Transcriptomic profiling and demographic analysis of Appalachian and non-Appalachian patients with pancreatic ductal adenocarcinoma using the Purity Independent Subtyping of Tumors Classifier.
Abstract
752 Background: Pancreatic ductal adenocarcinoma (PDAC) is a deadly malignancy with poor prognosis. A transcriptomic based algorithm called Purity Independent Subtyping of Tumors (PurIST) relies on expression profiling of a defined set of genes to stratify PDAC into classical and basal-like molecular subtypes. Though clinical trials are evaluating PurIST as a tool to guide chemotherapy clinical decisions, no study has investigated the utility of PurIST in the Appalachian population, which has many known health disparities. In this study, we apply PurIST to Appalachian and non-Appalachian patient cohorts and assess demographic variables between groups that may influence treatment outcomes. Methods: This 13-site study includes 780 PDAC patients via the Total Cancer Care protocol and was conducted via the Oncology Research Information Exchange Network (ORIEN) with Aster Insights. Patients were divided into two cohorts following the guidelines of the Appalachian Regional Commission and analyzed for differences in PurIST classification, tobacco use, alcohol use, and age at last contact. Results: Of the 780 PDAC patients assessed using PurIST, 562 (72.05%) were classical (497 strong classical; 165 Appalachian; 397 non-Appalachian), 63 (8.07%) were basal (22 strong basal; 13 Appalachian; 50 non-Appalachian), and 155 (19.87%) did not fall into a dichotomous subtype (59 Appalachian; 97 non-Appalachian). Significantly fewer individuals were able to be classified with PurIST in Appalachia (P=0.02321) and the Appalachian cohort trended toward increased classical subtype (P=0.1457). Appalachian patients were more likely to have a history of smoking (59.6% vs 49.9%; P=0.01756) and less likely to report alcohol consumption (50.5% vs 65.6%; P=0.000229). A trend toward more basal-like tumors was identified in advanced age individuals (P=0.02542; 20.5% in ages 85+ compared to 9.4% in individuals younger than 85), but it was not significant after statistical correction. Conclusions: We conducted the largest comparison of the PurIST algorithm in Appalachia to date and found increased expression of the classical subtype across all populations, with a trend toward higher classical and unclassifiable tumors within Appalachia. If PurIST is to be considered either as a prognostic or decision-making tool for PDAC patients, we must account for potential variability in different populations.
Article Details
Journal Info
Journal of Clinical Oncology
Lippincott Williams & Wilkins
Authors (16)
Chelsey Mckenna Williams
University of Kentucky - Markey Cancer Center, Lexington, KY
Reema Anil Patel
University of Kentucky, Lexington, KY
Michael J. Cavnar
Prakash Pandalai
Department of Surgery, University of Kentucky HealthCare, Lexington, KY
Emily Baiyee Toegel
University of Colorado Cancer Center, Denver, CO
Tiago Biachi de Castria
Memorial Sloan Kettering Cancer Center, New York, NY
Ashish Manne
The Ohio State University Comprehensive Cancer Center, Columbus, OH
Robert J. Rounbehler
Aster Insights, Hudson, FL
Patrick M. Boland
Rutgers Cancer Institute, New Brunswick, NJ
Carlos H.F. Chan
University of Iowa Holden Comprehensive Cancer Center, Iowa City, IA
Muneeb Rehman
Division of Hematology/Oncology, University of Virginia, Charlottesville, VA
Deepak Vadehra
Department of Medicine, Roswell Park Comprehensive Cancer Center , Buffalo, NY,
Dae Won Kim
H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
Michelle L. Churchman
Aster Insights, Hudson, FL
Derek B. Allison
Justin Miller