Platelet RNA yields a new diagnostic test for pancreatic cancer: a multicenter cohort

Abstract

Introduction: Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at advanced disease stages and invasive procedures are needed to confirm diagnosis. Innovative blood-based approaches are warranted to enable easier and earlier diagnosis. Platelet-derived RNA recently emerged as a new diagnostic biomarker in patients with lung cancer. The aim of this study was to evaluate specific platelet RNA profiles for patients with PDAC. Methods: Platelets of 135 PDAC patients (all disease stages), 250 age-matched healthy controls (HC) and 72 patients with benign pancreatobiliary disease were collected at four centers in Italy and the Netherlands. Samples were allocated to a training or validation cohort. After RNA isolation and amplification, Illumina sequencing was performed. Differential expression was tested by ANOVA-test. Sequentially, we performed swarm-enhanced classification to establish the most discriminating profiles between malignant and benign disease. Results: Patients with PDAC had significantly different platelet RNA profiles compared to HC (p-value < 0.0001). In the first validation cohort, the algorithm predicted PDAC from control groups with an accuracy of over 90%. Moreover, we classified early stage disease (stage I-IIa) correctly as PDAC and distinguished them from advanced and benign disease. Conclusions: There is an urgent need for minimally-invasive biomarkers to diagnose PDAC. Here we described our novel method to diagnose PDAC from platelet-derived RNA. This method showed robust differences between PDAC and control groups, even at early disease stages. Evaluation of premalignant lesions and treated patients is ongoing to prove its monitoring value and large-scale multicenter validation is warranted to facilitate implementation in the clinic.