Structure-based predictions broadly link transcription factor mutations to gene expression changes in cancers.

ABSTRACT: Thousands of unique mutations in transcription factors (TFs) arise in cancers, and the functional and biological roles of relatively few of these have been characterized. Here, we used structure-based methods developed specifically for DNA-binding proteins to systematically predict the consequences of mutations in several TFs that are frequently mutated in cancers. The explicit consideration of protein-DNA interactions was crucial to explain the roles and prevalence of mutations in TP53 and RUNX1 in cancers, and resulted in a higher specificity of detection for known p53-regulated genes among genetic associations between TP53 genotypes and genome-wide expression in The Cancer Genome Atlas, compared to existing methods of mutation assessment. Biophysical predictions also indicated that the

SUBMITTER: Ashworth J 

PROVIDER: S-EPMC4245936 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature