PROPOSED Local Coverage Determination (LCD)

MolDX: Gene Expression Profile Tests for Decision-Making in Castration Resistant and Metastatic Prostate Cancers

DL39688

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DL39688
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MolDX: Gene Expression Profile Tests for Decision-Making in Castration Resistant and Metastatic Prostate Cancers
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Issue

Issue Description

This LCD outlines limited coverage for this service with specific details under Coverage Indications, Limitations and/or Medical Necessity.

Issue - Explanation of Change Between Proposed LCD and Final LCD

CMS National Coverage Policy

Title XVIII of the Social Security Act, §1862(a)(1)(A) allows coverage and payment for only those services that are considered to be reasonable and necessary.

42 CFR §410.32(a) Diagnostic x-ray tests, diagnostic laboratory tests, and other diagnostic tests: Conditions

CMS Internet-Only Manual, Pub. 100-02, Medicare Policy Manual, Chapter 15, §80 Requirements for Diagnostic X-Ray, Diagnostic Laboratory, and Other Diagnostic Tests, §80.1.1 Certification Changes

Coverage Guidance

Coverage Indications, Limitations, and/or Medical Necessity

This is a coverage policy for gene expression profile tests that assess risk or predict therapeutic response in men who have an established diagnosis of castration resistant or metastatic prostate cancer.

Such testing is considered reasonable and necessary to help guide treatment decisions in men with prostate cancer and a life expectancy such that they are candidates for prostate cancer treatment according to the most recent nationally recognized guidelines at the time of testing or based on FDA labelling of drugs and biologics available as potential treatment options.

The scope of this policy includes gene expression profile tests regardless of methodology. It is exclusive of targeted and comprehensive genomic profiles (CGP) by next generation sequencing (NGS) and single biomarker expression analyses.

Coverage criteria:

1. BOTH of the following criteria must be met:

  1. The beneficiary is being actively managed for castration resistant or metastatic (hormone sensitive or castration resistant) prostate cancer.
  2. The beneficiary is within the population and has the indication for which the test was developed and validated.

2. At least 1 of the following criteria are met:

  1. The patient is a candidate for more than one management option, which could be considered to have varied, or increasing/decreasing levels of intensity based on a nationally recognized consensus guideline, and the physician and patient must decide among these treatments OR
  2. The patient is a candidate for more than one management option, and the test has shown that it predicts response to a specific therapy among accepted therapy options based on nationally recognized consensus guidelines and/or FDA labelling.

3. The patient has not been tested with the same or similar test for prostate cancer.

4. The patient has not received pelvic radiation or androgen deprivation therapy (ADT) prior to the biopsy or prostate resection specimen on which the test will be performed.

  • The only exception to this is for men who are naïve to secondary systemic therapies (that could be given after ADT monotherapy) AND at least 1 of the following is true:

a. They do not have other standard-of-care drug-targetable gene alterations to guide systemic therapy, as defined in nationally recognized guidelines OR
b. They have other standard-of-care drug-targetable gene alterations to guide systemic therapy, as defined in nationally recognized guidelines but they are not eligible for those therapies for another reason.

  1. The test demonstrates analytical validity (AV), clinical validity (CV) and clinical utility (CU), establishing a clear and significant biological/ molecular basis for stratifying patients and subsequently selecting (either positively or negatively) a clinical management in a clearly defined population.

  1. Clinical validity of any analytes (or expression profiles) measured must be established through a study published in the peer-reviewed literature for the intended use of the test in the intended population.

  1. If the test relies on an algorithm, the algorithm must be validated in a cohort that is not a development cohort for the algorithm.

  1. Testing must be performed according to Clinical Laboratory Improvement Amendments (CLIA) and/or Food and Drug Administration (FDA) regulations in an accredited laboratory.

  1. The lab providing the test is responsible for clearly indicating to treating physicians the population and indication(s) for test use.

  1. The test successfully completes a Molecular Diagnostic Services Program (MolDX®) Technical Assessment that ensures that AV, CV, and CU criteria set in this policy are met to establish the test as Reasonable and Necessary.

Genomic expression profile tests that demonstrate equivalent or superior analytical and clinical validity to those covered by this contractor will be considered reasonable and necessary for the same indications.

