Transcriptome-Based Prognostic and Predictive Biomarker Analysis of ENACT: A Randomized Controlled Trial of Enzalutamide in Men Undergoing Active Surveillance.

PURPOSE: Few studies have explored the potential for pharmacological interventions to delay disease progression in patients undergoing active surveillance (AS). This preplanned transcriptomic analysis of patient samples from the ENACT trial aims to identify biomarkers in patients on AS who are at increased risk for disease progression or who may derive the greatest benefit from enzalutamide treatment. PATIENTS AND METHODS: In the phase II ENACT (ClinicalTrials.gov identifier: NCT02799745) trial, patients on AS were randomly assigned 1:1 to 160 mg orally once daily enzalutamide monotherapy or continued AS for 1 year. Transcriptional analyses were conducted on biopsies collected at trial screening, year 1, and year 2. Three gene expression signatures were evaluated in samples collected at screening and in available samples from patients on AS at any time during surveillance (expanded cohort): Decipher genomic classifier, androgen receptor activity (AR-A) score, and Prediction Analysis of Microarray 50 (PAM50) cell subtype signature. RESULTS: The Decipher genomic classifier score was prognostic; higher scores were associated with disease progression in the expanded cohort and AS arm of the expanded cohort. Patients with higher Decipher scores had greater positive treatment effect from enzalutamide as measured by time to secondary rise in prostate-specific antigen >25% above baseline. In patients treated with enzalutamide, higher AR-A scores and PAM50 luminal subtypes were associated with a greater likelihood of negative biopsy incidence at year 2. CONCLUSION: This analysis suggests that the Decipher genomic classifier may be prognostic for disease progression in AS patients with low- to intermediate-risk prostate cancer. Higher Decipher and AR-A scores, as well as PAM50 luminal subtypes, may also serve as biomarkers for treatment response.

From Diabetes to Oncology: Glucagon-like Peptide-1 (GLP-1) Receptor Agonist's Dual Role in Prostate Cancer.

Glucagon-like peptide-1 (GLP-1), an incretin hormone renowned for its role in post-meal blood sugar regulation and glucose-dependent insulin secretion, has gained attention as a novel treatment for diabetes through GLP-1 receptor agonists (GLP-1-RA). Despite their efficacy, concerns have been raised regarding the potential associations between GLP-1-RA and certain malignancies, including medullary thyroid cancer. However, evidence of its association with prostate cancer (PCa) remains inconclusive. This review delves into the intricate relationship between GLP-1-RA and PCa, exploring the mechanisms through which GLP-1-Rs may impact PCa cells. We discuss the potential pathways involving cAMP, ERK, AMPK, mTOR, and P27. Furthermore, we underscore the imperative for additional research to elucidate the impact of GLP-1-RA treatment on PCa progression, patient outcomes, and potential interactions with existing therapies. Translational studies and clinical trials are crucial for a comprehensive understanding of the role of GLP-1-RA in PCa management.

Quantification and molecular correlates of tertiary lymphoid structures in primary prostate cancer.

OBJECTIVE: To morphologically describe tertiary lymphoid structures (TLS) in prostatectomy specimens and correlate them with clinical and transcriptomic features. METHODOLOGY: A total of 72 consecutive cases of entirely submitted radical prostatectomy (RP) patients tested with the Decipher Genomic Classifier were included in the study. Images were manually annotated using QuPath tools to denote tumor regions and each cluster of TLS. Clusters of lymphocytes that were surrounded on all four sides by tumor were defined as intra-tumor TLS (IT-TLS). Clusters of lymphocytes at the leading edge of carcinoma with either the prostatic pseudocapsule or benign parenchyma at one end were defined as peri-tumor TLS (PT-TLS). A classification algorithm to distinguish lymphocytes from non-lymphocytic cells using a supervised machine learning model was used. The associations between TLS formation and 265 gene expression-based signatures were examined. RESULTS: The magnitude of total TLS correlations with primary tumor gene expression signatures was moderate (~0.35-0.5) with several HLA, T-cell and B-cell Cluster signatures, showing positive correlation with various metrics for quantification of TLS. On the other hand, immune suppressive signatures (Treg, MDSC) were negatively correlated. While signatures for macrophages, NK cells and other immune cell types were uncorrelated for the most part. PT-TLS was associated with MHC signatures while IT TLS correlated with MHC and T-cell signatures. CONCLUSIONS: Clusters of inflammatory cells in the RP specimen can be divided spatially into PT TLS and IT-TLS, each with its unique molecular correlates of tumor immune microenvironment. The presence of TLS is positively correlated with MHC signatures, T- cell and B-cell cluster signatures but, negatively correlated with immune suppressive signatures. A subset of prostate cancer demonstrate a robust inflammatory response, and warrant further characterization in larger cohorts.

