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Molecular analysis of aggressive renal cell carcinoma with unclassified histology reveals distinct subsets

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  • Ying-Bei Chen

    (Memorial Sloan Kettering Cancer Center)

  • Jianing Xu

    (Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center)

  • Anders Jacobsen Skanderup

    (Computational Biology Program, Sloan Kettering Institute for Cancer Research, Memorial Sloan Kettering Cancer Center
    Present address: Computational and Systems Biology, Genome Institute of Singapore, 60 Biopolis St, Singapore 138672, Singapore)

  • Yiyu Dong

    (Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center)

  • A. Rose Brannon

    (Memorial Sloan Kettering Cancer Center)

  • Lu Wang

    (Memorial Sloan Kettering Cancer Center)

  • Helen H. Won

    (Memorial Sloan Kettering Cancer Center)

  • Patricia I. Wang

    (Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center)

  • Gouri J. Nanjangud

    (Molecular Cytogenetics Laboratory, Memorial Sloan Kettering Cancer Center)

  • Achim A. Jungbluth

    (Memorial Sloan Kettering Cancer Center)

  • Wei Li

    (Cell Biology Program, Sloan Kettering Institute for Cancer Research, Memorial Sloan Kettering Cancer Center)

  • Virginia Ojeda

    (Cell Biology Program, Sloan Kettering Institute for Cancer Research, Memorial Sloan Kettering Cancer Center)

  • A. Ari Hakimi

    (Urology Service, Memorial Sloan Kettering Cancer Center)

  • Martin H. Voss

    (Genitourinary Oncology Service, Memorial Sloan Kettering Cancer Center)

  • Nikolaus Schultz

    (Computational Biology Program, Sloan Kettering Institute for Cancer Research, Memorial Sloan Kettering Cancer Center)

  • Robert J. Motzer

    (Genitourinary Oncology Service, Memorial Sloan Kettering Cancer Center)

  • Paul Russo

    (Urology Service, Memorial Sloan Kettering Cancer Center)

  • Emily H. Cheng

    (Memorial Sloan Kettering Cancer Center
    Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center)

  • Filippo G. Giancotti

    (Cell Biology Program, Sloan Kettering Institute for Cancer Research, Memorial Sloan Kettering Cancer Center
    Present address: Department of Cancer Biology and David H. Koch Center for Applied Research of Genitourinary Cancers, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, USA)

  • William Lee

    (Computational Biology Program, Sloan Kettering Institute for Cancer Research, Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center)

  • Michael F. Berger

    (Memorial Sloan Kettering Cancer Center
    Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center)

  • Satish K. Tickoo

    (Memorial Sloan Kettering Cancer Center)

  • Victor E. Reuter

    (Memorial Sloan Kettering Cancer Center)

  • James J. Hsieh

    (Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center
    Genitourinary Oncology Service, Memorial Sloan Kettering Cancer Center
    Weill Cornell Medical College)

Abstract

Renal cell carcinomas with unclassified histology (uRCC) constitute a significant portion of aggressive non-clear cell renal cell carcinomas that have no standard therapy. The oncogenic drivers in these tumours are unknown. Here we perform a molecular analysis of 62 high-grade primary uRCC, incorporating targeted cancer gene sequencing, RNA sequencing, single-nucleotide polymorphism array, fluorescence in situ hybridization, immunohistochemistry and cell-based assays. We identify recurrent somatic mutations in 29 genes, including NF2 (18%), SETD2 (18%), BAP1 (13%), KMT2C (10%) and MTOR (8%). Integrated analysis reveals a subset of 26% uRCC characterized by NF2 loss, dysregulated Hippo–YAP pathway and worse survival, whereas 21% uRCC with mutations of MTOR, TSC1, TSC2 or PTEN and hyperactive mTORC1 signalling are associated with better clinical outcome. FH deficiency (6%), chromatin/DNA damage regulator mutations (21%) and ALK translocation (2%) distinguish additional cases. Altogether, this study reveals distinct molecular subsets for 76% of our uRCC cohort, which could have diagnostic and therapeutic implications.

Suggested Citation

  • Ying-Bei Chen & Jianing Xu & Anders Jacobsen Skanderup & Yiyu Dong & A. Rose Brannon & Lu Wang & Helen H. Won & Patricia I. Wang & Gouri J. Nanjangud & Achim A. Jungbluth & Wei Li & Virginia Ojeda & A, 2016. "Molecular analysis of aggressive renal cell carcinoma with unclassified histology reveals distinct subsets," Nature Communications, Nature, vol. 7(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms13131
    DOI: 10.1038/ncomms13131
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