Summary of Evidence

In the United States, prostate cancer (PC) is the most common cancer in men, with an estimated 288,300 new cases projected in 2023 representing roughly 29% of all new cancer cases in men.1 Men have a 12.6% chance of developing prostate cancer during their lifetime.1 Prostate cancer is also the second most common cause of cancer death in men with an estimated 34,700 deaths due to prostate cancer in 2023, representing 11% of cancer-related deaths in men.1 Prostate cancer incidence and deaths have increased since 2014 after two decades of decline; now, more than 30% of new cases are advanced cancers at diagnosis.1 Reports of a shift toward higher grade and stage at initial diagnosis have been attributed in large part to changes in prostate-specific antigen (PSA) screening practices.1 Prostate cancer incidence in African American men is 70% higher than in White men and prostate cancer mortality rates in African American men are approximately two to four times higher than those in every other racial and ethnic group.1 African American men may benefit more from screening and from testing for genomic biomarkers because they are more likely to harbor genomically aggressive cancer, even in categorically lower risk tumors.2,3 Most cases of prostate cancer are localized with excellent survival (>99%); however, the 5- year survival rate is substantially lower (~30%) for patients with distant metastasis.1,4

A mainstay of therapy in prostate cancer is androgen deprivation therapy (ADT). However, most castration sensitive prostate cancer (CSPC), also known as hormone sensitive prostate cancer (HSPC) eventually becomes resistant to ADT, a condition known as castration-resistant prostate cancer (CRPC).5 In recent years, the evidence has shown that combining additional therapies with ADT early during treatment for advanced and metastatic HSPC (mHSPC) prolongs time to CRPC and improves overall survival (OS).6-10 For this reason, combination therapy has become the standard of care in treating mHSPC.11-13 However, there are a number of options to use for combined therapy with ADT, including androgen receptor signaling inhibitors (ARSIs), chemotherapy, targeted therapy, immunotherapy, and combinations of these. Disease burden (i.e. volume of disease) plays an important differential role in response to therapy and is included in treatment guidelines.11,12 However, with the exception of specific recommended triplet therapies currently recommended for high volume mHSPC, the nationally recognized guidelines do not provide a preferred approach for choosing among the various options when dual combination therapy is appropriate.11-13 Further, some of the therapeutic options include agents with significant toxicities and side effects. In addition, prostate cancer is a heterogeneous disease with different underlying genomic signatures and phenotypes that respond differentially to available treatment options. As such, the use of molecular biomarkers to help guide the choice of therapy is a welcome addition to the treatment arsenal for advanced and metastatic prostate cancer.

Somatic and germline mutations in deoxyribonucleic acid (DNA) repair pathway genes occur in approximately 20% of prostate tumors.14,15 Hereditary prostate cancers are associated with hereditary breast and ovarian cancer (HBOC) and Lynch syndromes, resulting from germline mutations in homologous recombination repair (HRR) genes and DNA mismatch repair (MMR) genes, respectively.16,17 Patients with prostate cancer who have BRCA1/2 germline mutations in particular have increased risk of progression and decreased overall survival (OS).17,18 Patients with such HRR gene mutations respond to poly(adenosine diphosphate–ribose) polymerase (PARP) inhibition.19 Similarly, patients with MMR gene mutations, microsatellite instability and high tumor mutational burden may respond to pembrolizumab.20 An estimated 89% of mCRPC tumors contain a potentially actionable mutation; many of these are in the androgen receptor (AR) gene and AR-signaling pathways with germline mutations reported in approximately 12% of patients.15,21 For this reason, multigene tumor testing for somatic and/or germline mutations is recommended for patients with prostate cancer and is a covered service. Additionally, gene expression profile tests (GEPs) also take advantage of prostate cancer heterogeneity to further refine the risk for recurrence and metastasis and guide therapy selection for patients with prostate cancer.

Gene Expression Profile Tests

NCCN guidelines recommend the Decipher® Prostate (Veracyte) genomic risk classifier, a GEP, to inform adjuvant treatment if adverse features are found post-radical prostatectomy (RP) and to risk stratify patients with PSA resistance/recurrence after RP.11 Decipher® Prostate is a 22 RNA biomarker test that was developed using a whole-transcriptome based approach.22-24 The assay is performed on FFPE prostate cancer tumor tissue from the diagnostic biopsy or prostate resection tissue. Results are reported as a genomic classifier score (GC) between 0 and 1 (with higher scores indicating greater risk of metastasis) based on gene expression using a machine-learning algorithm. The molecular pathways represented include cell proliferation, cell death, invasion and metastasis, androgen signaling, immune activity and response, growth and differentiation, angiogenesis and metabolism functions. It has been clinically validated to predict the risk of prostate cancer metastasis at initial diagnosis or after radical prostatectomy.23,24

The Prediction Analysis of Microarray 50 gene expression profile (PAM50) is a well-studied primary tumor classification system initially developed from large-scale transcriptomic analyses of breast carcinoma.25-27 It is used to partition breast carcinomas into multiple intrinsic subtypes, including luminal A, luminal B, basal, HER2, and Normal-types. The classifier has subsequently demonstrated the ability to subtype other solid tumors, including urothelial and prostate cancers.28-30 In localized prostate cancer, a PAM50-based analysis of samples from seven cohort studies found that luminal B cancers displayed poor clinical outcomes following primary therapy but outcomes were improved with the use of ADT; further, luminal B tumors responded better than non–luminal B tumors to postoperative ADT.29 Additionally, prostate cancers classified by PAM50 as basal-like have been found to be highly enriched for low AR signaling, with features resembling mCRPC and high recurrence rates following primary treatment.31

