Biomarker Panels Associated with Diagnosis and Overall Survival in Hepatocellular Carcinoma Revealed from Protein-Protein and mRNA-miRNA Interaction Networks.

Abstract

Background: Hepatocellular carcinoma (HCC), the most common form of liver cancer, has a significant mortality rate, largely due to late diagnosis. Recent advances in medical research have demonstrated the potential of biomarkers for early detection. Moreover, the discovery and use of prognostic biomarkers offer a ray of hope in the fight against liver cancer.

Methods: Three gene transcript collections (GSE57957, GSE76427, and GSE84402) were retrieved from the GEO database, and significantly expressed genes were identified through a comprehensive screening process. Subsequently, key potential biomarkers were identified using various methods, including functional pathway enrichment, protein-protein interaction network analysis, mRNA-miR interaction study, and ROC curve and survival analysis.

Results: After analyzing the expression of hub proteins and miRs, 12 proteins were found to have AUC values greater than 0.9 and log-rank KM-plot p values less than 0.05. Therefore, these proteins can be considered as potential diagnostic and prognostic biomarkers. Among these proteins, the top 5 were CDC6, PTTG1, CDCA5, RACGAP1, and RAD51AP1. The microRNAs with the highest diagnostic significance (AUC≥0.8) were hsa-mir-101-3p, hsa-mir-195-5p, hsa-mir-130a-3p, hsa-mir-26b-5p, hsa-mir-29c-3p, hsa-mir-26a-5p, and hsa-mir-34a-5p. Notably, hsa-mir-34a-5p, hsa-mir-195-5p, and hsa-mir-130a-3p also showed prognostic potential as predictors of overall survival in HCC patients.

Conclusion: Harnessing the potential of these biomarkers will enable healthcare professionals to make informed decisions, leading to improved care and more favorable outcomes in the fight against HCC. However, the next step is to thoroughly validate these potential markers in large cohorts.