Key points are not available for this paper at this time.
Abstract Introduction: Mutational signatures, or unique patterns of genetic mutations due to exogenous and endogenous mutational processes, are being continuously identified through the analysis of cancer patients’ genomes. While cancer research has developed and mortality rates have declined, disparities in cancer outcomes have widened. Social determinants of health (SDOH), such as access to health care, education, and economic stability are essential to addressing health equity. While much research is ongoing regarding the identification and etiology of mutational signatures, little work has been published regarding the associations of these signatures with SDOH. Therefore, this study proposes an exploration into the relationships between the presence of mutational signatures and SDOH within an adult pan-cancer patient population. Methods: Variant calls from whole exome sequencing for each patient was used to infer the presence of 58 single base substitution (SBS) mutational signatures. Descriptive statistics were calculated for 455 unique patients. Previously documented associations between primary diagnosis site and distinct signatures were used to validate the predicted signatures in the patient population. Signature profiles were then linked to 208 patient health records with complete SDOH. Logistic regression predicting the presence of each signature was modeled for these patients. Full models for each signature included age, gender, Rural-Urban Commuting Area (RUCA) code, tobacco and alcohol usage, education, income, housing condition, and access to healthcare. Stepwise selection was used to determine significant variables. Results: The most common signatures in the complete population (n = 455) were SBS1 (clock-like; 98%) and SBS39 (95%), followed by SBS5 (clock-like; 38%) and SBS22 (aristolochic acid exposure; 36%). However, SBS24 (aflatoxin exposure; p =. 019) and SBS7a (UV exposure; p =. 002) were significantly more common in lung and skin cancer patients respectively. Each patient had 4. 1 signatures on average, with a range of 2-7. The average number of signatures per patient varied significantly by primary diagnosis (ANOVA p =. 014). Patients with a vulva/vagina (4. 8) or bladder/urinary tract (4. 9) diagnosis had the highest number of signatures while those with a liver (3. 3) or kidney (3. 6) diagnosis had the lowest. Logistic regression models for the population with SDOH (n = 208) showed poor housing condition was associated with SBS4 (tobacco smoking; p = 0. 091). Any issue in accessing healthcare was associated with SBS13 (AID/APOBEC; p = 0. 114) and SBS21 (MMR; p = 0. 076). Greater rurality was associated with SBS16 (p =. 144) and SBS21 (p =. 107). The relationship was inverse for SBS1 (p =. 121). Conclusion: Multiple significant relationships between different SDOH and mutational signatures was revealed, pointing the need to extend this research to larger patient populations with diverse SDOH. Citation Format: Padmapriya Swaminathan, McKenna Deaton, Crystal Hattum, Benjamin Solomon, William Spanos, David Starks, Rachel Elsey, Casey Williams, Tobias Meissner. Mutational signatures and their associations with social determinants of health abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 6160.
Swaminathan et al. (Fri,) studied this question.