Validation of a Genomic Classifier in the NRG Oncology/RTOG 0521 Phase III Trial of Docetaxel with Androgen Suppression and Radiotherapy for Localized High-Risk Prostate Cancer

PURPOSE/OBJECTIVE(S)

Decipher is a prognostic genomic classifier (GC) validated in several prospective NRG Oncology Phase III trials. Herein, we validate the GC in pre-treatment biopsy samples for risk stratification in a cohort of high-risk men treated with definitive radiotherapy and androgen suppression with or without docetaxel chemotherapy.

MATERIALS/METHODS

As per a pre-specified and approved NCI analysis plan (Navigator #1061), we obtained available formalin-fixed paraffin-embedded tissue from biopsy specimens from the NRG biobank from patients enrolled on the NRG/RTOG 0521 randomized phase III trial. After central review, the highest-grade tumors were profiled on clinical-grade whole-transcriptome arrays (Veracyte, San Diego, CA) and GC scores were obtained. Pre-specified categorical GC scores, adjusted for archival tissue analysis, were used to define higher (>0.46) and lower (≤0.46) risk groups. The primary objective was to validate the independent prognostic ability of GC for metastasis-free survival (MFS) with Cox multivariable analyses (MVA).

RESULTS

Samples were obtained from 283 consented, evaluable patients with tissue (50% of trial) yielding 183 (65%) GC scores that passed quality metrics, 91 from control and 92 from the interventional arm. Median age was 66 years, median PSA was 19.3 ng/uL (IQR: 8.1-41.4), 81% had clinical stage ≥T2 and 80% had Gleason score ≥8 (47% ≥9). Median GC score was 0.55 (IQR: 0.38-0.78) and overall the arms were balanced for key covariates. With a median follow-up of 9.9 years (IQR: 9.3, 10.7), 67 MFS events including 34 distant metastases (DM) were observed. On MVA, only the GC (per 0.1 unit) was independently associated with MFS (HR 1.12, 95% CI 1.01-1.25) as well as DM (sHR 1.22, 95% CI 1.06-1.41), whereas the 4 pre-defined trial risk groups used for stratification (based on Gleason score, T-stage and PSA), randomization and patient age were not. For categorical GC, on MVA, higher-risk GC patients (65%) had worse DM (sHR 2.82, 95% CI 1.1-7.3) compared to those with lower GC. Cumulative incidence of DM at 10-years was 27% for higher GC vs 9% (95% CI 7-18%) for lower GC. No biomarker-by-treatment interaction with GC and the addition of docetaxel was detected.

CONCLUSION

In pre-treatment biopsy samples from a randomized Phase 3 trial cohort, GC demonstrated its ability to further risk stratify clinically high-risk men demonstrating an independent association of GC score with DM and MFS. High-risk prostate cancer is a heterogeneous disease state and GC can improve risk stratification to help personalize shared decision-making. NRG-GU009/PREDICT-RT (NCT04513717) aims to determine the optimal therapy based on GC score for high-risk prostate cancer.

Predictive Value of Genomic Classifier Scores and Transcriptomic Data for Prostate Cancer Distant Metastasis Risk: A Multicenter Retrospective Study

PURPOSE/OBJECTIVE(S)

Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) has a greater specificity and sensitivity for detection of extraprostatic prostate cancer than conventional imaging. The Decipher genomic classifier is an established prognostic biomarker being evaluated for its ability to predict systemic treatment intensification. The relationship between Decipher scores and PSMA-based spread remains unknown, as do differences in transcriptomic patterns of PSMA PET-based spread in the de novo vs. recurrent setting.

