Simultaneous Identification of Multiple Driver Pathways in Cancer
作者： Mark D. M. Leiserson , Dima Blokh , Roded Sharan , Benjamin J. Raphael
DOI: 10.1371/JOURNAL.PCBI.1003054
关键词:
摘要: Distinguishing the somatic mutations responsible for cancer (driver mutations) from random, passenger is a key challenge in genomics. Driver generally target cellular signaling and regulatory pathways consisting of multiple genes. This heterogeneity complicates identification driver by their recurrence across samples, as different combinations are observed samples. We introduce Multi-Dendrix algorithm simultaneous de novo mutation data cohort The relies on two combinatorial properties pathway: high coverage mutual exclusivity. derive an integer linear program that finds set exhibiting these properties. apply to glioblastoma, breast cancer, lung identifies sets genes overlap with known – including Rb, p53, PI(3)K, cell cycle also novel mutually exclusive mutations, several transcription factors or other involved transcriptional regulation. These discovered directly no prior knowledge gene interactions. show outperforms algorithms identifying orders magnitude faster genome-scale data. Software available at: http://compbio.cs.brown.edu/software.
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