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AbstractBackgroundProstate cancer (PCa) is a clinically heterogeneous disease. The creation of an expression‐based subtyping model based on prostate‐specific biological processes was sought.MethodsUnsupervised 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.ResultsClustering 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).ConclusionsWith 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.

Objectives: Deaths from an unknown cause are difficult to adjudicate and oncologic studies of comparative effectiveness often demonstrate inconsistencies in incorporating these deaths and competing events (eg, heart disease and stroke) in their analyses. In this study, we identify cancer patients most at risk for death of an unknown cause. Methods: This retrospective, population-based study used cancer registry data from the Surveillance, Epidemiology, and End Results database (1992-2015). The absolute rate of unknown causes of death (COD) cases stratified by sex, marital status, race, treatment, and cancer site were calculated and a multivariable logistic regression model was applied to obtain adjusted odds ratios with 95% CIs. Results: Out of 7,154,779 cancer patients across 22 cancer subtypes extracted from Surveillance, Epidemiology, and End Results, 3,448,927 died during follow-up and 276,068 (7.4%) of these deaths were from unknown causes. Patients with an unknown COD had a shorter mean survival time compared with patients with known COD (36.3 vs 65.7 mo, P < 0.001). The contribution of unknown COD to total mortality was highest in patients with more indolent cancers (eg, prostate [12.7%], thyroid [12.3%], breast [10.7%]) and longer follow-up (eg, >5 to 10 y). One, 3, and 5-year cancer-specific survival (CSS) calculations including unknown COD were significantly decreased compared with CSS estimates excluding cancer patients with unknown COD. Conclusion: Of the patients, 7.4% died of unknown causes during follow-up and the proportion of death was higher with longer follow-up and among more indolent cancers. The attribution of high percentages of unknown COD to cancer or non-cancer causes could impact population-based cancer registry studies or clinical trial outcomes with respect to measures involving CSS and mortality.

241 Background: We previously reported on the use of gene expression profiling to characterize four primary subtypes in an analysis of over 100,000 prostate cancer primary tumors. Here we examine these subtypes and response to radiation (RT) after prostatectomy or chemotherapy in addition to androgen deprivation therapy (ADT) in hormone-sensitive metastatic prostate cancer (mHSPC). Methods: We examined a 215-gene prostate subtyping classifier (PSC) which groups luminal and basal gene expression profiles into one of four subtypes; luminal differentiated (LD), luminal proliferating (LP), basal immune (BI) and basal neuroendocrine-like (BN). The log-rank method was used to compare (i) metastasis-free survival between patients who did and did not receive salvage RT in the META855 cohort of localized disease patients treated with radical prostatectomy (n=855) and the (ii) overall survival of patients on the Phase III mHSPC EA3805 CHAARTED trial of ADT or ADT + docetaxel chemotherapy (n=160). Results: After radical prostatectomy, patients with BI tumors derived benefit from RT in terms of metastasis-free survival ( P=9.23e-4) while those with other subtype tumors did not (Each Log-rank P≥0.5). Patients with metastatic disease and LP tumors derived benefit from docetaxel (Log-rank P=0.002) while those with other subtypes tumors did not (Log-rank P=0.2). Conclusions: Basal-luminal subtyping segments tumors by relevant biological processes with potential implications for identifying patients who benefit from salvage radiation post prostatectomy and addition of docetaxel to ADT in mHSPC.