Canonical AREs are tumor suppressive regulatory elements in the prostate.

The androgen receptor (AR) is the central determinant of prostate tissue identity and differentiation, controlling normal, growth-suppressive prostate-specific gene expression 1 . It is also a key driver of prostate tumorigenesis, becoming "hijacked" to drive oncogenic transcription 2-5 . However, the regulatory elements determining the execution of the growth suppressive AR transcriptional program, and whether this can be reactivated in prostate cancer (PCa) cells remains unclear. Canonical androgen response element (ARE) motifs are the classic DNA binding element for AR 6 . Here, we used a genome-wide strategy to modulate regulatory elements containing AREs to define distinct AR transcriptional programs. We find that activation of these AREs is specifically associated with differentiation and growth suppressive transcription, and this can be reactivated to cause death in AR + PCa cells. In contrast, repression of AREs is well tolerated by PCa cells, but deleterious to normal prostate cells. Finally, gene expression signatures driven by ARE activity are associated with improved prognosis and luminal phenotypes in human PCa patients. This study demonstrates that canonical AREs are responsible for a normal, growth-suppressive, lineage-specific transcriptional program, that this can be reengaged in PCa cells for potential therapeutic benefit, and genes controlled by this mechanism are clinically relevant in human PCa patients.

Transcriptomic Heterogeneity of Expansile Cribriform and Other Gleason Pattern 4 Prostate Cancer Subtypes.

BACKGROUND: Prostate cancers featuring an expansile cribriform (EC) pattern are associated with worse clinical outcomes following radical prostatectomy (RP). However, studies of the genomic characteristics of Gleason pattern 4 subtypes are limited. OBJECTIVE: To explore transcriptomic characteristics and heterogeneity within Gleason pattern 4 subtypes (fused/poorly formed, glomeruloid, small cribriform, EC/intraductal carcinoma [IDC]) and the association with biochemical recurrence (BCR)-free survival. DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective cohort study including 165 men with grade group 2-4 prostate cancer who underwent RP at a single academic institution (2016-2020) and Decipher testing of the RP specimen. Patients with Gleason pattern 5 were excluded. IDC and EC patterns were grouped. Median follow-up was 2.5 yr after RP for patients without BCR. OUTCOMES MEASUREMENTS AND STATISTICAL ANALYSIS: Prompted by heterogeneity within pattern 4 subtypes identified via exploratory analyses, we investigated transcriptomic consensus clusters using partitioning around medoids and hallmark gene set scores. The primary clinical outcome was BCR, defined as two consecutive prostate-specific antigen measurements >0.2 ng/ml at least 8 wk after RP, or any additional treatment. Multivariable Cox proportional-hazards models were used to determine factors associated with BCR-free survival. RESULTS AND LIMITATIONS: In this cohort, 99/165 patients (60%) had EC and 67 experienced BCR. Exploratory analyses and clustering demonstrated transcriptomic heterogeneity within each Gleason pattern 4 subtype. In the multivariable model controlled for pattern 4 subtype, margin status, Cancer of the Prostate Risk Assessment Post-Surgical score, and Decipher score, a newly identified steroid hormone-driven cluster (hazard ratio 2.35 95% confidence interval 1.01-5.47) was associated with worse BCR-free survival. The study is limited by intermediate follow-up, no validation cohort, and lack of accounting for intratumoral and intraprostatic heterogeneity. CONCLUSIONS: Transcriptomic heterogeneity was present within and across each Gleason pattern 4 subtype, demonstrating there is additional biologic diversity not captured by histologic subtypes. This heterogeneity can be used to develop novel signatures and to classify transcriptomic subtypes, which may help in refining risk stratification following RP to further guide decision-making on adjuvant and salvage treatments. PATIENT SUMMARY: We studied prostatectomy specimens and found that tumors with similar microscopic appearance can have genetic differences that may help to predict outcomes after prostatectomy for prostate cancer. Our results demonstrate that further gene expression analysis of prostate cancer subtypes may improve risk stratification after prostatectomy. Future studies are needed to develop novel gene expression signatures and validate these findings in independent sets of patients.

F-SHARP: a Phase I/II trial of focal salvage high-dose-rate brachytherapy for Radiorecurrent prostate cancer.

