prostatectomy, a resected specimen, optionally a transurethral resection of prostate (TURP) specimen, or a biopsy of the prostate cancer, optionally a needle biopsy. 25. The method of any one of the preceding embodiments, wherein the sample is from a primary prostate tumor. 26. The method of any one of the preceding embodiments, wherein the population of metastatic patients comprises at least 10, 25, 50, 75 or 100 patients. 27. A kit for use in detecting a response to treatment according to any one of the preceding methods. 28. The kit of embodiment 27, the kit comprising reagents for obtaining the expression level of biomarkers comprising or consisting of each of the plurality of targets. 29. The kit of embodiment 28, wherein the reagents comprise primer(s) and / or probe(s) for obtaining the expression level of each of the plurality of targets. Terms

[0149] Unless defined otherwise or the context clearly dictates otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs when read in light of the current disclosure.

[0150] The term "polynucleotide" as used herein has its plain and ordinary meaning as understood in light of the specification, and refers to a polymer of greater than onenucleotide in length of ribonucleic acid (RNA), deoxyribonucleic acid (DNA), hybrid RNA / DNA, modified RNA or DNA, or RNA or DNA mimetics, including peptide nucleic acids (PNAs). The polynucleotides may be single- or double-stranded. The term includes polynucleotides composed of naturally-occurring nucleobases, sugars and covalent internucleoside (backbone) linkages as well as polynucleotides having non-naturally-occurring portions which function similarly. Such modified or substituted polynucleotides are well known in the art and for the purposes of the present disclosure, are referred to as "analogues." "Complementary" or "substantially complementary" has its plain and ordinary meaning as understood in light of the specification, and refers to the ability to hybridize or base pair between nucleotides or nucleic acids, such as, for instance, between a sensor peptide nucleic acid or polynucleotide and a target polynucleotide. Complementary nucleotides are, generally, A and T (or A and U), or C and G. Two single-stranded polynucleotides or PNAs are said to be substantially complementary when the bases of one strand, aligned and compared and with appropriate insertions or deletions, pair with at least about 80% of the bases of the other strand, usually at least about 90% to 95%, and more preferably from about 98 to 100%.

[0151] Substantial complementarity exists when a polynucleotide may hybridize under selective hybridization conditions to its complement. Selective hybridization may occur when there is at least about 65% complementarity over a stretch of at least 14 to 25 bases, for example at least about 75%, or at least about 90% complementarity. "Preferential binding" or "preferential hybridization" has its plain and ordinary meaning as understood in light of the specification, and refers to the propensity of one polynucleotide to bind to its complement in a sample as compared to a noncomplementary polymer in the sample.

[0152] Hybridization conditions may include salt concentrations of less than about 1M, more usually less than about 500 mM, for example less than about 200 mM. In some embodiments, hybridization between a peptide nucleic acid and a polynucleotide is done in solutions containing little or no salt. In some embodiments, hybridization temperatures are as low as 5° C, but are typically greater than 22° C, and more typically greater than about 30° C, for example in excess of about 37° C. Longer fragments may require higher hybridization temperatures for specific hybridization as is known in the art. Other factors may affect the stringency of hybridization, including base composition and length of the complementary strands, presence of organic solvents and extent of base mismatching, and the combination ofparameters used is more important than the absolute measure of any one alone. Other hybridization conditions which may be controlled include buffer type and concentration, solution pH, presence and concentration of blocking reagents to decrease background binding such as repeat sequences or blocking protein solutions, detergent type(s) and concentrations, molecules such as polymers which increase the relative concentration of the polynucleotides, metal ion(s) and their concentration(s), chelator(s) and their concentrations, and other conditions known in the art. "Multiplexing" has its plain and ordinary meaning as understood in light of the specification, and refers to an assay or other analytical method in which multiple analytes are assayed. In some embodiments, the multiple analytes are from the same sample. In some embodiments, the multiple analytes are assayed simultaneously. In some embodiments, the multiple analytes are assayed sequentially. In some embodiments, assaying the multiple analytes occurs in the same reaction volume. In some embodiments, assaying the multiple analytes occurs in separate or multiple reaction volumes.

[0153] A "target sequence" has its plain and ordinary meaning as understood in light of the specification, and refers to a region of the genome against which one or more probes can be designed. In some embodiments, “target sequence” is referred to as "PSR" or "probe selection region." In some embodiments, “target sequence” is a coding sequence or a non- coding sequence. In some embodiments, a “target sequence” comprises exonic and / or non- exonic sequences. In some embodiments, a “target sequence” comprises an ultraconserved region. In some embodiments, an ultraconserved region is a sequence that is at least 200 base pairs and is conserved across multiple species. An ultraconserved region may be exonic or non-exonic. Exonic sequences may comprise regions on a protein-coding gene, such as an exon, UTR, or a portion thereof. Non-exonic sequences may comprise regions on a protein- coding, non-protein-coding gene, or a portion thereof. For example, non-exonic sequences may comprise intronic regions, promoter regions, intergenic regions, a non-coding transcript, an exon anti-sense region, an intronic anti-sense region, UTR anti-sense region, non-coding transcript anti-sense region, or a portion thereof.

