The PCNA pseudogenes in the human genome

CRISPR/Cas9 as a New Antiviral Strategy for Treating Hepatitis Viral Infections

Hepatitis is an inflammatory liver disease primarily caused by hepatitis A (HAV), B (HBV), C (HCV), D (HDV), and E (HEV) viruses. The chronic forms of hepatitis resulting from HBV and HCV infections can progress to cirrhosis or hepatocellular carcinoma (HCC), while acute hepatitis can lead to acute liver failure, sometimes resulting in fatality. Viral hepatitis was responsible for over 1 million reported deaths annually. The treatment of hepatitis caused by viral infections currently involves the use of interferon-α (IFN-α), nucleoside inhibitors, and reverse transcriptase inhibitors (for HBV). However, these methods do not always lead to a complete cure for viral infections, and chronic forms of the disease pose significant treatment challenges. These facts underscore the urgent need to explore novel drug developments for the treatment of viral hepatitis. The discovery of the CRISPR/Cas9 system and the subsequent development of various modifications of this system have represented a groundbreaking advance in the quest for innovative strategies in the treatment of viral infections. This technology enables the targeted disruption of specific regions of the genome of infectious agents or the direct manipulation of cellular factors involved in viral replication by introducing a double-strand DNA break, which is targeted by guide RNA (spacer). This review provides a comprehensive summary of our current knowledge regarding the application of the CRISPR/Cas system in the regulation of viral infections caused by HAV, HBV, and HCV. It also highlights new strategies for drug development aimed at addressing both acute and chronic forms of viral hepatitis.

The interplay of long noncoding RNAs and hepatitis B virus

Hepatitis B Virus (HBV) infections remain a major global health burden with an estimated 296 million people living with a chronic infection and 884,000 HBV-related deaths annually. Notably, patients with a chronic hepatitis B (CHB) infection are at a 30-fold greater risk of developing hepatocellular carcinoma (HCC), the most common type of primary liver cancer, which is the 3rd deadliest cancer worldwide. Several groups have assessed HBV-related aberrant expression of host-cell long noncoding RNAs (lncRNAs) and how altered expression of specific lncRNAs affects HBV replication and progression to associated disease states. Given the challenges in establishing effective HBV models and analyzing transcriptomic data, this review focuses on lncRNA expression data primarily collected from clinical patient samples and primary human hepatocytes, with the subsequent mechanism of action analysis in cell lines or other model systems. Ultimately, understanding HBV-induced lncRNA-expression dysregulation could lead to new treatments and biomarkers for HBV infection and its associated diseases.

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

Objectives

A bibliometric analysis for non-coding RNA and hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) was performed to describe international research status and visualize the research scope and emerging trends over the last two decades on this topic.

Materials and methods

Research data of non-coding RNA and HBV-related HCC were retrieved and extracted from the Web of Science Core Collection (WoSCC) database from 1 January 2003 to 13 June 2022 and then analyzed by means of bibliometric methods. A total of 1,036 articles published in this field were assessed for specific characteristics, including the year of publication, journal, author, institution, country/region, references, and keywords. VOSviewer was employed to perform co-authorship, co-occurrence, and co-citation analyses accompanied by constructing a visual network.

Results

Overall, 1,036 reports on non-coding RNA and HBV-related HCC from 2003 to 2022 were retrieved from WoSCC. The publication has gradually increased during the last two decades with 324 journals involved. Most research records (748 publications and 23,184 citations) were concentrated in China. A co-occurrence cluster analysis for the top 100 keywords was performed and four clusters were generated: (1) non-coding RNA as a molecular marker for the diagnosis and prognosis of HBV-related HCC; (2) dysregulation of non-coding RNA by hepatitis B virus X protein (HBx); (3) non-coding RNA affecting the biological behaviors of HBV-related HCC; and (4) epidemiological study for the effects of non-coding RNA on the risk of HBV-related HCC.

Conclusion

The publications and citations involved in non-coding RNA and HBV-related HCC have increased over the last two decades associated with many countries, institutions, and authors. Our study revealed current development trends, global cooperation models, basic knowledge, research hotspots, and emerging frontiers in this field.

Diversity of Dysregulated Long Non-Coding RNAs in HBV-Related Hepatocellular Carcinoma

Infection with the hepatitis B virus (HBV) continues to pose a major threat to public health as approximately 292 million people worldwide are currently living with the chronic form of the disease, for which treatment is non-curative. Chronic HBV infections often progress to hepatocellular carcinoma (HCC) which is one of the world’s leading causes of cancer-related deaths. Although the process of hepatocarcinogenesis is multifaceted and has yet to be fully elucidated, several studies have implicated numerous long non-coding RNAs (lncRNAs) as contributors to the development of HCC. These host-derived lncRNAs, which are often dysregulated as a consequence of viral infection, have been shown to function as signals, decoys, guides, or scaffolds, to modulate gene expression at epigenetic, transcriptional, post-transcriptional and even post-translational levels. These lncRNAs mainly function to promote HBV replication and oncogene expression or downregulate tumor suppressors. Very few lncRNAs are known to suppress tumorigenesis and these are often downregulated in HCC. In this review, we describe the mechanisms by which lncRNA dysregulation in HBV-related HCC promotes tumorigenesis and cancer progression.

The Expression and Clinical Significance of PCNAP1 in Hepatocellular Carcinoma Patients

Background

Long noncoding RNAs (lncRNAs) play an important role in many cancer progression. The aim of this study was to evaluate the expression level and clinical significance of the lncRNA, proliferating cell nuclear antigen pseudogene 1 (PCNAP1), in cancer tissue and the plasma of patients with hepatocellular carcinoma (HCC).

Methods

Quantitative real-time polymerase chain reaction was used to detect the expression of PCNAP1 in HCC tissue, adjacent tissue, and plasma. Spearman's rank correlation analysis was performed to assess relationships among cancer tissue, plasma PCNAP1, and plasma AFP. Kaplan–Meier analysis was used to assess survival of HCC patient with high and low expression of PCNAP1. The survival difference was compared by the log-rank test. The use of plasma levels PCNAP1 for diagnosing HCC was evaluated by receiver operating characteristic curve analysis.

Results

The expression of PCNAP1 in HCC tissue was significantly higher than in adjacent tissue (P < 0.01). The PCNAP1 levels were related to the TNM stage, lymph node metastasis, and tumor maximum diameter (P < 0.05) but were not related to gender and age (P = 0.459 and 0.656). Patients with greater levels of PCNAP1 had poorer survival than patients with lower levels of expression (P < 0.01). Compared to the healthy control group, a gastric cancer group, and a colorectal cancer group, HCC patient plasma levels of PCNAP1 were significantly greater (P < 0.01). The area under the curve (AUC) of plasma PCNAP1 in HCC patients was 0.83 (95% CI: 0.78-0.88). With a cut-off value of plasma PCNAP1 at 1.27, an HCC diagnostic sensitivity of 70.08%, and a specificity of 85.04%, was the maximum diagnostic efficiency achieved.

Conclusion

This study demonstrates PCNAP1 levels to be increased in HCC patients. As such, PCNAP1 may be a new tool useful in disease diagnosis and prognosis.

Estrogenic Effect of Scoparia dulcis (Linn) Extract in Mice Uterus and In Silico Molecular Docking Studies of Certain Compounds with Human Estrogen Receptors

Background:

Scoparia dulcis Linn. is reported to be used by women of Assam and Arunachal Pradesh in northeast India for treating menstrual disorders. Scoparia dulcis contains compounds that bind with estrogen receptors (ERα and ERβ) evidenced by increased PCNA in endometrial epithelium.

Methods:

Crude extract was orally administered at the dose of 500 mg/kg body weight/day to the female mice (60–70 days old) in five different groups. Each group containing six females included: (I) cyclic control, (II) cyclic extract treated, (III) Ovariectomized (OVX)-vehicle treated (Control), (IV) OVX-E2 treated (V) OVX- extract treated. Extract was administered for eight days to the cyclic groups and three days to the OVX groups. PCNA was detected immunohistochemically in uterine tissues and signals were analyzed by Image J software (NIH, USA). Compounds were separated by GC-MS and identified using NIST. In silico molecular docking studies was performed with human estrogen receptors (ERα and ERβ). Molecular dynamics (MD) simulations of the best interacting compound was done using gromacs.

