Loss of TARBP2 Drives the Progression of Hepatocellular Carcinoma via miR-145-SERPINE1 Axis

RNA-binding proteins and exoribonucleases modulating miRNA in cancer: the enemy within

Recent progress in the investigation of microRNA (miRNA) biogenesis and the miRNA processing machinery has revealed previously unknown roles of posttranscriptional regulation in gene expression. The molecular mechanistic interplay between miRNAs and their regulatory factors, RNA-binding proteins (RBPs) and exoribonucleases, has been revealed to play a critical role in tumorigenesis. Moreover, recent studies have shown that the proliferation of hepatocellular carcinoma (HCC)-causing hepatitis C virus (HCV) is also characterized by close crosstalk of a multitude of host RBPs and exoribonucleases with miR-122 and its RNA genome, suggesting the importance of the mechanistic interplay among these factors during the proliferation of HCV. This review primarily aims to comprehensively describe the well-established roles and discuss the recently discovered understanding of miRNA regulators, RBPs and exoribonucleases, in relation to various cancers and the proliferation of a representative cancer-causing RNA virus, HCV. These have also opened the door to the emerging potential for treating cancers as well as HCV infection by targeting miRNAs or their respective cellular modulators.

Diagnostic role and immune correlates of programmed cell death-related genes in hepatocellular carcinoma

Programmed cell death (PCD) is thought to have multiple roles in tumors. Here, the roles of PCD-related genes were comprehensively analyzed to evaluate their values in hepatocellular carcinoma (HCC) diagnosis and prognosis. Gene expression and single-cell data of HCC patients, and PCD-related genes were collected from public databases. The diagnostic and prognostic roles of differentially expressed PCD-related genes in HCC were explored by univariate and multivariate Cox regression analyses. Single-cell data were further analyzed for the immune cells and expression of feature genes. Finally, we evaluated the expression of genes by quantitative real-time polymerase chain reaction and Western blot, and the proportion of immune cells was detected by flow cytometry in HCC samples. We obtained 52 differentially expressed PCD-related genes in HCC, based on which the consensus clustering analysis cluster 2 was found to have a worse prognosis than cluster 1. Then 10 feature genes were identified using LASSO analysis, and programmed cell death index (PCDI) was calculated to divided HCC patients into high-PCDI and low-PCDI groups. Worse prognosis was observed in high-PCDI group. Cox regression analysis showed that PCDI is an independent prognostic risk factor for HCC patients. Additionally, SERPINE1 and G6PD of feature genes significantly affect patient survival. Macrophages and Tregs were significantly positively correlated with PCDI. G6PD mainly expressed in macrophages, SERPINE1 mainly expressed in fibroblast. The experimental results confirmed the high expression of SERPINE1 and G6PD in HCC compared with the control, and the infiltration level of macrophages and Treg in HCC was also obviously elevated. PCDI may be a new predictor for the diagnosis of patients with HCC. The association of SERPINE1 and G6PD with the immune environment will provide new clues for HCC therapy.

An Inflammation-Associated Prognosis Model for Hepatocellular Carcinoma Based on Adenylate Uridylate- (AU-) Rich Element Genes

Hepatocellular carcinoma (HCC) is a typical inflammation-driven cancer and ranks sixth in the incidence rate worldwide. The role of adenylate uridylate- (AU-) rich element genes (AREGs) in HCC remains unclear. HCC-related datasets were acquired from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. Differentially expressed AREGs (DE-AREGs) between HCC samples and healthy controls were identified. The univariate Cox and LASSO analyses were performed to determine the prognostic genes. Furthermore, a signature and corresponding nomogram were configured for the clinical prediction of HCC. The potential signature-related biological significance was explored using functional and pathway enrichment analysis. Additionally, immune infiltration analysis was also performed. Finally, the expression of prognostic genes was verified using real-time quantitative polymerase chain reaction (RT-qPCR). A total of 189 DE-AREGs between normal and HCC samples were identified, wherein CENPA, TXNRD1, RABIF, UGT2B15, and SERPINE1 were selected to generate an AREG-related signature. Moreover, the prognostic accuracy of the AREG-related signature was also confirmed. Functional analysis indicated that the high-risk score was related to various functions and pathways. Inflammation and immune-related analyses indicated that the difference of T cell and B cell receptor abundance, microvascular endothelial cells (MVE), lymphatic endothelial cells (lye), pericytes, stromal cells, and the six immune checkpoints was statistically significant between the different risk groups. Similarly, RT-qPCR outcomes of these signature genes were also significant. In conclusion, an inflammation-associated signature based on five DE-AREGs was constructed, which could act as a prognostic indicator of patients with HCC.

