Methods of classifying prostate cancer

Abstract

The present disclosure provides, among other things, methods of classifying prostate cancer, methods of analyzing a prostate tumor sample, and methods of selecting a subject for removal and dissection of lymph nodes in the pelvis (PLND). Such methods can comprise detecting an expression level for one or more genes in a panel of cell cycle progression (CCP) genes and providing a clinical cell-cycle risk (CCR) score from the expression level of the genes in the panel of CCP genes and a Cancer of the Prostate Risk Assessment (CAPRA) score.

Description

[0001]Atty. Dkt. No.: 131588-1605 METHODS OF CLASSIFYING PROSTATE CANCER CROSS-REFERENCE TO RELATED APPLICATION This application claims the benefit of and priority to U.S. provisional application No. 63 / 695,262, filed on September 16, 2024, the entire disclosure of which is incorporated by reference herein. BACKGROUND The following description of the background of the present technology is provided simply as an aid in understanding the present technology and is not admitted to describe or constitute prior art to the present technology. Radical prostatectomy (RP) is a prostate cancer treatment that often includes pelvic lymph node dissection (PLND) to detect lymph node positive (pN+) prostate cancer (e.g., prostate cancer cell spread to lymph nodes near the prostate). Lymph node status at RP can be used to predict the probability of biochemical recurrence and other oncologic outcomes after surgery, and is included in clinical post-RP nomograms like CAPRA-S (Cooperberg, M. et al., Cancer vol.117,22 (2011): 5039-46). Failure to remove lymph nodes where cancer may have spread increases the risk of regional and distal metastasis. However, PLND also comes with the risk of additional side effects, such as bleeding and the formation of lymphoceles. PLND also increases operation time and can have low reimbursement. The National Comprehensive Cancer Network® (NCCN) states that “PLND can be excluded in patients with low predicted probability of nodal metastases by nomograms” and recommends the use of the Memorial Sloan Kettering Cancer Center (MSKCC) nomogram for estimating risk (NCCN 2023 Prostate Cancer Guidelines). Importantly, while NCCN has recommended a 2% risk threshold to perform PLND in the past, there are no evidence-based studies that define this threshold. Other published thresholds range from 2% to 7%, with other guidelines such as the European Association of Urology (EAU) recommending PLND for all high-risk patients and those with a predicted risk of positive lymph nodes above 5% (NCCN 2023 Prostate Cancer Guidelines, EAU 2019 Guidelines, Briganti A, et al., Eur Urol. Atty. Dkt. No.: 131588-1605 2012 Mar;61(3):480-7; Gandaglia G, et al., Eur Urol.2020 Aug;78(2):138-142; Milonas D, et al., Cent European J Urol. 2020;73(1):19-25). The MSKCC nomogram was originally published in Cagiannos 2003 (Cagiannos I, et al., J Urol. 2003 Nov;170(5):1798-803). A threshold of 2% risk resulted in 47.7% of patients identified as candidates to avoid PLND, with 12.1% of patients with positive lymph nodes being missed. The nomogram was later applied in another cohort and the 2% risk cutoff (“threshold”) resulted in identifying 22.3% of patients that could be spared PLND while missing 3.0% of patients with positive lymph nodes (Leyh-Bannurah SR, et al., Prostate. 2017 Apr;77(5):542-548). Further evaluation, as described herein, has also indicated that the MSKCC nomogram may overestimate risk of lymph node positive prostate cancer, resulting in additional subjects undergoing unnecessary PLND. Accordingly, there remains a need for improved methods of classifying prostate cancer (e.g., as potentially pN+ prostate cancer or not pN+ prostate cancer), analyzing prostate tumor samples, and selecting subjects for removal and dissection of lymph nodes in the pelvis (e.g., at the time of RP). SUMMARY OF THE INVENTION The present disclosure provides methods, systems, and kits for assessing a subject’s need for pelvic lymph node dissection (PLND) to detect lymph node positive (pN+) prostate cancer (e.g., prostate cancer cell spread to lymph nodes near the prostate). In particular, the disclosed methods, systems, and kits utilize a panel of cell cycle progression (CCP) genes and CAPRA scoring to assess whether a given subject with prostate cancer would benefit from having PLND in addition to a radical prostatectomy (RP). The methods, systems, and kits disclosed herein are highly predictive of lymph node involvement, and therefore improve personalized cancer for subjects with prostate cancer. In one aspect, the present disclosure provides methods of classifying prostate cancer, comprising: (a) reverse transcribing RNA extracted from a prostate biopsy taken from a subject with prostate cancer, thereby obtaining cDNA; (b) amplifying the cDNA of a panel of cell cycle progression (CCP) genes comprising one or more of FOXM1, CDC20, CDKN3, Atty. Dkt. No.: 131588-1605 CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L; (c) detecting an expression level for each gene in the panel of CCP genes; (d) providing a clinical cell-cycle risk (CCR) score from the expression level of the genes in the panel of CCP genes and a Cancer of the Prostate Risk Assessment (CAPRA) score; and (e) classifying the prostate cancer as potentially lymph node positive (pN+) prostate cancer if the CCR score exceeds a threshold value or not pN+ prostate cancer if the CCR score is below the threshold value. In some embodiments, the subject is a candidate for removal and dissection of lymph nodes in the pelvis (PLND). In some embodiments, PLND is recommended or performed if the CCR score exceeds the threshold value or not recommended or performed if the CCR score is below the threshold value. In some embodiments, the subject has a PSA of about 0.0 ng / ml to about 4.0 ng / ml, about 4.1 ng / ml to about 6.0 ng / ml, about 6.1 ng / ml to about 10.0 ng / ml, or above 10 ng / ml. In some embodiments, the subject has a clinical T stage of T1a, T1b, T1c, T2a, T2b, T2c, or T3a. In some embodiments, the subject has a Gleason Score of 3+3, 3+4, 3+5, 4+3, 4+4, 4+5, 5+3, 5+4, or 5+5. In some embodiments, the subject has a low-risk Gleason Score sum of 6. In some embodiments, the subject has a medium-risk Gleason Score sum of 7. In some embodiments, the subject has a high-risk Gleason Score sum of 8, 9, or 10. In some embodiments, the panel of CCP genes consists of FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L. In some embodiments, the expression level for each gene in the panel of CCP genes is normalized to an expression level of one or more housekeeping genes. In some embodiments, Atty. Dkt. No.: 131588-1605 the housekeeping genes comprise one or more of RPL38, UBA52, PSMC1, RPL4, RPL37, RPS29, SLC25A3, CLTC, TXNL1, PSMA1, RPL8, MMADHC, RPL13A, LOC728658, PPP2CA, and MRFAP1. In some embodiments, the CCR score is calculated with the equation: [(0.39×CAPRA)+(0.57×CCP value)] wherein CCP value is the average expression of normalized CCP genes. In some embodiments, the foregoing methods may further comprise providing an electronic or paper report of the CCR score to the subject or a physician treating the subject. In another aspect, the present disclosure provides methods of analyzing a prostate tumor sample, comprising: (a) extracting RNA from a prostate tumor biopsy from a subject; (b) reverse transcribing the RNA to cDNA; (c) detecting, in the CDNA, expression levels of a panel of cell cycle progression (CCP) genes comprising one or more of FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L; (d) normalizing the expression levels of the panel of CCP genes with expression levels of one or more housekeeping genes, thereby obtaining a CCP value; (e) preparing a Cancer of the Prostate Risk Assessment (CAPRA) score based on (i) age of the subject at diagnosis, (ii) prostate specific antigen (PSA) level of the subject at diagnosis, (iii) Gleason score of the biopsy, (iv) clinical stage, and (v) percent of biopsy cores involved with cancer; and (f) providing a CCR score based on the CCP value and CAPRA score. In some embodiments, the CCR score is calculated with the equation: [(0.39×CAPRA)+(0.57×CCP value)] wherein CCP value is the average expression of normalized CCP genes. In some embodiments, the housekeeping genes comprise one or more of RPL38, UBA52, PSMC1, RPL4, RPL37, RPS29, SLC25A3, CLTC, TXNL1, PSMA1, RPL8, MMADHC, RPL13A, LOC728658, PPP2CA, and MRFAP1. Atty. Dkt. No.: 131588-1605 In some embodiments, removal and dissection of lymph nodes in the pelvis (PLND) is recommended or performed if the CCR score exceeds the threshold value or not recommended or performed if the CCR score is below the threshold value. In some embodiments, the methods may further comprise providing an electronic or paper report of the CCR score to the subject or a physician treating the subject. In another aspect, the present disclosure provides methods of selecting a subject for removal and dissection of lymph nodes in the pelvis (PLND), comprising: (a) reverse transcribing RNA extracted from a prostate biopsy taken from a subject with prostate cancer, thereby obtaining cDNA; (b) amplifying the cDNA of a panel of cell cycle progression (CCP) genes comprising one or more of FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L; (c) detecting an expression level for each gene in the panel of CCP genes; (d) providing a clinical cell-cycle risk (CCR) score from the expression level of the genes in the panel of CCP genes and a Cancer of the Prostate Risk Assessment (CAPRA) score; and (e) selecting the subject for treatment if the CCR score exceeds a threshold value or active physician surveillance if the CCR score is below the threshold value. In some embodiments, treatment comprises PLND. In some embodiments, the subject has a PSA of about 0.0 ng / ml to about 4.0 ng / ml, about 4.1 ng / ml to about 6.0 ng / ml, about 6.1 ng / ml to about 10.0 ng / ml, or above 10 ng / ml. In some embodiments, the subject has a clinical T stage of T1a, T1b, T1c, T2a, T2b, T2c, or T3a. In some embodiments, the subject has a Gleason Score of 3+3, 3+4, 3+5, 4+3, 4+4, 4+5, 5+3, 5+4, 5+5. In some embodiments, the subject has a low-risk Gleason Score sum of 6. In some embodiments, the subject has a medium-risk Gleason Score sum of 7. In some embodiments, the subject has a high-risk Gleason Score sum of 8, 9, or 10. Atty. Dkt. No.: 131588-1605 In some embodiments, the expression level for each gene in the panel of CCP genes is normalized to an expression level of one or more housekeeping genes. In some embodiments, the housekeeping genes comprise one or more of RPL38, UBA52, PSMC1, RPL4, RPL37, RPS29, SLC25A3, CLTC, TXNL1, PSMA1, RPL8, MMADHC, RPL13A, LOC728658, PPP2CA, and