Project description:Per- and polyfluoroalkyl substances (PFAS) are a very large (thousands of chemicals) category; these substances have important industrial and consumer product applications. PFAS are highly persistent in the environment, and some are known to pose human health hazard. Regulatory agencies worldwide are considering restrictions and outright bans of PFAS; however, little data exists to make informed decisions. Therefore, a prioritization strategy is urgently needed for evaluation of potential hazards of PFAS. Structure-based grouping could expedite selection of PFAS for testing; still, the hypothesis that structure-effect relationships exist requires confirmation. We tested 26 structurally diverse PFAS from 8 groups in two human cell types from organs that are thought to be targets for PFAS. We used human induced pluripotent stem cell-derived hepatocytes and cardiomyocytes and tested concentration-response effects on both cell function and gene expression. Few phenotypic effects were observed in hepatocytes, but negative chronotropy was observed for 8 of 26 PFAS. Substance- and cell-dependent transcriptomic changes were more pronounced; however, little evidence of group-specific effects was observed. In hepatocytes, we found up-regulation of stress-related and extracellular matrix organization pathways, and down-regulation of fat metabolism. In cardiomyocytes, contractility-related pathways were most affected. Using these data, we derived phenotypic and transcriptomic point of departure estimates and compared them to predicted PFAS exposures. The conservative estimates for bioactivity and exposure were used to derive margin-of-exposure (MOE) for each PFAS. We found that most (23 of 26) PFAS had MOE>1. Overall, our data suggests that chemical structure-based grouping of PFAS may not be an appropriate strategy to predict their biological effects. This means that testing of the individual PFAS would be needed for confident decision-making. Our proposed strategy of using two human cell types and considering both phenotypic and transcriptomic effects, combined with dose-response analysis, may be used for prioritization of PFAS.

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An optimal posttreatment surveillance strategy for cancer survivors based on an individualized risk-based approach.

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An optimal posttreatment surveillance strategy for cancer survivors based on an individualized risk-based approach.

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