| Literature DB >> 29625053 |
Matthew H Bailey1, Collin Tokheim2, Eduard Porta-Pardo3, Sohini Sengupta1, Denis Bertrand4, Amila Weerasinghe1, Antonio Colaprico5, Michael C Wendl6, Jaegil Kim7, Brendan Reardon8, Patrick Kwok-Shing Ng9, Kang Jin Jeong10, Song Cao1, Zixing Wang11, Jianjiong Gao12, Qingsong Gao1, Fang Wang11, Eric Minwei Liu13, Loris Mularoni14, Carlota Rubio-Perez14, Niranjan Nagarajan4, Isidro Cortés-Ciriano15, Daniel Cui Zhou1, Wen-Wei Liang1, Julian M Hess7, Venkata D Yellapantula1, David Tamborero14, Abel Gonzalez-Perez14, Chayaporn Suphavilai4, Jia Yu Ko4, Ekta Khurana13, Peter J Park16, Eliezer M Van Allen8, Han Liang17, Michael S Lawrence18, Adam Godzik19, Nuria Lopez-Bigas20, Josh Stuart21, David Wheeler22, Gad Getz7, Ken Chen11, Alexander J Lazar23, Gordon B Mills10, Rachel Karchin24, Li Ding25.
Abstract
Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors. Published by Elsevier Inc.Entities:
Keywords: driver gene discovery; mutations of clinical relevance; oncology; structure analysis
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Year: 2018 PMID： 29625053 PMCID： PMC6029450 DOI： 10.1016/j.cell.2018.02.060
Source DB: PubMed Journal: Cell ISSN： 0092-8674 Impact factor: 41.582