A Novel Gene Pair CSTF2/DPE2A Impacts Prognosis and Cell Cycle of Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC), one of the commonest cancers at present, possesses elevated mortality. This study explored the predictive value of CSTF2/PDE2A for HCC prognosis. Methods: In this study, clinical information and RNA sequencing expression profiles of HCC patients were acquired from common databases. Kaplan-Meier curve compound with time-dependent ROC curve, nomogram model, and univariate/multivariate Cox analysis were carried out to access the prediction capacity of CSTF2/PDE2A. The immune status, tumor microenvironment, drug sensitivity, biological function and pathway between HCC and adjacent non-tumorous tissue were analyzed and compared. Finally, RT-qPCR, Western blot, and apoptosis assays were performed to verify the effect on HCC cells of CSTF2/PDE2A. Results: The optimal cut-off value of CSTF2, PDE2A and CSTF2/PDE2A was 6.95, 0.95 and 3.63, respectively. In TCGA and ICGC cohorts, the high group of CSTF2/PDE2A presented higher OS compared to low group. The area under the curve (AUC) for OS at 1-, 2-, and 3-years predicted by CSTF2/PDE2A were 0.731/0.695, 0.713/0.732 and 0.689/0.755, higher than the counterparts of the single gene CSTF2 and PDE2A. Multivariate Cox analysis revealed that CSTF2/PDE2A (HR = 1.860/3.236, 95% CI = 1.265-2.733/1.575-6.645) was an independent prognostic factor for HCC. The OS nomogram model created according to five independent factors including CSTF2/PDE2A showed excellent capacity for HCC prognosis. Furthermore, the immune status of the CSTF2/PDE2A high group was deleted, cell cycle-related genes and chemotherapy resistance were increased. Finally, cell experiments revealed distinct differences in the proliferation, apoptosis, protein and mRNA expression of HCC cells after si-CSTF2 transfection compared with the negative control. Conclusion: Taken together, the gene pair CSTF2/PDE2A is able to forecast the prognosis of HCC and regulates cell cycle, which is promising as a novel prognostic predictor of HCC.

TUG1 protects against ferroptosis of hepatic stellate cells by upregulating PDK4-mediated glycolysis.

The induction of ferroptosis in hepatic stellate cells (HSCs) has shown promise in reversing liver fibrosis. And ferroptosis has been confirmed to be associated with glycolysis. The objective of this study is to determine whether ferroptosis inhibition in HSCs, induced by elevation of recombinant pyruvate dehydrogenase kinase isozyme 4 (PDK4)-mediated glycolysis, could mediate the pathogenesis of liver fibrosis. Liver fibrosis was induced using CCl4, the level of which was assessed through histochemical staining. Lentivirus was used to modulate the expression of specific genes. And underlying mechanisms were explored using primary HSCs extracted from normal mice. The results confirmed that Taurine up-regulated gene 1 (TUG1) expression was upregulated in liver fibrotic tissues and HSCs, showing a positive correlation with fibrosis. In addition, TUG1 attenuated ferroptosis in HSCs by promoting PDK4-mediated glycolysis, thereby promoting the progression of liver fibrosis. Moreover, TUG1 was observed to impact HSCs activation, exacerbating liver fibrosis to some extent. In conclusion, our study revealed that TUG1 expression was elevated in mouse models of liver fibrosis and activated HSCs, which inhibited ferroptosis in HSCs through PDK4-mediated glycolysis. This finding may open up a new therapeutic strategy for liver fibrosis.

Characterization of neutrophil extracellular traps related gene pair for predicting prognosis in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a malignant disease with a high incidence rate, high mortality and poor prognosis. Neutrophil extracellular traps (NETs), as an extracellular reticular structure, promote the development and progression of cancer in the tumor microenvironment, and have a promising prospect as a prognostic indicator. In the present study, we elucidated the prognostic value of NET-related genes. METHODS: The NETs gene pair of The Cancer Genome Atlas cohort was constructed by least absolute shrinkage and selection operator analysis. Samples from the International Cancer Genome Consortium were performed to verify its feasibility. Kaplan-Meier analysis was used to compare the overall survival (OS) rate of the two subgroups. The independent predictors of OS were determined by univariate and multivariate Cox analysis. Furthermore, Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes pathway were analyzed by gene set enrichment analysis. The single sample gene set enrichment analysis method was performed to deplore the relationship of risk score with tumor immune microenvironment. The GSE149614 dataset was applied as single cell RNA level validation. PCR was performed to the detect mRNA expression profiles of NETs-related genes. RESULTS: Our analysis of the NETs-related model provides a promising prospect as a prognostic indicator. The OS of high-risk group patients was significantly reduced. The risk score was an important independent predictor of HCC prognosis. The Nomogram model suggested a favorable classification performance. The drug resistance and sensitivity of tumor cells to chemotherapeutics was significantly correlated with the prognostic gene expression. The immune status of the two risk groups showed a marked difference. CONCLUSIONS: The novel prognostic gene pair and immune landscape could predict the prognosis of HCC patients and provide a new understanding of immunotherapy in HCC.