Abstract / Summary
Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with the potential to disrupt metabolic processes and contribute to carcinogenesis; however, molecular evidence linking alternative and emerging PFAS to ovarian cancer (OC) remains limited. We conducted a biomarker-based case-control study integrating exposureomics with multi-omics profiling. Plasma samples from 128 patients with OC and 128 controls were analyzed for 26 PFAS, untargeted metabolomics, lipidomics, and clinical phenotypes, while urine samples from an additional 100 patients and 100 controls underwent untargeted metabolomic and clinical profiling. Single-compound, burden-based, and mixture models were integrated with PFAS-omics association scans, cross-matrix metabolite prioritization, observational exposure-omics-clinical association-chain analyses, and repeated internal cross-validation. Higher PFAS burdens were consistently associated with OC case status, and DONA, GenX, PFNA, PFPeS, PFUdA, and PFTrDA constituted an OC-prioritized six-PFAS mixture. DONA and GenX exhibited the broadest lipid-related bridging signals, particularly across phospholipids, lysophospholipids, sphingolipids, neutral lipids, and acylcarnitines. Integrated plasma and urine analyses further identified five shared metabolites-elaidic acid, hippuric acid, betaine, corticosterone, and taurocholic acid-that provided incremental and complementary discrimination beyond reference models based on clinical variables and tumor markers in internal cross-validation. Collectively, these findings demonstrate that both alternative and emerging PFAS are associated with a distinct OC-related molecular phenotype involving coordinated lipidomic, metabolomic, and hematologic alterations, while highlighting DONA and GenX as the most prominent exposure-related signals.