More recently, the Decipher GC, PAM50 classifier and other gene expression profile (transcriptomic) tests have been used to prognosticate and predict response to therapy in advanced and metastatic prostate cancers. The Chemohormonal Therapy Versus Androgen Ablation Randomized Trial for Extensive Disease in Prostate Cancer (CHAARTED) and the Systemic Therapy in Advancing or Metastatic Prostate Cancer: Evaluation of Drug Efficacy (STAMPEDE) trials demonstrated a survival benefit of ADT in combination with docetaxel compared to ADT monotherapy, particularly in the subgroup with high-volume disease.6,7,32 A subanalysis evaluated the association of three different transcriptomic signatures (Decipher GC, PAM50, and Androgen Receptor Activity (AR-A)) with the response to therapy in men with mHSPC from the CHAARTED trial.33 Expression profiling was performed on primary prostate cancer tissue. The study found a nearly even split between luminal B and basal tumor signatures; luminal A tumors were lacking, the rationale being that these tend to be enriched in localized prostate cancer. Additionally, prognostic information was found to vary according to transcriptomic subtype; for example, higher GCs were associated with lower OS and ttCRPC. Moreover, a positive effect of chemohormonal therapy on OS was observed across all GC (risk score) groups; however the relative benefit varied by GC group and was significantly greater in those with the highest GCs, termed Quartile 4 (Q4) [Q4: hazard ratio (HR) 0.41 [95% confidence interval (CI) 0.19–0.84], p=0.01], compared to those with the lowest GCs, termed Quartile 1 (Q1) [Q1: HR 0.72 [95% CI 0.29–1.73], p=0.46].33 Similarly, OS significantly improved in the PAM50 Luminal B subgroup that was treated with docetaxel (median OS: 29.8 vs 52.1 months, HR 0.45 (95%CI 0.25–0.81), p=0.007).33 Though this effect was not seen in the basal subgroup (even in those with high volume disease), patients with both luminal B and basal subtypes showed an improved time to CRPC (ttCRPC) with the addition of docetaxel. Finally, the addition of docetaxel improved both OS and ttCRPC in all AR-A subtypes.33 Therefore, though the benefit of combination therapy was seen across all subgroups, the magnitude of benefit was greatest in patients with specific transcriptomic signatures, particularly those with high GC score and luminal B subtype. This information can serve as a guide when counseling patients regarding choice of one specific therapeutic option over another.

Similar findings have been reported in men with CRPC. The Selective Prostate Androgen Receptor Targeting with ARN-509 (SPARTAN) trial found that the addition of apalutamide (APA), a second-generation ARSI, to ADT significantly improved metastasis-free survival (MFS), time to second progression (also referred to as time to progression-free survival 2 (PFS2), and OS in men with nonmetastatic CRPC (nmCRPC).34 A subanalysis evaluated the association of the Decipher GC and the PAM50 signatures with the response to therapy in men from the SPARTAN trial.35 The study found that although all patients had improved outcomes with the addition of APA to ADT vs. placebo + ADT, those with higher GC scores showed the greatest improvements in MFS (HR 0.21; 95% CI, 0.11-0.40; P < .001), OS (HR, 0.52; 95% CI, 0.29-0.94; P = .03), and PFS2 (HR, 0.39; 95% CI, 0.23-0.67; P = .001).35 In the placebo + ADT arm, patients with higher-risk GC scores showed significantly shorter MFS than those with lower-risk GC scores. However, when patients received combination therapy with APA + ADT, there was a substantial improvement in MFS outcomes for the GC-high patients such that the GC high- and low-risk scores showed similar and overlapping MFS, suggesting that the addition of APA overcame the poor prognosis associated with a high-risk GC score.35 Finally, patients with the luminal subtype in the APA + ADT arm had a significantly longer MFS (APA + ADT: HR, 0.40; 95% CI, 0.18-0.91; P = .03; placebo + ADT: HR, 0.66; 95% CI, 0.33-1.31; P = .23) compared with patients with basal subtype; similar trends were observed for OS and PFS2.35