PURPOSE The sequencing of androgen-deprivation therapy (ADT) with radiotherapy (RT) may affect outcomes for prostate cancer in an RT-field size-dependent manner. Herein, we investigate the impact of ADT sequencing for men receiving ADT with prostate-only RT (PORT) or whole-pelvis RT (WPRT). MATERIALS AND METHODS Individual patient data from 12 randomized trials that included patients receiving neoadjuvant/concurrent or concurrent/adjuvant short-term ADT (4-6 months) with RT for localized disease were obtained from the Meta-Analysis of Randomized trials in Cancer of the Prostate consortium. Inverse probability of treatment weighting (IPTW) was performed with propensity scores derived from age, initial prostate-specific antigen, Gleason score, T stage, RT dose, and mid-trial enrollment year. Metastasis-free survival (primary end point) and overall survival (OS) were assessed by IPTW-adjusted Cox regression models, analyzed independently for men receiving PORT versus WPRT. IPTW-adjusted Fine and Gray competing risk models were built to evaluate distant metastasis (DM) and prostate cancer–specific mortality. RESULTS Overall, 7,409 patients were included (6,325 neoadjuvant/concurrent and 1,084 concurrent/adjuvant) with a median follow-up of 10.2 years (interquartile range, 7.2-14.9 years). A significant interaction between ADT sequencing and RT field size was observed for all end points ( P interaction < .02 for all) except OS. With PORT (n = 4,355), compared with neoadjuvant/concurrent ADT, concurrent/adjuvant ADT was associated with improved metastasis-free survival (10-year benefit 8.0%, hazard ratio [HR], 0.65; 95% CI, 0.54 to 0.79; P < .0001), DM (subdistribution HR, 0.52; 95% CI, 0.33 to 0.82; P = .0046), prostate cancer–specific mortality (subdistribution HR, 0.30; 95% CI, 0.16 to 0.54; P < .0001), and OS (HR, 0.69; 95% CI, 0.57 to 0.83; P = .0001). However, in patients receiving WPRT (n = 3,049), no significant difference in any end point was observed in regard to ADT sequencing except for worse DM (HR, 1.57; 95% CI, 1.20 to 2.05; P = .0009) with concurrent/adjuvant ADT. CONCLUSION ADT sequencing exhibits a significant impact on clinical outcomes with a significant interaction with field size. Concurrent/adjuvant ADT should be the standard of care where short-term ADT is indicated in combination with PORT.

Introduction. Chromophobe renal cell carcinoma (chromophobe RCC) is the third major subcategory of renal tumors after clear cell RCC and papillary RCC, accounting for approximately 5% of all RCC subtypes. Other oncocytic neoplasms seen commonly in surgical pathology practice include the eosinophilic variant of chromophobe RCC, renal oncocytoma, and low-grade oncocytic unclassified RCC. Methods. In our recent next-generation sequencing based study, we nominated a lineage-specific novel biomarker LINC01187 (long intergenic non-protein coding RNA 1187) which was found to be enriched in chromophobe RCC. Like KIT (cluster of differentiation 117; CD117), a clinically utilized chromophobe RCC related biomarker, LINC01187 is expressed in intercalated cells of the nephron. In this follow-up study, we performed KIT immunohistochemistry and LINC01187 RNA in situ hybridization (RNA-ISH) on a cohort of chromophobe RCC and other renal neoplasms, characterized the expression patterns, and quantified the expression signals of the two biomarkers in both primary and metastatic settings. Results. LINC01187, in comparison to KIT, exhibits stronger and more uniform expression within tumors while maintaining temporal and spatial consistency. LINC01187 also is devoid of intra-tumoral heterogeneous expression pattern, a phenomenon commonly noted with KIT. Conclusions. LINC01187 expression can augment the currently utilized KIT assay and help facilitate easy microscopic analyses in routine surgical pathology practice.