[0154] In some embodiments, a probe is any polynucleotide capable of selectively hybridizing to a target sequence or its complement, or to an RNA version of either. A probe may comprise ribonucleotides, deoxyribonucleotides, peptide nucleic acids, and combinations thereof. In some embodiments, a probe may comprise one or more labels. In someembodiments, a probe is used to amplify one or both strands of a target sequence or an RNA form thereof, acting as a sole primer in an amplification reaction or as a member of a set of primers.

[0155] In some embodiments, a non-coding target may comprise a nucleotide sequence. The nucleotide sequence is a DNA or RNA sequence. A non-coding target may include a UTR sequence, an intronic sequence, or a non-coding RNA transcript. A non-coding target also includes sequences which partially overlap with a UTR sequence or an intronic sequence. A non-coding target also includes non-exonic transcripts.

[0156] In some embodiments, a coding target includes nucleotide sequences that encode for a protein and peptide sequences. The nucleotide sequence is a DNA or RNA sequence. The coding target includes protein-coding sequence. Protein-coding sequences include exon-coding sequences (e.g., exonic sequences).

[0157] In some embodiments, diagnosis of cancer may include the identification of cancer in a subject, determining the malignancy of the cancer, or determining the stage of the cancer.

[0158] In some embodiments, prognosis of cancer may include predicting the clinical outcome of the patient, assessing the risk of cancer recurrence, determining treatment modality, or determining and / or predicting treatment efficacy. "Having" is an open-ended phrase like "comprising" and "including," and includes circumstances where additional elements are included and circumstances where they are not. "Optional" or "optionally" means that the subsequently described event or circumstance may or may not occur, and that the description includes embodiments where the event or circumstance occurs and embodiments in which it does not.

[0159] As used herein ‘NED' has its plain and ordinary meaning as understood in light of the specification, and describes a clinically distinct disease state in which patients show no evidence of disease (NED') at least 5 years after surgery, ‘PSA' has its plain and ordinary meaning as understood in light of the specification, and describes a clinically distinct disease state in which patients show biochemical relapse only (two successive increases in prostate- specific antigen levels but no other symptoms of disease with at least 5 years follow up after surgery; ‘PSA') and 'SYS' has its plain and ordinary meaning as understood in light of the specification, and describes a clinically distinct disease state in which patients developbiochemical relapse and present with systemic cancer disease or metastases ('SYS') within five years after the initial treatment with radical prostatectomy.

[0160] The terms “METS”, “SYS”, “systemic event”, “Systemic progression”, “CR” or “Clinical Recurrence” have their plain and ordinary meanings as understood in light of the specification, and may be used interchangeably and generally refer to patients that experience BCR (biochemical recurrence) and that develop metastases (confirmed by bone or CT scan). The patients may experience BCR within 5 years of RP (radial prostectomy). The patients may develop metastases within 5 years of BCR. In some cases, patients regarded as METS may experience BCR after 5 years of RP.

[0161] As used herein, the term "about" refers to approximately a + / -10% variation from a given value. It is to be understood that such a variation is always included in any given value provided herein, whether or not it is specifically referred to.

[0162] Use of the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Thus, for example, reference to "a polynucleotide" includes a plurality of polynucleotides, reference to "a target" includes a plurality of such targets, reference to "a normalization method" includes a plurality of such methods, and the like. Additionally, use of specific plural references, such as "two," "three," etc., read on larger numbers of the same subject, unless the context clearly dictates otherwise.

[0163] Terms such as "connected," "attached," "linked" and "conjugated" are used interchangeably herein and encompass direct as well as indirect connection, attachment, linkage or conjugation unless the context clearly dictates otherwise.

[0164] Where a range of values is recited, it is to be understood that each intervening integer value, and each fraction thereof, between the recited upper and lower limits of that range is also disclosed, along with each subrange between such values. In some embodiments, the upper and lower limits of any range can independently be included in or excluded from the range, and each range where either, neither or both limits are included is also encompassed within the disclosure. Where a value being discussed has inherent limits, for example, where a component can be present at a concentration of from 0 to 100%, or where the pH of an aqueous solution can range from 1 to 14, those inherent limits are disclosed. Where a value is explicitly recited, it is to be understood that values, which are about the same quantity or amount as the recited value, are also within the scope of the disclosure, as are rangesbased thereon. In some embodiments, where a combination is disclosed, each sub-combination of the elements of that combination is also specifically disclosed and is within the scope of the disclosure. In some embodiments, where different elements or groups of elements are disclosed, combinations thereof are also disclosed. In some embodiments where any element of a disclosure is disclosed as having a plurality of alternatives, examples of that disclosure in which each alternative is excluded singly or in any combination with the other alternatives are also hereby disclosed; more than one element of an disclosure can have such exclusions, and all combinations of elements having such exclusions are hereby disclosed. References

