Integrated molecular analysis of clear-cell renal cell carcinoma
Seishi Ogawa and colleagues report an integrated genomics analysis of more than 100 clear-cell renal carcinoma samples. They analyze whole genomes or exomes, RNA sequences and DNA methylation in ∼100 paired specimens and perform SNP array-based copy number analysis for 240 specimens. They identify n...
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Published in | Nature genetics Vol. 45; no. 8; pp. 860 - 867 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Nature Publishing Group US
01.08.2013
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
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Summary: | Seishi Ogawa and colleagues report an integrated genomics analysis of more than 100 clear-cell renal carcinoma samples. They analyze whole genomes or exomes, RNA sequences and DNA methylation in ∼100 paired specimens and perform SNP array-based copy number analysis for 240 specimens. They identify new recurrently mutated pathways and new associations between DNA methylation, mutations, gene expression and copy number profiles.
Clear-cell renal cell carcinoma (ccRCC) is the most prevalent kidney cancer and its molecular pathogenesis is incompletely understood. Here we report an integrated molecular study of ccRCC in which ≥100 ccRCC cases were fully analyzed by whole-genome and/or whole-exome and RNA sequencing as well as by array-based gene expression, copy number and/or methylation analyses. We identified a full spectrum of genetic lesions and analyzed gene expression and DNA methylation signatures and determined their impact on tumor behavior. Defective VHL-mediated proteolysis was a common feature of ccRCC, which was caused not only by
VHL
inactivation but also by new hotspot
TCEB1
mutations, which abolished Elongin C–VHL binding, leading to HIF accumulation. Other newly identified pathways and components recurrently mutated in ccRCC included PI3K-AKT-mTOR signaling, the KEAP1-NRF2-CUL3 apparatus, DNA methylation, p53-related pathways and mRNA processing. This integrated molecular analysis unmasked new correlations between DNA methylation, gene mutation and/or gene expression and copy number profiles, enabling the stratification of clinical risks for patients with ccRCC. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1061-4036 1546-1718 1546-1718 |
DOI: | 10.1038/ng.2699 |