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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.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged into a world of maturing pathogen genomics, with more than 2 million genomes sequenced at the time of writing. The rise of more transmissible variants of concern that impact vaccine and therapeutic effectiveness has led to widespread interest in SARS-CoV-2 evolution.

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged into a world of maturing pathogen genomics, with &gt;2 million genomes sequenced at this writing. The rise of more transmissible variants of concern that affect vaccine and therapeutic effectiveness has led to widespread interest in SARS-CoV-2 evolution. Clinicians are also eager to take advantage of the information provided by SARS-CoV-2 genotyping beyond surveillance purposes. Here, we review the potential role of SARS-CoV-2 genotyping in clinical care. The review covers clinical use cases for SARS-CoV-2 genotyping, methods of SARS-CoV-2 genotyping, assay validation and regulatory requirements, clinical reporting for laboratories, and emerging issues in clinical SARS-CoV-2 sequencing. While clinical uses of SARS-CoV-2 genotyping are currently limited, rapid technological change along with a growing ability to interpret variants in real time foretell a growing role for SARS-CoV-2 genotyping in clinical care as continuing data emerge on vaccine and therapeutic efficacy.

AbstractAlthough cancer is highly heterogeneous, all metastatic cancer is considered American Joint Committee on Cancer (AJCC) Stage IV disease. The purpose of this project was to redefine staging of metastatic cancer. Internal validation of nationally representative patient data from the National Cancer Database (n = 461 357; 2010‐2013), and external validation using the Surveillance, Epidemiology and End Results database (n = 106 595; 2014‐2015) were assessed using the concordance index for evaluation of survival prediction. A Cox proportional hazards model was used for overall survival by considering identified phenotypes (latent classes) and other confounding variables. Latent class analysis was performed for phenotype identification, where Bayesian information criterion (BIC) and sample‐size‐adjusted BIC were used to select the optimal number of distinct clusters. Kappa coefficients assessed external cluster validation. Latent class analysis identified five metastatic phenotypes with differences in overall survival (P < .0001): (Stage IVA) nearly exclusive bone‐only metastases (n = 59 049, 12.8%; median survival 12.7 months; common in lung, breast and prostate cancers); (IVB) predominant lung metastases (n = 62 491, 13.5%; 11.4 months; common in breast, stomach, kidney, ovary, uterus, thyroid, cervix and soft tissue cancers); (IVC) predominant liver/lung metastases (n = 130 014, 28.2%; 7.0 months; common in colorectum, pancreatic, lung, esophagus and stomach cancers); (IVD) bone/liver/lung metastases predominant over brain (n = 61 004, 13.2%; 5.9 months; common in lung and breast cancers); and (IVE) brain/lung metastases predominant over bone/liver (n = 148 799, 32.3%; 5.7 months; lung cancer and melanoma). Long‐term survivors were identified, particularly in Stages IVA‐B. A pan‐cancer nomogram model to predict survival (STARS: site, tumor, age, race, sex) was created, validated and provides 13% better prognostication than AJCC: 1‐month concordance index of 0.67 (95% confidence interval [CI]: 0.66‐0.67) vs 0.61 (95% CI: 0.60‐0.61). STARS is simple, uses easily accessible variables, better prognosticates survival outcomes and provides a platform to develop novel metastasis‐directed clinical trials.