MATERIALS/METHODS

We retrospectively identified patients who (a) had undergone staging with a PSMA PET prior to treatment or for evaluation of recurrence post-radical prostatectomy (RP) at two institutions and (b) had transcriptomic data available from the Genomics Resource for Intelligent Discovery (GRID) database from either biopsy or RP specimens. We classified the PSMA PET pattern of spread using molecular imaging (mi) staging as localized (miT+N0M0), node-positive (miN1M0), distant metastasis (miM1a-c), or negative/non-diagnostic. We used logistic regression to calculate the odds ratios (OR) with 95% confidence intervals (CI) for distant metastasis risk based on Decipher score both pre-treatment and post-RP. As an exploratory analysis, we compared each of the staging groups for differences in important transcriptomic signatures. Kruskal-Wallis and Pearson chi-squared tests were used for continuous and categorical variables, respectively.

RESULTS

A total of 315 patients were included in this analysis (n = 164 pre-treatment, n = 151 post-RP). Eighty PSMA PET scans were negative, while 147 were miT+N0M0, 45 were miN1M0, and 43 were miM1a-c. A higher Decipher score was associated with distant metastasis (miM1a-c) on PSMA PET both pre-treatment (OR 1.3 [95% CI: 1.0-1.7] per 0.1 increase in Decipher score, P = 0.05) and post-RP (OR 1.2 [1.0-1.4] per 0.1 increase in Decipher score, P = 0.04). There were higher TP53 mutation (P = 0.01) and cell cycle progression (P = 0.04) signature scores in miM1a-c patients compared to miN1M0 or miT+N0M0 patients. Basal subtype was more prevalent per PAM50 in miM1a-c or miN1M0 patients (36%) than miT+N0M0 patients (19%, P=0.01). Patients with de novo miN1M0 or miM1a disease (n = 19) had higher Decipher scores (0.85 vs 0.57, P = 0.10) and IFNa response (P = 0.08) than patients with recurrent miN1M0 or miM1a disease (n = 35).

CONCLUSION

Higher Decipher scores were associated with distant metastasis on PSMA PET in both the de novo and recurrent setting. Transcriptomic differences in pathways related to proliferation, p53 status, and PAM50 classification were seen when comparing localized, node-positive, and distant metastatic disease. Patients with de novo miN1M0 or miM1a disease may harbor more aggressive disease than those with miN1M0 or miM1a disease at recurrence.

Transcriptomic Heterogeneity of Metastatic Disease Timing within Metastatic Castration-Sensitive Prostate Cancer

PURPOSE/OBJECTIVE(S)

Metastatic castration-sensitive prostate cancer (mCSPC) is commonly partitioned into high- and low-volume subgroups which have demonstrated differential biology, prognosis, and response to therapy. Timing of metastasis has similarly demonstrated differences in clinical outcomes, however less is known about any potential underlying biologic differences between these disease states. Herein we aim to compare transcriptomic differences between synchronous and metachronous mCSPC and identify any differential responses to therapy.

MATERIALS/METHODS

We performed an international multi-institutional retrospective review of men with mCSPC who completed RNA expression profiling evaluation of their primary tumor. Patients were stratified according to disease timing (synchronous vs metachronous). The primary endpoint was to identify differences in transcriptomic profiles between disease time. Median genomic scores between groups were compared with Mann-Whitney U test. Secondary analyses included determining clinical and transcriptomic variables associated with overall survival (OS) from time of metastasis. Survival analysis was performed with the Kaplan-Meier Method and Multivariable Cox regression.

RESULTS

A total of 252 patients were included with a median follow-up of 39.6 months. Patients with synchronous disease experienced worse 5-yr OS (39% vs 79%, p<0.01) and demonstrated lower median Androgen Receptor Activity (AR-A) (11.78 vs 12.64, p<0.01) and Hallmark Androgen Response (HAR) (3.15 vs 3.32; p<0.01). Multivariable cox-regression identified only high-volume disease (HR = 4.97, 95% CI 2.71-9.10; p<0.01) and HAR score (HR = 0.51, 95% CI 0.28-0.88; p = 0.02 significantly associated with OS. Finally, patients with synchronous (HR = 0.47, 95% CI 0.30-0.72; <0.01) but not metachronous (HR = 1.37, 95% CI 0.50-3.92; p = 0.56) disease were found to have better OS with Androgen Receptor (AR) + non-AR combination therapy as compared to monotherapy (p value for interaction = 0.05).