BACKGROUND: Intraprostatic local radiorecurrence (LRR) after definitive radiation is being increasingly identified due to the implementation of molecular positron emission tomography (PET)/computed tomography (CT) imaging for the evaluation of biochemical recurrence. Salvage high-dose rate (HDR) brachytherapy offers a promising local therapy option, with encouraging toxicity and efficacy based on early series. Furthermore, the incorporation of advanced imaging allows for focal HDR to further reduce toxicity to maximise the therapeutic ratio. The objectives of the 'focal salvage HDR brachytherapy for locally recurrent prostate cancer in patients treated with prior radiotherapy' (F-SHARP) trial are to determine the acute and late toxicity and efficacy outcomes of focal salvage HDR brachytherapy for LRR prostate cancer. STUDY DESIGN: The F-SHARP is a multi-institutional two-stage Phase I/II clinical trial of salvage focal HDR brachytherapy for LRR prostate cancer enrolling patients at three centres. ENDPOINTS: The primary endpoint is the acute radiation-related Grade ≥3 Common Terminology Criteria for Adverse Events (CTCAE, version 4.03) genitourinary (GU) and gastrointestinal (GI) toxicity rate, defined as within 3 months of brachytherapy. Secondary endpoints include acute and late CTCAE toxicity, biochemical failure, patterns of clinical progression, disease-specific and overall survival, and health-related quality of life, as measured by the International Prostate Symptom Score and 26-item Expanded Prostate Cancer Index Composite instruments. PATIENTS AND METHODS: Key eligibility criteria include: biopsy confirmed LRR prostate adenocarcinoma after prior definitive radiation therapy using any radiotherapeutic modality, no evidence of regional or distant metastasis, and cT1-3a Nx or N0 prostate cancer at initial treatment. All patients will have multiparametric magnetic resonance imaging and molecular PET/CT imaging if possible. In Stage 1, seven patients will be accrued. If there are two or more GI or GU Grade ≥3 toxicities, the study will be stopped. Otherwise, 17 additional patients will be accrued (total of 24 patients). For Stage 2, the cohort will expand to 62 subjects to study the efficacy outcomes, long-term toxicity profile, quality of life, and compare single- vs multi-fraction HDR. Transcriptomic analysis of recurrence biopsies will be performed to identify potential prognostic and predictive biomarkers.

Clinical-Genomic Risk Group Classification of Suspicious Lesions on Prostate Multiparametric-MRI.

The utilization of multi-parametric MRI (mpMRI) in clinical decisions regarding prostate cancer patients' management has recently increased. After biopsy, clinicians can assess risk using National Comprehensive Cancer Network (NCCN) risk stratification schema and commercially available genomic classifiers, such as Decipher. We built radiomics-based models to predict lesions/patients at low risk prior to biopsy based on an established three-tier clinical-genomic classification system. Radiomic features were extracted from regions of positive biopsies and Normally Appearing Tissues (NAT) on T2-weighted and Diffusion-weighted Imaging. Using only clinical information available prior to biopsy, five models for predicting low-risk lesions/patients were evaluated, based on: 1: Clinical variables; 2: Lesion-based radiomic features; 3: Lesion and NAT radiomics; 4: Clinical and lesion-based radiomics; and 5: Clinical, lesion and NAT radiomic features. Eighty-three mpMRI exams from 78 men were analyzed. Models 1 and 2 performed similarly (Area under the receiver operating characteristic curve were 0.835 and 0.838, respectively), but radiomics significantly improved the lesion-based performance of the model in a subset analysis of patients with a negative Digital Rectal Exam (DRE). Adding normal tissue radiomics significantly improved the performance in all cases. Similar patterns were observed on patient-level models. To the best of our knowledge, this is the first study to demonstrate that machine learning radiomics-based models can predict patients' risk using combined clinical-genomic classification.

Intratumoral androgen biosynthesis associated with 3ß-hydroxysteroid dehydrogenase 1 promotes resistance to radiotherapy in prostate cancer.