MRFAP1. In some embodiments, the CCR score is calculated with the equation: [(0.39×CAPRA)+(0.57×CCP value)] wherein CCP value is the average expression of normalized CCP genes. In some embodiments, the methods may further comprise providing an electronic or paper report of the CCR score to the subject or a physician treating the subject. In some embodiments, of the foregoing and disclosed methods, the threshold value is a CCR score of 0, 1, 2, 3, or 4 In some embodiments, of the foregoing and disclosed methods, the threshold value is a risk of having positive lymph nodes of from about 1% to about 10% BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 show distribution of CARPA, CCP, and CCR in Analysis Set 1 (N = 735). FIG. 2 shows the observed vs. expected positive lymph nodes (pN+) rates in Analysis Set 1 and published cohorts. The dashed line represents the line of equality. FIG. 3 shows the distribution of known number of dissected nodes in the four subcohorts of Analysis Set 1. The Ochsner and Martini Clinic (UKE) subcohorts have no patients with known number of dissected nodes. The vertical dashed line separates limited PLND (<10 dissected nodes) from extended PLND (≥10 dissected nodes). FIG. 4 shows the distribution of the number of dissected nodes in the subset of Analysis Set 1 with the variable known (N = 318). Atty. Dkt. No.: 131588-1605 FIG. 5 shows risk curves calculated from a model fit with CCR score predicting pN+ in the full analysis set 1 (N = 735) and from a model fit with CCR score and number of dissected nodes predicting pN+ in the subset of Analysis Set 1 with known number of dissected nodes (N = 318). The dashed vertical lines represent the CCR-based active surveillance (AS) threshold (CCR = 0.8) and multimodal (MM) treatment threshold (CCR = 2.112). FIG. 6 shows distributions of continuous CCR score compared to the probability of pN+ estimated by existing clinical nomograms in the clinical cohort (N = 89,209 for MSKCC comparisons, N = 86,566 for Partin table comparison). The dashed vertical lines represent the CCR-based thresholds. FIG. 7 shows distributions of the probability of pN+ estimated by the model fit with continuous CCR score and number of dissected nodes and MSKCC v1 in the clinical cohort (N = 89,209). The dashed line represent the line of equality. FIG. 8 shows distributions of the probability of pN+ estimated by the model fit with continuous CCR score and number of dissected nodes and MSKCC v2 in the clinical cohort (N = 89,209). The dashed line represent the line of equality. FIG. 9 shows distributions of the probability of pN+ estimated by the model fit with continuous CCR score and number of dissected nodes and Partin tables in the clinical cohort (N = 86,566). The dashed line represent the line of equality. FIG. 10 shows rates of discordance between risks estimated by a CCR-based model accounting for the number of nodes dissected and existing clinical nomograms in the clinical cohort when thresholds are set between 1% and 10% risk. DETAILED DESCRIPTION It is to be appreciated that certain aspects, modes, embodiments, variations and features of the present methods are described below in various levels of detail in order to provide a substantial understanding of the present technology. Atty. Dkt. No.: 131588-1605 The present disclosure is not to be limited in terms of the particular embodiments described in this application, which are intended as single illustrations of individual aspects of the disclosure. All the various embodiments of the present disclosure will not be described herein. Many modifications and variations of the disclosure can be made without departing from its spirit and scope, as will be apparent to those skilled in the art. Functionally equivalent methods and apparatuses within the scope of the disclosure, in addition to those enumerated herein, will be apparent to those skilled in the art from the foregoing descriptions. Such modifications and variations are intended to fall within the scope of the appended claims. The present disclosure is to be limited only by the terms of the appended claims, along with the full scope of equivalents to which such claims are entitled. It is to be understood that the present disclosure is not limited to particular uses, methods, reagents, compounds, compositions or biological systems, which can, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting. Radical prostatectomy (RP) is a prostate cancer treatment that often includes pelvic lymph node dissection (PLND) to detect lymph node metastasis. Failure to remove lymph nodes where cancer may have spread increases the risk of regional and distal metastasis. However, PLND also comes with the risk of additional side effects, such as bleeding and the formation of lymphoceles. PLND also increases operation time and can have low reimbursement. At present, there are no available, accurate methods of determining which subjects should undergo PLND (e.g., at RP). Current methods, such as the MSKCC nomogram for estimating risk, can either miss identifying patients who should undergo PLND and / or overestimate the risk of lymph node metastasis, resulting in some subjects undergoing unnecessary PLND. For example, the MSKCC nomogram was reported to use a threshold of 2% risk of lymph node positive prostate cancer, which resulted in 47.7% of patients identified as candidates to avoid PLND, with 12.1% of patients with positive lymph nodes being missed. The nomogram was later applied in another cohort and the 2% risk cutoff resulted in identifying 22.3% of patients that could be spared PLND while missing 3.0% of patients with Atty. Dkt. No.: 131588-1605 positive lymph nodes (Leyh-Bannurah SR, et al., Prostate.2017 Apr;77(5):542-548). Further evaluation, as described herein, has also indicated that the MSKCC nomogram may overestimate risk of lymph node metastasis, resulting in additional subjects undergoing unnecessary PLND. Accordingly, there remains a need for improved methods of classifying prostate cancer (e.g., as potentially pN+ prostate cancer or not pN+ prostate cancer), analyzing prostate tumor samples, and selecting subjects for removal and dissection of lymph nodes in the pelvis (e.g., at the time of RP). The present disclosure provides, among other things, improved methods of classifying prostate cancer (e.g., as potentially pN+ prostate cancer or not pN+ prostate cancer), methods of analyzing a prostate tumor sample, and methods of selecting a subject for removal and dissection of lymph nodes in the pelvis (PLND). Such methods can use a panel of cell cycle progression (CCP) genes and a Cancer of the Prostate Risk Assessment (CAPRA) score to provide a clinical cell-cycle risk (CCR) score indicative of risk of lymph node positive prostate cancer. None of the current clinically utilized methods use this particular panel of CCP genes or the CARPA score, much less both, to classify prostate cancer, analyze a prostate tumor sample, and / or select a subject to undergo PLND. Accordingly, the ordered combination of steps of technologies of the present disclosure are not well-known, routine, or conventional and constitute an improvement in the field of treating prostate cancer. Definitions Unless defined otherwise, all technical and scientific terms used herein have the meaning commonly understood by a person skilled in the art to which this disclosure belongs. The following references provide one of skill with a general definition of many of the terms used in the present disclosure. Singleton et al., Dictionary of Microbiology and Molecular Biology (2nd ed.1994); The Cambridge Dictionary of Science and Technology (Walker ed., 1988); The Glossary of Genetics, 5th Ed., R. Rieger et al. (eds.), Springer Verlag (1991); and Hale & Marham, The Harper Collins Dictionary of Biology (1991). As used herein, the following terms have the meanings ascribed to them below, unless specified otherwise. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. Atty. Dkt. No.: 131588-1605 As used herein, the singular form “a,” “an,” and “the” include singular and plural references unless the context clearly dictates otherwise. For example, the term “a cell” includes a single cell as well as a plurality of cells, including mixtures thereof. As used herein, the term “approximately” or “about” means plus or minus 10% as well as the specified number. For example, “about 10” should be understood as both “10” and “9-11”. As used herein, the term “biopsy” refers to a tissue sample excised from a subject (e.g., a subject with prostate cancer). Tissue samples may be obtained using any suitable method, including, but not limited to, needle biopsies, aspiration, scraping, excision using surgical equipment, etc. In some embodiments, a biopsy is or comprises a prostate biopsy (e.g., a prostate tumor biopsy). As used herein, the term “comparable” refers to two (or more) sets of conditions, circumstances, individuals, or populations that are sufficiently similar to one another to permit comparison of results obtained or phenomena observed. In some embodiments, comparable sets of conditions, circumstances, individuals, or populations are characterized by a plurality of substantially identical features and one or a small number of varied features. Those of ordinary skill in the art will appreciate that sets of circumstances, individuals, or populations are comparable to one another when characterized by a sufficient number and type of substantially identical features to warrant a reasonable conclusion that differences in results obtained or phenomena observed under or with different sets of circumstances, individuals, or populations are caused by or indicative of the variation in those features that are varied. Those skilled in the art will appreciate that relative language used herein (e.g., enhanced, activated, reduced, inhibited, etc.) will typically refer to comparisons made under comparable conditions. As used herein, “comprising” is to be interpreted as specifying the presence of the stated features, integers, steps, or components as referred to, but does not preclude the presence or addition of one or more features, integers, steps, or components, or groups thereof. Moreover, each of the terms “by”, “comprising,” “comprises”, “comprised of,” “including,” “includes,” “included,” “involving,” “involves,” “involved,” and “such as” are Atty. Dkt. No.: 131588-1605 used in their open, non-limiting sense and may be used interchangeably. Further, the term “comprising” is intended to include examples and aspects encompassed by the terms “consisting essentially of” and “consisting of.” Similarly, the term “consisting essentially of” is intended to include examples encompassed by the term “consisting of.” As used herein, “diagnostic information” or “information