CONCLUSION

We have demonstrated a potential biologic difference between metastatic timing of mCSPC. Specifically, for patients with low volume disease, those with metachronous low volume disease have a more hormone dependent transcriptional profile and exhibit a better prognosis than synchronous low volume disease.

A Precision Medicine Navigator Can Mitigate Inequities Associated with Utilization of Genomic Tests in Black Men with Prostate Cancer

PURPOSE/OBJECTIVE(S)

Black men with prostate cancer in the United States experience disproportionately worse clinical outcomes compared to other racial groups. Identifying more reliable prognosticators to address these inequities has thus been the subject of considerable research scrutiny. However, prognostic genomic tools and genomic biorepositories suffer from an even greater lack of racial diversity. Strategies to mitigate these amplifying developments in inequities are desperately needed. We hypothesized that the presence of a precision medicine navigator (PMN) may mitigate inequities with standard of care (SOC) genomic test utilization among Black men with prostate cancer.

MATERIALS/METHODS

We retrospectively reviewed prostate cancer consults within one healthcare system from 11/2/2021 to 1/2/2022. We compared the frequency of patients who received SOC Decipher or Tempus genomic testing in the 7 months prior to the PMN start (pre-PMN) to the 7 months afterward (post-PMN). Chi square analysis was used to compare subgroups. Binary logistic regression was used to calculate the odds of receiving genomic testing.

RESULTS

The sample included 693 patients, 44.9% (311/693) pre-PMN and 55.1% (382/693) post-PMN, with a median age of 68 in both groups. Pre- and post-PMN racial distributions were similar with 60.1% and 60.2% White, 35.1% and 34% Black, 3.2% and 3.7% Asian/Pacific Islander, and 1.3% and 2.1% Latino, respectively. Pre- and post-PMN NCCN risk category distribution was 15.2% and 10.4% low risk, 46.8% and 49.9% intermediate risk, and 38.1% and 39.7% high risk, respectively. Pre- and post-PMN groups had 14.5% and 17% distant metastases, 77.2% and 76.9% localized disease, 10.3% and 10% prior prostatectomy, 47% and 51% income below sample median, 51% and 52% with Medicare/Medicaid, and 47% and 48% seen at community hospitals, respectively. There were no statistically significant differences for these variables pre- and post-PMN. However, from pre- to post-PMN, the proportion of Black patients receiving genomic testing increased from 19% to 58%. Black patients seen post-PMN were six times more likely to receive testing (p<0.001). Significant increases in SOC genomic testing post-PMN also occurred among lower median income patients, patients with Medicare/Medicaid, and community hospital patients.

CONCLUSION

The presence of a PMN may improve disparate rates of Black patients receiving SOC genomic tests for prostate cancer compared to other racial groups and may alleviate genomic testing inequities among other demographics.

Longitudinal Profiling of Tumor RNA Expression Signatures Reveal Key Biological Features Associated with Response to Neoadjuvant Stereotactic Body Radiation Therapy in High-Risk Prostate Cancer

PURPOSE/OBJECTIVE(S)

Stereotactic body radiation therapy (SBRT) is a safe and effective treatment for localized prostate cancer (PCa). PREPARE-SBRT is a clinical trial testing the safety of neoadjuvant MRI-guided SBRT for men with high-risk localized PCa. We leveraged paired samples from pre-treatment biopsy and irradiated prostatectomy (RP) specimens to evaluate transcriptomic changes in irradiated tumors at acute time points following neoadjuvant SBRT.

MATERIALS/METHODS

Tumor RNA expression profiles were generated using Decipher GRID by Veracyte on 12 subjects with paired pre- and post-SBRT tissues (n = 24). Descriptive statistics using gene expression profiles describing key biological features [DNA damage & repair (DDR), tumor proliferation, suppressed immune, activated immune, tumor microenvironment (TME)] and an exploratory analysis of RT sensitivity score with binary classification as sensitive or resistant were reported. A control cohort of transcriptomic profiles of 803 matched untreated biopsy and matching RP samples from the same subjects were used to control for signature differences attributable to sample type.