[0165] The following references are incorporated herein by reference in their entirety. 1. James, N. D. et al. Addition of docetaxel, zoledronic acid, or both to first-line long-term hormone therapy in prostate cancer (STAMPEDE): survival results from an adaptive, multiarm, multistage, platform randomised controlled trial. Lancet (London, England) 387, 1163–1177 (2016). 2. Parker, J. S. et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol.27, 1160–1167 (2009). 3. Spratt, D. E. et al. Transcriptomic Heterogeneity of Androgen Receptor Activity Defines a de novo low AR-Active Subclass in Treatment Naïve Primary Prostate Cancer. Clin. Cancer Res.25, 6721–6730 (2019). 4. Erho, N. et al. Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy. PLoS One 8, e66855 (2013). 5. James, N. D. et al. Abiraterone for Prostate Cancer Not Previously Treated with Hormone Therapy. N. Engl. J. Med.377, 338–351 (2017). 6. Murray, M. L. et al. Data provenance and integrity of health-care systems data for clinical trials. Lancet Digit. Heal.4, e567–e568 (2022). 7. Nguyen, P. L. et al. Analysis of a biopsy-based genomic classifier in high-risk prostate cancer: Meta-analysis of the NRG Oncology / RTOG 9202, 9413, and 9902 phase III randomized trials. Int. J. Radiat. Oncol. Biol. Phys. (2023).doi:10.1016 / j.ijrobp.2022.12.035 Weiner, A. B. et al. A novel prostate cancer subtyping classifier based on luminal and basal phenotypes. Cancer 129, 2169–2178 (2023). Hamid, A. A. et al. Transcriptional profiling of primary prostate tumor in metastatic hormone-sensitive prostate cancer and association with clinical outcomes: correlative analysis of the E3805 CHAARTED trial. Ann. Oncol.32, 1157–1166 (2021). Vale, C. L. et al. Which patients with metastatic hormone-sensitive prostate cancer benefit from docetaxel: a systematic review and meta-analysis of individual participant data from randomised trials. Lancet Oncol.24, 783–797 (2023). Weiner, A. B. et al. A transcriptomic model for homologous recombination deficiency in prostate cancer. Prostate Cancer Prostatic Dis. (2021). doi:10.1038 / s41391-021- 00416-2 Rush, H. L. et al. Quality of Life in Men With Prostate Cancer Randomly Allocated to Receive Docetaxel or Abiraterone in the STAMPEDE Trial. J. Clin. Oncol. 40, 825– 836 (2022). Grist, E. et al. Accumulation of copy number alterations and clinical progression across advanced prostate cancer. Genome Med.14, 102 (2022). Hendry, S. et al. Assessing Tumor-infiltrating Lymphocytes in Solid Tumors: A Practical Review for Pathologists and Proposal for a Standardized Method From the International Immunooncology Biomarkers Working Group: Part 1: Assessing the Host Immune Response, TILs in Invas. Adv. Anat. Pathol.24, 235–251 (2017). Gautier, L., Cope, L., Bolstad, B. M. & Irizarry, R. A. affy—analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 20, 307–315 (2004). Piccolo, S. R. et al. A single-sample microarray normalization method to facilitate personalized-medicine workflows. Genomics 100, 337–344 (2012). (2022), R Core Team (R Foundation for Statistical Computing, Vienna, A. R: A language and environment for statistical computing. Available at: https: / / www.r- project.org / .EXAMPLES

[0166] The detailed method used in the following examples are provided following the Example 4. Example 1: Cohort summary

[0167] Figure 1 depicts an embodiment of an experimental and analytical work flow for generating clinical-grade transcriptome profiles from 1523 patients with metastatic (N=832) or non-metastatic (N=691) prostate cancer recruited at start of long-term ADT to the STAMPEDE platform protocol. Figure 2 depicts an embodiment of a sample flow diagram for an embodiment of a docetaxel trial. Figure 3 depicts some embodiments of patients that were randomized at 105 UK clinical trial sites between 5thOctober 2005 and 31stMarch 2013 to either standard-of-care alone (control arm, N=463) or with docetaxel (N=233) or docetaxel and zoledronic acid (N=199) or between 15thNovember 2011 and 17thJanuary 2014 to standard-of-care alone (N=419) or with abiraterone (N=375).166 patients were shared controls during the period of overlapping recruitment, 15thNovember 2011 to 31stMarch 2013. There were no noticeable differences in clinical-pathological characteristics compared with the full trial cohort.

[0168] The tissue tested reflected the mode of diagnosis of this patient group in the UK, namely 1427 prostate core biopsies, 91 prostate trans-urethral resections and 5 radical prostatectomies. The 1523 biomarker-cohort was identified using haematoxylin and eosin (H&E) slides from 2261 tumor samples centrally reviewed for sufficient tumor content. Median time from biopsy to randomization for patients starting their primary treatment for synchronous metastatic or high-risk localized disease (N=1466, 96%) was 77 days (IQR=36- 118).67% of high-risk localized patients in the docetaxel trials (none of the metastatic) were planned for radical radiotherapy. ADT was administered prior to tissue sampling for 198 (13%) patients (median: 14 days, IQR=6-27; 6% of non-metastatic [N=39], 8% of metastatic low- volume [N=27], 28% of metastatic high-volume [N=121], 22% of metastatic volume unknown [N=11]). Patients were followed up for a median of 8 years until closure to long-term follow- up of the docetaxel trials on the 13th July 2018. Through record linkage to civil registration of deaths accessed February 2024, an additional 202 deaths (103 metastatic, 99 non-metastatic patients) were recorded.Example 2: Transcriptome classifier overview

