Prognostic MicroRNA Panel for HCV-Associated HCC: Integrating Computational Biology and Clinical Validation
Abstract BackgroundEarly detection of hepatocellular carcinoma (HCC) will reduce morbidity and mortality rates of this poorly diagnosed widely-spread disease. Dysregulation in microRNA (miRNAs) expression is associated with HCC progression. MethodsThe objective is to identify a panel of differentially expressed miRNAs (DE-miRNAs) to enhance HCC early prediction in hepatitis C virus (HCV) infected patients. Candidate miRNAs were selected using bioinformatic analysis of microarray and RNA-sequencing datasets, resulting in nine DE- miRNAs (miR-142, miR-150, miR-183, miR-199a, miR-215, miR-217, miR-224, miR-424 and miR-3607). Their expressions were validated in the serum of 44 healthy individuals, 62 non-cirrhotic HCV patients, 67 cirrhotic-HCV and 72 HCV-associated HCC patients using real time PCR (qPCR).ResultsThere was a significant increase in serum concentrations of the nine-candidate miRNAs in HCC and HCV patients relative to healthy individuals. MiR-424, miR-199a, miR-142, and miR-224 expressions were significantly altered in HCC compared to non-cirrhotic patients. While miR-199a and miR-183 showed differential expression in cirrhotic relative to non-cirrhotic patients. A panel of 5 miRNAs improved sensitivity and specificity of HCC detection to 100% and 95.12% relative to healthy controls. Distinguishing HCC from HCV-treated patients was achieved by 70.8% sensitivity and 61.9% specificity using the combined panel, compared to alpha-fetoprotein (51.4% sensitivity and 60.67% specificity).ConclusionMiR-142, miR-183, miR-199a, miR-224 and miR-424 novel panel could serve as non-invasive biomarker for HCC early prediction in chronic HCV patients.