Half of all men with advanced prostate cancer (PCa) inherit at least 1 copy of an adrenal-permissive HSD3B1 (1245C) allele, which increases levels of 3ß-hydroxysteroid dehydrogenase 1 (3ßHSD1) and promotes intracellular androgen biosynthesis. Germline inheritance of the adrenally permissive allele confers worse outcomes in men with advanced PCa. We investigated whether HSD3B1 (1245C) drives resistance to combined androgen deprivation and radiotherapy. Adrenally permissive 3ßHSD1 enhanced resistance to radiotherapy in PCa cell lines and xenograft models engineered to mimic the human adrenal/gonadal axis during androgen deprivation. The allele-specific effects on radiosensitivity were dependent on availability of DHEA, the substrate for 3ßHSD1. In lines expressing the HSD3B1 (1245C) allele, enhanced expression of DNA damage response (DDR) genes and more rapid DNA double-strand break (DSB) resolution were observed. A correlation between androgen receptor (AR) expression and increased DDR gene expression was confirmed in 680 radical prostatectomy specimens. Treatment with the nonsteroidal antiandrogen enzalutamide reversed the resistant phenotype of HSD3B1 (1245C) PCa in vitro and in vivo. In conclusion, 3ßHSD1 promotes prostate cancer resistance to combined androgen deprivation and radiotherapy by upregulating DNA DSB repair. This work supports prospective validation of early combined androgen blockade for high-risk men harboring the HSD3B1 (1245C) allele.

Analysing the tumor transcriptome of prostate cancer to predict efficacy of Lu-PSMA therapy.

RATIONALE: 177Lu-PSMA ([177Lu]Lutetium-PSMA-617) therapy is an effective treatment option for patients with prostate specific membrane antigen (PSMA)-positive metastatic castration-resistant prostate cancer, but still shows a non-responder rate of approximately 30%. Combination regimes of programmed death-ligand 1 (PD-L1) inhibition and concomitant 177Lu-PSMA therapy have been proposed to increase the response rate. However, the interplay of immune landscape and 177Lu-PSMA therapy efficacy is poorly understood. METHODS: Between March 2018 and December 2021, a total of 168 patients were referred to 177Lu-PSMA therapy in our department and received a mean total dose of 21.9 GBq (three cycles in mean). All patients received baseline PSMA positron emission tomography to assess the PSMA uptake. The histopathological specimen of the primary prostate tumor was available with sufficient RNA passing quality control steps for genomic analysis in n=23 patients. In this subset of patients, tumor RNA transcriptomic analyses assessed 74 immune-related features in total, out of which n=24 signatures were not co-correlated and investigated further for outcome prognostication. RESULTS: In the subset of patients who received 177Lu-PSMA therapy, PD-L1 was not significantly associated with OS (HR per SD change (95% CI) 0.74 (0.42 to 1.30); SD: 0.18; p=0.29). In contrast, PD-L2 signature was positively associated with longer OS (HR per SD change 0.46 (95% CI 0.29 to 0.74); SD: 0.24; p=0.001; median OS 17.2 vs 5.7 months in higher vs lower PD-L2 patients). In addition, PD-L2 signature correlated with PSA-response (ϱ=-0.46; p=0.04). The PD-L2 signature association with OS was significantly moderated by L-Lactatdehydrogenase (LDH) levels (Cox model interaction p=0.01). CONCLUSION: Higher PD-L2 signature might be associated with a better response to 177Lu-PSMA therapy and warrants further studies investigating additional immunotherapy. In contrast, PD-L1 was not associated with outcome. The protective effect of PD-L2 signature might be present only in men with lower LDH levels.

Genomic Tumor Correlates of Clinical Outcomes Following Organ-Sparing Chemoradiation Therapy for Bladder Cancer.

PURPOSE: There is an urgent need for biomarkers of radiation response in organ-sparing therapies. Bladder preservation with trimodality therapy (TMT), consisting of transurethral tumor resection followed by chemoradiation, is an alternative to radical cystectomy for muscle-invasive bladder cancer (MIBC), but molecular determinants of response are poorly understood. EXPERIMENTAL DESIGN: We characterized genomic and transcriptomic features correlated with long-term response in a single institution cohort of patients with MIBC homogeneously treated with TMT. Pretreatment tumors from 76 patients with MIBC underwent whole-exome sequencing; 67 underwent matched transcriptomic profiling. Molecular features were correlated with clinical outcomes including modified bladder-intact event-free survival (mBI-EFS), a composite endpoint that reflects long-term cancer control with bladder preservation. RESULTS: With a median follow-up of 74.6 months in alive patients, 37 patients had favorable long-term response to TMT while 39 had unfavorable long-term response. Tumor mutational burden was not associated with outcomes after TMT. DNA damage response gene alterations were associated with improved locoregional control and mBI-EFS. Of these alterations, somatic ERCC2 mutations stood out as significantly associated with favorable long-term outcomes; patients with ERCC2 mutations had significantly improved mBI-EFS [HR, 0.15; 95% confidence interval (CI), 0.06-0.37; P = 0.030] and improved BI-EFS, an endpoint that includes all-cause mortality (HR, 0.33; 95% CI, 0.15-0.68; P = 0.044). ERCC2 mutant bladder cancer cell lines were significantly more sensitive to concurrent cisplatin and radiation treatment in vitro than isogenic ERCC2 wild-type cells. CONCLUSIONS: Our data identify ERCC2 mutation as a candidate biomarker associated with sensitivity and long-term response to chemoradiation in MIBC. These findings warrant validation in independent cohorts.