[0169] Using normalized pan-transcriptome gene values, we generated a score for the Decipher Prostate Gene Classifier (hereafter referred to as Decipher), a risk-model signature developed for intermediate-risk localized disease (see, e.g., Nguyen, P. L. et al. Int. J. Radiat. Oncol. Biol. Phys. 116(3):521-529 (2023); incorporated herein by reference in its entirety). We have extensively studied the Decipher signature in localized prostate cancer so we compared Decipher across tumors from men (N=81,594) diagnosed with early localized through to very high-risk localized or metastatic prostate cancer. We identified a progressive shift to higher scores in more advanced disease (Figure 4A). Within the STAMPEDE population, there was a statistically-significant increase in Decipher score in node-negative versus node-positive non-metastatic tumors (F test [two-way ANOVA], p=2.71x10-11) but not across any other step-wise increase in metastatic burden (Figure 4B). Example 3: Primary analysis: prediction of treatment benefit

[0170] To minimize penalization for evaluation of multiple predictive tests and therefore allow greater certainty that gene expression classifiers could predict sensitivity to docetaxel or abiraterone, we pre-specified a restricted number of “primary” signatures for predictive testing prior to linking of expression and clinical data. As detailed in the Statistical Outcome Analyses below, prior evidence from the CHAARTED trial and other studies (e.g., Phillips, et al., Int’l J. Radiation Oncol. Biol. Physics, 117(2):S34-S35 (2023), informed our primary hypotheses that supported prognostic testing of Decipher and that basal-luminal subtyping (e.g., PAM50 and / or PSC) could predict docetaxel.

[0171] Decipher as a continuous variable (score range 0.07 to 1.0) strongly associated with overall survival in the docetaxel trial, with each 0.1 increment increasing hazards of death by 11% (adjusted hazard ratio [HR], 1.11; 95% confidence interval [CI], 1.06- 1.15, p=2x10-7) in patients with metastatic disease and 14% (HR=1.14; 95% CI=1.08-1.20, p=4x10-6) in non-metastatic disease. We confirmed a consistent prognostic effect by trial treatment allocation and for secondary outcome measures.

[0172] Dichotomized Decipher scores (‘high’, >0.80; ‘lower’, ≤0.80;) were pre- specified to have equally-sized groups of metastatic patients. This represents a higher value than used to categorize localized cancers as high risk. For the Decipher signature, we confirmedour primary hypothesis and identified that in patients with metastatic disease, docetaxel clinically- and statistically-significantly improved survival in high Decipher (HR=0.64, 95% CI=0.48-0.86) but not in lower Decipher (HR=0.96, 95% CI=0.71-1.30) tumors (interaction p=0.039, Figure 5A, B). We observed associations consistent with this primary analysis in sensitivity and sub-group analyses (Figures 7A, 7B, and 8). For metastatic progression-free survival, we observed consistency for greater effect in metastatic patients with high Decipher tumors, but the interaction was not statistically-significant (p=0.098, Figures 7A, 7B, and 8). In non-metastatic patients, although the effect of docetaxel was numerically greater in high Decipher tumors (high, HR=0.75, 95% CI=0.44-1.28; lower, HR=1.04, 95% CI=0.68-1.59), this was neither large enough for an interaction effect (p=0.302) nor to clinically-justify docetaxel for this population (Figure 6).

[0173] Given metastatic high-volume disease has been suggested for selecting patients for docetaxel, we then demonstrated in an exploratory analysis that the direction of treatment effect prediction by Decipher was consistent (notwithstanding limited statistical precision in subgroups) in high-volume (high Decipher HR=0.72, 95% CI=0.49-1.07; lower: HR=1.16, 95% CI=0.77-1.74) and low-volume (high Decipher HR=0.53, 95% CI=0.32-0.88; lower: HR=0.78, 95% CI=0.47-1.30) metastatic disease (Figure 5C, D, E, F). Finally, we estimated that in metastatic patients, docetaxel increased 5-year restricted mean survival times by 8 months (95% CI=2-13) in high Decipher, compared to 0 months (95% CI=[-4]-5) in lower Decipher tumors (Figure 5G, Figure 9).

[0174] Table 4. Primary analyses. (A) Biomarker prognostic association with overall survival: hazard ratio interval estimates from Cox proportional hazards models fitted in the full biomarker cohort, and adjusted for trial arm allocation and baseline clinical staging (multivariable multiple imputation analysis) with partial log-likelihood ratio significance test p-values. Decipher (B) Subgroup treatment effect of docetaxel on overall survival: hazard ratio interval estimates from Cox proportional hazards models adjusted for baseline clinical staging (multivariable multiple imputation analysis) with partial log-likelihood ratio significance test p-values. M1, metastatic; M0, non-metastatic. “*” denotes statistically-significant results. HR, hazard ratio; CI, confidence interval.Table 4A Nonmetastatic Metastatic Signature Effect HR 95% CI p HR 95% CI p -6* -7*Docetaxel Bi k M t S b ff t HR 95% CI 9* 02 29 96

