Carcinogenesis Advance Access first published online on February 22, 2008
This version published online on February 28, 2008
Carcinogenesis, doi:10.1093/carcin/bgn053
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Comparison of induced and cancer-associated mutational spectra using multivariate data analysis
1 Cancer Informatics Group, Institute of Life Science, Swansea Medical School, Swansea University, Singleton Park, SA2 8PP
2 Developmental Medicine Group, Institute of Life Science, Swansea Medical School, Swansea University, Singleton Park, SA2 8PP
3 Molecular Epidemiology Unit, Leeds Institute for Genetics, Health and Therapeutics, The Light Laboratories, University of Leeds, LS2 9JT
4 Pathology and Tumour Biology, Leeds Institute of Molecular Medicine, Wellcome Trust Brenner Building, St James's University Hospital, Leeds LS9 7TF
One of the most useful tools for investigating the aetiopathology of cancer is the mutation spectrum, which comprises the type and distribution of mutations within a gene sequence. Many studies have generated mutagen-induced spectra using in vitro or in vivo model systems in an attempt to find correlations with those observed in cancer-associated genes such as the TP53 tumour suppressor gene. Consequently, meaningful similarities in the types of mutation found in induced and human spectra have been demonstrated. However, it is more difficult to draw such conclusions about the distribution or sequence context of mutations when they arise in different target sequences. We have developed an analytical approach for base substitution spectra that captures information for both sequence context and mutation type simultaneously. The resulting mutation signature is a fixed set of data points that allows comparison of multiple mutation spectra regardless of sequence. We have applied this method to a mixed set of mutation spectra observed in exons 5, 7 and 8 of TP53 from cancers of brain, breast, skin, colon, eosophagus, liver, head and neck, stomach and lung (smokers and non-smokers), and spectra induced by benzo(a)pyrene diolepoxide, UVB, UVC, simulated sunlight and hydroxyl radicals in the cII, supF and yeast p53 model systems. We demonstrate that this approach allows human cancer and mutagen-induced signatures to be grouped together according to similarity. Specifically, the analysis reveals key differences between smoking and non-smoking related lung cancer for TP53 mutations and the mutability of CpG sites between exons in skin cancer
Received November 12, 2007; revised January 18, 2008; accepted February 12, 2008.
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