A miRNA Combination as Promising Biomarker for Hepatocellular Carcinoma Diagnosis: A Study Based on Bioinformatics Analysis

Background: miRNAs dysregulate in hepatocellular carcinoma (HCC), showing promise for diagnostic biomarkers which may be found through exploration of differentially expressed miRNAs when comparing HCC and normal liver tissues. Materials and Methods: In the present research, candidate miRNAs were selected and verified using screening dataset GSE12717 and training dataset GSE10694, respectively. A miRNA combination was constructed using stepwise logistic regression analysis and validated using two datasets GSE74618 and TCGA. Target genes of miRNAs in the combination were obtained using a miRNA target gene prediction database. Functional analysis was conducted using an online tool DAVID. We also analyzed the mRNA-Seq data of project LIHC from TCGA to identify the hub target genes of the miRNAs. Results: A miRNA combination, which is composed of hsa-miR-221 and hsa-miR-29c was defined in this study. The miRNA combination is more effective in discriminating HCC patients from normal individuals than individual miRNAs. Additionally, the combined miRNAs showed a lower misdiagnosis rate than AFP in HCC diagnosis. In terms of the functional analysis, a total of 27 target genes of hsa-miR-221 and 96 target genes of hsa-miR-29c were obtained. Among which, INSIG1 was the common target of the two miRNAs. It was also found that both previously mentioned miRNAs played important roles in the regulation of transcription, cell proliferation, and involvement in cancer-related pathways. Lastly, 2 hub target genes of hsa-miR-221 and 16 hub target genes of hsa-miR-29c were obtained. Conclusion: We established a miRNA combination as a promising tool for HCC diagnosis, and the target genes we predicted provide possible points of penetration for researching these two miRNAs in HCC.