[0175] In the Examples above, we confirmed that the expression-based Decipher signature can provide clinically-important information in advanced prostate cancer independent of prognostic clinical variables, including Gleason score and metastatic burden. Notably, we confirm clinically-relevant heterogeneity of docetaxel effect in cancer sub-types defined by Decipher expression profile. This represents a clinically-implementable predictive biomarker for selecting patients for docetaxel. We achieved statistical rigor by limiting the number of predictive tests and using a locked signature (i.e. Decipher). Presently docetaxel is included in triplet therapy together with ADT and an ARPI based on physician or patient preference. Use of clinical features to guide use of docetaxel results in over-treatment of many patients and under-treatment of others. This is a major medical challenge given the notable detriment of docetaxel on quality of life. Although Decipher high tumors benefit fromabiraterone, given the non-overlapping mechanisms of actions, use of Decipher to predict benefit for addition of docetaxel to ADT can be extrapolated to docetaxel added to ADT and an ARPI.

[0176] In conclusion, we showed that Decipher measured at diagnosis from routinely-acquired primary tumors can classify advanced prostate cancers into clinically-useful groups that predict ADT + docetaxel treatment benefit. Experimental Methods

[0177] Below are methods used in the examples above.

[0178] Patient Cohort: Patients were randomized in the STAMPEDE platform protocol (Medical Research Council PR08, NCT00268476, EUDRACT: 2004-000193-31, ISRCTN: ISRCTN78818544, protocol v21 included in Supplementary information) that was sponsored by the Medical Research Council (up to 2013) and is now sponsored by University College London. Briefly, all patients had histologically-confirmed prostate adenocarcinoma and were eligible if they had metastatic disease confirmed on conventional whole-body computed tomography and technetium bone scans or localized, high-risk disease that was node-positive or, if node-negative, had at least two of tumor stage category T3 / 4, PSA ≥40ng / ml, Gleason score 8-10. Prostate serum antigen prior to LHRHa was obtained up to 6 months before randomization. Gleason score, age, stage, WHO performance status and metastatic state, namely non-metastatic and lymph node-negative or positive, or metastatic were recorded by clinical sites and accessed from the STAMPEDE trial database. Metastatic volume was further classified into high or low volume based on the presence of visceral metastases or ≥4 bone metastases with ≥1 outside the vertebral bodies or pelvis. Date of biopsy was obtained from histopathology reports, date of start of LHRHa was recorded at time of randomization. All patients signed informed consent to participate in the STAMPEDE trial and for use of their tissue for research (REC04 / MRE07 / 35).

[0179] Study Design: Analyses were overseen by the STAMPEDE Biological Research Group and defined in the STRATOSPHERE (STratification for RAtional Treatment- Oncomarker Pairings of STAMPEDE patients starting long-term Hormone treatment) consortium protocol for molecular studies on tumors collected from patients treated in the STAMPEDE trial (v2 dated 10thDecember 2018 included in Supplementary information),approved by an independent Research Ethics Committee (REC18 / LO / 1235) and the STAMPEDE Trial Management Group and Trial Steering Committee. The framework for analyses was two-stage: feasibility analyses for genome, methylome or transcriptome on a pilot cohort of 50-100 patients (Stage I) followed by extension of the approach with the highest success rate (Stage II). The success rate for expression array analysis was 92% so this was selected as the preferred approach (N=109 core biopsies from 50 control arm patients, presented at ASCO Genitourinary Cancers Symposium, February 2020, San Francisco USA, abstract #153). Genomic analyses are described elsewhere.

[0180] Prior to inspection of any association with clinical data from the abiraterone trial, a statistical analysis plan (v1.0, 21 / 03 / 2022) selected a single signature for primary prognostic analysis, Decipher, and four signatures (AR-A, PAM50, PSC and Decipher in this order using a closed hierarchical test) for primary predictive analyses (i.e., interaction of signature with treatment effect). For the docetaxel analysis, a separate analysis plan selected three signatures (Decipher, PAM50 and PSC) for predictive and prognostic testing due to prior signals observed from the abiraterone STAMPEDE trial and the CHAARTED trial (v1.0 03 / 07 / 2023). Both statistical analysis plans were revised (v2.004 / 03 / 2024 and 19 / 03 / 2024) to pool prognostic analyses across both trials and change the primary endpoint to overall survival, enabled by the greater statistical power afforded by linkage to civil registrations of death in February 2024.

[0181] Sample retrieval and processing: Tissue blocks were retrieved from STAMPEDE trial sites when requested by the Medical Research Council Clinical Trials Unit at UCL and centralized at the Wales Cancer Biobank- Biofanc Canser Cymru, where all identifying details were removed. Tissue blocks were transferred to the UCL Cancer Institute (London, UK) for processing and sample type was recorded. Central pathology review (authors: LM, DMB) of freshly-cut H&E slides was performed. This included assigning central Gleason score and categorization of infiltrating tumor immune cells (following the International Immunooncology Biomarkers Working Group methodology). Tumor infiltrating lymphocytes were counted within the tumor compartment only and separately assessed for each diagnostic core biopsy. A semiquantitative analysis was performed, with discrete values given according to the proportion of cells that were infiltrating lymphocytes (0-80%) and cases were then categorised as 0-5% or 6-10% or 11-20% or >20%.

