Detection of circulating exosomal miR-17-5p serves as a novel non-invasive diagnostic marker for non-small cell lung cancer patients.

Journal: Pathology, Research And Practice
Published:
Abstract

Exosome-shuttled bioactive miRNAs act as novel non-invasive biomarkers for cancer diagnosis have received increasing attention. In this study, we aimed to investigate the expression signatures of exosomal miRNAs and develop a serum exosome-derived miRNA panel for diagnosis of non-small cell lung cancer (NSCLC). The miR-17-92 cluster including 6 miRNAs (miR-17-5p, miR-18a-5p, miR-19a-3p, miR-19b-1-5p, miR-20a-5p and miR-92a-1-5p) was selected as potential diagnostic candidate molecule. Then, expression profiles of the candidate miRNAs were firstly analyzed in 43 pairs of serum samples from the training set by quantitative real-time PCR, and the dysregulated miRNA along with three tumor markers (carcinoembryonic antigen, CEA; cytokeratin 19 fragment, CYFRA21-1; squamous cell carcinoma antigen, SCCA) were further validated in two independent cohorts, which consisted of training set (including 100 NSCLC patients and 90 healthy controls) and validation set (including 72 NSCLC patients and 47 healthy controls). The expression of miR-17-5p was significantly up-regulated in NSCLC patients compared with the healthy controls (P < 0.001), suggesting that miR-17-5p might have considerable clinical value in the diagnosis of NSCLC. Based on the data from the training set, we next used a logistic regression model to construct a 4-molecule panel consisting of miR-17-5p and three tumor markers for NSCLC diagnosis. The performance of such 4-molecule panel was verified with an area under the ROC curve of 0.860 (95% CI = 0.802 to 0.906, sensitivity = 63.0% and specificity = 93.3%) and 0.844 (95% CI = 0.766 to 0.904, sensitivity = 76.4% and specificity = 76.6%) in the training set and validation set, respectively. In conclusion, the newly developed diagnostic panel consisting of exosomal miR-17-5p, CEA, CYFRA21-1 and SCCA may have considerable clinical value in the diagnosis of NSCLC.

Authors
Yi Zhang, Yingmei Zhang, Yunhong Yin, Shuhai Li