Background: Women with polycystic ovary syndrome (PCOS) have a substantially increased risk of endometrial cancer (EC), yet the biological mechanisms underpinning this association remain incompletely understood. Insulin-like growth factor (IGF)-associated signaling has been implicated, but existing evidence is conflicting. Methods: This feasibility and hypothesis-generating study combined a small clinical cohort with exploratory transcriptomics, in vitro and in silico analyses. Serum IGF1 and IGFBP-3 were measured in women with PCOS (n = 12 for IGF-1 and n = 6 for IGFBP-3) and controls (n = 24 for IGF1 and n = 7 for IGFBP-3). Pooled serum, stratified by IGF bioactivity, was applied to a human endometrial cancer cell line (HEC1A) to further assess effects on cell viability, cell cycle distribution, and downstream signaling, in addition to exploratory RNA sequencing (n=1 biological replicate per condition). Computational analysis of publicly available endometrial cancer datasets was used to contextualize experimental findings. Results: Serum IGF1 and IGFBP-3 levels did not differ significantly between PCOS and control groups. However, pooled PCOS serum increased EC cell viability and altered cell cycle progression compared with control serum. Pharmacological inhibition of IGF1R partially attenuated these effects, suggesting that IGF-associated pathways may contribute but are unlikely to act in isolation. Exploratory transcriptomic profiling of serum-treated EC cells supported enrichment of IGF-associated metabolic and growth programs (including mTORC1, PI3K/AKT/mTOR, glycolysis and oxidative phosphorylation), consistent with context-dependent modulation rather than IGF-only dependence. In silico analyses demonstrated frequent alterations in PI3K/AKT/mTOR-related genes in endometrial cancer, consistent with pathway-level vulnerability rather than IGF1-specific dependence. Conclusion: As a feasibility study, these findings suggest that PCOS serum contains factors that promote EC cell growth, with partial involvement of IGF signaling. However, multiple metabolic and hormonal pathways are likely to contribute. Larger, better-controlled studies incorporating insulin, sex steroids, and multiple EC models are required before causal inferences can be made.