Psychosocial Stress, Vaginal Microbiome, and Ovarian Cancer: An Integrative Framework

Duke University, Durham NC

Investigators

Abstract

Despite therapeutic advances, ovarian cancer (OC) remains the most lethal gynecological malignancy with a 51% five-year survival rate. Advanced-stage disease presentation is a critical determinant of poor outcomes, yet the biological mechanisms underlying heterogeneity in OC outcomes remain poorly understood. Emerging evidence suggests that psychosocial stress (PSS) may contribute to ovarian tumorigenesis and progression through inflammatory pathways. Recent research indicates that PSS may lead to vaginal microbiome dysregulation (dysbiosis), which has been associated with increased OC risk and advanced-stage disease. However, no studies have examined the full pathway between PSS, vaginal dysbiosis, and advanced-stage OC. This research will test the central hypothesis that multi-dimensional PSS leads to vaginal dysbiosis, contributing to advanced-stage OC and poorer survival outcomes. We will utilize the NIH-supported ORCHiD study, comprising newly diagnosed OC patients across nine US states with comprehensive psychosocial measures and vaginal microbiome data. We will develop an Integrated Psychosocial Stress Index (IPSI) that incorporates individual stress measures and neighborhood-level stressors. Our preliminary findings from 132 participants demonstrate distinct vaginal microbiome profiles associated with clinical cancer stage and independent associations between PSS measures and advanced-stage OC. Aim 1 will develop and validate the IPSI and evaluate its relationship with vaginal dysbiosis. Aim 2 will examine whether vaginal dysbiosis mediates the relationship between multi-dimensional PSS and advanced-stage OC. Aim 3 will determine the association between multi-dimensional PSS and OC survival, evaluating dysbiosis as a potential mediator. This integrative framework will elucidate novel biological mechanisms underlying OC progression and survival, informing targeted clinical interventions. By identifying modifiable biological and psychosocial risk factors, this research will advance understanding of the stress-microbiome-cancer axis and identify potential therapeutic targets. Training will include cancer epidemiology, biostatistics/bioinformatics, and microbiome methods, preparing me for independent translational molecular epidemiology research focused on improving cancer outcomes through mechanistic understanding.