A microRNA-based test improves endoscopic ultrasound-guided cytologic diagnosis of pancreatic cancer.

Background & Aims: Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) in combination with cytopathology is the optimal method for diagnosis and staging of pancreatic ductal adenocarcinoma (PDAC) and other pancreatic lesions. Its clinical utility, however, can be limited by high rates of indeterminate or false-negative results. We aimed to develop and validate a microRNA (miRNA)-based test to improve preoperative detection of PDAC.
Methods: Levels of miRNAs were analyzed in a centralized clinical laboratory by relative quantitative polymerase chain reaction in 95 formalin-fixed paraffin-embedded specimens and 228 samples collected by EUS-FNA during routine evaluations of patients with solid pancreatic masses at 4 institutions in the United States, 1 in Canada, and 1 in Poland.
Results: We developed a 5-miRNA expression classifier, consisting of MIR24, MIR130B, MIR135B, MIR148A, and MIR196, that could identify PDAC in well-characterized, formalin-fixed, paraffin-embedded specimens. Detection of PDAC in EUS-FNA samples increased from 78.8% by cytology analysis alone (95% confidence interval, 72.2%-84.5%) to 90.8% when combined with miRNA analysis (95% confidence interval, 85.6%-94.5%). The miRNA classifier correctly identified 22 additional true PDAC cases among 39 samples initially classified as benign, indeterminate, or nondiagnostic by cytology. Cytology and miRNA test results each were associated significantly with PDAC (P < .001), with positive predictive values greater than 99% (95% confidence interval, 96%-100%).
Conclusions: We developed and validated a 5-miRNA classifier that can accurately predict which preoperative pancreatic EUS-FNA specimens contain PDAC. This test might aid in the diagnosis of pancreatic cancer by reducing the number of FNAs without a definitive adenocarcinoma diagnosis, thereby reducing the number of repeat EUS-FNA procedures.
(Copyright © 2014 AGA Institute. Published by Elsevier Inc. All rights reserved.)