BACKGROUND Nivolumab, a programmed death-1 checkpoint inhibitor, demonstrated encouraging overall survival in uncontrolled studies in previously treated patients with advanced renal cell carcinoma. This randomized, open-label, phase 3 study compared nivolumab with everolimus in renal cell carcinoma after prior treatment. METHODS Eight hundred twenty-one patients with advanced clear-cell renal cell carcinoma previously treated with one or two antiangiogenic therapies were randomized (1:1) to receive nivolumab 3 mg/kg intravenously every 2 weeks or everolimus 10-mg tablet orally once daily. Primary end point was overall survival. Secondary end points included objective response rate and safety. RESULTS Median (95% confidence interval [CI]) overall survival was 25.0 months (21.8 to not estimable) with nivolumab and 19.6 months (17.6 to 23.1) with everolimus. The hazard ratio for risk of death with nivolumab versus everolimus was 0.73 (98.5% CI, 0.57 to 0.93; P=0.0018), meeting the predefined criterion for superiority (P≤0.0148). Objective response rate was greater with nivolumab (25%) than everolimus (5%; odds ratio 5.98; 95% CI, 3.68 to 9.72; P<0.001). Median (95% CI) progression-free survival was 4.6 months (3.7 to 5.4) with nivolumab and 4.4 months (3.7 to 5.5) with everolimus (hazard ratio, 0.88; 95% CI, 0.75 to 1.03; P=0.11). Grade 3 or 4 treatment-related adverse events occurred in 19% (nivolumab) and 37% (everolimus) of patients; most common was fatigue (3%) with nivolumab and anemia (8%) with everolimus. CONCLUSIONS Overall survival was longer and fewer grade 3 or 4 adverse events occurred for nivolumab versus everolimus in treatment-experienced patients with advanced renal cell carcinoma. ClinicalTrials.gov Identifier: NCT01668784

BACKGROUND Nivolumab plus ipilimumab produced objective responses in patients with advanced renal-cell carcinoma in a pilot study. This phase 3 trial compared nivolumab plus ipilimumab with sunitinib for previously untreated clear-cell advanced renal-cell carcinoma. METHODS We randomly assigned adults in a 1:1 ratio to receive either nivolumab (3 mg per kilogram of body weight) plus ipilimumab (1 mg per kilogram) intravenously every 3 weeks for four doses, followed by nivolumab (3 mg per kilogram) every 2 weeks, or sunitinib (50 mg) orally once daily for 4 weeks (6-week cycle). The coprimary end points were overall survival (alpha level, 0.04), objective response rate (alpha level, 0.001), and progression-free survival (alpha level, 0.009) among patients with intermediate or poor prognostic risk. RESULTS A total of 1096 patients were assigned to receive nivolumab plus ipilimumab (550 patients) or sunitinib (546 patients); 425 and 422, respectively, had intermediate or poor risk. At a median follow-up of 25.2 months in intermediate- and poor-risk patients, the 18-month overall survival rate was 75% (95% confidence interval [CI], 70 to 78) with nivolumab plus ipilimumab and 60% (95% CI, 55 to 65) with sunitinib; the median overall survival was not reached with nivolumab plus ipilimumab versus 26.0 months with sunitinib (hazard ratio for death, 0.63; P<0.001). The objective response rate was 42% versus 27% (P<0.001), and the complete response rate was 9% versus 1%. The median progression-free survival was 11.6 months and 8.4 months, respectively (hazard ratio for disease progression or death, 0.82; P = 0.03, not significant per the prespecified 0.009 threshold). Treatment-related adverse events occurred in 509 of 547 patients (93%) in the nivolumab-plus-ipilimumab group and 521 of 535 patients (97%) in the sunitinib group; grade 3 or 4 events occurred in 250 patients (46%) and 335 patients (63%), respectively. Treatment-related adverse events leading to discontinuation occurred in 22% and 12% of the patients in the respective groups. CONCLUSIONS Overall survival and objective response rates were significantly higher with nivolumab plus ipilimumab than with sunitinib among intermediate- and poor-risk patients with previously untreated advanced renal-cell carcinoma. (Funded by Bristol-Myers Squibb and Ono Pharmaceutical; CheckMate 214 ClinicalTrials.gov number, NCT02231749.)

No abstract

Summary Muscle-invasive bladder cancers (MIBCs) are biologically heterogeneous and have widely variable clinical outcomes and responses to conventional chemotherapy. We discovered 3 molecular subtypes of MIBC that resembled established molecular subtypes of breast cancer. Basal MIBCs shared biomarkers with basal breast cancers and were characterized by p63 activation, squamous differentiation, and more aggressive disease at presentation. Luminal MIBCs contained features of active PPARγ and estrogen receptor (ER) transcription and were enriched with activating FGFR3 mutations and potentially FGFR inhibitor sensitivity. p53-like MIBCs were consistently resistant to neoadjuvant MVAC chemotherapy, and all chemoresistant tumors adopted a p53-like phenotype after therapy. Our observations have important implications for prognostication, the future clinical development of targeted agents, and disease management with conventional chemotherapy.

INTRODUCTION: Immunotherapy targeting the programmed cell death protein–1 (PD-1) axis elicits durable antitumor responses in multiple cancer types. However, clinical responses vary, and biomarkers predictive of response may help to identify patients who will derive the greatest therapeutic benefit. Clinically validated biomarkers predictive of response to the anti–PD-1 monoclonal antibody pembrolizumab include PD-1 ligand 1 (PD-L1) expression in specific cancers and high microsatellite instability (MSI-H) regardless of tumor type. Tumor mutational burden (TMB) and T cell–inflamed gene expression profile (GEP) are emerging predictive biomarkers for pembrolizumab. Both PD-L1 and GEP are inflammatory biomarkers indicative of a T cell–inflamed tumor microenvironment (TME), whereas TMB and MSI-H are indirect measures of tumor antigenicity generated by somatic tumor mutations. However, the relationship between these two categories of biomarkers is not well characterized. RATIONALE: This study assessed the potential for TMB and a T cell–inflamed GEP to jointly predict clinical response to pembrolizumab in >300 patient samples with advanced solid tumors and melanoma across 22 tumor types from four KEYNOTE clinical trials. To assess the individual and joint clinical utility of TMB and GEP, patients were stratified in four biomarker–defined clinical response groups [GEP low and TMB low (GEPlo TMBlo), GEP low and TMB high (GEPlo TMBhi), GEPhi TMBlo, and GEPhi TMBhi] based on predefined cutoffs for TMB and GEP. These patient–defined biomarker groups were further used to guide transcriptome and exome analyses of tumors in a large molecular database [The Cancer Genome Atlas (TCGA)] (n = 6384 tumors) to identify targetable patterns of biology that may modulate response and resistance. RESULTS: TMB and GEP exhibited only modest correlation and were independently predictive of response across the KEYNOTE clinical datasets. We found that objective response rates were strongest in patients with GEPhi TMBhi (37 to 57%), moderate in those with GEPhi TMBlo (12 to 35%) and GEPlo TMBhi (11 to 42%), and reduced or absent in those with GEPlo TMBlo (0 to 9%) (see the figure). Additionally, longer progression–free survival times were seen in patients with higher levels of both TMB and GEP. Findings were comparable when TMB and PD-L1 expression were jointly assessed. Within TCGA database, GEP and TMB again had a low correlation, demonstrating the potential to jointly stratify transcriptomic and genomic features across cancer types. Specific gene expression patterns reflective of TME biology showed significant associations with TMB, GEP, or both. In particular, gene set enrichment analysis identified proliferative and stromal, myeloid, and vascular biology corresponding to specific TMB-defined subgroups within GEPhi tumors. In TMBhi tumors, indication-dependent somatic DNA alterations in key cancer driver genes showed a strong negative association with GEP. CONCLUSION: This analysis shows that TMB and inflammatory biomarkers (T cell–in...