Use of the Decipher genomic classifier among men with prostate cancer in the United States.

BACKGROUND: Management of localized or recurrent prostate cancer since the 1990s has been based on risk stratification using clinicopathological variables, including Gleason score, T stage (based on digital rectal exam), and prostate-specific antigen (PSA). In this study a novel prognostic test, the Decipher Prostate Genomic Classifier (GC), was used to stratify risk of prostate cancer progression in a US national database of men with prostate cancer. METHODS: Records of prostate cancer cases from participating SEER (Surveillance, Epidemiology, and End Results) program registries, diagnosed during the period from 2010 through 2018, were linked to records of testing with the GC prognostic test. Multivariable analysis was used to quantify the association between GC scores or risk groups and use of definitive local therapy after diagnosis in the GC biopsy-tested cohort and postoperative radiotherapy in the GC-tested cohort as well as adverse pathological findings after prostatectomy. RESULTS: A total of 572 545 patients were included in the analysis, of whom 8927 patients underwent GC testing. GC biopsy-tested patients were more likely to undergo active active surveillance or watchful waiting than untested patients (odds ratio [OR] =2.21, 95% confidence interval [CI] = 2.04 to 2.38, P < .001). The highest use of active surveillance or watchful waiting was for patients with a low-risk GC classification (41%) compared with those with an intermediate- (27%) or high-risk (11%) GC classification (P < .001). Among National Comprehensive Cancer Network patients with low and favorable-intermediate risk, higher GC risk class was associated with greater use of local therapy (OR = 4.79, 95% CI = 3.51 to 6.55, P < .001). Within this subset of patients who were subsequently treated with prostatectomy, high GC risk was associated with harboring adverse pathological findings (OR = 2.94, 95% CI = 1.38 to 6.27, P = .005). Use of radiation after prostatectomy was statistically significantly associated with higher GC risk groups (OR = 2.69, 95% CI = 1.89 to 3.84). CONCLUSIONS: There is a strong association between use of the biopsy GC test and likelihood of conservative management. Higher genomic classifier scores are associated with higher rates of adverse pathology at time of surgery and greater use of postoperative radiotherapy.In this study the Decipher Prostate Genomic Classifier (GC) was used to analyze a US national database of men with prostate cancer. Use of the GC was associated with conservative management (ie, active surveillance). Among men who had high-risk GC scores and then had surgery, there was a 3-fold higher chance of having worrisome findings in surgical specimens.

Transcriptomic Signatures Associated With Outcomes in Recurrent Prostate Cancer Treated With Salvage Radiation, Androgen-Deprivation Therapy, and Enzalutamide: Correlative Analysis of the STREAM Trial.

PURPOSE: Men with rising prostate-specific antigen (PSA) after radical prostatectomy (RP) may progress despite radiation and androgen-deprivation therapy (ADT). Tissue-based transcriptomic signatures can identify who may benefit from a more aggressive systemic approach. METHODS: We performed a retrospective analysis of a prospective phase II multicenter trial of enzalutamide, ADT, and salvage radiotherapy in men with rising PSA after RP. Tumor tissue was analyzed using the Decipher platform for gene expression, including a novel prostate subtyping classifier, PTEN loss, homologous recombination deficiency (HRD), and ADT response. Cox models were used to associate signature scores with progression-free survival (PFS). RESULTS: Of the 38 men enrolled, 31 had tissue with sufficient-quality RNA for genomic analysis. Luminal differentiated (LD) subtype tumors had the longest 3-year PFS at 89% compared with 19% in the luminal proliferating subtype. Men with signatures of PTEN loss (hazard ratio [HR], 1.32; 95% CI, 1.07 to 1.64; P = .01) or HRD (HR, 1.21; 95% CI, 1.05 to 1.39; P = .009) had worse PFS, while those with higher ADT response signature scores (HR, 0.75; 95% CI, 0.61 to 0.94; P = .01) were associated with improved PFS. Analysis of these signatures in a large cohort (n = 5,330) of RP samples from patients with biochemical recurrence found that these signatures provide complementary information related to outcomes with salvage radiation. CONCLUSION: Despite aggressive systemic therapy with salvage radiation, nearly 50% of high-risk men relapse within 3 years. We show that LD and higher ADT sensitivity tumors had favorable outcomes. Those with a luminal proliferating subtype, PTEN loss, and/or HRD signatures had poor outcomes despite ADT/radiation and enzalutamide and may benefit from alternative approaches.

