Exposure to particulate matter (PM) has been linked to an increased risk of multiple diseases, primarily lung cancer, through various molecular mechanisms. However, the mutagenic potential of PM remains unclear. This study aimed to provide a comprehensive description of genetic mutations and mutagenic signatures resulting from chronic exposure to PM10 or PM2.5. Using whole exome sequencing, we identified driver mutations and mutational signatures in A549 cells, a lung epithelial cell model subjected to weekly exposure to either PM10 or PM2.5, for a period of 28 weeks. The number of single nucleotide variations, insertions, and deletions increased depending on the duration of exposure. PM10 generated the highest number of genomic alterations. Amplifications in SYK (oncogene) and mutations in NCOR1 (tumor suppressor gene) were prevalent in cells exposed to either PM10 or PM2.5; however, other mutations were exclusive, such as TP53 and ANK3 for PM10, and ERCC1 and ERCC2 for PM2.5. Different p53-related signaling pathways were most enriched by driver mutations upon exposure to both PM10 and PM2.5, particularly the glucose deprivation pathway. Exposure to either PM10 or PM2.5 resulted in high frequencies of C > A substitutions and one-base insertions/deletions in microhomology sites. The single-base substitution (SBS) signature SBS05, related to the nucleotide excision DNA repair pathway, contributed the most to both PM10-and PM2.5-exposed cells. The contribution of signature SBS18, related to oxidative stress, was observed in cells exposed to either PM10 or PM2.5, but a greater contribution was observed in PM2.5-exposed cells. In addition, SBS03 and SBS36, which are related to different DNA damage repair mechanisms, were observed more frequently in PM10-exposed cells. We assessed the mutagenic potential of PM10 and PM2.5, as a complete mixture, identifying mutated driver genes and mutational signatures generated by chronic PM exposure, which could contribute to the development of cancer, cardiovascular, and digestive diseases.
Keywords: Cancer genomics; Lung cancer; PM(10) and PM(2.5); mutational signatures; mutations.
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