Stead, LF, Thygesen, H, Westhead, DR et al. (1 more author) (2015) Using common variants to indicate cancer genes. International Journal of Cancer, 136 (1). 241 - 245. ISSN 0020-7136
Abstract
The catalogue of tumour-specific somatic mutations (SMs) is growing rapidly owing to the advent of next-generation sequencing. Identifying those mutations responsible for the development and progression of the disease, so-called driver mutations, will increase our understanding of carcinogenesis and provide candidates for targeted therapeutics. The phenotypic consequence(s) of driver mutations cause them to be selected for within the tumour environment, such that many approaches aimed at distinguishing drivers are based on finding significantly somatically mutated genes. Currently, these methods are designed to analyse, or be specifically applied to, nonsynonymous mutations: those that alter an encoded protein. However, growing evidence suggests the involvement of noncoding transcripts in carcinogenesis, mutations in which may also be disease-driving. We wished to test the hypothesis that common DNA variation rates within humans can be used as a baseline from which to score the rate of SMs, irrespective of coding capacity. We preliminarily tested this by applying it to a dataset of 159,498 SMs and using the results to rank genes. This resulted in significant enrichment of known cancer genes, indicating that the approach has merit. As additional data from cancer sequencing studies are made publicly available, this approach can be refined and applied to specific cancer subtypes. We named this preliminary version of our approach PRISMAD (polymorphism rates indicate somatic mutations as drivers) and have made it publicly accessible, with scripts, via a link at www.precancer.leeds.ac.uk/software-and-datasets.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2015, The Authors. Reproduced in accordance with the publisher's self-archiving policy. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial No Derivates (CC BY-NC-ND 3.0) licence, which permits others to download this work and share it with others, provided the original work is unchanged, properly cited and the use is non-commercial. |
Keywords: | Cancer driver genes; Next-generation sequencing; Somatic mutation; DNA Mutational Analysis; Gene Frequency; Genes, Neoplasm; Genome-Wide Association Study; High-Throughput Nucleotide Sequencing; Humans; MicroRNAs; Models, Genetic; Mutation; Neoplasms; Polymorphism, Genetic; Software |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Molecular and Cellular Biology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Mar 2015 10:51 |
Last Modified: | 22 Aug 2015 11:53 |
Published Version: | http://dx.doi.org/10.1002/ijc.28951 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1002/ijc.28951 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:83684 |