A plasma 9-microRNA signature for lung cancer early detection: a multicenter analysis.

Abstract

Lung cancer remains the leading cause of cancer-related deaths worldwide. Low-dose computed tomography (LD-CT) screening, combined with effective minimally invasive molecular testing such circulating microRNA, has the potential to reduce the burden of lung cancer. However, their clinical application requires further validation, including studies across diverse patient cohorts from different countries. In this study, we propose a signature of 9 circulating miRNAs derived from a robust multi-platform workflow with a multi-center design, for a total of 276 lung cancer and 451 non-cancer controls, based on the data from two European LD-CT screening cohorts (Poland and Italy). The classification performance of the signature was stable in the two screening cohorts, with AUC=0.78 (SE, 76%; SP, 67%; ACC=70%), and AUC=0.75 (SE, 82%; SP, 68%; ACC=71%) in the Polish and Italian cohorts, respectively. The diagnostic accuracy of the signature was remarkably independent of age, gender, smoking (status and intensity), nodule size, and density. Additionally, the signature demonstrated strong performance in detecting stage I lung cancer, with AUC=0.76 (95%CI: 0.68-0.84), and 0.69 (95%CI: 0.49-0.89) in the Polish and Italian cohorts respectively, with a prediction ability of 63-73%. The signature's ability to discriminate benign nodules was satisfactory, with AUC=0.71 (95%CI: 0.58-0.84). The proposed panel of 9 circulating miRNAs provides a robust and precise diagnostic tool to substantially advance the effectiveness of the LD-CT screening program.