The whole-genome panorama of cancer drivers
Radhakrishnan SabarinathaniD, Oriol PichiD, Iñigo MartincorenaiD, Carlota Rubio-PereziD, Malene JuuliD, Jeremiah WalaiD, Steven SchumacheriD, Ofer ShapiraiD, Nikos SidiropoulosiD, Sebastian M. WaszakiD, David TamboreroiD, Loris MularoniiD, Esther RheinbayiD, Henrik HornshøjiD, Jordi Deu-PonsiD, Ferran MuiñosiD, Johanna BertliD, Qianyun GuoiD, Chad J. CreightoniD, Joachim WeischenfeldtiD, Jan O. KorbeliD, Gad GetziD, Peter J. CampbelliD, Jakob S. PederseniD, Rameen BeroukhimiD, , on behalf of the PCAWG Drivers and Functional Interpretation Group and the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Network
Abstract
The advance of personalized cancer medicine requires the accurate identification of the mutations driving each patients tumor. However, to date, we have only been able to obtain partial insights into the contribution of genomic events to tumor development. Here, we design a comprehensive approach to identify the driver mutations in each patients tumor and obtain a whole-genome panorama of driver events across more than 2,500 tumors from 37 types of cancer. This panorama includes coding and non-coding point mutations, copy number alterations and other genomic rearrangements of somatic origin, and potentially predisposing germline variants. We demonstrate that genomic events are at the root of virtually all tumors, with each carrying on average 4.6 driver events. Most individual tumors harbor a unique combination of drivers, and we uncover the most frequent co-occurring driver events. Half of all cancer genes are affected by several types of driver mutations. In summary, the panorama described here provides answers to fundamental questions in cancer genomics and bridges the gap between cancer genomics and personalized cancer medicine.
02 /Specification & Classification
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