Systematic analysis of somatic mutations driving cancer: Uncovering functional protein regions in disease development

Bálint Mészáros, András Zeke, A. Reményi, I. Simon, Z. Dosztányi

Research output: Article

3 Citations (Scopus)

Abstract

Background: Recent advances in sequencing technologies enable the large-scale identification of genes that are affected by various genetic alterations in cancer. However, understanding tumor development requires insights into how these changes cause altered protein function and impaired network regulation in general and/or in specific cancer types. Results: In this work we present a novel method called iSiMPRe that identifies regions that are significantly enriched in somatic mutations and short in-frame insertions or deletions (indels). Applying this unbiased method to the complete human proteome, by using data enriched through various cancer genome projects, we identified around 500 protein regions which could be linked to one or more of 27 distinct cancer types. These regions covered the majority of known cancer genes, surprisingly even tumor suppressors. Additionally, iSiMPRe also identified novel genes and regions that have not yet been associated with cancer. Conclusions: While local somatic mutations correspond to only a subset of genetic variations that can lead to cancer, our systematic analyses revealed that they represent an accompanying feature of most cancer driver genes regardless of the primary mechanism by which they are perturbed during tumorigenesis. These results indicate that the accumulation of local somatic mutations can be used to pinpoint genes responsible for cancer formation and can also help to understand the effect of cancer mutations at the level of functional modules in a broad range of cancer driver genes. Reviewers: This article was reviewed by Sándor Pongor, Michael Gromiha and Zoltán Gáspári.

Original languageEnglish
Article number23
JournalBiology Direct
Volume11
Issue number1
DOIs
Publication statusPublished - máj. 5 2016

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ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology
  • Applied Mathematics
  • Modelling and Simulation
  • Ecology, Evolution, Behavior and Systematics

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