Pancreatic ductal adenocarcinoma (PDAC) is the 3rd most lethal cancer in the United States disproportionately affects Black and African Americans (BAAs) with higher incidence and mortality. The American Cancer Society predicts that the number of deaths from pancreatic cancer in the state of Florida (4,280) will be second in the USA only to California (5,250). Acinar ductal metaplasia (ADM) is a key factor for disease progression. Benefiting from CaRE2, previous awardee’s laboratory results showed that the renin-angiotensin-aldosterone system (RAAS) as highly activated during ADM and suppressed during its reversal, with stronger effects in Hispanics than Caucasians or BAAs. Thus, RAAS inhibitors, antihypertensive medications, may reduce pancreatic cancer risk, which can be examined via epidemiological big data analyses. However, BAAs are less likely to receive these medications due to concerns about less prevention on stroke, and more side effects (i.e. cough and angioedema). Several genetic variants may further impact patients’ response to RAAS inhibitors (i.e., patients with CYP2C9*2 and *3 alleles may have higher risk on PDAC due to reduction on the efficacy of ARBs). Our overarching goal is to reduce pancreatic cancer incidence and address health disparities by: (1) assessing the real-world RAAS inhibitors’ association with new-onset pancreatic cancer by race, (2) evaluate modification by genetics affecting RAAS inhibitor efficacy. We will communicate results with community representatives and enhance patient education on RAAS inhibitor use. Randomized controlled trials would be ideal approach to address above hypothesis, yet such RCT is not feasible due to sample size, cost of genetic testing, and the requirement for a prolonged follow-up duration. Benefiting from the innovation and feasibility, epidemiological big data analyses together with patient engagement and dissemination hold the potential to be funded by major funding institute and yield substantial savings with minimal spending.
Given the integrated approaches of this study, the need for expertise in pharmacoepidemiology, cancer biology, genomics, machine learning, Big Data and racial disparity, the multiple PI model has been chosen with equal input expected from each of the four PIs. Most importantly, partnership will be strengthened through future monthly meetings, supplemented by ongoing communication via email, Zoom, and in-person discussions to address daily issues and review progress. Each PI will lead scientific directions aligned with their expertise—Dr. Jiao in epidemiological Big Data analyses, Drs. Rhie and Huang in cancer biology and genomics, and Dr. Ali in racial disparities and community engagement—while they will collaborate on study design. By explicitly focusing on why BAA patients have worse pancreatic cancer outcomes, our research aligns with NIH’s goals of reducing health disparities. Our hope is that this research will lead to tangible reductions in pancreatic cancer incidence and mortality in at-risk populations, moving the needle toward improved cancer outcomes.
If you share our interest in reducing cancer health disparities, please consider becoming a member of the CaRE² center. Investigators, trainees, community leaders, and advocates are welcome.
