Perfluorooctanesulfonic acid (PFOS) induced cancer related DNA methylation alterations in human breast cells: A whole genome methylome study.
JSON
Pierozan P, Höglund A, Theodoropoulou E, Karlsson O
Sci. Total Environ. 949 (-) 174864 [2024-11-01; online 2024-07-20]
DNA methylation plays a pivotal role in cancer. The ubiquitous contaminant perfluorooctanesulfonic acid (PFOS) has been epidemiologically associated with breast cancer, and can induce proliferation and malignant transformation of normal human breast epithelial cells (MCF-10A), but the information about its effect on DNA methylation is sparse. The aim of this study was to characterize the whole-genome methylome effects of PFOS in our breast cell model and compare the findings with previously demonstrated DNA methylation alterations in breast tumor tissues. The DNA methylation profile was assessed at single CpG resolution in MCF-10A cells treated with 1 μM PFOS for 72 h by using Enzymatic Methyl sequencing (EM-seq). We found 12,591 differentially methylated CpG-sites and 13,360 differentially methylated 100 bp tiles in the PFOS exposed breast cells. These differentially methylated regions (DMRs) overlapped with 2406 genes of which 494 were long non-coding RNA and 1841 protein coding genes. We identified 339 affected genes that have been shown to display altered DNA methylation in breast cancer tissue and several other genes related to cancer development. This includes hypermethylation of GACAT3, DELEC1, CASC2, LCIIAR, MUC16, SYNE1 and hypomethylation of TTN and KMT2C. DMRs were also found in estrogen receptor genes (ESR1, ESR2, ESRRG, ESRRB, GREB1) and estrogen responsive genes (GPER1, EEIG1, RERG). The gene ontology analysis revealed pathways related to cancer phenotypes such as cell adhesion and growth. These findings improve the understanding of PFOS's potential role in breast cancer and illustrate the value of whole-genome methylome analysis in uncovering mechanisms of chemical effects, identifying biomarker candidates, and strengthening epidemiological associations, potentially impacting risk assessment.
Bioinformatics Support for Computational Resources [Service]
NGI Uppsala (SNP&SEQ Technology Platform) [Service]
National Genomics Infrastructure [Service]
PubMed 39032741
DOI 10.1016/j.scitotenv.2024.174864
Crossref 10.1016/j.scitotenv.2024.174864
pii: S0048-9697(24)05013-7