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

Area of Science:

• Genomics
• Cancer Research
• Mutagenesis

Background:

• Mutation spectra are crucial for understanding cancer aetiopathology, but comparing induced and human spectra is challenging due to sequence context differences.
• Previous studies demonstrated similarities in mutation types but struggled with distribution and sequence context comparisons.
• The TP53 tumor suppressor gene is frequently studied for its role in various cancers.

Purpose of the Study:

• To develop and validate an analytical approach for comparing base substitution spectra that simultaneously captures mutation type and sequence context.
• To enable direct comparison of mutation spectra across different genes and experimental systems, regardless of sequence.
• To apply this method to TP53 mutation spectra from diverse human cancers and various mutagen-induced models.

Main Methods:

• Developed an analytical approach to create a 'mutation signature' from base substitution spectra, integrating sequence context and mutation type.
• Applied the method to TP53 mutation spectra from human cancers (brain, breast, skin, colon, etc.) and mutagen-induced spectra (BPDE, UVB, UVC, simulated sunlight, hydroxyl radicals) in model systems (cII, supF, yeast p53).
• Analyzed similarities and differences between human cancer and mutagen-induced mutation signatures.

Main Results:

• The developed analytical approach successfully groups human cancer and mutagen-induced mutation signatures based on similarity.
• Key differences were identified between smoking- and non-smoking-related lung cancer TP53 mutations.
• Distinct mutability patterns of CpG sites were observed in skin cancer exons.

Conclusions:

• The new analytical method provides a robust framework for comparing diverse mutation spectra, overcoming limitations of sequence context.
• This approach facilitates a deeper understanding of mutagenic mechanisms in human cancers.
• The findings highlight specific mutational differences related to smoking and CpG site activity in cancer development.