Histology Specific Molecular Biomarkers: Ushering in a New Era of Precision Radiation Oncology.

Histopathology and clinical staging have historically formed the backbone for allocation of treatment decisions in oncology. Although this has provided an extremely practical and fruitful approach for decades, it has long been evident that these data alone do not adequately capture the heterogeneity and breadth of disease trajectories experienced by patients. As efficient and affordable DNA and RNA sequencing have become available, the ability to provide precision therapy has become within grasp. This has been realized with systemic oncologic therapy, as targeted therapies have demonstrated immense promise for subsets of patients with oncogene-driver mutations. Further, several studies have evaluated predictive biomarkers for response to systemic therapy within a variety of malignancies. Within radiation oncology, the use of genomics/transcriptomics to guide the use, dose, and fractionation of radiation therapy is rapidly evolving but still in its infancy. The genomic adjusted radiation dose/radiation sensitivity index is one such early and exciting effort to provide genomically guided radiation dosing with a pan-cancer approach. In addition to this broad method, a histology specific approach to precision radiation therapy is also underway. Herein we review select literature surrounding the use of histology specific, molecular biomarkers to allow for precision radiotherapy with the greatest emphasis on commercially available and prospectively validated biomarkers.

Genomic Classifier Performance in Intermediate-Risk Prostate Cancer: Results From NRG Oncology/RTOG 0126 Randomized Phase 3 Trial.

PURPOSE: Intermediate-risk prostate cancer is a heterogeneous disease state with diverse treatment options. The 22-gene Decipher genomic classifier (GC) retrospectively has shown to improve risk stratification in these patients. We assessed the performance of the GC in men with intermediate-risk disease enrolled in NRG Oncology/RTOG 01-26 with updated follow-up. METHODS AND MATERIALS: After National Cancer Institute approval, biopsy slides were collected from NRG Oncology/RTOG 01-26, a randomized phase 3 trial of men with intermediate-risk prostate cancer randomized to 70.2 Gy versus 79.2 Gy of radiation therapy without androgen deprivation therapy. RNA was extracted from the highest-grade tumor foci to generate the locked 22-gene GC model. The primary endpoint for this ancillary project was disease progression (composite of biochemical failure, local failure, distant metastasis, prostate cancer-specific mortality, and use of salvage therapy). Individual endpoints were also assessed. Fine-Gray or cause-specific Cox multivariable models were constructed adjusting for randomization arm and trial stratification factors. RESULTS: Two-hundred fifteen patient samples passed quality control for analysis. The median follow-up was 12.8 years (range, 2.4-17.7). On multivariable analysis, the 22-gene GC (per 0.1 unit) was independently prognostic for disease progression (subdistribution hazard ratio [sHR], 1.12; 95% confidence interval [CI], 1.00-1.26; P = .04), biochemical failure (sHR, 1.22; 95% CI, 1.10-1.37; P < .001), distant metastasis (sHR, 1.28; 95% CI, 1.06-1.55; P = .01), and prostate cancer-specific mortality (sHR, 1.45; 95% CI, 1.20-1.76; P < .001). Ten-year distant metastasis in GC low-risk patients was 4% compared with 16% for GC high-risk patients. In patients with lower GC scores, the 10-year difference in metastasis-free survival rate between arms was -7%, compared with 21% for higher GC patients (P-interaction = .04). CONCLUSIONS: This study represents the first validation of a biopsy-based gene expression classifier, assessing both its prognostic and predictive value, using data from a randomized phase 3 trial of intermediate-risk prostate cancer. Decipher improves risk stratification and can aid in treatment decision-making in men with intermediate-risk disease.

Radiogenomic profiling of prostate tumors prior to external beam radiotherapy converges on a transcriptomic signature of TGF-ß activity driving tumor recurrence.

