Abstract
BACKGROUND: Evidence indicates that the risk of developing a secondary ovarian cancer (OC) is correlated with estrogen receptor (ER) status. However, the clinical significance of the relationship between ER-associated breast cancer (BC) and clear cell ovarian cancer (CCOC) remains elusive. METHODS: Independent single nucleotide polymorphisms (SNPs) strongly correlated with exposure were extracted, and those associated with confounders and outcomes were removed using the PhenoScanner database. SNP effects were extracted from the outcome datasets with minor allele frequency > 0.01 as the filtration criterion. Next, valid instrumental variables (IVs) were obtained by harmonizing exposure and outcome effects and further filtered based on F-statistics (> 10). Mendelian randomization (MR) assessment of valid IVs was carried out using inverse variance weighted (IVW), MR Egger (ME), weighted median (WM), and multiplicative random effects-inverse variance weighted (MRE-IVW) methods. For sensitivity analysis and visualization of MR findings, a heterogeneity test, a pleiotropy test, a leave-one-out test, scatter plots, forest plots, and funnel plots were employed. RESULTS: MR analyses with all four methods revealed that CCOC was not causally associated with ER-negative BC (IVW results: odds ratio (OR) = 0.89, 95% confidence interval (CI) = 0.66-1.20, P = 0.431) or ER-positive BC (IVW results: OR = 0.99, 95% CI = 0.88-1.12, P = 0.901). F-statistics were computed for each valid IV, all of which exceeded 10. The stability and reliability of the results were confirmed by sensitivity analysis. CONCLUSIONS: Our findings indicated that CCOC dids not have a causal association with ER-associated BC. The absence of a definitive causal link between ER-associated BC and CCOC suggested a minimal true causal influence of ER-associated BC exposure factors on CCOC. These results indicated that individuals afflicted by ER-associated BC could alleviate concerns regarding the developing of CCOC, thereby aiding in preserving their mental well-being stability and optimizing the efficacy of primary disease treatment.