LINC00624 affects hepatocellular carcinoma proliferation and apoptosis through the miR-342-3p/DNAJC5 axis.

LINC00624 is a long noncoding RNA (lncRNA) which was seldom investigated before. The goal of our study is to clarify the expression and underlying network of LINC00624 in hepatocellular carcinoma (HCC). Here, both HCC and normal living cell lines were employed. Real-time quantitative PCR and western blot were used to determine the pattern of genes and proteins. Colony formation, flow cytometry and western blot tests were used to determine cell proliferation and apoptosis, respectively. Dual luciferase was used to verify molecule-molecule interactions. LINC00624 expression was increased in HCC cell lines and miR-342-3p was decreased. Elimination of LINC00624 increased proliferation while decreasing cell apoptosis. LINC00624 acted as a molecular sponge for miR-342-3p, hence facilitating DNAJC5 expression. Functional tests demonstrated that miR-342-3p suppression could reverse the effect of LINC00624 silence and overexpression of DNAJC5 significantly mitigated the biological consequences of miR-342-3p. These finding demonstrated that LINC00624 aggravated HCC progression by modulating proliferation and apoptosis via targeting miR-342-3p/DNAJC5 axis. These data support that inhibition of LINC00624 may a potential treatment strategies of HCC.

The construction of a prognostic model by apoptosis-related genes to predict survival, immune landscape, and medication in cholangiocarcinoma.

BACKGROUND: Cholangiocarcinoma (CCA) is a highly aggressive and invasive malignant tumor of the bile duct, with a poor prognosis and a high mortality rate. Currently, there is a lack of effective targeted treatment methods and reliable biomarkers for prognosis. METHODS: We downloaded RNA-seq and clinical data of CCA from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases as training and test sets. The apoptosis-related genes were obtained from the Molecular Signatures Database (MsigDB) database. We used univariate/multivariate Cox regression and Lasso regression analyses to construct a riskscore prognostic model. Based on the median riskscore, we clustered the patients into high-risk (HR) and low-risk (LR) groups. We carried out Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of differentially expressed genes (DEGs) in HR and LR groups. The single sample gene set enrichment analysis (ssGSEA) was employed to analyze the immune infiltration of the HR and LR groups. The CellMiner database was utilized to predict drugs and perform molecular docking on drugs and target proteins. RESULTS: We identified 8 genes with prognostic significance to construct a prognostic model. Results of GO and KEGG demonstrated that DEGs were mainly enriched in biological functions such as fatty acid metabolic processes and pathways such as the cAMP signaling pathway. Results of ssGSEA uncovered that immune cells such as DCs and Macrophages in the HR group, as well as immune functions such as Check-point and Parainflammation, were considerably higher than those in the LR group. Drug sensitivity prediction and results of molecular docking revealed that Rigosertib targeted the prognostic genes MAP3K1. HYPOTHEMYCIN and AMG900 effectively targeted JUN. CONCLUSION: Our project suggested that the prognostic model with apoptotic features can effectively predict prognosis in CCA patients, proffering prognostic biomarkers and potential therapeutic targets for CCA patients.