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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 capture 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, oesophagus, liver, head and neck, stomach and lung (smokers and non-smokers) and spectra induced by benzo[  a  ]pyrene diol epoxide, ultraviolet (UV) B, 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.

Comparison of induced and cancer-associated mutational spectra using multivariate data analysis