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  • Molecular Subsets in Renal ...
    Motzer, Robert J.; Banchereau, Romain; Hamidi, Habib; Powles, Thomas; McDermott, David; Atkins, Michael B.; Escudier, Bernard; Liu, Li-Fen; Leng, Ning; Abbas, Alexander R.; Fan, Jinzhen; Koeppen, Hartmut; Lin, Jennifer; Carroll, Susheela; Hashimoto, Kenji; Mariathasan, Sanjeev; Green, Marjorie; Tayama, Darren; Hegde, Priti S.; Schiff, Christina; Huseni, Mahrukh A.; Rini, Brian

    Cancer cell, 12/2020, Letnik: 38, Številka: 6
    Journal Article

    Integrated multi-omics evaluation of 823 tumors from advanced renal cell carcinoma (RCC) patients identifies molecular subsets associated with differential clinical outcomes to angiogenesis blockade alone or with a checkpoint inhibitor. Unsupervised transcriptomic analysis reveals seven molecular subsets with distinct angiogenesis, immune, cell-cycle, metabolism, and stromal programs. While sunitinib and atezolizumab + bevacizumab are effective in subsets with high angiogenesis, atezolizumab + bevacizumab improves clinical benefit in tumors with high T-effector and/or cell-cycle transcription. Somatic mutations in PBRM1 and KDM5C associate with high angiogenesis and AMPK/fatty acid oxidation gene expression, while CDKN2A/B and TP53 alterations associate with increased cell-cycle and anabolic metabolism. Sarcomatoid tumors exhibit lower prevalence of PBRM1 mutations and angiogenesis markers, frequent CDKN2A/B alterations, and increased PD-L1 expression. These findings can be applied to molecularly stratify patients, explain improved outcomes of sarcomatoid tumors to checkpoint blockade versus antiangiogenics alone, and develop personalized therapies in RCC and other indications. Display omitted •Genomics of 823 RCC tumors, including 134 sarcomatoid tumors, reveals 7 subtypes•Subtype specific angiogenesis, immune, metabolic, stromal, and cell-cycle profiles•Differential prevalence of PBRM1, KDM5C, CDKN2A/2B, and TP53 alterations in subsets•Differential outcomes to VEGF blockade alone or in combination with anti-PD-L1 Motzer et al. perform integrative multi-omics analyses of 823 renal cancer tumors from a randomized clinical trial. A robust molecular classification scheme, based on transcriptional and gene alteration profiles and differential clinical outcomes to VEGF blockade alone or in combination with anti-PD-L1, informs personalized treatment strategies and future therapeutic development in RCC.