New Software Tool Identifies Driver Genes and Pathways in Cancer Sequencing Studies

Driver mutations are required for the expression of a cancer phenotype, whereas passenger mutations are irrelevant to tumor development and accumulate through DNA replication. A major challenge facing the field of cancer genome sequencing has been identifying cancer-associated driver gene mutations.

Investigators at the Medical College of Wisconsin (Milwaukee, USA) have described a powerful and flexible statistical framework for identifying driver genes and driver signaling pathways in cancer genome-sequencing studies. Biological knowledge of the mutational process in tumors was fully integrated into their statistical models, which included such variables as the length of protein-coding regions, transcript isoforms, variation in mutation types, differences in background mutation rates, the redundancy of genetic code, and multiple mutations in one gene.

A detailed description of the software tool, which was nicknamed DrGaP—for Driver Genes and Pathways—was published in the August 15, 2013, online edition of the American Journal of Human Genetics.

"DrGaP is immediately applicable to cancer genome sequencing studies and will lead a more complete identification of altered driver genes and driver signaling pathways in cancer," said senior author Dr. Pengyuan Liu, associate professor of physiology at the Medical College of Wisconsin. "Biological knowledge of the mutation process is fully integrated into the models, and provides several significant improvements and increased power over current methods."

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