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Accurate prediction of the functional effects of genetic variation in cancer is critical for realizing the promise of precision
medicine. Due to a lack of statistically rigorous approaches and training data, differentiating driver mutations from
passenger mutations remains a major challenge in cancer research. We develope a novel Bayesian method, xDriver that
combines mutations and their sequence-derived functional features (such as GERP scores) with gene expression in a population
of tumor samples to identify mutations that significantly alter gene expression landscapes. We demonstrate using 752 breast
cancer samples in the cancer genome atlas that our integrative approach is able to significantly improve the accuracy of driver
mutation identification over existing approaches that do not perform such integration. In particular, our approach is able to
enhance the functional prioritization of so-called “tail” (rare) mutations and more accurately delineate cancer subtype specific
mutations (such as PIK3CA mutants associated with lymph node negative patients). Importantly, scores generated by our
model achieve the best agreement with in vitro functional cell viability data obtained from transfected Ba/F3 and MCF10A
cell-lines, compared to predictions from other commonly used algorithms. Our results exemplify the importance of integrating
gene expression in predicting candidate driver mutations. This integrative study has the potential to impact functional genomic
experiments and is expected to link cancer genomic event to precision medicine.
Zixing Wang has completed his PhD degree in Genome Science and Technology at the University of Tennessee in 2011, with the thesis on the TGF-beta function in neuron development. After graduation, he moved on and switched to Bioinformatics and Computational Biology. Currently he is working as a Post-doc at MD Anderson Cancer Center, University of Texas. His main research interest focuses on data mining, machine learning, especially with their integration and application in cancer genomic and precision medicine. He has published 16 scientific papers in international well-recognized journals. He has been ACM SIG and ISMB member and also served as journal reviewer for many top-tier journals in the field of bioinformatics and systems biology.