Molecular subtype, biological sex and age shape melanoma tumour evolution

Abstract

Background: Many cancer types display sex and age disparity in incidence and outcome. The mutational load of tumours, including melanoma, varies according to sex and age. However, there are no tools to explore systematically whether clinical variables such as age and sex determine the genomic landscape of cancer.

Objectives: To establish a mathematical approach using melanoma mutational data to analyse how sex and age shape the tumour genome.

Methods: We model how age-related (clock-like) somatic mutations that arise during cell division, and extrinsic (environmental ultraviolet radiation) mutations accumulate in cancer genomes.

Results: Melanoma is driven primarily by cell-intrinsic age-related mutations and extrinsic ultraviolet radiation-induced mutations, and we show that these mutation types differ in magnitude and chronology and by sex in the distinct molecular melanoma subtypes. Our model confirms that age and sex are determinants of cellular mutation rate, shaping the final mutation composition. We show mathematically for the first time how, similarly to noncancer tissues, melanoma genomes reflect a decline in cell division during ageing. We find that clock-like mutations strongly correlate with the acquisition of ultraviolet-induced mutations, but critically, men present a higher number and rate of cell-division-linked mutations.

Conclusions: These data indicate that the contribution of environmental damage to melanoma likely extends beyond genetic damage to affect cell division. Sex and age determine the final mutational composition of melanoma.

Figure 1. The molecular subtypes of melanoma present distinct ratios of clock-like and UVR mutations per unit of time

(A) Correlation analysis between somatic mutations due to clock-like Signature 1 mutations in cutaneous melanomas and age. Dots represent the median number of mutations for each age. (B) Correlation analysis between clock-like Signature 1 mutations in the molecular subtypes of cutaneous melanomas (BRAF: red; NRAS: blue) and age. Dots represent the median number of mutations for each age. (C) Ratio of number of signature 1 mutations per year across the molecular subtypes of cutaneous melanoma. (D) Correlation analysis between somatic mutations due to UVR Signature 7 mutations in cutaneous melanomas and age. Dots represent the median number of mutations for each age. (E) Correlation analysis between UVR Signature 7 mutations in the molecular subtypes of cutaneous melanomas (BRAF: red; NRAS: blue) and age. Dots represent the median number of mutations for each age. (F) Ratio of number of Signature 7 mutations per year across the molecular subtypes of cutaneous melanoma.

Figure 2. Ageing affects the intrinsic mutation rate of the molecular subtypes

(A) Correlation analysis between clock-like Signature 1 mutations per year and age in cutaneous melanomas. Dots represent the median number of mutations for each age. (B) Distribution curves displaying Signature 1 mutation frequency across age ranges (red: 50-60 year-old range; green: 60-70 year-old range; blue: 70-80 year-old range; purple: 80-90 year-old range). (C) Exponential model for the accumulation of Signature 1 mutations in all melanomas. This curve models the Poisson mean distribution of mutations at each age, with age-dependent rate. (D) Exponential model for the accumulation of Signature 1 mutations in the molecular subtypes of cutaneous melanoma (BRAF: red; NF1: green; NRAS: blue; W3: purple). This curve models the Poisson mean distribution of mutations at each age, with age-dependent rate. (E) Change in Signature 1 mutations per year with age across BRAF, NRAS and W3 subtypes.

Figure 3. The Signature 7 UVR imprint predominates in melanoma and is tightly correlated to cell division Signature 1 mutations

(A) Mutation signature spectra and proportions in BRAF, NF1, NRAS, and W3 cutaneous melanomas. (B) Correlation analysis between somatic mutations due to extrinsic, UVR-driven Signature 7 mutations in cutaneous melanomas and intrinsic, clock-like Signature 1 mutations. (C) Correlation analysis between somatic mutations due to extrinsic, UVR-driven Signature 7 mutations in cutaneous melanomas subtypes and intrinsic, clock-like Signature 1 mutations (BRAF: red; NRAS: blue).

Figure 4. Melanoma in males accumulate more Signature 1 mutations

(A) Difference in Signature 1 mutations per age between males and females. (B) Difference in Signature 1 mutations per age between males and females by subtype (BRAF and NRAS). (C) Exponential model for accumulation of Signature 1 mutations by sex. This curve models the Poisson mean distribution of mutations at each age, with age-dependent rate. (D) Change of Signature 1 mutations per age over time, according to sex.

Figure 5. Summary findings.

(A) UV-light somatic mutations are strongly associated to the rate of cell-division mutations, suggesting that an extrinsic mutational process (UV) influences the intrinsic mutational process due to cell division. The rate of cell division in male melanoma is more strongly correlated to UV damage than in females. (B) Cancer cells bear the genomic imprint of decreasing rate of cell division during ageing.