Abstract 1074: Plasma EV profiling facilitates low abundance biomarker discovery in pancreatic cancer

Abstract

Abstract The lack of reliable biomarkers for early detection of pancreatic ductal adenocarcinoma (PDAC) results in poor prognosis due to advanced disease at diagnosis. Biopsies for pancreatic cancer are known to be particularly difficult to perform because of the location of the pancreas and low volume of primary tumors that metastasize aggressively. Currently, there is no blood test or other screening modality in use, for stratification of individuals with higher-than-average risk (5-8-fold) of developing PDAC in their lifetime. Given this existing void in the US and worldwide, an FDA-compliant, minimally invasive, quantitative biomarker test for the early detection of PDAC would be critical for screening subpopulations with, a) inherent genetic or familial predisposition; history of chronic pancreatitis; c) precursor lesions of pancreas; and d) older patients (>50 years) with new onset diabetes or sudden weight loss. Extracellular vesicles (EVs) are shed by normal and cancer cells and carry a rich molecular cargo that can be leveraged for biomarker discovery. Whereas molecular profiling of bio-fluids poses intrinsic limitations for detection of low abundant, disease-specific biomarkers due to matrix effects; EVs, on the other hand, offer promise as a robust and minimally invasive biomarker resource. Mass spectrometry data were developed in our laboratory, based on multi-omics (proteomics, lipidomics and metabolomics) analyses of plasma EVs derived from patients diagnosed with early-stage PC (N=60), pancreatitis (N=39), precursor lesions of pancreas (N=45) as well as normal controls (N=50). These clinically annotated samples were made available by the Georgetown University Medical Center (GUMC) repository. Feature selection using a training-validation design allowed the development of a multiplexed biomarker panel comprising of 12-analytes (5-lipids, 2-metabolites and 5-proteins) that can robustly stratify early-stage PC from normal controls with high accuracy (AUC>95%). Availability of a FDA compliant, multi-analyte-based classification algorithm that can stratify patients with precursor lesions of the pancreas that are at potential risk of progression to PC with > 90% specificity and sensitivity is a critical clinical need. Refinement of panel to improve positive predictive value as well as identification of markers predictive of progression of precursor lesions to malignant transformation is ongoing. Citation Format: Shivani Bansal, Shu Wang, Yaoxiang Li, Sunil Bansal, Jill Smith, John B. Tyburski, Keith Unger, Amrita Cheema. Plasma EV profiling facilitates low abundance biomarker discovery in pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1074.