RESULTS

Key tumor biology signatures most frequently observed were DDR (15/24), TME (11/24) and tumor proliferation (11/24). Signatures associated with tumor proliferation were disproportionately represented in pre-treatment samples (10/11) whereas TME-associated signatures were enriched predominantly in irradiated RP samples (8/11). Collectively, immune-related immune signatures skewed towards immune activation. All 3 samples annotated with suppressed immune signatures were from pre-treatment specimens whereas 75% (6/8) of samples annotated with activated immune status were from irradiated specimens. Additionally, conversion from suppressed to activated immune status was observed in 2 of 3 subjects (66%). In total, 42% of specimens (10/24) were designated as radio-resistant by RT sensitivity score. Among 8 baseline specimens annotated with RT resistant status, 75% of subjects (6/8) converted to RT sensitive status after neoadjuvant SBRT. Interestingly, in the two subjects with persistent radio-resistant status in pre- and post-samples there was associated with upregulation of TGF-β or PI3K-AKT pathway activation signatures.

CONCLUSION

Pre- and post-SBRT transcriptomic signatures were heterogeneous and dynamic in a cohort of 12 patients with high-risk localized PCa highlighting the importance of studying longitudinal changes in individual patients. These data highlight an opportunity to leverage tumor RNA expression profiles to personalize patient and treatment selection and augment radiation response assessment.

CLINICAL TRIALS

gov ID (NCT03663218).

Dynamic Changes of Molecular Subtype Classification and Genomic Classifier Scores in High-Risk Prostate Cancer Patients Undergoing Pre-Operative Stereotactic Body Radiation Therapy

PURPOSE/OBJECTIVE(S)

The radiobiology of irradiated human prostate cancer (PCa) remains poorly understood as irradiated tissues often remain in situ. PREPARE-SBRT (NCT03663218) is a clinical trial testing the safety of neoadjuvant MRI-guided stereotactic body radiation therapy (SBRT) for men with high-risk PCa. We leveraged paired samples from pre-treatment biopsy and irradiated prostatectomy (RP) specimens to evaluate transcriptomic changes in irradiated tumors at acute timepoints following SBRT.

MATERIALS/METHODS

Tumor RNA expression profiles were generated using Decipher GRID by Veracyte on 12 subjects enrolled on NCT03663218 with paired pre/post-SBRT tissues (n = 24). Descriptive statistics using Decipher Genomic Classifier (GC) Score [0-1] and GC risk group (low/int/high) were generated from a validated 22-gene GC. Tumor biology signatures reported as dichotomous variables evaluated changes in androgen receptor (AR) activity [higher v lower] and cell cycle progression (CCP) [lower v higher]. Decipher prostate subtype classifier [PSC, luminal differentiated (LD), luminal proliferating (LP), basal immune (BI), basal neuroendocrine like (BN)] classification and PAM50 molecular subtype [luminal A (lumA), luminal B (lumB), basal] at pre/post-SBRT timepoints were reported. A control cohort of transcriptomic profiles of 803 matched untreated biopsy and RP samples from the same patients were used to control for signature differences attributable to sample type.

RESULTS

The median pre- and post-SBRT GC scores were 0.55 and 0.72 (Δ+0.17), respectively. By comparison, median GC scores in a control cohort (n = 803) of biopsy and RP specimens were 0.50 and 0.56 (Δ+0.06), respectively. SBRT increased GC score in 9/12 subjects (75%) with a median increase of 0.3. Changes in GC score resulted in reclassification of baseline GC risk in 7 of 12 subjects with 71% of reclassified subjects (5/7) transitioning to a higher genomic risk. 92% of subjects (11/12) had higher AR activity scores at baseline. Of this subgroup, 5/11 (45%) converted to lower AR activity score after SBRT. CCP signatures remained stable in 9 of 12 subjects (75%) with 7/12 subjects exhibiting lower CCP score at baseline and only 1 subject transitioning from lower to higher CCP score. Distribution of PAM50 molecular subtype at baseline and after SBRT was lumA (33>53%), lumB (25>17%), basal (42>25%) resulting in 83% of subjects (10/12) annotated to a different PAM50 molecular subtype at pre/post-SBRT assessment. PSC subtype distribution at baseline was LD (33%), LP (25%), BI (33%) and BN (8%). Strikingly, after SBRT, 92% (11/12) of subjects were classified as BI molecular subtype with several immune activation signatures also increased after SBRT.