[0182] The tumor block containing the index core (selected using the following hierarchy: the highest primary Gleason score, the highest secondary Gleason score and the longest tumor length) was sectioned onto 10 to 15 glass slides. Between 6thMarch 2019 and 10thMarch 2022 (abiraterone trial) and between October 2022 and October 2023 (docetaxel trials), mRNA was extracted from the next freshly-cut, 5 or 10-mm sections and analysed for expression of 1.4 million genome-wide features (including all known genes and most of the non-coding RNAs) in the Veracyte CLIA lab (San Diego, CA, USA) using high-density oligonucleotide arrays (Affymetrix Human Exon 1.0 ST, ThermoFisher, Santa Clara, CA, USA). Expression data was quality controlled by visualizing density and relative expression plots before and after background correction and quantile normalization using the affy package in R (see, Gautier, L., et al. Bioinformatics 20, 307–315 (2004); incorporated herein by refereince in its entirety). Multi-dimensional scaling (MDS) plots were used to inspect for possible batch effects and corrected using psva14 if needed. Data normalisation was performed using Single Channel Array Normalisation, where each sample was compared to itself using control probes from the array. The Decipher GRID including expression profiles of >100,512 cancers from prospective clinical use of the Decipher and retrospective studies of institutional cohorts was used to check the clustering solution and its analytical validity. These patients’ data were de-identified in accordance with the Safe Harbor method described in the HIPAA Privacy Rule 45 CFR 164.514(b) and (c) prior to analysis (Veracyte, Inc., San Diego, CA). Lab researchers had no access to clinical data other than pseudo-anonymized local pathology reports.

[0183] Statistical outcome analyses: Analyses were performed using R (v4.3.0) by unblinded clinical trial unit statisticians according to pre-specified statistical analysis plans. The primary outcome was overall survival (time from randomisation to death from any cause). This was obtained from case report forms based on data from the final lock and additionally participants in England and Wales were linked to civil registrations of death in February 2024. The secondary outcome tested when there was a significant association with overall survival was metastatic progression-free survival (MPFS, time to first of: distant metastases progression, skeletal-related event confirmed as disease progression, or death classified as due to prostate cancer).

[0184] To estimate the prognostic effect of a signature, multivariable Cox proportional hazards models were used with covariate adjustment for baseline characteristics: treatment arm allocation, age (continuous), WHO performance status (0; 1-2), regular aspirin or non-steroidal anti-inflammatory drugs use (no; yes, used as a randomisation minimisation factor to concurrent STAMPEDE trials testing celecoxib), serum PSA prior to start of ADT (ng / ml, log-transformed), Gleason score assessed by local pathologist (<=6; 7; >=8), tumour stage (T0-T2; T3; T4), nodal stage and in M1 cases metastasis volume categorisation (low volume vs high volume as per CHAARTED definition) (see, Hamid, A. A. et al., Ann. Oncol. 32:1157–1166 (2021); incorporated herein by reference in its entirety). Point and interval hazard ratios provided a measure of signature association with hazards of death. Statistical significance was assessed using partial likelihood ratio tests with a Bonferroni-corrected p- value threshold of 0.05 / 60=8.3.10-4. For continuous signatures, hazard ratios were raised to the power of 1 standard deviation (estimated from the signature in the full biomarker cohort, n=1523) to produce standardised hazard ratios (sdHR). These measure the effect of a 1 standard deviation increase in the signature on its original scale. Standardising this way helps compare the clinical significance of signatures by overcoming differences in scale.

[0185] Subgroup-specific hazard ratios for the treatment effect of docetaxel / abiraterone were compared to assess the clinical significance of the predictive effect. Partial likelihood ratios tests were used to assess statistical significance. Deviations from the proportional hazards assumption in the prognostic or predictive effect of interest were identified using Grambsch-Therneau tests with log-transformed time, and assessed further by examining cumulative hazards curves.

[0186] Nodal stage, tumour stage, and metastatic volume missingness was associated with prognosis, PSA, and initiation of ADT, and therefore assumed to be missing at random (MAR). Multiple imputation with chained equations (MICE) was used to impute all three variables in M0 and M1 separately. Baseline covariates, presence of metastases by site at randomisation (bone, lung, liver, node), prior ADT exposure, Nelson-Aalen estimates of cumulative hazard, death status, Decipher score, PAM50 class, PSC class, and AR-A score were used in the imputation model.

[0187] Two sensitivity analyses were performed. First, complete case analyses along MICE estimates were prepared. Second, analyses were reproduced in the subset ofparticipants with tissue collected before initiation of ADT to verify that important findings from the main analysis were not accidental byproducts of ADT altering transcriptomic and morphological features.

[0188] Data availability: Gene expression data are deposited on NCBI Gene Expression Omnibus (GEO Series accession number GSE224644). The remaining data may be made available from the inventors upon request.

Claims

WHAT IS CLAIMED IS:

1. A method comprising: (a) obtaining or having obtained an expression level of a plurality of targets in a sample obtained from a subject with metastatic prostate cancer, wherein the plurality of targets comprises or consists of at least one target nucleic acid sequence selected from each of at least five of: UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, GLYATL1, PCAT-32, DNAH5, S1PR4, NFIB, and EPPK1; the biomarkers / genes listed in Table 1; the biomarkers / genes listed in Table 2; or the biomarkers / genes listed in Table 3; and (b) determining a response to treatment comprising ADT and a taxane compound, optionally wherein the taxane compound is docetaxel, that the subject with metastatic prostate cancer is expected to have based on at least the expression level of each of the plurality of targets in the sample obtained in step (a).

