Non-coding RNA and hepatitis B virus-related hepatocellular carcinoma: A bibliometric analysis and systematic review

An In-Depth Approach to the Associations between MicroRNAs and Viral Load in Patients with Chronic Hepatitis B-A Systematic Review and Meta-Analysis

Scientists study the molecular activities of the hepatitis B virus (HBV). However, in vivo experiments are scarce. Some microRNAs are HBV-related, but their exact mechanisms are unknown. Our study provides an up-to-date view of the associations between microRNAs and HBV-DNA levels in chronically infected individuals. We conducted this large-scale research on five databases according to PRISMA guidance. Joanna Briggs Institute tools and Newcastle Ottawa Quality Assessment scores helped with quality evaluations. R 4.2.2 performed statistical computations for the meta-analysis. DIANA-microT 2023 and g:Profiler enriched the predictions of liver genes associated with miR-122 and miR-192-5p. From the 1313 records, we eliminated those irrelevant to our theme, non-article methodologies, non-English entries, and duplicates. We assessed associations between microRNAs and HBV-DNA levels. Overall, the pooled correlations favoured the general idea of the connection between non-coding molecules and viremia levels. MiR-122 and miR-192-5p were the most researched microRNAs, significantly associated with HBV-DNA levels. The connections between miR-122, miR-192-5p, let-7, miR-215, miR-320, and viral loads need further in vivo assessment. To conclude, this study evaluates systematically, for the first time, the correlations between non-coding molecules and viremia levels in patients. Our meta-analysis emphasizes potentially important pathways toward new inhibitors of the viral replication cycle.

The oncogenic role of hepatitis B virus X gene in hepatocarcinogenesis: recent updates

Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancers with high mortality rate. Among its various etiological factors, one of the major risk factors for HCC is a chronic infection of hepatitis B virus (HBV). HBV X protein (HBx) has been identified to play an important role in the HBV-induced HCC pathogenesis since it may interfere with several key regulators of many cellular processes. HBx localization within the cells may be beneficial to HBx multiple functions at different phases of HBV infection and associated hepatocarcinogenesis. HBx as a regulatory protein modulates cellular transcription, molecular signal transduction, cell cycle, apoptosis, autophagy, protein degradation pathways, and host genetic stability via interaction with various factors, including its association with various non-coding RNAs. A better understanding on the regulatory mechanism of HBx on various characteristics of HCC would provide an overall picture of HBV-associated HCC. This article addresses recent data on HBx role in the HBV-associated hepatocarcinogenesis.

Hepatitis B Virus and microRNAs: A Bioinformatics Approach

In recent decades, microRNAs (miRNAs) have emerged as key regulators of gene expression, and the identification of viral miRNAs (v-miRNAs) within some viruses, including hepatitis B virus (HBV), has attracted significant attention. HBV infections often progress to chronic states (CHB) and may induce fibrosis/cirrhosis and hepatocellular carcinoma (HCC). The presence of HBV can dysregulate host miRNA expression, influencing several biological pathways, such as apoptosis, innate and immune response, viral replication, and pathogenesis. Consequently, miRNAs are considered a promising biomarker for diagnostic, prognostic, and treatment response. The dynamics of miRNAs during HBV infection are multifaceted, influenced by host variability and miRNA interactions. Given the ability of miRNAs to target multiple messenger RNA (mRNA), understanding the viral-host (human) interplay is complex but essential to develop novel clinical applications. Therefore, bioinformatics can help to analyze, identify, and interpret a vast amount of miRNA data. This review explores the bioinformatics tools available for viral and host miRNA research. Moreover, we introduce a brief overview focusing on the role of miRNAs during HBV infection. In this way, this review aims to help the selection of the most appropriate bioinformatics tools based on requirements and research goals.

Prognostic value and immune landscapes of immunogenic cell death-related lncRNAs in hepatocellular carcinoma

BACKGROUND

Both immunogenic cell death (ICD) and long noncoding RNAs (lncRNAs) are strongly associated with tumor development, but the mechanism of action of ICD-associated lncRNAs in hepatocellular carcinoma (HCC) remains unclear.

METHODS

We collected data from 365 HCC patients from The Cancer Genome Atlas (TCGA) database. We formulated a prognostic signature of ICD-associated lncRNAs and a nomogram to predict prognosis. To explore the potential mechanisms and provide clinical guidance, survival analysis, enrichment analysis, tumor microenvironment analysis, tumor mutation burden (TMB), and drug sensitivity prediction were conducted based on the subgroups obtained from the risk score.

RESULTS

A prognostic signature of seven ICD-associated lncRNAs was constructed. Kaplan-Meier (K-M) survival curves showed a more unfavorable outcome in high-risk patients. The nomogram had a higher predictive value than the nomogram constructed without the risk model. Enrichment analysis confirmed that risk lncRNAs were closely associated with cell proliferation and mitosis. Most of the immune checkpoints currently used in therapy (e.g., PDCD1 and CTLA4) appeared to be elevated in high-risk patients. Tumor microenvironment analysis showed differential expression of lymphocytes (including natural killer cells, regulatory T cells, etc.) in the high-risk group. TMB had a higher incidence of mutations in the high-risk group (P=0.004). Chemotherapy drug sensitivity prediction provides effective guidelines for individual therapy. RT-qPCR of human HCC tissues verified the accuracy of the model.

CONCLUSION

We constructed an effective prognostic signature for patients with HCC using seven ICD-lncRNAs, which provides guidance for the prognostic assessment and personalized treatment of patients.

Rubella Virus Infections: A Bibliometric Analysis of the Scientific Literature from 2000 to 2021

Rubella virus (RuV) generally causes a mild infection, but it can sometimes lead to systemic abnormalities. This study aimed to conduct a bibliometric analysis of over two decades of RuV research. Medical studies published from 2000 to 2021 were analyzed to gain insights into and identify research trends and outputs in RuV. R and VOSviewer were used to conduct a bibliometric investigation to determine the globally indexed RuV research output. The Dimensions database was searched with RuV selected as the subject, and 2500 published documents from the preceding two decades were reviewed. The number of publications on RuV has increased since 2003, reaching its peak in 2020. There were 12,072 authors and 16,769 author appearances; 88 publications were single-authored and 11,984 were multi-authored. The United States was the most influential contributor to RuV research, in terms of publications and author numbers. The number of RuV-related articles has continued to increase over the past few years due to the significant rubella burden in low-income nations. This study will aid in formulating plans and policies to control and prevent RuV infections.