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.