Multi-omic Predictive Markers for Ovarian Cancer Therapy Response and Outcomes - Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy, with more than 20,000 newly- diagnosed cases and over 13,000 deaths in the United States each year. Unfortunately, there has been little change in survival since platinum-based therapies were introduced over 30 years ago. Because the search for newer, more effective agents has not been fruitful, aggressive surgery plus platinum-based chemotherapy remains the standard first-line treatment of the disease. However, individual response to platinum therapy is highly variable and unpredictable. Eventually, most women develop and succumb to platinum-resistant disease. No way exists to identify who will respond poorly to platinum-based therapy; nor are there any clinically-validated interventions to improve therapy response. Biomarkers that can predict therapy response, provide an early indication of efficacy, support patient treatment stratification, and suggest interventions to improve therapy response and survival are urgently needed. Basic cancer research discoveries in EOC and other solid tumors suggest that gut bacteria impact how a woman responds to platinum-based therapy by influencing the local tumor microenvironment (TME). Thus, gut bacteria may serve as predictive biomarkers of therapy response and outcome. However, there have been no human studies of gut bacteria and EOC therapy response, nor on the interactions among gut bacteria, TME immunity, and treatment response and outcome. Our preliminary findings in women with newly-diagnosed EOC support the animal model data. Backed by the laboratory research data and based on our preliminary findings in an EOC population, we propose to develop predictive microbiome-based biomarkers that will lead to better patient stratification. In Aim 1, we will assess the gut microbiome and systemic metabolome in 104 newly diagnosed EOC cases to identify gut bacteria predictive of response and outcome to platinum-based therapy. In Aim 2 we will use immune-profiling assays to assess TME immune infiltrates and immune gene expression in our cohort. We will then use the high- dimensional genomic, metabolomic and transcriptomic data generated from Aims 1 and 2 to identify favorable and unfavorable gut microbiomes associated with therapy response, outcomes, and local tumor immunity. We will also identify gut bacteria that can serve as intervention targets to improve therapy efficacy or block cancer progression. Our team will then be well positioned to conduct human trials to assess the effects of altering gut bacteria composition on EOC outcomes. We will also be well positioned to pursue mechanistic studies to illuminate how gut bacteria impact therapy response and outcome, thus further identifying treatment targets. This proposal uses existing biospecimens from previously-funded NCI projects together with clinical annotating data to generate high-dimensional, multi-omic data in order to develop predictive and prognostic biomarkers for patient selection or stratification.
