Fluorine Mass Balance, including Total Fluorine, Extractable Organic Fluorine, Oxidizable Precursors, and Target Per- and Polyfluoroalkyl Substances, in Pooled Human Serum from the Tromsø Population in 1986, 2007, and 2015.

Of the thousands of per- and polyfluoroalkyl substances (PFAS) known to exist, only a small fraction (≤1%) are commonly monitored in humans. This discrepancy has led to concerns that human exposure may be underestimated. Here, we address this problem by applying a comprehensive fluorine mass balance (FMB) approach, including total fluorine (TF), extractable organic fluorine (EOF), total oxidizable precursors (TOP), and selected target PFAS, to human serum samples collected over a period of 28 years (1986, 2007, and 2015) in Tromsø, Norway. While concentrations of TF did not change between sampling years, EOF was significantly higher in 1986 compared to 2007 and 2015. The ∑12PFAS concentrations were highest in 2007 compared to 1986 and 2015, and unidentified EOF (UEOF) decreased from 1986 (46%) to 2007 (10%) and then increased in 2015 (37%). While TF and EOF were not influenced by sex, women had higher UEOF compared to men, opposite to target PFAS. This is the first FMB in human serum to include TOP, and it suggests that precursors with >4 perfluorinated carbon atoms make a minor contribution to EOF (0-4%). Additional tools are therefore needed to identify substances contributing to the UEOF in human serum.

Legacy and alternative per- and polyfluoroalkyl substances (PFAS) alter the lipid profile of HepaRG cells.

Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals used in various industrial and consumer products. They have gained attention due to their ubiquitous occurrence in the environment and potential for adverse effects on human health, often linked to immune suppression, hepatotoxicity, and altered cholesterol metabolism. This study aimed to explore the impact of ten individual PFAS, 3 H-perfluoro-3-[(3-methoxypropoxy) propanoic acid] (PMPP/Adona), ammonium perfluoro-(2-methyl-3-oxahexanoate) (HFPO-DA/GenX), perfluorobutanoic acid (PFBA), perfluorobutanesulfonic acid (PFBS), perfluorodecanoic acid (PFDA), perfluorohexanoic acid (PFHxA), perfluorohexanesulfonate (PFHxS), perfluorononanoic acid (PFNA), perfluorooctanoic acid (PFOA), and perfluorooctanesulfonic acid (PFOS) on the lipid metabolism in human hepatocyte-like cells (HepaRG). These cells were exposed to different concentrations of PFAS ranging from 10 µM to 5000 µM. Lipids were extracted and analyzed using liquid chromatography coupled with mass spectrometry (LC- MS-QTOF). PFOS at 10 µM and PFOA at 25 µM increased the levels of ceramide (Cer), diacylglycerol (DAG), N-acylethanolamine (NAE), phosphatidylcholine (PC), and triacylglycerol (TAG) lipids, while PMPP/Adona, HFPO-DA/GenX, PFBA, PFBS, PFHxA, and PFHxS decreased the levels of these lipids. Furthermore, PFOA and PFOS markedly reduced the levels of palmitic acid (FA 16.0). The present study shows distinct concentration-dependent effects of PFAS on various lipid species, shedding light on the implications of PFAS for essential cellular functions. Our study revealed that the investigated legacy PFAS (PFOS, PFOA, PFBA, PFDA, PFHxA, PFHxS, and PFNA) and alternative PFAS (PMPP/Adona, HFPO-DA/GenX and PFBS) can potentially disrupt lipid homeostasis and metabolism in hepatic cells. This research offers a comprehensive insight into the impacts of legacy and alternative PFAS on lipid composition in HepaRG cells.

Total oxidizable precursors assay for PFAS in human serum.

Per- and polyfluoroalkyl substances (PFAS) are a class of chemicals including over 4700 substances. As a limited number of PFAS is routinely analyzed in human serum, complementary analytical methods are required to characterize the overlooked fraction. A promising tool is the total oxidizable precursors (TOP) assay to look for precursors by oxidation to perfluoroalkyl acids (PFAA). The TOP assay was originally developed for large volumes of water and had to be adapted for 250 µL of human serum. Optimization of the method was performed on serum samples spiked with model precursors. Oxidative conditions similar to previous TOP assay methods were not sufficient for complete oxidation of model precursors. Prolonged heating time (24 h) and higher oxidant amount (95 mg of Na2S2O8 per 225 µL of serum) were needed for complete conversion of the model precursors and accomplishing PFAA yields of 35-100 %. As some precursors are not fully converted to PFAA, the TOP assay can only provide semi-quantitative estimates of oxidizable precursors in human serum. However, the TOP assay can be used to give indications about the identity of unknown precursors by evaluating the oxidation products, including perfluoroalkyl sulfonic acids (PFSA) and perfluoroalkyl ether carboxylic acids (PFECA). The optimized TOP assay for human serum opens the possibility for high-throughput screening of human serum for undetected PFAA precursors.

neoANT-HILL: an integrated tool for identification of potential neoantigens.

BACKGROUND: Cancer neoantigens have attracted great interest in immunotherapy due to their capacity to elicit antitumoral responses. These molecules arise from somatic mutations in cancer cells, resulting in alterations on the original protein. Neoantigens identification remains a challenging task due largely to a high rate of false-positives. RESULTS: We have developed an efficient and automated pipeline for the identification of potential neoantigens. neoANT-HILL integrates several immunogenomic analyses to improve neoantigen detection from Next Generation Sequence (NGS) data. The pipeline has been compiled in a pre-built Docker image such that minimal computational background is required for download and setup. NeoANT-HILL was applied in The Cancer Genome Atlas (TCGA) melanoma dataset and found several putative neoantigens including ones derived from the recurrent RAC1:P29S and SERPINB3:E250K mutations. neoANT-HILL was also used to identify potential neoantigens in RNA-Seq data with a high sensitivity and specificity. CONCLUSION: neoANT-HILL is a user-friendly tool with a graphical interface that performs neoantigens prediction efficiently. neoANT-HILL is able to process multiple samples, provides several binding predictors, enables quantification of tumor-infiltrating immune cells and considers RNA-Seq data for identifying potential neoantigens. The software is available through github at https://github.com/neoanthill/neoANT-HILL.