CONCLUSION

A majority of subjects demonstrate a post-SBRT increase in GC score with reclassification of genomic-prognostic risk group in 58%. An enrichment of the basal-immune molecular subtype was observed following SBRT suggesting a convergence towards this biology in irradiated tumors.

Transcriptomic and clinical heterogeneity of metastatic disease timing within metastatic castration-sensitive prostate cancer

BACKGROUND

Metastatic castration-sensitive prostate cancer (mCSPC) is commonly classified into high- and low-volume subgroups which have demonstrated differential biology, prognosis, and response to therapy. Timing of metastasis has similarly demonstrated differences in clinical outcomes; however, less is known about any underlying biologic differences between these disease states. Herein, we aim to compare transcriptomic differences between synchronous and metachronous mCSPC and identify any differential responses to therapy.

PATIENTS AND METHODS

We performed an international multi-institutional retrospective review of men with mCSPC who completed RNA expression profiling evaluation of their primary tumor. Patients were stratified according to disease timing (synchronous versus metachronous). The primary endpoint was to identify differences in transcriptomic profiles between disease timing. The median transcriptomic scores between groups were compared with the Mann-Whitney U test. Secondary analyses included determining clinical and transcriptomic variables associated with overall survival (OS) from the time of metastasis. Survival analysis was carried out with the Kaplan-Meier method and multivariable Cox regression.

RESULTS

A total of 252 patients were included with a median follow-up of 39.6 months. Patients with synchronous disease experienced worse 5-year OS (39% versus 79%; P < 0.01) and demonstrated lower median androgen receptor (AR) activity (11.78 versus 12.64; P < 0.01) and hallmark androgen response (HAR; 3.15 versus 3.32; P < 0.01). Multivariable Cox regression identified only high-volume disease [hazard ratio (HR) = 4.97, 95% confidence interval (CI) 2.71-9.10; P < 0.01] and HAR score (HR = 0.51, 95% CI 0.28-0.88; P = 0.02) significantly associated with OS. Finally, patients with synchronous (HR = 0.47, 95% CI 0.30-0.72; P < 0.01) but not metachronous (HR = 1.37, 95% CI 0.50-3.92; P = 0.56) disease were found to have better OS with AR and non-AR combination therapy as compared with monotherapy (P value for interaction = 0.05).

CONCLUSIONS

We have demonstrated a potential biologic difference between metastatic timing of mCSPC. Specifically, for patients with low-volume disease, those with metachronous low-volume disease have a more hormone-dependent transcriptional profile and exhibit a better prognosis than synchronous low-volume disease.

Transcriptional profiling of primary prostate tumor in metastatic hormone-sensitive prostate cancer and association with clinical outcomes: correlative analysis of the E3805 CHAARTED trial

BACKGROUND

The phase III CHAARTED trial established upfront androgen-deprivation therapy (ADT) plus docetaxel (D) as a standard for metastatic hormone-sensitive prostate cancer (mHSPC) based on meaningful improvement in overall survival (OS). Biological prognostic markers of outcomes and predictors of chemotherapy benefit are undefined.

PATIENTS AND METHODS

Whole transcriptomic profiling was performed on primary PC tissue obtained from patients enrolled in CHAARTED prior to systemic therapy. We adopted an a priori analytical plan to test defined RNA signatures and their associations with HSPC clinical phenotypes and outcomes. Multivariable analyses (MVAs) were adjusted for age, Eastern Cooperative Oncology Group status, de novo metastasis presentation, volume of disease, and treatment arm. The primary endpoint was OS; the secondary endpoint was time to castration-resistant PC.