PURPOSE Metastasis-free survival (MFS), but not event-free survival, is a validated surrogate end point for overall survival (OS) in men treated for localized prostate cancer. It remains unknown if this holds true in biochemically recurrent disease after radical prostatectomy. Leveraging NRG/RTOG 9601, we aimed to determine the performance of intermediate clinical end points (ICEs) as surrogate end points for OS in recurrent prostate cancer. MATERIALS AND METHODS NRG/RTOG 9601 randomly assigned 760 men with recurrence after prostatectomy to salvage radiation therapy with 2 years of placebo versus bicalutamide 150 mg daily. ICEs assessed were biochemical failure (BF) per NRG/RTOG 9601 (prostate-specific antigen nadir + 0.3-0.5 ng/mL or initiation of salvage hormone therapy; [BF1]) and NRG/RTOG 0534 (prostate-specific antigen nadir+2 ng/mL; [BF2]), distant metastasis (DM), and MFS (DM or death). Surrogacy was assessed by the Prentice criteria and a two-stage meta-analytic approach (condition one assessed at the patient level with Kendall's τ and condition two assessed by randomly dividing the entire trial cohort into 10 pseudo trial centers and calculating the average R2 between treatment hazard ratios for ICE and OS). RESULTS BF1, BF2, DM, and MFS satisfied the four Prentice criteria. However, with the two-condition meta-analytic approach, there was strong correlation between MFS and OS (τ = 0.86), moderate correlation between DM and OS (τ = 0.66), and weaker correlation between BF1 (τ = 0.25) or BF2 (τ = 0.40) and OS. Similarly, for condition two, the treatment effect of antiandrogen therapy on MFS and OS were correlated ( R2 = 0.67), but this was not true for BF1 ( R2 = 0.09), BF2 ( R2 = 0.12), or DM ( R2 = 0.18) and OS. CONCLUSION MFS is also a strong surrogate for OS in men receiving salvage radiation therapy for recurrence after prostatectomy. Caution should be used when inferring survival benefit from effects on BF in biochemically recurrent prostate cancer. Lack of comorbidity data did not allow us to assess whether BF in men with no/minimal comorbidity could serve as a surrogate for OS.

277 Background: The prognostic importance of local failure (LF) after definitive radiotherapy (RT) in patients with NCCN intermediate- (IRPCa) and high-risk prostate cancer (HRPCa) remains unclear, particularly given the likelihood that occult distant metastases (DMs) at presentation may be the true driver of natural history. Here, we leverage individual patient data (IPD) from 18 randomized control trials (RCTs) to evaluate the prognostic impact of LF and the kinetics of DM after RT. Methods: IPD for 18 RCTs were obtained from the Meta-Analysis of Randomized trials in Cancer of the Prostate (MARCAP) Consortium, comprising a total of 12533 patients (6288 HRPCa & 6245 IRPCa). Multivariable Cox proportional hazards (PH) models were developed to evaluate the relationship between overall survival (OS), PCa-specific survival (PCSS), DM-free survival (DMFS) & LF as a time-dependent covariate, adjusted for clinicodemographic parameters. Markov PH models, defined via transitions between 4 states, were developed to evaluate the aforementioned relationship. Proportional hazards assumption was imposed and examined for both models. Time is from randomization. Results: Median follow-up was 9.1 years. There were 795 (13%) LF & 1288 (21%) DM events for patients with HRPCa; these numbers were 449 (7%) & 451 (7%) for IRPCa. For HRPCa & IRPCa, 81% and 81% of DMs developed from a clinically relapse-free state (cRFS), with a median time of 46 and 60 months, respectively (p < 0.0001). 39% & 13% of DM events occurred within 2 years after RT for HRPCa & IRPCa, respectively. At later time points, DM events were more likely to emerge after an LF event for both HRPCa (9% vs. 34% between 0-2 vs. 8-10 years post-RT, p = 0.001) and IRPCa (10% vs. 34% between 0-2 vs. 8-10 years post-RT, p = 0.008). LF was significantly associated with OS (hazard ratio [HR] 1.17, 95% confidence interval [CI] 1.06–1.30), PCSS (HR 2.02, 95% CI 1.75-2.33) & DMFS (HR 1.94, 95% CI 1.75–2.15) (p < 0.01 for all) in patients with HRPCa. LF was also significantly associated with DMFS (HR 1.57, 95% CI 1.36–1.81) but not OS in patients with IRPCa. Patients who had not transitioned to the LF state had a significantly lower HR of transitioning to a PCa-specific death state than those who transitioned to the LF state (HR 0.32, 95% CI 0.21–0.50, p < 0.001). Conclusions: LF is an independent prognosticator of OS, PCSS & DMFS in HRPCa and of DMFS in IRPCa. The predominant mode of DM development is from the cRFS state, underscoring the importance of accurate upfront staging & systemic therapy. However, particularly at late time points, an increasing proportion of DM events originated after diagnosis of a LF, constituting a “second wave” of DM events. This suggests that optimizing local control is also important, though the majority of DM events appear prior to a clinically-detected LF.