Year: 2019
Type: article
Abstract: Identifying and distinguishing cancer driver genes among thousands of candidate mutations remains a major challenge. Accurate identification of driver genes and driver mutations is critical for advancing cancer research and personalizing treatment based on accurate stratification of patients. Due to inter-tumor genetic heterogeneity many driver mutations within a gene occur at low frequencies, which make it challenging to distinguish them from non-driver mutations. We have developed a novel method for identifying cancer driver genes. Our approach utilizes multiple complementary types of information, specifically cellular phenotypes, cellular locations, functions, and whole body physiological phenotypes as features. We demonstrate that our method can accurately identify known cancer driver genes and distinguish between their role in different types of cancer. In addition to confirming known driver genes, we identify several novel candidate driver genes. We demonstrate the utility of our method by validating its predictions in nasopharyngeal cancer and colorectal cancer using whole exome and whole genome sequencing.
Source: Scientific Reports
Institutions: King Abdullah University of Science and Technology, University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, King Abdulaziz University, King Abdul Aziz University Hospital, King Abdulaziz Hospital, University of Cambridge, National Institute for Health and Care Research, NIHR Surgical Reconstruction and Microbiology Research Centre, Health Data Research UK
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $1,790
Funders: National Science Foundation, Wellcome Trust, Cancer Research UK, National Institute for Health and Care Research, King Abdullah University of Science and Technology, Surgical Reconstruction and Microbiology Research Centre, Horizon 2020 Framework Programme, Imperial Experimental Cancer Medicine Centre, Medical Research Council, Birmingham Biomedical Research Centre
Awards: G1235327559, G1374303215, G1786638435, G198788104, G2344873991, G3431621117, Molecular stratification of rectal cancer., Molecular stratification of rectal cancer., G439089712, G4573211438, G5352452687, G5407366650, G5435355457, cROP: Common Reference Ontologies and Applications for Plant Biology, G6352856463, G6994625197, G7230862021, G7692565448, G8067857331, MICA: Stratification in COloRectal cancer: from biology to Treatment prediction: S-CORT
OpenAlex ID: W2991479679