Integrated analysis of multiple transcriptomic data identifies ST8SIA6‑AS1 and LINC01093 as potential biomarkers in HBV‑associated liver cancer

The mechanisms of long-non-coding RNAs (lncRNAs) in hepatitis B virus (HBV) infection-associated liver cancer remain largely unclear. Therefore, the aim of the present study was to investigate the regulatory mechanisms of lncRNAs in this disease. HBV-liver cancer related transcriptome expression profile data (GSE121248 and GSE55092) from the Gene Expression Omnibus database and survival prognosis information from The Cancer Genome Atlas (TCGA) database were obtained for analysis. The limma package was used to identify the overlapped differentially expressed RNAs (DERs), including DElncRNAs and DEmRNAs, in the GSE121248 and GSE55092 datasets. The screened optimized lncRNA signatures were used to develop a nomogram model based on the GSE121248 dataset, which was validated using the GSE55092 and TCGA datasets. A competitive endogenous RNA (ceRNA) network was constructed based on the screened prognosis-associated lncRNA signatures from TCGA dataset. In addition, the levels of specific lncRNAs were evaluated in HBV-infected human liver cancer tissues and cells, and Cell Counting Kit-8, ELISA and Transwell assays were performed to evaluate the effects of the lncRNAs in HBV-expressing liver cancer cells. A total of 535 overlapped DERs, including 30 DElncRNAs and 505 DEmRNAs, were identified in the GSE121248 and GSE55092 datasets. An optimized DElncRNA signature comprising 10 lncRNAs was used to establish a nomogram. ST8SIA6-AS1 and LINC01093 were identified as lncRNAs associated with HBV-liver cancer prognosis in TCGA dataset, and were applied to construct a ceRNA network. Reverse transcription-quantitative PCR analysis showed that ST8SIA6-AS1 was upregulated and LINC01093 was downregulated in HBV-infected human liver cancer tissues and HBV-expressing liver cancer cells compared with non-HBV-infected controls. ST8SIA6-AS1 knockdown and LINC01093 overexpression independently reduced the number of copies of HBV DNA, the levels of hepatitis B surface antigen and hepatitis B e antigen, as well as cell proliferation, migration and invasion. In summary, the present study identified ST8SIA6-AS1 and LINC01093 as two potential biomarkers that may be effective therapeutic targets for HBV-associated liver cancer.

The diagnostic and prognostic implications of PRKRA expression in HBV-related hepatocellular carcinoma

Background

Hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) accounts for more than half of total HCC patients in developing countries. Currently, HBV-related HCC diagnosis and prognosis still lack specific biomarkers. Here, we investigated if PRKRA expression in peripheral blood could be a potential biomarker for the diagnosis/prognosis of HBV-related HCC.

Methods

The expression of PRKRA in HBV-related HCC was firstly analyzed using TCGA and GEO databases. The results were confirmed in a validation cohort including 152 blood samples from 77 healthy controls and 75 HCC patients, 60 of which were infected with HBV. The potential diagnostic and prognostic values of PRKRA were also evaluated by the area under the receiver operator characteristic curve (AUROC) and Kaplan–Meier method, respectively.

Results

PRKRA was significantly upregulated in HCC patients, especially in those with HBV infections. In addition, the combination of PRKRA expression in peripheral blood with serum AFP and CEA levels displayed a better diagnostic performance (AUROC = 0.908, 95% CI 0.844–0.972; p < 0.001). Notably, when serum AFP is less than 200 ng/mL, PRKRA expression demonstrated better diagnostic capability. Furthermore, PRKRA expression levels were associated with expression of EIF2AK2 and inflammatory cytokine genes.

Conclusions

Triple combination testing of blood PRKRA expression, serum AFP and CEA levels could be a noninvasive strategy for diagnosis; and the elevation of PRKRA expression could predicate poor prognosis for HBV-related HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13027-022-00430-6.

Histone Deacetylase Inhibitor Trichostatin A Reduces Endothelial Cell Proliferation by Suppressing STAT5A-Related Gene Transcription

Inhibitors of histone deacetylases (HDACi) have shown promising effects in preclinical applications for the treatment of many diseases. Confusedly though, the effects of the HDACi trichostatin A (TSA) on angiogenesis are variable among different diseases. This study investigated the direct effects of TSA on endothelial cells, which plays essential roles in angiogenesis and the underlying molecular events. TSA reduced the viability of human umbilical vein endothelial cells (HUVECs), in which proliferation-related genes including BIRC5, CKS1B, and NDC80 were found to be involved. Furthermore, signal transducer and activator of transcription 5 A (STAT5A) was demonstrated to be reduced by TSA and to mediate TSA-induced downregulation of BIRC5, CKS1B, and NDC80 and HUVEC proliferation. Mechanistically, data showed that STAT5A directly bound to the promoters of BIRC5, CKS1B, and NDC80 and activated their transcription through special DNA sequence sites. Finally, the TSA–STAT5A–BIRC5, CKS1B, and NDC80 axis also worked in a cancerous endothelial cell angiogenesis model. The results of this study revealed novel mechanisms underlying the effects of TSA on endothelial cells and provided insights for angiogenesis-associated diseases.