An Evolutionary Approach for Identifying Driver Mutations in Colorectal Cancer

Jasmine Foo, Lin L. Liu, Kevin Leder, Markus Riester, Yoh Iwasa, Christoph Lengauer, Franziska Michor

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


The traditional view of cancer as a genetic disease that can successfully be treated with drugs targeting mutant onco-proteins has motivated whole-genome sequencing efforts in many human cancer types. However, only a subset of mutations found within the genomic landscape of cancer is likely to provide a fitness advantage to the cell. Distinguishing such “driver” mutations from innocuous “passenger” events is critical for prioritizing the validation of candidate mutations in disease-relevant models. We design a novel statistical index, called the Hitchhiking Index, which reflects the probability that any observed candidate gene is a passenger alteration, given the frequency of alterations in a cross-sectional cancer sample set, and apply it to a mutational data set in colorectal cancer. Our methodology is based upon a population dynamics model of mutation accumulation and selection in colorectal tissue prior to cancer initiation as well as during tumorigenesis. This methodology can be used to aid in the prioritization of candidate mutations for functional validation and contributes to the process of drug discovery.

Original languageEnglish (US)
Article numbere1004350
JournalPLoS computational biology
Issue number9
StatePublished - 2015

Bibliographical note

Publisher Copyright:
© 2015 Foo et al.


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