Mutation pattern analysis reveals polygenic mini-drivers associated with relapse after surgery in lung adenocarcinoma
Affiliation
RNA Biology Group, CRUK Manchester Institute, The University of Manchester, Alderley Park, Manchester, SK10 4TG, UKIssue Date
2018
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The genomic lesions found in malignant tumours exhibit a striking degree of heterogeneity. Many tumours lack a known driver mutation, and their genetic basis is unclear. By mapping the somatic mutations identified in primary lung adenocarcinomas onto an independent coexpression network derived from normal tissue, we identify a critical gene network enriched for metastasis-associated genes. While individual genes within this module were rarely mutated, a significant accumulation of mutations within this geneset was predictive of relapse in lung cancer patients that have undergone surgery. Since it is the density of mutations within this module that is informative, rather than the status of any individual gene, these data are in keeping with a 'mini-driver' model of tumorigenesis in which multiple mutations, each with a weak effect, combine to form a polygenic driver with sufficient power to significantly alter cell behaviour and ultimately patient outcome. These polygenic mini-drivers therefore provide a means by which heterogeneous mutation patterns can generate the consistent hallmark changes in phenotype observed across tumours.Citation
Bennett L, Howell M, Memon D, Smowton C, Zhou C, Miller CJ. Mutation pattern analysis reveals polygenic mini-drivers associated with relapse after surgery in lung adenocarcinoma. Scientific Reports [Internet]. 2018 Oct 4;8(1).Journal
Sci RepDOI
10.1038/s41598-018-33276-3PubMed ID
30287876Additional Links
https://dx.doi.org/10.1038/s41598-018-33276-3Type
ArticleLanguage
enae974a485f413a2113503eed53cd6c53
10.1038/s41598-018-33276-3
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