Details

Autor(en) / Beteiligte

• Chen, Ying-Bei
• Xu, Jianing
• Skanderup, Anders Jacobsen
• Dong, Yiyu
• Brannon, A. Rose
• Wang, Lu
• Won, Helen H.
• Wang, Patricia I.
• Nanjangud, Gouri J.
• Jungbluth, Achim A.
• Li, Wei
• Ojeda, Virginia
• Hakimi, A. Ari
• Voss, Martin H.
• Schultz, Nikolaus
• Motzer, Robert J.
• Russo, Paul
• Cheng, Emily H.
• Giancotti, Filippo G.
• Lee, William
• Berger, Michael F.
• Tickoo, Satish K.
• Reuter, Victor E.
• Hsieh, James J.

Titel

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

Ist Teil von

• Nature communications, 2016-10, Vol.7 (1), p.13131-13131, Article 13131

Ort / Verlag

London: Nature Publishing Group UK

Erscheinungsjahr

2016

Quelle

MEDLINE

Beschreibungen/Notizen

• 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. A subset of renal cell carcinomas have uncertain histology and are aggressive in nature. Here, the authors examine this group of unclassified renal cancers using genomics techniques and identify further subclasses of the tumours that have differing prognoses.