Subtype-Specific Causal Effects of Antidiabetic Drug Targets on Ovarian Cancer: Mendelian Randomization and Colocalization Evidence

Background Ovarian cancer (OC), characterized by a high mortality rate and limited treatment options, underscores the urgent need to identify novel therapeutic targets to advance individualized precision therapy. Exploring the potential of antidiabetic drug target genes as therapeutic candidates may expand the treatment repertoire of diverse OC subtypes. Methods Leveraging datasets involving the Ovarian Cancer Association Consortium, the eQTLGen consortium, and the Genotype-Tissue Expression database, we implemented an integrated analytical framework combining two-sample Mendelian randomization (MR), summary data-based MR (SMR), as well as colocalization analysis to assess the association between target genes of antidiabetic drugs with the risk and survival of different ovarian cancer subtypes. Results We systematically analyzed the target genes from nine antidiabetic drugs for associations with nine OC phenotypes. Notably, multiple target genes showed consistent and significant associations with specific OC subtypes. For instance, AKR1A1 was linked to low-grade serous OC; HMGCR and KCNJ11 to clear cell OC; ITGAL and AKR1B1 to mucinous OC; and AKR1A1 and ITGAL to endometrioid OC—with these associations supported by at least two MR methods. In contrast, the genetic associations for high-grade serous OC (HGSOC) incidence risk were less robust, as they were only supported by a single MR method. In contrast, the survival outcome of HGSOC demonstrated a more reliable genetic link, with DPP4 consistently implicated by both SMR and colocalization analysis, suggesting a potential role in prognosis rather than initiation. This divergence highlights subtype-specific biological mechanisms, in which antidiabetic drug targets may influence HGSOC progression differently from its development. Conclusion Our study presents the initial systematic findings highlighting the substantial heterogeneity in the relationships between OC and diabetes mellitus across different pathological subtypes by integrating multiple MR approaches. These findings offer a critical theoretical foundation for developing pathology-specific therapeutic targets for OC.