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

We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes-wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant-characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.