2. A method comprising: (a) obtaining or having obtained an expression level of a plurality of targets in a sample obtained from a subject with metastatic prostate cancer, wherein the plurality of targets comprises or consists of at least one target nucleic acid sequence selected from each of at least five of: UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, GLYATL1, PCAT-32, DNAH5, S1PR4, NFIB, and EPPK1; the biomarkers / genes listed in Table 1; the biomarkers / genes listed in Table 2; or the biomarkers / genes listed in Table 3; (b) determining or having determined a response to treatment comprising ADT and a taxane compound, optionally wherein the taxane compound is docetaxel, that the subject with metastatic prostate cancer is expected to have based on at least the expression level of each of the plurality of targets in the sample obtained in step (a); and (c) administering or having administered to the subject with metastatic prostate cancer in (b) a treatment selected from: (i) a treatment comprising ADT and the taxane compound, optionally wherein the taxane compound is docetaxel; or (ii) a treatment comprising ADT and not comprising the taxane compound, optionally wherein the taxane compound is docetaxel,wherein the treatment is selected based on the expected response to treatment comprising ADT and the taxane compound, optionally wherein the taxane compound is docetaxel, determined in (b).

3. The method of claim 1 or 2, wherein the expected response to treatment comprising ADT and the taxane compound is one or more of the following: a) overall survival, metastasis-free survival, progression-free survival, and / or metastatic progression-free survival, b) overall survival, progression-free survival, and / or metastatic progression-free survival, c) overall survival at 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15 years, or a range defined by any two of the preceding values, or d) overall survival at 3 years.

4. The method of claim 2 or 3, wherein the treatment (i) comprising ADT and the taxane compound further comprises an Androgen Receptor Pathway Inhibitor (ARPI), optionally wherein the ARPI is abiraterone, apalutamide, darolutamide, or enzalutamide.

5. The method of claim 4, wherein the treatment (i) comprising ADT and the taxane compound further comprises abiraterone and optionally a corticosteroid, optionally wherein the corticosteroid is prednisone or prednisolone.

6. The method of any one of claims 1-5, wherein the plurality of targets comprises or consists of 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 or 22 target nucleic acid sequences, optionally wherein each target nucleic acid sequence is selected from a different gene, and / or not more than 2 target nucleic acid sequences are from the same gene, optionally wherein not more than 3 genes have 2 target nucleic acid sequences.

7. The method of any one of claims 1-6, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, and TNFRSF19.

8. The method of any one of claims 1-7, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3 and ANO7.

9. The method of any one of claims 1-8, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2,TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, PCAT-32, S1PR4, NFIB, and EPPK1.

10. The method of any one of claims 1-9, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of USAP1, PCDH7, THBS2, TNFRSF19, CAMK2N1, IQGAP3, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1P4 / PCAT-80, PCAT-32, S1PR4, NFIB, and EPPK1, and two nucleic acid sequences of each of UBE2C, MYBPC1, and ANO7, .

11. The method of any one of claims 1-8, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, IQGAP3, ANO7, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, LASP1, GLYATL1, DNAH5 S1PR4, NFIB, and EPPK1.

12. The method of any one of claims 1-8, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, GLYATL1, DNAH5, S1PR4, NFIB, and EPPK1, and two nucleic acid sequences of each of IQGAP3, ANO7 and LASP1.

13. The method of any one of claims 1-9, wherein the plurality of targets comprises or consists of a nucleic acid sequence of each of UBE2C, NUSAP1, PCDH7, THBS2, TNFRSF19, MYBPC1, CAMK2N1, ZWILCH, PBX1, TSBP1 / C6orf10, RABGAP1, GLYATL1P4 / PCAT-80, PCAT-32, S1PR4, NFIB, EPPK1, and two nucleic acid sequences of each of IQGAP3, ANO7 and LASP1.

14. The method of any one of claims 1-13, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets.

15. The method of any one of claims 1-14, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and wherein said determining or having determined comprises determining or having determined that the subject with metastatic prostate cancer: (i) is expected to respond better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being high; or(ii) is expected to respond less or only minimally better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being high being low.

16. The method of any one of claims 1-15, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and wherein said determining or having determined comprises determining or having determined that the subject with metastatic prostate cancer: (i) is expected to respond better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score of the sample being high; or (ii) is expected to respond less or only minimally better to treatment comprising ADT and the taxane compound than to treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score of the sample being low.

17. The method of any one of claims 2-16, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and wherein the method comprises: (i) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and the taxane compound based on the risk score for the sample being high; or (ii) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and not comprising the taxane compound based on the risk score being low.

18. The method of any one of claims 2-17, wherein said determining or having determined comprises calculating a risk score for the sample based on at least the expression level of each of the plurality of targets, and wherein the method comprises: (i) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and the taxane compound based on the riskscore for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score for the sample being high; or (ii) selecting for administration and / or administering, or having administered, to the patient a treatment comprising ADT and not comprising the taxane compound based on the risk score for the sample being below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score for the sample being low.