The gene expression association studies described above were conducted in primary tissue from prospective, double-blind, randomized trials, though the transcriptomic analysis was performed retrospectively. Both of the studies (one evaluating mHSPC and the other evaluating nmCRPC) found that although all patients seemed to benefit from combination therapy with ADT, the greatest benefit of combination therapy (with docetaxel or APA) was seen in patients with high Decipher scores and in those with the luminal B subtype of prostate cancer.33,35 Similarly, a retrospective analysis of 634 tissue biopsy samples from four cohorts of men with mCRPC found that patients with luminal tumors (found to be enriched with genes associated with androgen signaling) had significantly better survival (HR, 0.27; 95% CI, 0.14-0.53; P < .001) than patients with basal tumors (HR, 0.62; 95% CI, 0.36-1.04, P = .07) when treated with ARSI combination therapy; this study also noted that the basal signature was also seen almost exclusively in the small cell/ neuroendocrine subtype tumors.36 Importantly, in this study, when they examined patients who received prior ARSI therapy, the difference between luminal and basal tumors disappeared.36

Studies have also evaluated the transcriptome of metastatic prostate tissue samples. A recent study of men with mCRPC who progressed on ADT evaluated whether genomic and transcriptomic features from metastatic biopsies prior to treatment (with enzalutamide, abiraterone, or docetaxel) would be predictive of de novo treatment resistance to enzalutamide, which occurs in approximately one-third of men.37 The transcriptional findings demonstrated that gene sets linked to low AR expression and a basal/stem cell signature were activated in nonresponders and were associated with a more aggressive phenotype and worse outcomes, as has been reported by others.36-38 Lower AR transcriptional activity was associated with enzalutamide resistance; however, levels of AR mRNA and protein expression were similar between nonresponders and responders, suggesting that AR changes may not be good predictors of enzalutamide response.37 Notably, only a single metastatic site was biopsied prior to treatment; despite this, these biopsies did show features strongly associated with de novo enzalutamide resistance, suggesting that single-site biopsy may be adequate.37 Another retrospective study evaluated archived biopsies of mCRPC samples from men who had died of prostate cancer to look for whether the PAM50 classification can partition mCRPC into subtypes reflecting cell of origin and whether these correlate with specific genomic aberrations or cellular phenotypes.39 Basal tumors were found to be largely resistant to ADT plus docetaxel and, as noted in prior studies,37,38 the neuroendocrine (NE) tumors in the cohort were found to almost exclusively classify as basal.39 Importantly, these cells with small cell NE differentiation are generally AR-null.40,41 This is unlike the mCRPC adenocarcinomas that have retained AR signaling but still express luminal or basal signatures in near-equal proportions, indicating that there are multiple drivers of the mCRPC phenotype, an observation that also been documented in other reports.39,40 Finally, though phenotypes of most primary tumors and their metastases remained intact despite therapy with ADT, docetaxel and ARSIs, there were observed instances of discordance in cases where multiple metastatic tumors were acquired. This occurred in 40% of men (n = 23) for who at least one tumor received a discordant classification from other tumors; for a subset of these, the assignment to a particular phenotype lacked confidence.39 Excluding tumors with lower confidence PAM50 classification (<0.75) resulted in a 78% concordance across tumors within an individual.39 Multiple additional studies have also found (using a number of different genomic test methodologies) a high degree of homogeneity between metastatic lesions within an individual.42-44 Further research is needed to better define intra-individual genomic tumor heterogeneity and divergence as well as phenotypic plasticity that may occur as a result of pressures from systemic therapies.

Analysis of Evidence (Rationale for Determination)

Treatment approaches that utilize a patient’s genomic signatures for the selection of optimal therapeutics have become a standard of care for many disorders. Comprehensive genomic profiling using NGS and select biomarker testing are already considered to be standard-of-care and covered services for Medicare beneficiaries with prostate cancer. Additionally, the Decipher GC has been a covered service for Medicare beneficiaries with localized prostate cancer. There is now evidence to support its use (and that of other gene expression profiles) in the advanced and metastatic prostate cancer setting. It is still expected that a patient will only require one such test for his prostate cancer indication, preferably on a primary tumor sample. However, not all men initially present with localized disease. Therefore, men who were not previously tested using a GEP for localized cancer (because they initially present with advanced or metastatic disease or because they were not previously tested for their localized cancer for some other reason) may still benefit from GEP testing of their tumor.

For castration resistant and metastatic prostate cancers, combination therapy with more than one systemic and/or radiation/radioisotope-based modality is a mainstay of treatment. However, there are multiple therapeutic options available and guidelines do not necessarily recommend the use of these agents in any other particular combination or in any particular series, particularly for low-volume advanced and metastatic disease.11,12 For some of these men, the choice may involve time and sequence -i.e. earlier combination therapy with a preferred (for multiple possible reasons) choice of drug if the results of a genomic expression profile suggest a benefit. For others, the choice may be whether to begin a therapy that they would otherwise have been unwilling to consider, if their genomic signature is found to respond particularly well to that therapy. Here we underscore the significant adverse events reported with some of the treatment options. The CHAARTED trial reported severe (Grade 3 and 4) adverse events with the use of docetaxel in approximately 30% of men.6 Additionally, a Cochrane review found that the addition of taxane-based chemotherapy to ADT increases the incidence of Grade III to V adverse events compared to ADT alone (risk ratio (RR) 2.98, 95% CI 2.19 to 4.04; low-certainty evidence); this would result in 405 more Grade III to V adverse events per 1,000 men (95% CI 243 to 621 more events).45 Antiandrogens have their own array of side effects.46 Therefore, though the choice of therapy is influenced by multiple clinical factors, including volume of disease and eligibility for chemotherapy, if a patient’s transcriptomic signature shows a differential positive benefit with a particular treatment option (a non-chemotherapy based option, for example) that information may facilitate choice of treatment, given the array of available options with their varying side effect profiles. Importantly, the differential responses to specific therapies based on transcriptomic signatures have been shown to impact survival outcomes and as such, these tests have demonstrated clinical value.