RESULTS

The analytic cohort of 160 patients demonstrated marked differences in transcriptional profile compared with localized PC, with a predominance of luminal B (50%) and basal (48%) subtypes, lower androgen receptor activity (AR-A), and high Decipher risk disease. Luminal B subtype was associated with poorer prognosis on ADT alone but benefited significantly from ADT + D [OS: hazard ratio (HR) 0.45; P = 0.007], in contrast to basal subtype which showed no OS benefit (HR 0.85; P = 0.58), even in those with high-volume disease. Higher Decipher risk and lower AR-A were significantly associated with poorer OS in MVA. In addition, higher Decipher risk showed greater improvements in OS with ADT + D (HR 0.41; P = 0.015).

CONCLUSION

This study demonstrates the utility of transcriptomic subtyping to guide prognostication in mHSPC and potential selection of patients for chemohormonal therapy, and provides proof of concept for the possibility of biomarker-guided selection of established combination therapies in mHSPC.

Abstract P5-12-01: A novel gene expression signature prognostic for both locoregional and distant failure and predictive for adjuvant radiotherapy

Background: Most patients with early stage breast cancer (BC) are treated with adjuvant radiotherapy (RT) following breast conserving surgery (BCS) to prevent locoregional recurrences (LRR). No predictive tools are currently available to select patients for RT, resulting in considerable over- and under treatment. We aimed to create and validate a gene expression-based classifier to prognosticate for LRR and to stratify patients for treatment with RT.

Patients and methods: A 27-gene expression signature was developed using three publicly available early stage BC gene expression datasets where patients were treated with RT and had detailed local recurrence information. The largest of the datasets was used to train the signature, and the other two datasets were used for signature refinement. As age was the strongest clinical factor for the endpoint in the training dataset, it was included in the model, resulting in a final clinical-genomic classifier of 27 genes and age. The classifier was locked before external validation in the SweBCG91-RT trial. This phase III clinical trial included primary tumors from 765 patients and for which gene expression data was available. The trial randomized node-negative BC patients to +/- RT following BCS, with sparse use of adjuvant systemic treatment (9%) and a median follow-up of 14.0 years for LRR in patients free from event. The classifier was validated using Cox regression with LRR as the primary endpoint, and hazard ratios (HRs) were calculated using the raw continuous classifier score (range: 0.5 to 2.5).

Results: The novel classifier was highly prognostic for LRR in SweBCG91-RT patients treated with RT (HR=7.5[3.3-16.9], p&lt;0.001), and remained prognostic in multivariate analysis (MVA) that included systemic treatment, subtype and grade (HR=7.2[3.1-16.4], p&lt;0.001). To a lesser extent, the classifier was also prognostic for LRR in patients not treated with RT (HR=1.9[1.0-3.5], p=0.03; MVA HR=1.9[1.0-3.3], p=0.05). Patients at high risk of LRR had a smaller effect of RT, and the treatment predictive potential was confirmed by testing for interaction (pinteraction=0.008). In patients treated with RT, age and the genomic component of the model were both prognostic for LRR (p&lt;0.01) as well as predictive for RT response (pinteraction&lt;0.05) and provided independent information (p&lt;0.01). The combined classifier has increased performance over its individual components (10-year AUC=0.72, 0.67, 0.65 for the classifier, age, and genomic component, respectively). While the novel signature was prognostic for metastasis (HR=4.3[2.3-7.8], p&lt;0.0001), calculated scores from previously published signatures to the metastasis endpoint, including the Oncotype-like score, were not prognostic for LRR.

Conclusions: This novel gene expression signature is highly prognostic for LRR, can identify patients at risk of LRR despite RT, and appears to be treatment predictive for adjuvant RT. Furthermore, the current signature is highly prognostic for metastasis. In contrast, calculated scores of previously published signatures modeled for the metastasis endpoint had inferior performance for LRR. These results underscore both the importance of signatures prognostic for LRR and the similarities in the biology of LRR and distant failure.