for use in diagnosis” is any information that is useful in determining whether a patient has a disease, disorder, and / or condition and / or in classifying the disease, disorder, and / or condition into a phenotypic category or any category having significance with regard to prognosis of the disease or condition, or likely response to treatment (either treatment in general or any particular treatment) of the disease or condition. Similarly, diagnosis refers to providing any type of diagnostic information, including, but not limited to, whether a subject is likely (e.g., at an increased or high risk) to have a disease or condition, state, staging or characteristic of the disease or condition as manifested in the subject, information related to prognosis and / or information useful in selecting an appropriate treatment. Selection of treatment may include the choice of a particular therapeutic agent or other treatment modality such as surgery, etc., a choice about whether to withhold or deliver therapy, a choice relating to dosing regimen (e.g., frequency or level of one or more doses of a particular therapeutic agent or combination of therapeutic agents), etc. As used herein, the terms “improved”, “increased”, or “reduced”, or grammatically comparable comparative terms, indicate values that are relative to a comparable reference measurement. For example, in some embodiments, an assessed value achieved with an agent of interest may be “improved” relative to that obtained with a comparable reference agent. Alternatively or additionally, in some embodiments, an assessed value achieved in a subject or system of interest may be “improved” relative to that obtained in the same subject or system under different conditions (e.g., prior to or after an event such as administration of an agent of interest, assessment using nomograms, such as the MSKCC nomogram), or in a different, comparable subject (e.g., in a comparable subject or system that differs from the subject or system of interest in presence of one or more indicators of a particular disease, disorder or condition of interest, or in prior exposure to a condition or agent, etc.). In some embodiments, comparative terms refer to statistically relevant differences (e.g., that are of a Atty. Dkt. No.: 131588-1605 prevalence and / or magnitude sufficient to achieve statistical relevance). Those skilled in the art will be aware, or will readily be able to determine, in a given context, a degree and / or prevalence of difference that is required or sufficient to achieve such statistical significance. As used herein, “normalizing” or “normalized” in the context of gene expression levels refers to the genes (e.g., housekeeping genes) whose expression is used to calibrate or normalize the measured expression of the gene of interest (e.g., CCP genes). The normalization ensures accurate comparison of expression of a test gene (e.g., a CCP gene) between different samples and / or relative to a threshold value. As used herein, the terms “prognostic information” and “predictive information” are used interchangeably to refer to any information that may be used to indicate any aspect of the course of a disease, disorder, and / or condition either in the absence or presence of treatment. Such information may include, but is not limited to, the average life expectancy of a patient, the likelihood that a patient will survive for a given amount of time (e.g., 6 months, 1 year, 5 years, etc.), the likelihood that a patient will be cured of a disease, the likelihood that a patient's disease will respond to a particular therapy (wherein response may be defined in any of a variety of ways), the likelihood that a subject will or will not have metastatic prostate cancer. Prognostic and predictive information are included within the broad category of diagnostic information. As used herein, “reference”, as those of skill in the art will appreciate, in many embodiments described herein, is a determined value or characteristic of interest is compared with an appropriate reference. In some embodiments, a reference value or characteristic is one determined for a comparable cohort, individual, population, or sample. In some embodiments, a reference value or characteristic is tested and / or determined substantially simultaneously with the testing or determination of the characteristic or value of interest. In some embodiments, a reference characteristic or value is or comprises a historical reference, optionally embodied in a tangible medium. Typically, as would be understood by those skilled in the art, a reference value or characteristic is determined under conditions comparable to those utilized to determine or analyze the characteristic or value of interest. Atty. Dkt. No.: 131588-1605 As used herein, the term “subject” or “patient” refers to any organism upon which embodiments of the invention may be used or administered, e.g., for experimental, screening, diagnostic, prophylactic, and / or therapeutic purposes. Typical subjects include animals (e.g., mammals such as mice, rats, rabbits, non-human primates, and humans; insects; worms; etc.). Methods and Systems of Classifying Prostate Cancer, Analyzing a Prostate Tumor Sample, and Selecting a Subject for Removal and Dissection of Pelvic Lymph Nodes The present disclosure provides, among other things, methods and systems of classifying prostate cancer potentially pN+ prostate cancer or not pN+ prostate cancer (also referred to as negative lymph node status or pN-), methods of analyzing a prostate tumor sample, and methods of selecting a subject for removal and dissection of lymph nodes in the pelvis (PLND). Such methods can use a panel of cell cycle progression (CCP) genes and a Cancer of the Prostate Risk Assessment (CAPRA) score to provide a clinical cell-cycle risk (CCR) score indicative of risk of lymph node positive prostate cancer. None of the current clinically utilized methods for assessing lymph node involvement or the need for radical prostatectomy (RP) use this particular panel of CCP genes in combination with the CARPA score to classify prostate cancer (e.g., as potentially pN+ prostate cancer or not pN+ prostate cancer), analyze a prostate tumor sample, and / or select a subject to undergo PLND. Accordingly, the ordered combination of steps of technologies of the present disclosure are not well-known, routine, or conventional and constitute an improvement in the field of treating prostate cancer, including by providing an output (e.g., a CCR score) which can assist patients and / or their medical providers with information to make improved treatment decisions. The disclosed methods and systems improve personalized care and provide the first ever evidence-based assessment for selecting whether a given subject with prostate cancer is a good candidate for PLND (i.e., whether he is likely to have pN+ cancer or lymph node involvement). In one aspect, the present disclosure provides a method of classifying a prostate cancer, comprising: (a) reverse transcribing RNA extracted from a prostate biopsy taken from a subject with prostate cancer, thereby obtaining cDNA; (b) amplifying the cDNA of a panel Atty. Dkt. No.: 131588-1605 of cell cycle progression (CCP) genes comprising one or more of FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L; (c) detecting an expression level for each gene in the panel of CCP genes; (d) providing a clinical cell-cycle risk (CCR) score from the expression level of the genes in the panel of CCP genes and a Cancer of the Prostate Risk Assessment (CAPRA) score; and (e) classifying the prostate cancer as potentially lymph node positive (pN+) prostate cancer if the CCR score exceeds a threshold value or not pN+ prostate cancer if the CCR score is below the threshold value. In another aspect, the present disclosure provides a method of analyzing a prostate tumor sample, comprising: (a) extracting RNA from a prostate tumor biopsy from a subject; (b) reverse transcribing the RNA to cDNA; (c) detecting, in the CDNA, expression levels of a panel of cell cycle progression (CCP) genes comprising one or more of FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L; (d) normalizing the expression levels of the panel of CCP genes with expression levels of one or more housekeeping genes, thereby obtaining a CCP value; (e) preparing a Cancer of the Prostate Risk Assessment (CAPRA) score based on (i) age of the subject at diagnosis, (ii) prostate specific antigen (PSA) level of the subject at diagnosis, (iii) Gleason score of the biopsy, (iv) clinical stage, and (v) percent of biopsy cores involved with cancer; and (f) providing a CCR score based on the CCP value and CAPRA score. In another aspect, the present disclosure provides a method selecting a subject for removal and dissection of lymph nodes in the pelvis (PLND), comprising: (a) reverse transcribing RNA extracted from a prostate biopsy taken from a subject with prostate cancer, thereby obtaining cDNA; (b) amplifying the cDNA of a panel of cell cycle progression (CCP) genes comprising one or more of FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L; (c) detecting an expression level for each gene in the panel of Atty. Dkt. No.: 131588-1605 CCP genes; (d) providing a clinical cell-cycle risk (CCR) score from the expression level of the genes in the panel of CCP genes and a Cancer of the Prostate Risk Assessment (CAPRA) score; and (e) selecting the subject for treatment if the CCR score exceeds a threshold value or active physician surveillance if the CCR score is below the threshold value. In some embodiments, the treatment comprises PLND. In some embodiments, the treatment comprises radical prostatectomy with PLND. In some embodiments, the treatment comprises radical prostatectomy without PLND. In some embodiments, the treatment comprises radiation therapy. In general, the sample utilized for assessing CCP genes and / or the sample utilized for CAPRA may be one or more prostate biopsies or another suitable tissue or biological sample such as blood, plasma, or serum. The sample(s) used for assessing CCP genes and CAPRA may the same sample (i.e., the same biopsy is used for both) or different samples (i.e., two different biopsies are used: one for CCP gene assessment and one for CAPRA). For the purposes of the present disclosure, the sample(s) may be obtained from a subject as part of a diagnosis of prostate cancer or after affirmative diagnosis of prostate cancer. In general, the sample(s) will be taken from the subject prior to radical prostatectomy to aid in selection of the subject as an appropriate candidate for PLND, and may occur after the subject has otherwise been diagnosed with prostate cancer (e.g., based on PSA levels, ultrasound assessment, prior biopsy, or other diagnostic modalities). In