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Sci Rep. 2014 Mar 27;4:4482. doi: 10.1038/srep04482.

Modelling mutational landscapes of human cancers in vitro.

Author information

1
Molecular Mechanisms and Biomarkers Group, International Agency for Research on Cancer, 69008 Lyon, France.
2
German Cancer Research Center (Deutsches Krebsforschungszentrum), D69120 Heidelberg, Germany.
3
Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, 69008 Lyon, France.
4
Department of Gastroenterology and Hepatology, Graduate School of Medicine, Kyoto University, Kyoto 606-8507, Japan.
5
Faculty of Medicine and Health, University of Leeds, Leeds LS2 9JT, United Kingdom.
6
Biostatistics Group, International Agency for Research on Cancer, 69008 Lyon, France.
7
1] German Cancer Research Center (Deutsches Krebsforschungszentrum), D69120 Heidelberg, Germany [2] Faculty of Medicine and Health, University of Leeds, Leeds LS2 9JT, United Kingdom.

Abstract

Experimental models that recapitulate mutational landscapes of human cancers are needed to decipher the rapidly expanding data on human somatic mutations. We demonstrate that mutation patterns in immortalised cell lines derived from primary murine embryonic fibroblasts (MEFs) exposed in vitro to carcinogens recapitulate key features of mutational signatures observed in human cancers. In experiments with several cancer-causing agents we obtained high genome-wide concordance between human tumour mutation data and in vitro data with respect to predominant substitution types, strand bias and sequence context. Moreover, we found signature mutations in well-studied human cancer driver genes. To explore endogenous mutagenesis, we used MEFs ectopically expressing activation-induced cytidine deaminase (AID) and observed an excess of AID signature mutations in immortalised cell lines compared to their non-transgenic counterparts. MEF immortalisation is thus a simple and powerful strategy for modelling cancer mutation landscapes that facilitates the interpretation of human tumour genome-wide sequencing data.

PMID:
24670820
PMCID:
PMC5259794
DOI:
10.1038/srep04482
[Indexed for MEDLINE]
Free PMC Article

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