Assessing the Mutational Consequences of Chronic Arsenic Exposure Using Patient-Derived Tumor Samples and In Vitro Systems.

Authors

Niyati Jain, Kathryn Demanelis, Evan Wu, Muhammad G Kibriya, Farzana Jasmine, Emma Wilkinson, Syed Emdadul Haque, Mohammed Kamal, Saequa Habib, Qamruzzaman Chowdhury, Farida Arjuman, Habibul Ahsan, Lixing Yang, Yu-Ying He, Brandon L Pierce

Published in

Environmental and molecular mutagenesis. Volume 67. Issue 8-9.

Abstract

Inorganic arsenic, a naturally occurring metalloid found in groundwater, is a well-established human carcinogen. Epidemiological studies from highly contaminated regions link chronic arsenic exposure to increased risks of skin, lung, bladder, and kidney cancer. However, studies investigating the mechanisms driving arsenic-related mutagenicity in human tumors remain limited. To improve our understanding, we analyzed whole-exome sequencing (WES) data from tumor samples of 17 cancer patients treated in Dhaka, Bangladesh, with known or suspected exposure based on toenail arsenic concentrations. These patients included bladder (n = 9), kidney (n = 6), and lung (n = 2) cancers. The mutational burden (mutations per megabase) across all exomes ranged from 23 to 117 for single-base substitutions (SBS) and 2 to 13 for small insertions and deletions (indel). We showed that SBS and indel signatures, including SBS5, SBS6, ID6, and ID19 contributed the highest mutation load across all exomes. However, we did not observe associations between arsenic exposure levels and any mutational signature. We additionally analyzed WES data from two cell line models of chronic arsenic exposure, HaCaT skin epithelial and BEAS-2B lung epithelial cells exposed to low-dose of arsenite (100 nM) for 28 weeks. Consistent with the patient-derived results, we observed no exposure-related mutational burden or signature. Taken together, our findings suggest that arsenic alone may have limited independent mutagenic effects and instead may act through co-carcinogenic mechanisms. However, limited sensitivity to detect low-frequency mutations and small sample sizes potentially reduced our ability to capture mutational processes that may be associated with chronic arsenic exposure.

PMID:
42920328
Bibliographic data and abstract were imported from PubMed on 24 Oct 2026.

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