some embodiments, the panel of CCP genes comprises FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L. For the purposes of the disclosed systems, methods, and kits, the panel of CCP genes may comprise or consist of at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 21, at least 22, at least 23, at least 24, at least 25, at least 26, at least 27, at least 28, at least 29, at least 30, or all 31 of the recited CCP genes. For the purposes of the disclosed systems, methods, and kits, the panel of CCP genes may comprise or consist of 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, or 31 of the recited CCP genes. For example, in some embodiments, the panel of CCP Atty. Dkt. No.: 131588-1605 genes may comprise or consist of ASPM, CDC2, CDCA8, CDKN3, DTL, FOXM1, KIAA0101, NUSAP1, PRC1, and TK1. For the purposes of the disclosed systems, methods, and kits, the panel of CCP genes may comprise or consist of 10-15, 10-20, 10-25, 10-30, 15- 20, 15-25, 15-30, or 20-30 of the recited CCP genes. In some embodiments, the panel of CCP genes consists of FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L. In some embodiments, the expression level for each gene in the panel of CCP genes is normalized to an expression level of one or more housekeeping genes. In some embodiments, the housekeeping genes comprise one or more of RPL38, UBA52, PSMC1, RPL4, RPL37, RPS29, SLC25A3, CLTC, TXNL1, PSMA1, RPL8, MMADHC, RPL13A, LOC728658, PPP2CA, and MRFAP1. For the purposes of the disclosed systems, methods, and kits, the panel of CCP genes may comprise or consist of at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, or all 11 of the recited housekeeping genes. For the purposes of the disclosed systems, methods, and kits, the panel of CCP genes may comprise or consist of 3-11, 3-10, 4-11, 4-10, 5-11, 5-10, 6-11, 6-10, 7-11, 7-10, 8-11, or 8-10 of the recited housekeeping genes. For example, in some embodiments, the one or more housekeeping genes may comprise or consist of CLTC, PSMA1, RPL4, RPS29, SLC25A3, and UBA52. In some embodiments, the housekeeping genes comprise RPL38. In some embodiments, the housekeeping genes comprise UBA52. In some embodiments, the housekeeping genes comprise PSMC1. In some embodiments, the housekeeping genes comprise RPL4. In some embodiments, the housekeeping genes comprise RPL37. In some embodiments, the housekeeping genes comprise RPS29. In some embodiments, the housekeeping genes comprise SLC25A3. In some embodiments, the housekeeping genes comprise CLTC. In some embodiments, the housekeeping genes comprise TXNL1. In some embodiments, the housekeeping genes comprise PSMA1. In some embodiments, the housekeeping genes comprise RPL8. In some embodiments, the housekeeping genes comprise MMADHC. In some embodiments, the housekeeping genes comprise RPL13A. In some embodiments, the housekeeping genes comprise LOC728658. In Atty. Dkt. No.: 131588-1605 some embodiments, the housekeeping genes comprise PPP2CA. In some embodiments, the housekeeping genes comprise MRFAP1. In some embodiments, the panel of CCP genes may comprise or consist of ASPM, CDC2, CDCA8, CDKN3, DTL, FOXM1, KIAA0101, NUSAP1, PRC1, and TK1, and the one or more housekeeping genes may comprise or consist of CLTC, PSMA1, RPL4, RPS29, SLC25A3, and UBA52. In some embodiments, the CCR score is calculated with the equation: [(0.39×CAPRA)+(0.57×CCP value)], wherein CCP value is the average expression of normalized CCP genes. In some embodiments, removal and dissection of lymph nodes in the pelvis (PLND) is recommended or performed if the CCR score exceeds the threshold value or not recommended or performed if the CCR score is below the threshold value. The threshold may be based on CCR score or percent risk of having positive lymph nodes. For example, the threshold CCR may be about 0.0, about 0.1, about 0.2, about 0.3, about 0.4, about 0.5, about 0.6, about 0.7, about 0.8, about 0.9, about 1.0, about 1.1, about 1.2, about 1.3, about 1.4, about 1.5, about 1.6, about 1.7, about 1.8, about 1.9, about 2.0, about 2.1, about 2.2, about 2.3, about 2.4, about 2.5, about 2.6, about 2.7, about 2.8, about 2.9, about 3.0, about 3.1, about 3.2, about 3.3, about 3.4, about 3.5, about 3.6, about 3.7, about 3.8, about 3.9, about 4.0, about 4.1, about 4.1, about 4.2, about 4.3, about 4.4, about 4.5, about 4.6, about 4.7, about 4.8, about 4.9, or about 5.0. In some embodiments, the threshold CCR may be 0.0, 0.1, 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, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4.0, 4.1, 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, or 5.0. In some embodiments, the threshold CCR may be about 0 to about 5, about 0 to about 4, about 0 to about 3, about 0 to about 2, about 0 to about 1, about 1 to about 5, about 1 to about 4, about 1 to about 3, about 1 to about 2, about 2 to about 5, about 2 to about 4, or about 2 to about 3. In some embodiments, the threshold CCR may be 0.0 – 5.0, 0.5 – 5.0, 1.0 – 5.0, 1.5 – 5.0, 2.0 – 5.0, 2.5 – 5.0, 3.0 – 5.0, 0.0 – 4.5, 0.5 – 4.5, 1.0 – 4.5, 1.5 – 4.5, 2.0 – 4.5, 2.5 – 4.5, 3.0 – 4.5, 0.0 – 4.0, 0.5 – 4.0, 1.0 – 4.0, 1.5 – 4.0, 2.0 – 4.0, 2.5 – 4.0, or 3.0 – 4. 0. Atty. Dkt. No.: 131588-1605 The disclosed methods can further comprise providing a report (e.g., an electronic report, a paper report) of the CCR score to the subject or a physician treating the subject. In some embodiments, methods of classifying a prostate cancer of the present disclosure further comprise providing an electronic or paper report of the CCR score to the subject or a physician treating the subject. Methods described herein can also be used in combination with any other diagnostic information and / or prognostic information (e.g., to inform the treatment of a subject with prostate cancer). Methods of the present disclosure can comprise extracting RNA from a prostate biopsy (e.g., a prostate tumor biopsy) taken from a subject with prostate cancer. RNA can be extracted from a prostate biopsy (e.g., a prostate tumor biopsy) by (1) harvesting cells or tissue (e.g., obtaining a prostate biopsy, a prostate tumor biopsy); (2) lysing the cells from the prostate biopsy; (3) inactivating RNAses; (4) capturing the RNA; (5) separating the RNA from at least some of the components with which it was associated when initially produced (e.g., DNA, proteins, other cellular components); whether in nature and / or in an experimental setting); and (6) resuspending or eluting the RNA. Harvesting tissues or cells may be completed by, for example, needle biopsy, aspiration, scraping, or excision using surgical equipment. Subsequently, the cells may be lysed using lysis buffers (e.g., comprising a chaotropic agent) and / or by mechanical disruption. In step (3), RNAses may be inactivated by, for example, using chaotropic agents and / or other RNAse inhibitors. Following lysis and RNAse inactivation, RNA can be captured by localizing the RNA to a specific liquid phase during liquid-liquid extraction (e.g., phenol chloroform extraction) or capture through binding to a surface, such as a silica surface or magnetic beads. Separating RNA from at least some of the components with which it was associated when initially produced can be completed by, for example, degrading DNA with DNAse (e.g., RNAse-free DNAse) and degrading proteins with proteinase K. Alternative or additional methods include dissolving the sample in buffers containing guanidinium salts to remove proteins and / or washing away components with which the RNA was associated when initially produced while the RNA is bound to a solid-support (e.g., silica beads, silica Atty. Dkt. No.: 131588-1605 column). Finally, the extracted RNA can be eluted or resuspended in water or a buffer (e.g., a buffer suitable for use in downstream applications and / or analyses). In some embodiments, the extracted RNA is quantified and / or the quality of the RNA assessed prior to reverse transcribing the RNA to complementary DNA (cDNA). Spectroscopic and / or electrophoretic methods can be used to quantify extracted RNA or to assess its quality (e.g., integrity). Methods of the present disclosure can also comprise reverse transcribing RNA extracted from a prostate biopsy (e.g., a prostate tumor biopsy) taken from a subject with prostate cancer, to thereby obtain cDNA. To reverse transcribe RNA extracted from a prostate biopsy (e.g., prostate tumor biopsy) to cDNA, reverse transcriptases (RNA- dependent DNA polymerases) are utilized. Reverse transcriptases include, for example, AMV reverse transcriptase and MMLV reverse transcriptase. In addition to enzyme, the main reaction components for reverse transcription (also referred to as “cDNA synthesis”) include RNA template (e.g., pre-treated to remove genomic DNA), buffer, deoxyribonucleotide triphosphate (dNTPs), dithiothreitol, RNase inhibitor, nuclease-free water, and primers (e.g., random hexamers, poly(dT)). Reverse transcription reactions involve three main steps: primer annealing, DNA polymerization, and enzyme deactivation. The temperature and duration of these steps can vary by primer choice, target RNA, and reverse transcriptase used. Methods of the present disclosure can comprise amplifying the cDNA, for example, amplifying the cDNA of a panel of cell cycle progression (CCP) genes. In some embodiments, the cDNA prepared from the reverse transcription is not separated from at least some of the components with which it was associated when initially produced (“purified”) before cDNA amplification. In some embodiments, the DNA prepared from the reverse transcription is separated from at least some of the components with which it was associated when initially produced (“purified”) before cDNA amplification. cDNA can be amplified by, for example, polymerase chain reaction (PCR), such as real-time PCR (e.g., TaqMan, OpenArray™ technologies) and quantitative PCR (qPCR). Methods of the present disclosure can also comprise detecting an expression level of one or more genes (or each gene) in the panel of CCP genes. Detecting can expression level Atty. Dkt. No.: 131588-1605 can be determined via the PCR of the amplification (e.g., real-time PCR, qPCR). Alternatively, expression levels for one or more CCP genes, or each CCP gene in a panel, can be determined using, for example, microarray. In the case of measuring RNA levels for the genes by real-time quantitative PCR (qPCR) assay following a reverse transcription reaction, a cycle threshold (Ct) is typically determined for each gene in a panel of CCP genes and each housekeeping gene, i.e., the number of cycle at which the fluoescence from a qPCR reaction above background is detectable. The overall expression of the one or more housekeeping genes can be represented by a “normalizing value” which can be generated by combining the expression