Nov 7, 2017

Bayesian inference of negative and positive selection in human cancers

Nature Genetics
Donate Weghorn, Shamil R Sunyaev

Abstract

Cancer genomics efforts have identified genes and regulatory elements driving cancer development and neoplastic progression. From a microevolution standpoint, these are subject to positive selection. Although elusive in current studies, genes whose wild-type coding sequences are needed for tumor growth are also of key interest. They are expected to experience negative selection and stay intact under pressure of incessant mutation. The detection of significantly mutated (or undermutated) genes is completely confounded by the genomic heterogeneity of cancer mutation. Here we present a hierarchical framework that allows modeling of coding point mutations. Application of the model to sequencing data from 17 cancer types demonstrates an increased power to detect known cancer driver genes and identifies new significantly mutated genes with highly plausible biological functions. The signal of negative selection is very subtle, but is detectable in several cancer types and in a pan-cancer data set. It is enriched in cell-essential genes identified in a CRISPR screen, as well as in genes with reported roles in cancer.

  • References33
  • Citations17

References

  • References33
  • Citations17

Citations

Mentioned in this Paper

Study
Genome
Genes
Neoplasms
Nucleic Acid Sequencing
Biologic Development
Cancer Gene Mutation
Genomics
Sequencing
Neoplastic Syndromes, Hereditary

Related Feeds

CRISPR in Cancer

CRISPR-Cas system enables the editing of genes to create or correct mutations. Given that genome instability and mutation is one of the hallmarks of cancer, the CRISPR-Cas system is being explored to genetically alter and eliminate cancer cells. Here is the latest research.

Cancer Genomics (Keystone)

Cancer genomics approaches employ high-throughput technologies to identify the complete catalog of somatic alterations that characterize the genome, transcriptome and epigenome of cohorts of tumor samples. Discover the latest research using such technologies in this feed.

Cancer Genomics

Cancer genomics employ high-throughput technologies to identify the complete catalog of somatic alterations that characterize the genome, transcriptome and epigenome of cohorts of tumor samples. Discover the latest research here.

CRISPR (general)

Clustered regularly interspaced short palindromic repeats (CRISPR) are DNA sequences in the genome that are recognized and cleaved by CRISPR-associated proteins (Cas). CRISPR-Cas system enables the editing of genes to create or correct mutations. Discover the latest research on CRISPR here.

CRISPR Ribonucleases Deactivation

CRISPR-Cas system enables the editing of genes to create or correct mutations. This feed focuses on mechanisms that underlie deactivation of CRISPR ribonucleases. Here is the latest research.