Background-Intratumor heterogeneity may foster tumor evolution and adaptation and hinder personalized-medicine strategies that depend on results from single tumor-biopsy samples.

As compared with placebo, treatment with sorafenib prolongs progression-free survival in patients with advanced clear-cell renal-cell carcinoma in whom previous therapy has failed; however, treatment is associated with increased toxic effects. (ClinicalTrials.gov number, NCT00073307 [ClinicalTrials.gov].).

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Clear cell renal carcinomas (ccRCCs) can display intratumor heterogeneity (ITH). We applied multiregion exome sequencing (M-seq) to resolve the genetic architecture and evolutionary histories of ten ccRCCs. Ultra-deep sequencing identified ITH in all cases. We found that 73-75% of identified ccRCC driver aberrations were subclonal, confounding estimates of driver mutation prevalence. ITH increased with the number of biopsies analyzed, without evidence of saturation in most tumors. Chromosome 3p loss and VHL aberrations were the only ubiquitous events. The proportion of C>T transitions at CpG sites increased during tumor progression. M-seq permits the temporal resolution of ccRCC evolution and refines mutational signatures occurring during tumor development.

We describe results from IMmotion150, a randomized phase 2 study of atezolizumab (anti-PD-L1) alone or combined with bevacizumab (anti-VEGF) versus sunitinib in 305 patients with treatment-naive metastatic renal cell carcinoma. Co-primary endpoints were progression-free survival (PFS) in intent-to-treat and PD-L1+ populations. Intent-to-treat PFS hazard ratios for atezolizumab + bevacizumab or atezolizumab monotherapy versus sunitinib were 1.0 (95% confidence interval (CI), 0.69-1.45) and 1.19 (95% CI, 0.82-1.71), respectively; PD-L1+ PFS hazard ratios were 0.64 (95% CI, 0.38-1.08) and 1.03 (95% CI, 0.63-1.67), respectively. Exploratory biomarker analyses indicated that tumor mutation and neoantigen burden were not associated with PFS. Angiogenesis, T-effector/IFN-γ response, and myeloid inflammatory gene expression signatures were strongly and differentially associated with PFS within and across the treatments. These molecular profiles suggest that prediction of outcomes with anti-VEGF and immunotherapy may be possible and offer mechanistic insights into how blocking VEGF may overcome resistance to immune checkpoint blockade.