of all housekeeping genes, either weighted eaqually (straight addition or averaging) or by different predefined coefficients. For example, in a simplest manner, the normalizing value CtH can be the cycle threshold (Ct) of one single housekeeping gene, or an average of the Ctvalues of 2 or more, preferably 10 or more, or 15 or more housekeeping genes, in which case, the predefined coefficient is 1 / N, where N is the total number of housekeeping genes used. Thus, CtH= (CtH1+ CtH2+...CtHn) / N. Depending on the housekeeping genes used, and the weight desired to be given to each housekeeping gene, any coefficients (from 0 / N to N / N) can be given to the housekeeping genes in weighting the expression of such housekeeping genes. That is, CtH= xCtH1+ yCtH2+...zCtHn, wherein x + y +…+ z = 1. Further, the CCP value provided in the technologies of the present disclosure represents the overall expression levels of the panel of CCP genes. In one embodiment, to provide a CCP value in the methods of the present disclosure, the normalized expression for a gene of the panel of CCP genes can be obtained by normalizing the measured Ctfor the gene against the CtH, i.e., ΔCt1 = (Ct1 - CtH). Thus, the CCP value representing the overall expression levels of the panel of CCP genes can be provided by combining the normalized expression of all CCP genes, either by straight addition or averaging (i.e., weighted eaqually) or by a different predefined coefficient. For example, the simplest approach is averaging the normalized expression of all genes in the panel of CCP genes: test value = (ΔCt1 + ΔCt2 +…+ Atty. Dkt. No.: 131588-1605 ΔCtn) / n. Depending on the genes in the panel of CCP genes used, different weight can also be given to different genes in the panel of CCP genes in the technologies described herein. Subjects The present disclosure provides, among other things, methods of classifying prostate cancer comprising reverse transcribing RNA extracted from a prostate biopsy taken from a subject with prostate cancer, methods of analyzing a prostate tumor sample comprising extracting RNA from a prostate tumor biopsy from a subject, and methods of selecting a subject for removal and dissection of lymph nodes in the pelvis (PLND). Thus, the subject of such methods is a subject with a prostate cancer. In some embodiments, the prostate cancer is an adenocarcinoma. In some embodiments, the prostate cancer is a small cell carcinoma (e.g., small cell neuroendocrine carcinoma). In some embodiments, the prostate cancer is a large cell carcinoma. In some embodiments, the prostate cancer is a transitional call carcinoma. In some embodiments, the prostate cancer is a sarcoma. In some embodiments, the prostate cancer is a Stage I prostate cancer. In some embodiments, the prostate cancer is a Stage II-A prostate cancer. In some embodiments, the prostate cancer is a Stage II-B prostate cancer. In some embodiments, the prostate cancer is a Stage II-C prostate cancer. In some embodiments, the prostate cancer is a Stage III-A prostate cancer. In some embodiments, the prostate cancer is a Stage III-B prostate cancer. In some embodiments, the prostate cancer is a Stage III-C prostate cancer. In some embodiments, the prostate cancer is a Stage IV-A prostate cancer. In some embodiments, the prostate cancer is a Stage IV-B prostate cancer. In some embodiments, the subject of the methods of the present disclosure is a candidate for radical prostatectomy (RP). In some embodiments, the subject of the methods of the present disclosure is a candidate for removal and dissection of lymph nodes in the pelvis (PLND). In some embodiments, the subject of methods of the present disclosure has a certain Prostate-Specific Antigen (PSA) level. PSA is a protein produced by normal, as well as Atty. Dkt. No.: 131588-1605 malignant, cells of the prostate gland. The blood level of PSA is often elevated in people with prostate cancer and, in some cases, is used to monitor the progression of prostate cancer in subjects who have already been diagnosed with the disease or to aid in the detection of prostate cancer. In some embodiments, in methods of the present disclosure, a circulating prostate specific antigen (PSA) amount is determined for the subject. In some embodiments, the subject has a PSA of about 0.0 ng / ml to about 4.0 ng / ml, about 4.1 ng / ml to about 6.0 ng / ml, about 6.1 ng / ml to about 10.0 ng / ml, or above 10 ng / ml. In some embodiments, the subject has a PSA of about 0.0 ng / ml. In some embodiments, the subject has a PSA of about 0.5 ng / ml. In some embodiments, the subject has a PSA of about 1.0 ng / ml. In some embodiments, the subject has a PSA of about 2.0 ng / ml. In some embodiments, the subject has a PSA of about 3.0 ng / ml. In some embodiments, the subject has a PSA of about 4.0 ng / ml. In some embodiments, the subject has a PSA of about 5.0 ng / ml. In some embodiments, the subject has a PSA of about 6.0 ng / ml. In some embodiments, the subject has a PSA of about 7.0 ng / ml. In some embodiments, the subject has a PSA of about 8.0 ng / ml. In some embodiments, the subject has a PSA of about 9.0 ng / ml. In some embodiments, the subject has a PSA of about 10.0 ng / ml. Prostate cancer can also be clinically staged by TNM staging, also referred to as a “clinical T stage.” TNM refers to Tumor, Node, Metastasis and describes the size of the cancer and how far it has grown. Tumor (T) describes the size or area of the cancer and has four main stages, T1 to T4. T1 means the cancer is too small to be seen on a scan, or felt during an examination of the prostate. It’s divided into T1a, T1b and T1c. T1a means that the cancer is in less than 5% of the removed tissue. T1b means that the cancer is in 5% or more of the removed tissue. T1c cancers are found by biopsy, for example after a raised PSA level. T2 means the cancer is completely inside the prostate gland. T2a means the tumor has invaded one-half (or less) of one side of the prostate. T2b means the tumor has spread to more than one-half of one side of the prostate, but not to both sides. T2c means the cancer has invaded both sides of the prostate. T3 means the cancer has broken through the capsule (covering) of the prostate gland. It’s divided into T3a and T3b. T3a means the cancer has broken through the capsule (covering) of the prostate gland. T3b means the cancer has spread Atty. Dkt. No.: 131588-1605 into the tubes that carry semen (seminal vesicles). T4 means the cancer has spread into other body organs nearby, such as the back passage, bladder, or the pelvic wall. In some embodiments, the subject has a clinical T stage of T1a, T1b, T1c, T2a, T2b, T2c, or T3a. In some embodiments, the subject has a clinical T stage of T1a. In some embodiments, the subject has a clinical T stage of T1b. In some embodiments, the subject has a clinical T stage of T1c. In some embodiments, the subject has a clinical T stage of T2a. In some embodiments, the subject has a clinical T stage of T2b. In some embodiments, the subject has a clinical T stage of T2c. In some embodiments, the subject has a clinical T stage of T13a. Gleason Score is a grading system for prostate cancer which evaluates how abnormal the cancer cells in a biopsy sample look under a microscope and how quickly they are likely to grow and spread. Most prostate cancers contain cells that are different grades. The Gleason Score is calculated by adding together the two grades of cancer cells that make up the largest areas of the biopsied tissue sample. For example, a first grade of 3 and a second grade of four are added together to provide a Gleason Score of 7. The Gleason Score usually ranges from 6 to 10. The lower the Gleason Score, the more the cancer cells look like normal cells and are likely to grow and spread slowly. A Gleason Score of 6 is considered low-risk, 7 of medium- risk, and 8, 9, or 10 of high-risk. In some embodiments, a subject of the present disclosure has a Gleason Score of 3+3, 3+4, 3+5, 4+3, 4+4, 4+5, 5+3, 5+4, or 5+5. In some embodiments, a subject of the present disclosure has a Gleason Score of 3+3. In some embodiments, a subject of the present disclosure has a Gleason Score of 3+4. In some embodiments, a subject of the present disclosure has a Gleason Score of 3+5. In some embodiments, a subject of the present disclosure has a Gleason Score of 4+3. In some embodiments, a subject of the present disclosure has a Gleason Score of 4+4. In some embodiments, a subject of the present disclosure has a Gleason Score of 4+5. In some embodiments, a subject of the present disclosure has a Gleason Score of 5+3. In some embodiments, a subject of the present disclosure has a Gleason Score of 5+4. In some embodiments, a subject of the present disclosure has a Gleason Score of 5+5. Atty. Dkt. No.: 131588-1605 In some embodiments, a subject of the present disclosure has a prostate cancer with a Gleason score sum of 6, 7, 8, 9, or 10. In some embodiments, the subject has a prostate cancer with a Gleason score sum of 1-5. In some embodiments, the subject has a prostate cancer with a Gleason score sum of 6-10. In some embodiments, the subject has a prostate cancer with a Gleason score sum of 8-10. In some embodiments, the subject has a prostate cancer with a Gleason score of 1. In some embodiments, the subject has a prostate cancer with a Gleason score sum of 2. In some embodiments, the subject has a prostate cancer with a Gleason score sum of 3. In some embodiments, the subject has a prostate cancer with a Gleason score sum of 4. In some embodiments, the subject has a prostate cancer with a Gleason score sum of 5. In some embodiments, the subject has a prostate cancer with a Gleason score sum of 6. In some embodiments, the subject has a prostate cancer with a Gleason score sum of 7. In some embodiments, the subject has a prostate cancer with a Gleason score sum of 8. In some embodiments, the subject has a prostate cancer with a Gleason score sum of 9. In some embodiments, the subject has a prostate cancer with a Gleason score sum of 10. Panel of CCP Genes A panel of cell cycle progression (CCP) genes of the present disclosure comprises one or more of FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L. In some embodiments, the panel of CCP genes comprises FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L. In some embodiments, the panel of CCP genes consist of FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L. Atty. Dkt. No.: 131588-1605 The various potential genes of a panel of CCP genes, including an example reference sequence are summarized in Table 1. Table 1: Summary of CCP genes. Atty. Dkt. No.: 131588-1605 Atty. Dkt. No.: 131588-1605 Housekeeping Genes Methods of the present disclosure can comprise normalizing the expression level for each gene in the panel of CCP