There remain unmet needs in this space, including the continued lack of evidence for the most appropriate sequencing of available treatments and for the most optimal approaches for treatment combinations and intensification of therapy. Moreover, the data to-date do not clearly demonstrate a differential benefit between the various dual combination treatment options, as there are not head-to-head studies directly comparing outcomes with ADT plus docetaxel versus ADT plus an ARSI in men with different transcriptomic profiles. Nevertheless, it has become clear that even within a single risk stratum there is significant heterogeneity in the underlying biology of prostate cancer that can be further stratified. It is also clear that genomic expression profiles have defined subtypes of tumors that show a greater or lesser magnitude of response to specific therapies that can impact survival. Finally, it is important to remember that even the currently recommended triple therapy combinations for men with high volume metastatic disease are based on the trials that were performed and showed a survival benefit.47,48 Importantly, these did not include head-to-head comparisons with all possible combinations of available ARSI options. Systematic reviews and meta-analyses have reported that, even among these patients, certain dual combinations may result in similar outcomes to those afforded by the triple combination therapies.49,50 The literature in this space is progressing rapidly and it is possible that gene expression signatures may help inform therapy for this group of men as well.

Genomic expression profiling in the guidance of prostate cancer therapy remains an actively evolving area of medicine. There are abstracts and preprints of journal articles we could not consider, as they were not fully reviewed peer-reviewed publications at the time of drafting this local coverage determination. There is also active ongoing research on the relationship between tumor volume and cancer biology and aggressiveness.51 Additionally, research on the biology and potential therapeutic value of the genomics of the metastatic lesions themselves continues to evolve.52 Further, genomic studies are being performed to help guide not only the choice of additional systemic therapies but also precision radiotherapy options in prostate cancer.53 As such, this contractor will continue to monitor the evidence, and new developments may impact this coverage decision.

Finally, the mention of specific tests in this policy as part of the literature review does not automatically imply coverage by this contractor.

