The whole-genome panorama of cancer drivers
By
Radhakrishnan Sabarinathan,
Oriol Pich,
Inigo Martincorena,
Carlota Rubio-Perez,
Malene Juul,
Jeremiah Wala,
Steven Schumacher,
Ofer Shapira,
Nikos Sidiropoulos,
Sebastian M Waszak,
David Tamborero,
Loris Mularoni,
Esther Rheinbay,
Henrik Hornshøj,
Jordi Deu-Pons,
Ferran Muinos,
Johanna Bertl,
Qianyun Guo,
Chad J. Creighton,
Joachim Weischenfeldt,
Jan Korbel,
Gad Getz,
Peter J. Campbell,
Jakob Skou Pedersen,
Rameen Beroukhim,
Abel Gonzalez-Perez,
Nuria Lopez-Bigas,
on behalf of the PCAWG Drivers and Functional Interpretation Group and the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Network
Posted 20 Sep 2017
bioRxiv DOI: 10.1101/190330
The advance of personalized cancer medicine requires the accurate identification of the mutations driving each patient's 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 patient's 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.
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