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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-10-07

AUTHORS

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. Ari Hakimi, Martin H. Voss, Nikolaus Schultz, Robert J. Motzer, Paul Russo, Emily H. Cheng, Filippo G. Giancotti, William Lee, Michael F. Berger, Satish K. Tickoo, Victor E. Reuter, James J. Hsieh

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. More... »

PAGES

13131

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  • Journal

    TITLE

    Nature Communications

    ISSUE

    1

    VOLUME

    7

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/ncomms13131

    DOI

    http://dx.doi.org/10.1038/ncomms13131

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1048068890

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/27713405


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