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Bibliography
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  24. Spratt DE, Yousefi K, Deheshi S, et al. Individual patient-level meta-analysis of the performance of the decipher genomic classifier in high-risk men after prostatectomy to predict development of metastatic disease. J Clin Oncol. 2017;35(18):1991-1998.
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  26. Wallden B, Storhoff J, Nielsen T, et al. Development and verification of the PAM50-based Prosigna breast cancer gene signature assay. BMC Med Genomics. 2015;8:54.
  27. Parker JS, Mullins M, Cheang MC, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27(8):1160-1167. doi:10.1200/JCO.2008.18.1370
  28. Choi W, Porten S, Kim S, et al. Identification of distinct basal and luminal subtypes of muscle-invasive bladder cancer with different sensitivities to frontline chemotherapy. Cancer Cell. 2014;25(2):152-165. doi:10.1016/j.ccr.2014.01.009
  29. Zhao SG, Chang SL, Erho N, et al. Associations of luminal and basal subtyping of prostate cancer with prognosis and response to androgen deprivation therapy. JAMA Oncol. 2017;3(12):1663-1672. doi:10.1001/jamaoncol.2017.0751
  30. Zhao SG, Chen WS, Das R, et al. Clinical and genomic implications of luminal and basal subtypes across carcinomas. Clin Cancer Res. 2019;25(8):2450-2457. doi:10.1158/1078-0432.CCR-18-3121
  31. Spratt DE, Alshalalfa M, Fishbane N, 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. 2019;25(22):6721-6730. doi:10.1158/1078-0432.CCR-19-1587
  32. Kyriakopoulos CE, Chen YH, Carducci MA, et al. Chemohormonal therapy in metastatic hormone-sensitive prostate cancer: long-term survival analysis of the randomized phase III E3805 CHAARTED trial. J Clin Oncol. 2018;36(11):1080-1087. doi:10.1200/JCO.2017.75.3657
  33. Hamid AA, Huang HC, Wang V, 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. 2021;32(9):1157-1166. doi:10.1016/j.annonc.2021.06.003
  34. Smith MR, Saad F, Chowdhury S, et al. Apalutamide treatment and metastasis-free survival in prostate cancer. N Engl J Med. 2018;378(15):1408-1418. doi:10.1056/NEJMoa1715546
  35. Feng FY, Thomas S, Saad F, et al. Association of molecular subtypes with differential outcome to apalutamide treatment in nonmetastatic castration-resistant prostate cancer. JAMA Oncol. 2021;7(7):1005-1014. doi:10.1001/jamaoncol.2021.1463
  36. Aggarwal R, Rydzewski NR, Zhang L, et al. Prognosis associated with luminal and basal subtypes of metastatic prostate cancer. JAMA Oncol. 2021;7(11):1644-1652. doi:10.1001/jamaoncol.2021.3987
  37. Alumkal JJ, Sun D, Lu E, et al. Transcriptional profiling identifies an androgen receptor activity-low, stemness program associated with enzalutamide resistance. Proc Natl Acad Sci U S A. 2020;117(22):12315-12323. doi:10.1073/pnas.1922207117
  38. Zhang D, Park D, Zhong Y, et al. Stem cell and neurogenic gene-expression profiles link prostate basal cells to aggressive prostate cancer. Nat Commun. 2016;7:10798.
  39. Coleman IM, DeSarkar N, Morrissey C, et al. Therapeutic implications for intrinsic phenotype classification of metastatic castration-resistant prostate cancer. Clin Cancer Res. 2022;28(14):3127-3140. doi:10.1158/1078-0432.CCR-21-4289
  40. Labrecque MP, Coleman IM, Brown LG, et al. Molecular profiling stratifies diverse phenotypes of treatment-refractory metastatic castration-resistant prostate cancer. J Clin Invest. 2019;129(10):4492-4505.
  41. Beltran H, Prandi D, Mosquera JM, et al. Divergent clonal evolution of castration-resistant neuroendocrine prostate cancer. Nat Med. 2016;22(3):298-305. doi:10.1038/nm.4045
  42. Kumar A, Coleman I, Morrissey C, et al. Substantial interindividual and limited intraindividual genomic diversity among tumors from men with metastatic prostate cancer. Nat Med. 2016;22(4):369-378. doi:10.1038/nm.4053
  43. Aryee MJ, Liu W, Engelmann JC, et al. DNA methylation alterations exhibit intraindividual stability and interindividual heterogeneity in prostate cancer metastases. Sci Transl Med. 2013;5(169):169ra10. doi:10.1126/scitranslmed.3005211
  44. Liu W, Laitinen S, Khan S, et al. Copy number analysis indicates monoclonal origin of lethal metastatic prostate. Nat Med. 2009;15(5):559-565. doi:10.1038/nm.1944
  45. Sathianathen NJ, Philippou YA, Kuntz GM, et al. Taxane-based chemohormonal therapy for metastatic hormone-sensitive prostate cancer. Cochrane Database Syst Rev. 2018;10(10):CD012816.
  46. Nowakowska MK, Ortega RM, Wehner MR, Nead KT. Association of second-generation antiandrogens with cognitive and functional toxic effects in randomized clinical trials: a systematic review and meta-analysis [published online ahead of print, 2023 May 25]. JAMA Oncol. 2023;e230998. doi:10.1001/jamaoncol.2023.0998
