RT Journal Article
SR Electronic
T1 Mutation-Profile-Based Methods for Understanding Selection Forces in Cancer Somatic Mutations: A Comparative Analysis
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 021147
DO 10.1101/021147
A1 Zhan Zhou
A1 Yangyun Zou
A1 Gangbiao Liu
A1 Jingqi Zhou
A1 Jingcheng Wu
A1 Shimin Zhao
A1 Zhixi Su
A1 Xun Gu
YR 2017
UL http://biorxiv.org/content/early/2017/07/02/021147.abstract
AB Human genes perform different functions and exhibit different effects on fitness in cancer and normal cell populations. Here, we present an evolutionary approach to measuring the selective pressure on human genes in both cancer and normal cell genomes using the well-known dN/dS (nonsynonymous to synonymous substitution rate) ratio. We develop a new method called the mutation-profile-based Nei-Gojobori (mpNG) method, which applies sample-specific nucleotide substitution profiles instead of conventional substitution models to calculating dN/dS ratios in cancer and normal populations. Compared with previous studies that focused on positively selected genes in cancer genomes, which potentially represent the driving force behind tumor initiation and development, we employed an alternative approach to identifying cancer-constrained genes that strengthen negative selection pressure in tumor cells. In cancer cells, we found a conservative estimate of 45 genes under intensified positive selection and 16 genes under strengthened purifying selection relative to germline cells. The cancer-specific positively selected genes were enriched for cancer genes and human essential genes, while several cancer-specific negatively selected genes were previously reported as prognostic biomarkers for cancers. Thus, our computation pipeline used to identify positively and negatively selected genes in cancer may provide useful information for understanding the evolution of cancer somatic mutations.