genes to an expression level of one or more housekeeping genes. Housekeeping genes are genes that generally are stably expressed in cells, irrespective of tissue type, developmental stage, cell cycle state, or external signal, and in some cases, are essential for basic cellular functions. In some embodiments, at least 2, 5, 10, 15, or 16 housekeeping genes are used to normalize the expression level of each gene in the panel of CCP genes as described herein. In some embodiments, 1 housekeeping gene is used to normalize the expression level of each gene in the panel of CCP genes. In some embodiments, 2 housekeeping genes are used to normalize the expression level of each gene in the panel of CCP genes. In some embodiments, 5 housekeeping genes are used to normalize the expression level of each gene in the panel of CCP genes. In some embodiments, 10 housekeeping genes are used to normalize the expression level of each gene in the panel of CCP genes. In some embodiments, 15 housekeeping genes are used to normalize the expression level of each gene in the panel of CCP genes. In some embodiments, 16 housekeeping genes are used to normalize the expression level of each gene in the panel of CCP genes. The amount of gene expression of such normalizing genes can be averaged, combined together by straight additions or by a defined algorithm. Some examples of particularly useful housekeeping genes for use in the methods of the present disclosure include those listed in Table 3 below. Table 3: Summary of housekeeping genes. Atty. Dkt. No.: 131588-1605 CARPA Score The University of California, San Francisco developed the Cancer of the Prostate Risk Assessment (CAPRA) score. The CARPA score is a 0 to 10 score and can predict, with a certain level of accuracy, an individual’s likelihood of metastasis, cancer-specific mortality, and overall mortality. The score is calculated using points assigned to: (i) age of the subject at diagnosis, (ii) PSA level of the subject at diagnosis (e.g., prostate cancer diagnosis), (iii) Gleason score of the biopsy, (iv) clinical stage, and (v) percent of biopsy cores involved with cancer. Subsequently, the number of points for each category are added together to provide a CARPA score. These variables are outlined in Table 4. Table 4: CARPA variables. Atty. Dkt. No.: 131588-1605 A CAPRA score of 0 to 2 indicates low-risk or metastasis, cancer-specific mortality, and overall mortality, a CAPRA score of 3 to 5 indicates intermediate-risk of metastasis, cancer-specific mortality, and overall mortality., and a CAPRA score of 6 to 10 indicates high-risk of metastasis, cancer-specific mortality, and overall mortality. Threshold Value A threshold value for use in accordance with technologies of the present disclosure can be a certain CCR score or a certain percentage of risk of having positive lymph nodes (e.g., lymph node positive prostate cancer). Typically, a certain CCR score is associated with a certain percentage of risk. For example, risks of pN+ between 2% and 10% may be observed for CCR scores between 1 and 3; however, the estimated risk may be subject to change based on additional data. For the purposes of the present disclosure, a threshold value for active surveillance (AS) may be set at a CCR score of about 0.8 (e.g., about 0.5, about Atty. Dkt. No.: 131588-1605 0.6, about 0.7, about 0.8, about 0.9, about 1.0, or about 1.1 or any number in between 0.5- 1.1). A CCR score of 0.8 corresponds to a 10-year risk of prostate cancer specific mortality given conservative management of about 3.2% (though, as noted above, the estimated risk for a given score may vary slightly over time with the additional of further cohorts to the data set). For the purposes of the present disclosure, a threshold value for multi-modal (MM) treatment may be set at a CCR score of about 2.112 (e.g., about 1.8, about 1.9, about 2.0, about 2.1, about 2.2, about 2.4, or about 2.4 or any number in between 1.8-2.4). A CCR score of 2.112 corresponds to a 10-year risk of metastasis given single-mode therapy of 8.9% (though, as noted above, the estimated risk for a given score may vary slightly over time with the additional of further cohorts to the data set). In some embodiments, the threshold value is a CCR score. In some embodiments, the CCR score is a score of 0, 1, 2, 3, or 4. In some embodiments, the threshold value is a CCR score of 0-4. In some embodiments, the threshold value is a CCR score of 0-3. In some embodiments, the threshold value is a CCR score of 0-2. In some embodiments, the threshold value is a CCR score of 0-1. In some embodiments, the threshold value is a CCR score of 1- 4. In some embodiments, the threshold value is a CCR score of 2-4. In some embodiments, the threshold value is a CCR score of 3-4. In some embodiments, the threshold value is a CCR score of 0. In some embodiments, the threshold value is a CCR score of 1. In some embodiments, the threshold value is a CCR score of 2. In some embodiments, the threshold value is a CCR score of 3. In some embodiments, the threshold value is a CCR score of 4. In some embodiments, the threshold value is a risk of having positive lymph nodes (e.g., lymph node positive prostate cancer). In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 1% to about 10%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 2% to about 10%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 3% to about 10%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 4% to about 10%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 5% to about 10%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 6% to about 10%. In some embodiments, the threshold value is a risk of having positive lymph Atty. Dkt. No.: 131588-1605 nodes of from about 7% to about 10%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 8% to about 10%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 9% to about 10%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 2% to about 9%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 2% to about 8%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 2% to about 7%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 2% to about 6%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 2% to about 5%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 2% to about 4%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 2% to about 3%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 3% to about 9%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 3% to about 8%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 3% to about 7%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 3% to about 6%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 3% to about 5%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 3% to about 4%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 4% to about 9%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 4% to about 8%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 4% to about 7%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 4% to about 6%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 4% to about 5%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 5% to about 9%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 5% to about 8%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 5% to about 7%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 5% to about 6%. In some embodiments, the threshold value is a Atty. Dkt. No.: 131588-1605 risk of having positive lymph nodes of from about 6% to about 9%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 6% to about 8%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 6% to about 7%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 7% to about 9%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 7% to about 8%. In some embodiments, the threshold value is a risk of having positive lymph nodes of from about 8% to about 9%. In some embodiments, the threshold value is a risk of having positive lymph nodes of about 1%. In some embodiments, the threshold value is a risk of having positive lymph nodes of about 2%. In some embodiments, the threshold value is a risk of having positive lymph nodes of about 3%. In some embodiments, the threshold value is a risk of having positive lymph nodes of about 4%. In some embodiments, the threshold value is a risk of having positive lymph nodes of about 5%. In some embodiments, the threshold value is a risk of having positive lymph nodes of about 6%. In some embodiments, the threshold value is a risk of having positive lymph nodes of about 7%. In some embodiments, the threshold value is a risk of having positive lymph nodes of about 8%. In some embodiments, the threshold value is a risk of having positive lymph nodes of about 9%. In some embodiments, the threshold value is a risk of having positive lymph nodes of about 10%. Examples Example 1: Combined Clinical Risk (CCR) Score Can Classify Prostate Cancer Lymph Node Status at Radical Prostatectomy (RP) Currently, National Comprehensive Cancer Network® (NCCN) guidelines recommend the use of a clinical monogram (e.g., that developed by Memorial Sloan Kettering Cancer Center (MSKCC)) to classify prostate cancer as likely to have spread to the lymph nodes (also referred to as lymph node involvement or positive lymph node status, pN+). However, methods that can more accurately determine classification of prostate cancer likelihood of lymph node involvement are needed. Atty. Dkt. No.: 131588-1605 To evaluate the ability of a CCR to classify prostate cancer as potentially pN+ prostate cancer (e.g., as having lymph node involvement) at the time of RP, subjects (analysis set 1) with a known biopsy Cell Cycle Progression (CCP) value within the clinical reportable range (-2.2 to 4.7 on the CCP scale, 1.8 to 8.7 on the CCR score or shifted CCP scale, inclusive), either from retrospective testing of tissue from diagnostic biopsy or simulated biopsy, or prospective clinical testing of tissue from diagnostic biopsy were evaluated. Such subjects also were treated with RP with removal and dissection of lymph nodes in the pelvis (PLND) and had a known pN stage from RP. The subjects also had known clinical variables used to calculate CARPA, NCCN, and the MSKCC nomogram. Partin table probabilities are not estimable patients for T1a, T1b, or T3a disease, but these patients were not excluded from analysis set 1 (primary and secondary Gleason scores ≥ 3, clinical T stage ≤ T3a, known number of total and positive cores taken at diagnostic biopsy). In addition to analysis set 1, a clinical cohort was also evaluated. Analysis set 1 and the clinical cohort are summarized in Table 5, with the distribution of select clinical and molecular variables shown in FIG. 1. Table 5: Distribution of clinical and molecular variables in Analysis Set 1 (N = 735) and the Clinical Cohort (N = 89,209). Results are reported as Median (IQR) or N (%), * indicates Mean (IQR). Atty. Dkt. No.: 131588-1605 N (%) or Median (IQR); *Mean (IQR) The observed rate of positive lymph nodes (pN+) in analysis set 1 was 4.2%, but the expected rate given the distribution of clinical variables in the analysis set was 9.9% as derived from the MSKCC clinical nomogram (Table 5). This low observed pN+ rate was of concern and may be a result of the MSKCC nomogram overestimating risk or bias in analysis set 1. Observed vs. Expected pN+ rate – MSKCC Nomogram Overestimates Risk The potential MSKCC nomogram overestimation of risk and bias was further evaluated. While there are several validations of the MSKCC clinical nomogram, only a handful report both the observed pN+ rate and the mean MSKCC estimate of pN+ for the published cohort (including Meijer D et al., Eur Urol. 2021 Aug;80(2):234-242; Soeterik, T. F. W. et al., BJU international, 128(2), 236–243; Lucciola, S. et al., Prostate cancer and prostatic diseases, 26(2), 379–387, and Di Pierro et al., Cancers, 15(6), 1683). The observed versus expected rate of pN+ from analysis set 1 and four external validations of the MSKCC clinical nomogram are shown in FIG. 2. Interestingly, all four studies had higher observed and expected rates than analysis set 1, but observed rates in other Atty. Dkt. No.: 131588-1605 published studies ranged from ~5% to ~30% (not included here due to no reported mean MSKCC risk). Of the four studies with reported observed and expected rates, MSKCC appeared to overestimate risk in ¾ cohorts and underestimate risk in ¼ cohorts. However, this pattern was not particularly strong. Therefore, it was assumed that any overestimation of risk by the MSKCC nomogram is cohort-specific and other factors may be the potential cause for the discrepancy of observed vs expected pN+ rates in this cohort. Low Observed Rates of pN+ Due to False pN- (negative lymph node status) Extended PLND is defined by physical boundaries within the body (NCCN guidelines), and typically includes at least 10 lymph nodes. Thus, extended PLND was defined in the data set as at least 10 dissected lymph nodes. It is well documented that extended PLND is more likely to find evidence of pN+ than limited PLND (Milonas D et al., Cent European J Urol. 2020), and may be because high risk patients are more likely to have pN+ and are more likely to have a larger number of nodes dissected; and the more lymph node involvement is evaluated, the more likely it is to be found. To explore the impact of the number of dissected nodes on pN+ rates in the data set, analysis set 1 was limited to the N = 318 patients with known number of dissected nodes, 13 of which were pN+. Number of dissected nodes was known for only subjects evaluated at the Durham, Virginia (DUK) and Comprehensive Urology subcohorts of analysis set 1 (FIG. 3). The distribution of number of dissected nodes in this subset of patients is shown in FIG. 4. As analysis set 1 was limited to patients with higher numbers of lymph nodes dissected, the observed pN+ rate approaches the expected pN+ rate calculated as the mean MSKCC risk estimation, indicating that the number of lymph nodes dissected has a meaningful impact on predicting pN+ in the data set. This was formally assessed using univariable and bivariable logistic regression models summarized in Table 6. Both continuous CCR score and the number of dissected nodes were significant univariable predictors of pN+, and in a bivariable analysis both remained significant. This indicated that unique predictive information was contributed by both continuous CCR score and the number of nodes dissected and therefore the number of nodes dissected should be accounted for in analyses. Atty. Dkt. No.: 131588-1605 Table 6: Results of univariable and a bivariable logistic regression model with continuous CCR score and / or number of dissected nodes predicting pN+ in the subset of analysis set 1 with known number of dissected nodes (N = 318). Continuous CCR predicting pN+ As shown in Table 6, continuous CCR score was a significant predictor of pN+ after accounting for the number of nodes dissected. This allow predicted risks to be calculated for given combinations of CCR score and number of nodes dissected, producing the results shown FIG. 5. The risk calculated by a model fit with only CCR score in the full analysis set 1 (N = 735, OR 3.24 (95% CI 2.15, 5.4), p < 0.001) resulted in a risk curve with a substantially different shape than a model fit with CCR score and the number of nodes dissected, then calculating risk assuming 10 or 20 nodes dissected (the minimum and median number of nodes dissected in an extended PLND (Meijer D et al., Eur Urol. 2021 Aug;80(2):234-242; Soeterik, T. F. W. et al., BJU international, 128(2), 236–243; and Di Pierro et al., Cancers, 15(6), 1683). This is further evidenced that accounting for the number of nodes dissected has a meaningful impact on risk estimation. Additionally, there were wide confidence intervals around the estimated risks shown in FIG. 5 and summarized for the CCR scores associated with the Prolaris AS and MM thresholds in Table 7. These wide confidence intervals were understood to be caused by a relatively small analysis set size with known number of nodes dissected, a small number of events, and a small number of patients with at least 10 lymph nodes dissected. Table 7: Estimates of risk of pN+ with 95% confidence intervals calculated by a model with continuous CCR score and the number of dissected nodes. Atty. Dkt. No.: 131588-1605 Example 2: Comparison of CCR and Existing Clinical Nomograms Continuous CCR adds statistically significant information to clinical nomograms The present example demonstrates, among other things, that continuous CCR adds statistically significant information to clinical nomograms. In multivariable logistic regression models with continuous CCR score, the number of dissected nodes, and one of the clinical nomograms (CAPRA, MSKCC (both versions), Partin tables), CCR remained statistically significant (Tables 8-11). This indicated that the CCR score, including the molecular information contained in the CCP score, contributed significant predictive information independent of all information contributed by the number of nodes dissected and the clinical nomograms. The number of dissected nodes was also significant across all four models, further indicating the variable’s predictive significance. None of the clinical nomograms achieved significance in the multivariable models, indicating that their predictive ability was fully captured by the combination of continuous CCR score and the number of dissected nodes. Table 8: Results of a multivariable logistic regression model with continuous CCR score, number of dissected nodes, and CAPRA predicting pN+ in the subset of analysis set 1 with known number of dissected nodes (N = 318). Atty. Dkt. No.: 131588-1605 Table 9: Results of a multivariable logistic regression model with continuous CCR score, number of dissected nodes, and MSKCC v1 (no considering number of positive and negative biopsy cores) predicting pN+ in the subset of analysis set 1 with known number of dissected nodes (N = 318). Table 10: Results of a multivariable logistic regression model with continuous CCR score, number of dissected nodes, and MSKCC v2 predicting pN+ in the subset of analysis set 1 with known number of dissected nodes (N = 318). Table 11: Results of a multivariable logistic regression model with continuous CCR score, number of dissected nodes, and risk from Partin tables predicting pN+ in the subset of analysis set 1 with known number of dissected nodes and known Partin table predicted risk (N = 315). CCR-based risk calculations reclassify a meaningful proportion of patients for PLND For a CCR-based estimation of pN+ risk to be clinically meaningful and improved, it should identify different patients as candidates for PLND compared to existing clinical nomograms (e.g., MSKCC (both versions), Partin tables). The distributions of CCR scores and risk of pN+ from existing clinical nomograms was shown for the clinical cohort (N = Atty. Dkt. No.: 131588-1605 89,209) in FIG. 6. While correlations between the variables were fairly high (≥0.70), there was spread in predicted risk of pN+ for any given CCR score, meaning there was possibility for reclassification. The model fit with continuous CCR score and number of dissected nodes in the subset of Analysis Set 1 was also used to predict risk of pN+ in the clinical cohort assuming 10 dissected nodes and 20 dissected nodes. The distribution of CCR-based risks compared to risk from the existing clinical nomograms are shown in FIGs. 7-9. Interestingly, for the MSKCC clinical nomograms, the correlations between risk estimates were higher when the CCR-based model assumed 20 dissected nodes rather than 10 dissected nodes. This indicated that the MSKCC nomogram may have been trained on a data set with an average number of nodes dissected closer to 20 than to 10. Published thresholds for recommending PLND versus sparing a patient PLND range from 2% to 7% risk (National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology, Prostate Cancer. Version 1.2023. September 2022, EAU Guidelines. Edn. 2019. presented at the EAU Annual Congress Barcelona. ISBN 978-94-92671-04-2, Gandaglia G et al., European Urology. 2020.). In the past, NCCN has used a 2% risk threshold, but no recommended threshold is currently given in NCCN guidelines. Therefore, thresholds between 1% and 10% were explored. FIG. 10 shows the proportion of patients in the clinical cohort that would receive a different PLND recommendation (recommended vs. spared) from the given clinical nomogram and the CCR-based model. The discordance / reclassification rate depended on the selected threshold as well as the assumed number of dissected nodes inputted to CCR-based model. Assuming 20 dissected nodes and a threshold of 2%, over a quarter of patients would be reclassified by the CCR-based model and the “gold standard,” MSKCC v2. Taken together, the results of the present Examples demonstrate that CCR is predictive of pN+ after accounting for number of nodes dissected, Continuous CCR is more predictive than CAPRA alone after accounting for number of nodes dissected, CCR adds significant predictive information to clinical nomograms after accounting for number of nodes dissected, and CCR and number of nodes-based model reclassifies a clinically Atty. Dkt. No.: 131588-1605 meaningful proportion of patients. Such results indicate that Continuous CCR provides improved methods in determining / classifying prostate cancer for PLND over known methods, and as such provide improvements in the field of treating prostate cancer.

Claims

Atty. Dkt. No.: 131588-1605 WHAT IS CLAIMED IS:

1. A method of classifying prostate cancer, comprising: (a) reverse transcribing RNA extracted from a prostate biopsy taken from a subject with prostate cancer, thereby obtaining cDNA; (b) amplifying the cDNA of a panel of cell cycle progression (CCP) genes comprising one or more of FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L; (c) detecting an expression level for each gene in the panel of CCP genes; (d) providing a clinical cell-cycle risk (CCR) score from the expression level of the genes in the panel of CCP genes and a Cancer of the Prostate Risk Assessment (CAPRA) score; and (e) classifying the prostate cancer as potentially lymph node positive (pN+) prostate cancer if the CCR score exceeds a threshold value or not pN+ prostate cancer if the CCR score is below the threshold value.

2. The method of claim 1, wherein the subject is a candidate for removal and dissection of lymph nodes in the pelvis (PLND).

3. The method of claim 2, wherein PLND is recommended or performed if the CCR score exceeds the threshold value or not recommended or performed if the CCR score is below the threshold value.

4. The method of any one of claims 1-3, wherein the subject has a PSA of about 0.0 ng / ml to about 4.0 ng / ml, about 4.1 ng / ml to about 6.0 ng / ml, about 6.1 ng / ml to about 10.0 ng / ml, or above 10 ng / ml.

5. The method of any one of claims 1-4, wherein the subject has a clinical T stage of T1a, T1b, T1c, T2a, T2b, T2c, or T3a.

6. The method of any one of claims 1-5, wherein the subject has a Gleason Score of 3+3, 3+4, 3+5, 4+3, 4+4, 4+5, 5+3, 5+4, or 5+5.Atty. Dkt. No.: 131588-1605 7. The method of claim 6, wherein the subject has a low-risk Gleason Score sum of 6.

8. The method of claim 6, wherein the subject has a medium-risk Gleason Score sum of 7.

9. The method of claim 6, wherein the subject has a high-risk Gleason Score sum of 8, 9, or 10.

10. The method of any one of claims 1-9, wherein the panel of CCP genes consists of FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L.

11. The method of any one of claims 1-10, wherein the expression level for each gene in the panel of CCP genes is normalized to an expression level of one or more housekeeping genes.

12. The method of claim 11, wherein the housekeeping genes comprise one or more of RPL38, UBA52, PSMC1, RPL4, RPL37, RPS29, SLC25A3, CLTC, TXNL1, PSMA1, RPL8, MMADHC, RPL13A, LOC728658, PPP2CA, and MRFAP1.

13. The method of any one of claims 1-12, wherein the CCR score is calculated with the equation: [(0.39×CAPRA)+(0.57×CCP value)] wherein CCP value is the average expression of normalized CCP genes.

14. The method of any one of claims 1-13, further comprising providing an electronic or paper report of the CCR score to the subject or a physician treating the subject.

15. A method of analyzing a prostate tumor sample, comprising: (a) extracting RNA from a prostate tumor biopsy from a subject; (b) reverse transcribing the RNA to cDNA; (c) detecting, in the CDNA, expression levels of a panel of cell cycle progression (CCP) genes comprising one or more of FOXM1, CDC20, CDKN3, CDC2, KIF11,Atty. Dkt. No.: 131588-1605 KIAA0101, NUSAP1, CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L; (d) normalizing the expression levels of the panel of CCP genes with expression levels of one or more housekeeping genes, thereby obtaining a CCP value; (e) preparing a Cancer of the Prostate Risk Assessment (CAPRA) score based on (i) age of the subject at diagnosis, (ii) prostate specific antigen (PSA) level of the subject at diagnosis, (iii) Gleason score of the biopsy, (iv) clinical stage, and (v) percent of biopsy cores involved with cancer; and (f) providing a CCR score based on the CCP value and CAPRA score.

16. The method of claim 15, wherein the CCR score is calculated with the equation: [(0.39×CAPRA)+(0.57×CCP value)] wherein CCP value is the average expression of normalized CCP genes.

17. The method of claim 15 or 16, wherein the housekeeping genes comprise one or more of RPL38, UBA52, PSMC1, RPL4, RPL37, RPS29, SLC25A3, CLTC, TXNL1, PSMA1, RPL8, MMADHC, RPL13A, LOC728658, PPP2CA, and MRFAP1.

18. The method of any one of claims 15-17, wherein removal and dissection of lymph nodes in the pelvis (PLND) is recommended or performed if the CCR score exceeds the threshold value or not recommended or performed if the CCR score is below the threshold value.

19. The method of any one of claims 15-18, further comprising providing an electronic or paper report of the CCR score to the subject or a physician treating the subject.

20. A method of selecting a subject for removal and dissection of lymph nodes in the pelvis (PLND), comprising: (a) reverse transcribing RNA extracted from a prostate biopsy taken from a subject with prostate cancer, thereby obtaining cDNA; (b) amplifying the cDNA of a panel of cell cycle progression (CCP) genes comprising one or more of FOXM1, CDC20, CDKN3, CDC2, KIF11, KIAA0101, NUSAP1,Atty. Dkt. No.: 131588-1605 CENPF, ASPM, BUB1B, RRM2, DLGAP5, BIRC5, KIF20A, PLK1, TOP2A, TK1, PBK, ASF1B, C18orf24, RAD54L, PTTG1, CDCA3, MCM10, PRC1, DTL, CEP55, RAD51, CENPM, CDCA8, and ORC6L; (c) detecting an expression level for each gene in the panel of CCP genes; (d) providing a clinical cell-cycle risk (CCR) score from the expression level of the genes in the panel of CCP genes and a Cancer of the Prostate Risk Assessment (CAPRA) score; and (e) selecting the subject for treatment if the CCR score exceeds a threshold value or active physician surveillance if the CCR score is below the threshold value. 21 The method of claim 20, wherein treatment comprises PLND.

22. The method of claim 20 or 21, wherein the subject has a PSA of about 0.0 ng / ml to about 4.0 ng / ml, about 4.1 ng / ml to about 6.0 ng / ml, about 6.1 ng / ml to about 10.0 ng / ml, or above 10 ng / ml.

23. The method of claim any one of claims 20-22, wherein the subject has a clinical T stage of T1a, T1b, T1c, T2a, T2b, T2c, or T3a.

24. The method of any one of claims 20-23, wherein the subject has a Gleason Score of 3+3, 3+4, 3+5, 4+3, 4+4, 4+5, 5+3, 5+4, 5+5.

25. The method of claim 24, wherein the subject has a low-risk Gleason Score sum of 6.

26. The method of claim 24, wherein the subject has a medium-risk Gleason Score sum of 7.

27. The method of claim 24, wherein the subject has a high-risk Gleason Score sum of 8, 9, or 10.

28. The method of any one of claims 20-27, wherein the expression level for each gene in the panel of CCP genes is normalized to an expression level of one or more housekeeping genes.Atty. Dkt. No.: 131588-1605 29. The method of claim 28, wherein the housekeeping genes comprise one or more of RPL38, UBA52, PSMC1, RPL4, RPL37, RPS29, SLC25A3, CLTC, TXNL1, PSMA1, RPL8, MMADHC, RPL13A, LOC728658, PPP2CA, and MRFAP1.

30. The method of any one of claims 20-29, wherein the CCR score is calculated with the equation: [(0.39×CAPRA)+(0.57×CCP value)] wherein CCP value is the average expression of normalized CCP genes.

31. The method of any one of claims 20-30, further comprising providing an electronic or paper report of the CCR score to the subject or a physician treating the subject.

32. The method of any one of claims 1-14 or 18-31, wherein the threshold value is a CCR score of 0, 1, 2, 3, or 4 33. The method of any one of claims 1-14 or 18-31, wherein the threshold value is a risk of having positive lymph nodes of from about 1% to about 10%.

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