  47. Fizazi K, Foulon S, Carles J, et al. Abiraterone plus prednisone added to androgen deprivation therapy and docetaxel in de novo metastatic castration-sensitive prostate cancer (PEACE-1): a multicentre, open-label, randomised, phase 3 study with a 2×2 factorial design. Lancet. 2022;399(10336):1695-1707. doi:10.1016/S0140-6736(22)00367-1
  48. Smith MR, Hussain M, Saad F, et al. Darolutamide and survival in metastatic, hormone-sensitive prostate cancer. N Engl J Med. 2022;386(12):1132-1142. doi:10.1056/NEJMoa2119115
  49. Riaz IB, Naqvi SAA, He H, et al. First-line systemic treatment options for metastatic castration-sensitive prostate cancer: a living systematic review and network meta-analysis. JAMA Oncol. 2023;9(5):635-645. doi:10.1001/jamaoncol.2022.7762
  50. Hoeh B, Garcia CC, Wenzel M, et al. Triplet or doublet therapy in metastatic hormone-sensitive prostate cancer: updated network meta-analysis stratified by disease volume [published online ahead of print, 2023 Apr 11]. Eur Urol Focus. 2023;S2405-4569(23)00094-9. doi:10.1016/j.euf.2023.03.024
  51. Ramaswamy A, Proudfoot JA, Ross AE, Davicioni E, Schaeffer EM, Hu JC. Prostate cancer tumor volume and genomic risk. Eur Urol Open Sci. 2023;48:90-97.
  52. Thysell E, Köhn L, Semenas J, et al. Clinical and biological relevance of the transcriptomic-based prostate cancer metastasis subtypes MetA-C. Mol Oncol. 2022;16(4):846-859. doi:10.1002/1878-0261.13158
  53. Sutera P, Deek MP, Van der Eecken K, et al. Genomic biomarkers to guide precision radiotherapy in prostate cancer. Prostate. 2022;82 Suppl 1(Suppl 1):S73-S85. doi:10.1002/pros.24373
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Bibliography
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  8. Fizazi K, Tran N, Fein L, et al. Abiraterone plus prednisone in metastatic, castration-sensitive prostate cancer. N Engl J Med. 2017;377(4):352-360. doi:10.1056/NEJMoa1704174
  9. Beer TM, Armstrong AJ, Rathkopf DE, et al. Enzalutamide in metastatic prostate cancer before chemotherapy. N Engl J Med. 2014;371(5):424-433. doi:10.1056/NEJMoa1405095
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  14. Cancer Genome Atlas Research Network. The molecular taxonomy of primary prostate cancer. Cell. 2015;163(4):1011-1025. doi:10.1016/j.cell.2015.10.025
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  18. Messina C, Cattrini C, Soldato D, et al. BRCA mutations in prostate cancer: prognostic and predictive implications. J Oncol. 2020;2020:4986365. doi:10.1155/2020/4986365
  19. de Bono J, Mateo J, Fizazi K, et al. Olaparib for metastatic castration-resistant prostate cancer. N Engl J Med. 2020;382(22):2091-2102. doi:10.1056/NEJMoa1911440
  20. Gillette CM, Yette GA, Cramer SD, Graham LS. Management of advanced prostate cancer in the precision oncology era. Cancers (Basel). 2023;15(9):2552. doi:10.3390/cancers15092552
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  22. Erho N, Crisan A, Vergara IA, et al. Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy. PLoS One. 2013;8(6):e66855.
  23. Kim HL, Li P, Huang HC, et al. Validation of the Decipher Test for predicting adverse pathology in candidates for prostate cancer active surveillance. Prostate Cancer Prostatic Dis. 2019;22(3):399-405. doi:10.1038/s41391-018-0101-6
  24. Spratt DE, Yousefi K, Deheshi S, et al. Individual patient-level meta-analysis of the performance of the decipher genomic classifier in high-risk men after prostatectomy to predict development of metastatic disease. J Clin Oncol. 2017;35(18):1991-1998.
  25. Sørlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A. 2001;98(19):10869-10874. doi:10.1073/pnas.191367098
  26. Wallden B, Storhoff J, Nielsen T, et al. Development and verification of the PAM50-based Prosigna breast cancer gene signature assay. BMC Med Genomics. 2015;8:54.
  27. Parker JS, Mullins M, Cheang MC, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27(8):1160-1167. doi:10.1200/JCO.2008.18.1370
  28. Choi W, Porten S, Kim S, et al. Identification of distinct basal and luminal subtypes of muscle-invasive bladder cancer with different sensitivities to frontline chemotherapy. Cancer Cell. 2014;25(2):152-165. doi:10.1016/j.ccr.2014.01.009
  29. Zhao SG, Chang SL, Erho N, et al. Associations of luminal and basal subtyping of prostate cancer with prognosis and response to androgen deprivation therapy. JAMA Oncol. 2017;3(12):1663-1672. doi:10.1001/jamaoncol.2017.0751
  30. Zhao SG, Chen WS, Das R, et al. Clinical and genomic implications of luminal and basal subtypes across carcinomas. Clin Cancer Res. 2019;25(8):2450-2457. doi:10.1158/1078-0432.CCR-18-3121
  31. Spratt DE, Alshalalfa M, Fishbane N, 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. 2019;25(22):6721-6730. doi:10.1158/1078-0432.CCR-19-1587
  32. Kyriakopoulos CE, Chen YH, Carducci MA, et al. Chemohormonal therapy in metastatic hormone-sensitive prostate cancer: long-term survival analysis of the randomized phase III E3805 CHAARTED trial. J Clin Oncol. 2018;36(11):1080-1087. doi:10.1200/JCO.2017.75.3657
  33. Hamid AA, Huang HC, Wang V, 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. 2021;32(9):1157-1166. doi:10.1016/j.annonc.2021.06.003
  34. Smith MR, Saad F, Chowdhury S, et al. Apalutamide treatment and metastasis-free survival in prostate cancer. N Engl J Med. 2018;378(15):1408-1418. doi:10.1056/NEJMoa1715546
  35. Feng FY, Thomas S, Saad F, et al. Association of molecular subtypes with differential outcome to apalutamide treatment in nonmetastatic castration-resistant prostate cancer. JAMA Oncol. 2021;7(7):1005-1014. doi:10.1001/jamaoncol.2021.1463
  36. Aggarwal R, Rydzewski NR, Zhang L, et al. Prognosis associated with luminal and basal subtypes of metastatic prostate cancer. JAMA Oncol. 2021;7(11):1644-1652. doi:10.1001/jamaoncol.2021.3987
  37. Alumkal JJ, Sun D, Lu E, et al. Transcriptional profiling identifies an androgen receptor activity-low, stemness program associated with enzalutamide resistance. Proc Natl Acad Sci U S A. 2020;117(22):12315-12323. doi:10.1073/pnas.1922207117
  38. Zhang D, Park D, Zhong Y, et al. Stem cell and neurogenic gene-expression profiles link prostate basal cells to aggressive prostate cancer. Nat Commun. 2016;7:10798.
  39. Coleman IM, DeSarkar N, Morrissey C, et al. Therapeutic implications for intrinsic phenotype classification of metastatic castration-resistant prostate cancer. Clin Cancer Res. 2022;28(14):3127-3140. doi:10.1158/1078-0432.CCR-21-4289
  40. Labrecque MP, Coleman IM, Brown LG, et al. Molecular profiling stratifies diverse phenotypes of treatment-refractory metastatic castration-resistant prostate cancer. J Clin Invest. 2019;129(10):4492-4505.
  41. Beltran H, Prandi D, Mosquera JM, et al. Divergent clonal evolution of castration-resistant neuroendocrine prostate cancer. Nat Med. 2016;22(3):298-305. doi:10.1038/nm.4045
  42. Kumar A, Coleman I, Morrissey C, et al. Substantial interindividual and limited intraindividual genomic diversity among tumors from men with metastatic prostate cancer. Nat Med. 2016;22(4):369-378. doi:10.1038/nm.4053
  43. Aryee MJ, Liu W, Engelmann JC, et al. DNA methylation alterations exhibit intraindividual stability and interindividual heterogeneity in prostate cancer metastases. Sci Transl Med. 2013;5(169):169ra10. doi:10.1126/scitranslmed.3005211
  44. Liu W, Laitinen S, Khan S, et al. Copy number analysis indicates monoclonal origin of lethal metastatic prostate. Nat Med. 2009;15(5):559-565. doi:10.1038/nm.1944
  45. Sathianathen NJ, Philippou YA, Kuntz GM, et al. Taxane-based chemohormonal therapy for metastatic hormone-sensitive prostate cancer. Cochrane Database Syst Rev. 2018;10(10):CD012816.
  46. Nowakowska MK, Ortega RM, Wehner MR, Nead KT. Association of second-generation antiandrogens with cognitive and functional toxic effects in randomized clinical trials: a systematic review and meta-analysis [published online ahead of print, 2023 May 25]. JAMA Oncol. 2023;e230998. doi:10.1001/jamaoncol.2023.0998
  47. Fizazi K, Foulon S, Carles J, et al. Abiraterone plus prednisone added to androgen deprivation therapy and docetaxel in de novo metastatic castration-sensitive prostate cancer (PEACE-1): a multicentre, open-label, randomised, phase 3 study with a 2×2 factorial design. Lancet. 2022;399(10336):1695-1707. doi:10.1016/S0140-6736(22)00367-1
  48. Smith MR, Hussain M, Saad F, et al. Darolutamide and survival in metastatic, hormone-sensitive prostate cancer. N Engl J Med. 2022;386(12):1132-1142. doi:10.1056/NEJMoa2119115
  49. Riaz IB, Naqvi SAA, He H, et al. First-line systemic treatment options for metastatic castration-sensitive prostate cancer: a living systematic review and network meta-analysis. JAMA Oncol. 2023;9(5):635-645. doi:10.1001/jamaoncol.2022.7762
  50. Hoeh B, Garcia CC, Wenzel M, et al. Triplet or doublet therapy in metastatic hormone-sensitive prostate cancer: updated network meta-analysis stratified by disease volume [published online ahead of print, 2023 Apr 11]. Eur Urol Focus. 2023;S2405-4569(23)00094-9. doi:10.1016/j.euf.2023.03.024
  51. Ramaswamy A, Proudfoot JA, Ross AE, Davicioni E, Schaeffer EM, Hu JC. Prostate cancer tumor volume and genomic risk. Eur Urol Open Sci. 2023;48:90-97.
  52. Thysell E, Köhn L, Semenas J, et al. Clinical and biological relevance of the transcriptomic-based prostate cancer metastasis subtypes MetA-C. Mol Oncol. 2022;16(4):846-859. doi:10.1002/1878-0261.13158
  53. Sutera P, Deek MP, Van der Eecken K, et al. Genomic biomarkers to guide precision radiotherapy in prostate cancer. Prostate. 2022;82 Suppl 1(Suppl 1):S73-S85. doi:10.1002/pros.24373

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