Obesity-associated adipokines correlate with survival in epithelial ovarian cancer

ObjectivesObesity impacts outcome in women with epithelial ovarian cancer (EOC), although its exact role and the molecular mechanisms remain poorly defined. Adipocytes secrete leptin and adiponectin, and the leptin to adiponectin (L:A) ratio is correlated with poor survival in other malignancies. We hypothesized that the L:A ratio is associated with survival in women with EOC.MethodsWe queried the institutional tumor registry for patients with advanced stage EOC and identified a cohort of 161 women with banked fasting prediagnostic serum samples. Patients underwent cytoredutive surgery followed by platinum-based chemotherapy. Sera were assayed for leptin and adiponectin, and clinico-pathologic data were abstracted. Standard statistical tests were performed.Results161 patients met inclusion criteria. We identified a significant correlation between BMI and leptin and the L:A ratio, but not adiponectin, in this cohort (r = 0.46, 0.46, and − 0.13, respectively; p = 0.001, 0.001, and 0.106). Women with low L:A ratios demonstrated statistically longer disease-specific survival (57 months) compared to those with median or high levels (49 and 37 months, respectively; p = 0.02). On multivariate analysis, we determined that BMI and age, but not L:A ratio, retained significance as independent prognostic factors for survival (p = 0.04, 0.004, and 0.895, respectively).ConclusionsIn this cohort, the L:A ratio correlated statistically with clinical outcome, but did not independently predict survival. Obesity remains a modifiable risk factor in women with EOC. Further studies are needed to determine if leptin and/or adiponectin may be potential therapeutic targets in obese women with EOC.

► We predict that the leptin to adiponectin (L:A) ratio correlates with survival in ovarian cancer.
► We retrospectively evaluated the association between serum L:A ratio and survival.
► A high L:A ratio correlated with poor clinical outcome, but did not independently predict survival.