Citation Format: Sjöström M, Chang SL, Fishbane N, Davicioni E, Zhao SG, Hartman L, Holmberg E, Feng FY, Speers CW, Pierce LJ, Malmström P, Fernö M, Karlsson P. A novel gene expression signature prognostic for both locoregional and distant failure and predictive for adjuvant radiotherapy [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-12-01.

Utilization of biopsy-based genomic classifier to predict distant metastasis after definitive radiation and short-course ADT for intermediate and high-risk prostate cancer

BACKGROUND

We examined the ability of a biopsy-based 22-marker genomic classifier (GC) to predict for distant metastases after radiation and a median of 6 months of androgen deprivation therapy (ADT).

METHODS

We studied 100 patients with intermediate-risk (55%) and high-risk (45%) prostate cancer who received definitive radiation plus a median of 6 months of ADT (range 3-39 months) from 2001-2013 at a single center and had available biopsy tissue. Six to ten 4 micron sections of the needle biopsy core with the highest Gleason score and percentage of tumor involvement were macrodissected for RNA extraction. GC scores (range, 0.04-0.92) were determined. The primary end point of the study was time to distant metastasis. Median follow-up was 5.1 years. There were 18 metastases during the study period.

RESULTS

On univariable analysis (UVA), each 0.1 unit increase in GC score was significantly associated with time to distant metastasis (hazard ratio: 1.40 (1.10-1.84), P=0.006) and remained significant after adjusting for clinical variables on multivariable analysis (MVA) (adjusted hazard ratio: 1.36 (1.04-1.83), P=0.024). The c-index for 5-year distant metastasis was 0.45 (95% confidence interval: 0.27-0.64) for Cancer of the Prostate Risk Assessment score, 0.63 (0.40-0.78) for National Comprehensive Cancer Network (NCCN) risk groups, and 0.76 (0.57-0.89) for the GC score. Using pre-specified GC risk categories, the cumulative incidence of metastasis for GC>0.6 reached 20% at 5 years after radiation (P=0.02).

CONCLUSIONS

We believe this is the first demonstration of the ability of the biopsy-based GC score to predict for distant metastases after definitive radiation and ADT for intermediate- and high-risk prostate cancer. Patients with the highest GC risk (GC>0.6) had high rates of metastasis despite multi-modal therapy suggesting that they could potentially be candidates for treatment intensification and/or enrollment in clinical trials of novel therapy.

Cell cycle-coupled expansion of AR activity promotes cancer progression

The androgen receptor (AR) is required for prostate cancer (PCa) survival and progression, and ablation of AR activity is the first line of therapeutic intervention for disseminated disease. While initially effective, recurrent tumors ultimately arise for which there is no durable cure. Despite the dependence of PCa on AR activity throughout the course of disease, delineation of the AR-dependent transcriptional network that governs disease progression remains elusive, and the function of AR in mitotically active cells is not well understood. Analyzing AR activity as a function of cell cycle revealed an unexpected and highly expanded repertoire of AR-regulated gene networks in actively cycling cells. New AR functions segregated into two major clusters: those that are specific to cycling cells and retained throughout the mitotic cell cycle ('Cell Cycle Common'), versus those that were specifically enriched in a subset of cell cycle phases ('Phase Restricted'). Further analyses identified previously unrecognized AR functions in major pathways associated with clinical PCa progression. Illustrating the impact of these unmasked AR-driven pathways, dihydroceramide desaturase 1 was identified as an AR-regulated gene in mitotically active cells that promoted pro-metastatic phenotypes, and in advanced PCa proved to be highly associated with development of metastases, recurrence after therapeutic intervention and reduced overall survival. Taken together, these findings delineate AR function in mitotically active tumor cells, thus providing critical insight into the molecular basis by which AR promotes development of lethal PCa and nominate new avenues for therapeutic intervention.