TY - JOUR
T1 - Comprehensive identification of mutational cancer driver genes across 12 tumor types
AU - Tamborero, David
AU - Gonzalez-Perez, Abel
AU - Perez-Llamas, Christian
AU - Deu-Pons, Jordi
AU - Kandoth, Cyriac
AU - Reimand, Jüri
AU - Lawrence, Michael S.
AU - Getz, Gad
AU - Bader, Gary D.
AU - Ding, Li
AU - Lopez-Bigas, Nuria
N1 - Funding Information:
We acknowledge funding from the Spanish Ministry of Science and Technology (grant number SAF2009-06954 and SAF2012-36199) and the Spanish National Institute of Bioinformatics (INB). This work was supported by NRNB (U.S. National Institutes of Health, National Center for Research Resources grant number P41 GM103504). We gratefully acknowledge the contributions from the TCGA Research Network and its TCGA Pan-Cancer Analysis Working Group (contributing consortium members are listed in Supplementary Note 1).
PY - 2013
Y1 - 2013
N2 - With the ability to fully sequence tumor genomes/exomes, the quest for cancer driver genes can now be undertaken in an unbiased manner. However, obtaining a complete catalog of cancer genes is difficult due to the heterogeneous molecular nature of the disease and the limitations of available computational methods. Here we show that the combination of complementary methods allows identifying a comprehensive and reliable list of cancer driver genes. We provide a list of 291 high-confidence cancer driver genes acting on 3,205 tumors from 12 different cancer types. Among those genes, some have not been previously identified as cancer drivers and 16 have clear preference to sustain mutations in one specific tumor type. The novel driver candidates complement our current picture of the emergence of these diseases. In summary, the catalog of driver genes and the methodology presented here open new avenues to better understand the mechanisms of tumorigenesis.
AB - With the ability to fully sequence tumor genomes/exomes, the quest for cancer driver genes can now be undertaken in an unbiased manner. However, obtaining a complete catalog of cancer genes is difficult due to the heterogeneous molecular nature of the disease and the limitations of available computational methods. Here we show that the combination of complementary methods allows identifying a comprehensive and reliable list of cancer driver genes. We provide a list of 291 high-confidence cancer driver genes acting on 3,205 tumors from 12 different cancer types. Among those genes, some have not been previously identified as cancer drivers and 16 have clear preference to sustain mutations in one specific tumor type. The novel driver candidates complement our current picture of the emergence of these diseases. In summary, the catalog of driver genes and the methodology presented here open new avenues to better understand the mechanisms of tumorigenesis.
UR - http://www.scopus.com/inward/record.url?scp=84885129618&partnerID=8YFLogxK
U2 - 10.1038/srep02650
DO - 10.1038/srep02650
M3 - Article
C2 - 24084849
AN - SCOPUS:84885129618
SN - 2045-2322
VL - 3
JO - Scientific reports
JF - Scientific reports
M1 - 2650
ER -