Identification of Novel Immune-infiltration Related miRNAs that can Predict the Prognosis of Patients with Hepatocellular Carcinoma

Background: Although immune checkpoint inhibitors (ICIs) have achieved important breakthroughs in the treatment of liver cancer, most hepatocellular carcinoma (HCC) patients do not respond to ICIs, and their clinical outcome remains unsatisfactory. The tumor microenvironment (TME), which contains immune cells and other molecules, probably influences both the prognosis and the response to immunotherapy in HCC. Here, using integrated bioinformatics analyses, we identified key molecules (immune cells and immune-related microRNAs (miRNAs)) as potential prognostic markers for HCC. Method: MRNA and miRNA expression profiles and clinicopathological data were extracted from the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) data collection. A total of 22 immune cell types from HCC patients were assessed using a deconvolution algorithm (known as CIBERSORT). Both Kaplan-Meier analysis and Cox proportional hazards regression were used to evaluate the prognostic value of the immunocytes. The correlations between differentially expressed miRNAs and tumor-infiltrating immune cells were investigated using the Pearson correlation coefficient. Machine learning approaches were employed to identify prognostic miRNAs. The miRTarBase database was used to construct a DEmiRNA-target gene network. Function enrichment analyses were performed using Metascape software. The relationships between two specific miRNAs and the expression of immune markers (antigen presenting machinery (APM) and tumor-infiltrating lymphocytes (TILs)) as well as cell checkpoint markers were also analyzed. Results: : A total of 19 T regulatory cell (Treg)-related miRNAs were identified by machine learning approaches ( p 0.2). Metascape revealed that Treg-related miRNA-target networks were significantly enriched in biological processes including cellular responses to stress, mitotic cell cycle and myeloid cell differentiation. Using univariate Cox regression analysis on an independent dataset, GSE31384, 19 miRNAs were evaluated for their importance in overall survival (OS). Two hub miRNAs (hsa-miR-877 and hsa-miR-137) were found to significantly impact on OS. Therefore, we assessed the association between these two miRNAs and immune markers (APM, TILs) and cell checkpoint markers (programmed cell death-1 (PD-1), programmed death-ligand 1 (PD-L1), cytotoxic T-lymphocyte antigen-4 (CTLA-4), B- and T-lymphocyte attenuator (BTLA)), and found statistically significant associations in both the TCGA and GSE31384 datasets. Conclusion: Our study showed that hsa-miR-877 and hsa-miR-137 were significantly associated with poor prognosis in HCC through their effects on Tregs and immune checkpoint markers in the TME. These results suggest that hsa-miR-877 and hsa-miR-137 might serve as novel therapeutic targets for HCC.