19. The method of any one of claims 1-18, wherein the expected better response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of at least 10%, 20%, 30%, 40% or 45% as compared to a treatment comprising ADT and not comprising the taxane compound and the expected less or minimally better response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of not greater than 15%, 10% or 5% as compared to a treatment comprising ADT and not comprising the taxane compound, optionally wherein overall survival is at 1, 2, 3, 4 or 5 years.

20. The method of any one of claims 1-19, wherein the determined expected response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of at least 10%, 20%, 30%, 40% or 45% as compared to a treatment comprising ADT and not comprising the taxane compound, optionally wherein the increase in overall survival is at 1, 2, 3, 4 or 5 years, and / or optionally wherein the expected response is based on the risk score for the sample being above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being high.

21. The method of any one of claims 14-20, wherein calculated risk score for the sample is above the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score is high.

22. The method of any one of claims 1-19, wherein the determined expected response to treatment comprising ADT and the taxane compound in the subject comprises an increase in overall survival of not greater than 15%, 10% or 5% as compared to a treatment comprising ADT and not comprising the taxane compound, optionally wherein the increase in overall survival is at 1, 2, 3, 4 or 5 years, and / or optionally wherein the expected response isbased on the risk score for the sample being below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score being low.

23. The method of any one of claims 1-19, or 22, wherein calculated risk score for the sample is below the median value of the risk score observed in a population of metastatic patients, and / or optionally the risk score is low.

24. The method of any one of claims 14-23, wherein the risk score is on a scale from 0 to 1, and wherein: the high score comprises or consists of risk scores > 0.80 or > 0.85 and the low score comprises or consists of risk scores ≤ 0.80 or ≤ 0.85, optionally wherein the high score comprises or consists of risk scores > 0.85 and the low score comprises or consists of risk scores ≤ 0.

85.

25. The method of any one of claims 14-24, wherein the expected better response to, selecting for and / or administering treatment comprising ADT and the taxane compound is based on the risk score being equal to the median value of the risk score observed in a population of metastatic patients.

26. The method of any one of claims 14-24, wherein the expected less or minimally better response to treatment comprising ADT and the taxane compound, or selecting for and / or administering treatment comprising ADT and not comprising the taxane compound is based on the risk score being equal to the median value of the risk score observed in a population of metastatic patients.

27. The method of any one of the preceding claims, wherein said determining or having determined the expected response of the subject with metastatic prostate cancer to treatment comprising ADT and the taxane compound is not based on prognostic clinical variables, optionally wherein the prognostic clinical variables are tumor stage, nodal stage, metastatic tumor volume categorization, a Gleason score and / or a serum PSA level of the subject.

28. The method of any one of claims 1-26, wherein said determining or having determined the expected response of the subject with metastatic prostate cancer to treatment comprising ADT and the taxane compound is further based on one or more prognostic clinical variables, optionally wherein the prognostic clinical variables are tumor stage, nodal stage,metastatic tumor volume categorization, a Gleason score and / or a serum PSA level of the subject.

29. The method of any one of the preceding claims, wherein said obtaining or having obtained the expression level of the plurality of targets comprises utilizing a microarray to assess on the plurality of targets, performing qPCR on the plurality of targets, and / or sequencing the plurality of targets.

30. The method of any one of the preceding claims, wherein the metastatic prostate cancer is castration-sensitive prostate cancer.

31. The method of any one of claims 1-30, wherein the subject has low-volume metastatic cancer, optionally wherein the low-volume metastatic cancer subject does not have a visceral metastasis, and does not have ≥ 4 bone metastases with ≥ 1 outside the vertebral bodies or pelvis.

32. The method of any one of claims 1-30, wherein the subject has high-volume metastatic cancer, optionally wherein the high-volume metastatic cancer subject has a visceral metastasis, or has ≥ 4 bone metastases with ≥ 1 outside the vertebral bodies or pelvis.

33. The method of any one of the preceding claims, wherein the taxane compound is selected from docetaxel, paclitaxel, and cabazitaxel, optionally wherein the taxane compound is docetaxel.

34. The method of any one of the preceding claims, wherein the taxane compound is not docetaxel.

35. The method of any one of the preceding claims, wherein the taxane compound is paclitaxel.

36. The method of any one claims 1-34, wherein the taxane compound is cabazitaxel.

37. The method of any one of the preceding claims, wherein the sample is from a radical prostatectomy, a resected specimen, optionally a transurethral resection of prostate (TURP) specimen, or a biopsy of the prostate cancer, optionally a needle biopsy.

38. The method of any one of the preceding claims, wherein the sample is from a primary prostate tumor.

39. The method of any one of the claims 16-38, wherein the population of metastatic patients comprises at least 10, 25, 50, 75 or 100 patients.

40. A kit for use in determining a response to treatment according to any one of the preceding methods.

41. The kit of claim 40, the kit comprising reagents for obtaining the expression level of biomarkers comprising or consisting of each of the plurality of targets.

42. The kit of claim 41, wherein the reagents comprise primer(s) and / or probe(s) for obtaining the expression level of each of the plurality of targets.

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