Germline Fitness Based Scoring of Cancer Mutations.

Fischer, A, Greenman, C and Mustonen, V (2011) Germline Fitness Based Scoring of Cancer Mutations. Genetics, 188 (2). pp. 383-393. ISSN 1943-2631

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Abstract

A key goal in cancer research is to find the genomic alterations which underlie malignant cells. Genomics has proven successful in identifying somatic variants at a large scale. However, it has become evident that a typical cancer exhibits a heterogenous mutation pattern across samples. Cases where the same alteration is observed repeatedly seem to be the exception rather than the norm. Thus, pinpointing the key alterations (driver mutations) from a back- ground of variations with no direct causal link to cancer (passenger mutations) is difficult. Here we analyze somatic missense mutations from cancer samples and their healthy tissue counterparts (germline mutations) from the viewpoint of germline fitness. We calibrate a scoring system from protein domain alignments to score mutations and their target loci. We show first that this score predicts to a good degree the rate a key goal in cancer research is to find the genomic alterations which underlie malignant cells. Genomics has proven successful in identifying somatic variants at a large scale. However, it has become evident that a typical cancer exhibits a heterogenous mutation pattern across samples. Cases where the same alteration is observed repeatedly seem to be the exception rather than the norm. Thus, pinpointing the key alterations (driver mutations) from a back- ground of variations with no direct causal link to cancer (passenger mutations) is difficult. Here we analyze somatic missense mutations from cancer samples and their healthy tissue counterparts (germline mutations) from the viewpoint of germline fitness. We calibrate a scoring system from protein domain alignments to score mutations and their target loci. We show first that this score predicts to a good degree the rate of polymorphism of the observed germline variation. The scoring is then applied to somatic mutations. We show that candidate cancer genes prone to copy number loss harbor mutations with germline fitness effects that are significantly more deleterious than expected by chance. This suggest that missense mutations play a driving role in tumour suppressor genes. Furthermore, these mutations fall preferably onto loci in sequence neighborhoods which are high scoring in terms of germline Fitness. In contrast, for somatic mutations in candidate onco genes we do not observe a statistically significant effect. These results help to inform how to exploit germline fitness predictions in discovering new genes and mutations responsible for cancer.

Item Type: Article
Faculty \ School: Faculty of Science > School of Computing Sciences

University of East Anglia > Faculty of Science > Research Groups > Computational Biology (subgroups are shown below) > Analysis and models of genomic variation
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Depositing User: Christopher Greenman
Date Deposited: 22 Jun 2011 10:54
Last Modified: 21 Apr 2020 16:36
URI: https://ueaeprints.uea.ac.uk/id/eprint/30580
DOI: 10.1534/genetics.111.127480

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