Background: Patients with localized prostate cancer have historically been assigned to clinical risk groups based on local disease extent, serum prostate specific antigen (PSA), and tumor grade. Clinical risk grouping is used to determine the intensity of treatment with external beam radiotherapy (EBRT) and androgen deprivation therapy (ADT), yet a substantial proportion of patients with intermediate and high risk localized prostate cancer will develop biochemical recurrence (BCR) and require salvage therapy. Prospective identification of patients destined to experience BCR would allow treatment intensification or selection of alternative therapeutic strategies. Methods: Twenty-nine individuals with intermediate or high risk prostate cancer were prospectively recruited to a clinical trial designed to profile the molecular and imaging features of prostate cancer in patients undergoing EBRT and ADT. Whole transcriptome cDNA microarray and whole exome sequencing were performed on pretreatment targeted biopsy of prostate tumors (n=60). All patients underwent pretreatment and 6-month post EBRT multiparametric MRI (mpMRI), and were followed with serial PSA to assess presence or absence of BCR. Genes differentially expressed in the tumor of patients with and without BCR were investigated using pathways analysis tools and were similarly explored in alternative datasets. Differential gene expression and predicted pathway activation were evaluated in relation to tumor response on mpMRI and tumor genomic profile. A novel TGF-ß gene signature was developed in the discovery dataset and applied to a validation dataset. Findings: Baseline MRI lesion volume and PTEN/TP53 status in prostate tumor biopsies correlated with the activation state of TGF-ß signaling measured using pathway analysis. All three measures correlated with the risk of BCR after definitive RT. A prostate cancer-specific TGF-ß signature discriminated between patients that experienced BCR vs. those that did not. The signature retained prognostic utility in an independent cohort. Interpretation: TGF-ß activity is a dominant feature of intermediate-to-unfavorable risk prostate tumors prone to biochemical failure after EBRT with ADT. TGF-ß activity may serve as a prognostic biomarker independent of existing risk factors and clinical decision-making criteria. Funding: This research was supported by the Prostate Cancer Foundation, the Department of Defense Congressionally Directed Medical Research Program, National Cancer Institute, and the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research.

A novel prostate cancer subtyping classifier based on luminal and basal phenotypes.

BACKGROUND: Prostate cancer (PCa) is a clinically heterogeneous disease. The creation of an expression-based subtyping model based on prostate-specific biological processes was sought. METHODS: Unsupervised machine learning of gene expression profiles from prospectively collected primary prostate tumors (training, n = 32,000; evaluation, n = 68,547) was used to create a prostate subtyping classifier (PSC) based on basal versus luminal cell expression patterns and other gene signatures relevant to PCa biology. Subtype molecular pathways and clinical characteristics were explored in five other clinical cohorts. RESULTS: Clustering derived four subtypes: luminal differentiated (LD), luminal proliferating (LP), basal immune (BI), and basal neuroendocrine (BN). LP and LD tumors both had higher androgen receptor activity. LP tumors also had a higher expression of cell proliferation genes, MYC activity, and characteristics of homologous recombination deficiency. BI tumors possessed significant interferon γactivity and immune infiltration on immunohistochemistry. BN tumors were characterized by lower androgen receptor activity expression, lower immune infiltration, and enrichment with neuroendocrine expression patterns. Patients with LD tumors had less aggressive tumor characteristics and the longest time to metastasis after surgery. Only patients with BI tumors derived benefit from radiotherapy after surgery in terms of time to metastasis (hazard ratio [HR], 0.09; 95% CI, 0.01-0.71; n = 855). In a phase 3 trial that randomized patients with metastatic PCa to androgen deprivation with or without docetaxel (n = 108), only patients with LP tumors derived survival benefit from docetaxel (HR, 0.21; 95% CI, 0.09-0.51). CONCLUSIONS: With the use of expression profiles from over 100,000 tumors, a PSC was developed that identified four subtypes with distinct biological and clinical features. PLAIN LANGUAGE SUMMARY: Prostate cancer can behave in an indolent or aggressive manner and vary in how it responds to certain treatments. To differentiate prostate cancer on the basis of biological features, we developed a novel RNA signature by using data from over 100,000 prostate tumors-the largest data set of its kind. This signature can inform patients and physicians on tumor aggressiveness and susceptibilities to treatments to help personalize cancer management.

Transcriptomic Heterogeneity in High-risk Prostate Cancer and Implications for Extraprostatic Disease at Presentation on Prostate-specific Membrane Antigen Positron Emission Tomography.

Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) has greater specificity and sensitivity for detection of extraprostatic prostate cancer (PCa) at presentation than conventional imaging. Although the long-term clinical significance of acting on these findings is unknown, it has been shown that the risk of upstaging is prognostic for long-term outcomes in men with high-risk (HR) or very high-risk (VHR) PCa. We evaluated the association between the risk of upstaging on PSMA PET and the Decipher genomic classifier score, a known prognostic biomarker in localized PCa that is being evaluated for its predictive ability to direct systemic therapy intensification. In a cohort of 4625 patients with HR or VHR PCa, the risk of upstaging on PSMA PET was significantly correlated with the Decipher score (p < 0.001). These results should be seen as hypothesis-generating and warrant further studies on the causal pathways linking PSMA findings, Decipher scores, extraprostatic disease, and long-term clinical outcomes. PATIENT SUMMARY: We found significant correlation between the risk of having prostate cancer outside the prostate gland on a sensitive scan (based on prostate-specific membrane antigen [PSMA]) at initial staging and the Decipher genetic score. The results warrant further studies on the causal pathways between PSMA scan findings, Decipher scores, disease outside the prostate, and long-term outcomes.

Prostate Cancer Tumor Volume and Genomic Risk.

Background: Despite the historic association of higher prostate cancer volume with worse oncologic outcomes, little is known about the impact of tumor volume on cancer biology. Objective: To characterize the relationship between tumor volume (measured by percent positive cores [PPC]) and cancer biology (measured by Decipher genomic risk classifier [GC]) in men who underwent prostate biopsy. Design setting and participants: Prostate biopsies from 52 272 men profiled with Decipher captured in a population-based prospective tumor registry were collected from 2016 to 2021. Outcome measurements and statistical analysis: The degree of distribution and correlation of PPC with a GC score across grade group (GG) strata were examined using the Mann-Whitney U test, Pearson correlation coefficient, and multivariable linear regression controlled for clinicopathologic characteristics. Results and limitations: A total of 38 921 (74%) biopsies passed quality control (14 331 GG1, 16 159 GG2, 5661 GG3, 1775 GG4, and 995 GG5). Median PPC and GC increased with sequentially higher GG. There was an increasingly positive correlation (r) between PPC and GC in GG2-5 prostate cancer (r [95% confidence interval {CI}]: 0.07 [0.5, 0.8] in GG2, 0.15 [0.12, 0.17] in GG3, 0.20 [0.15, 0.24] in GG4, and 0.25 [0.19, 0.31] in GG5), with no correlation in GG1 disease (r = 0.01, 95% CI [-0.001, 0.03]). In multivariable linear regression, GC was significantly associated with higher PPC for GG2-5 (all p < 0.05) but was not significantly associated with PPC for GG1. Limitations include retrospective design and a lack of final pathology from radical prostatectomy specimens. Conclusions: Higher tumor volume was associated with worse GC for GG2-5 prostate cancer, whereas tumor volume was not associated with worse GC for GG1 disease. The finding that tumor volume is not associated with worse cancer biology in GG1 disease encourages active surveillance for most patients irrespective of tumor volume. Patient summary: We studied the relationship between prostate cancer tumor volume and cancer biology, as measured by the Decipher genomic risk score, in men who underwent prostate biopsy. We found that tumor volume was not associated with worse cancer biology for low-grade prostate cancer. Our findings reassuringly support recent guidelines to recommend active surveillance for grade group 1 prostate cancer in most patients, irrespective of tumor volume.

Clinical testing of transcriptome-wide expression profiles in high-risk localized and metastatic prostate cancer starting androgen deprivation therapy: an ancillary study of the STAMPEDE abiraterone Phase 3 trial.

Metastatic and high-risk localized prostate cancer respond to hormone therapy but outcomes vary. Following a pre-specified statistical plan, we used Cox models adjusted for clinical variables to test associations with survival of multi-gene expression-based classifiers from 781 patients randomized to androgen deprivation with or without abiraterone in the STAMPEDE trial. Decipher score was strongly prognostic (p<2×10-5) and identified clinically-relevant differences in absolute benefit, especially for localized cancers. In metastatic disease, classifiers of proliferation, PTEN or TP53 loss and treatment-persistent cells were prognostic. In localized disease, androgen receptor activity was protective whilst interferon signaling (that strongly associated with tumor lymphocyte infiltration) was detrimental. Post-Operative Radiation-Therapy Outcomes Score was prognostic in localized but not metastatic disease (interaction p=0.0001) suggesting the impact of tumor biology on clinical outcome is context-dependent on metastatic state. Transcriptome-wide testing has clinical utility for advanced prostate cancer and identified worse outcomes for localized cancers with tumor-promoting inflammation.