Statistical method on nonrandom clustering with application to somatic mutations in cancer.

ABSTRACT:

Background

Human cancer is caused by the accumulation of tumor-specific mutations in oncogenes and tumor suppressors that confer a selective growth advantage to cells. As a consequence of genomic instability and high levels of proliferation, many passenger mutations that do not contribute to the cancer phenotype arise alongside mutations that drive oncogenesis. While several approaches have been developed to separate driver mutations from passengers, few approaches can specifically identify activating driver mutations in oncogenes, which are more amenable for pharmacological intervention.

Results

We propose a new statistical method for detecting activating mutations in cancer by identifying nonrandom clusters of amino acid mutations in protein sequences. A probability model

SUBMITTER: Ye J 

PROVIDER: S-EPMC2822753 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature