Abstract
Background: Biomarkers are urgently needed for pancreatic ductal adenocarcinoma (PDAC). Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) is the cornerstone for diagnosing PDAC. We developed a method for discovery of PDAC biomarkers using the discarded EUS-FNA liquid.Methods: This retrospective study included 58 patients with suspected pancreatic lesions who underwent EUS-FNA. Protein extracts from EUS-FNA liquid were analyzed by mass spectrometry. Proteomic and clinical data were modeled by supervised statistical learning to identify protein markers and clinical variables that distinguish PDAC.Results: Statistical modeling revealed a protein signature for PDAC screening that achieved high sensitivity and specificity (0.92, 95 % confidence interval [CI] 0.79-0.98, and 0.85, 95 %CI 0.67-0.93, respectively). We also developed a protein signature score (PSS) to guide PDAC diagnosis. In combination with patient age, the PSS achieved 100 % certainty in correctly identifying PDAC patients > 54 years. In addition, 3 /4 inconclusive EUS-FNA biopsies were correctly identified using PSS.Conclusions: EUS-FNA-derived fluid is a rich source of PDAC proteins with biomarker potential. The PSS requires further validation and verification of the feasibility of measuring these proteins in patient sera.