Results:

The results showed cell proliferation in the uterine endometrium evidenced by PCNA. Two phytocompounds, Octadecanoic acid and methyl stearate showed binding affinity with ERα and ERβ.

Conclusion:

Scoparia dulcis contains compounds having binding affinity with ERα and ERβ. The present study is the first report on compounds from Scoparia dulcis showing binding affinity with human estrogen receptors which may have biological effect on female reproduction.

LncRNA PCNAP1 modulates hepatitis B virus replication and enhances tumor growth of liver cancer

Rationale: Hepatitis B virus (HBV) is a major risk factor for liver cancer, in which HBV covalently closed circular DNA (cccDNA) plays crucial roles. However, the effect of pseudogene-derived long noncoding RNAs (lncRNAs) acting as functional regulators of their ancestral gene expression on HBV replication and hepatocellular carcinoma (HCC) remains unclear. In this study, we speculated that the pseudogene-derived lncRNA PCNAP1 and its ancestor PCNA might modulate HBV replication and promote hepatocarcinogenesis.

Methods: We investigated the roles of lncRNA PCNAP1 in contribution of HBV replication through modulating miR-154/PCNA/HBV cccDNA signaling in hepatocarcinogenesis by using CRISPR/Cas9, Southern blot analysis, confocal assays, et al. in primary human hepatocytes (PHH), HepaRG cells, HepG2-NTCP cells, hepatoma carcinoma cells, human liver-chimeric mice model, transgenetic mice model, in vitro tumorigenicity and clinical patients.

Results: Interestingly, the expression levels of PCNAP1 and PCNA were significantly elevated in the liver of HBV-infectious human liver-chimeric mice. Clinically, the mRNA levels of PCNAP1 and PCNA were increased in the liver of HBV-positive/HBV cccDNA-positive HCC patients. Mechanistically, PCNA interacted with HBV cccDNA in a HBc-dependent manner. PCNAP1 enhanced PCNA through sponging miR-154 targeting PCNA mRNA 3′UTR. Functionally, PCNAP1 or PCNA remarkably enhanced HBV replication and accelerated the growth of HCC in vitro and in vivo.

Conclusion: We conclude that lncRNA PCNAP1 enhances the HBV replication through modulating miR-154/PCNA/HBV cccDNA signaling and the PCNAP1/PCNA signaling drives the hepatocarcinogenesis. Our finding provides new insights into the mechanism by which lncRNA PCNAP1 enhances HBV replication and hepatocarcinogenesis.

BLASSO: integration of biological knowledge into a regularized linear model

Background

In RNA-Seq gene expression analysis, a genetic signature or biomarker is defined as a subset of genes that is probably involved in a given complex human trait and usually provide predictive capabilities for that trait. The discovery of new genetic signatures is challenging, as it entails the analysis of complex-nature information encoded at gene level. Moreover, biomarkers selection becomes unstable, since high correlation among the thousands of genes included in each sample usually exists, thus obtaining very low overlapping rates between the genetic signatures proposed by different authors. In this sense, this paper proposes BLASSO, a simple and highly interpretable linear model with l₁-regularization that incorporates prior biological knowledge to the prediction of breast cancer outcomes. Two different approaches to integrate biological knowledge in BLASSO, Gene-specific and Gene-disease, are proposed to test their predictive performance and biomarker stability on a public RNA-Seq gene expression dataset for breast cancer. The relevance of the genetic signature for the model is inspected by a functional analysis.

Results

BLASSO has been compared with a baseline LASSO model. Using 10-fold cross-validation with 100 repetitions for models’ assessment, average AUC values of 0.7 and 0.69 were obtained for the Gene-specific and the Gene-disease approaches, respectively. These efficacy rates outperform the average AUC of 0.65 obtained with the LASSO. With respect to the stability of the genetic signatures found, BLASSO outperformed the baseline model in terms of the robustness index (RI). The Gene-specific approach gave RI of 0.15±0.03, compared to RI of 0.09±0.03 given by LASSO, thus being 66% times more robust. The functional analysis performed to the genetic signature obtained with the Gene-disease approach showed a significant presence of genes related with cancer, as well as one gene (IFNK) and one pseudogene (PCNAP1) which a priori had not been described to be related with cancer.

Conclusions

BLASSO has been shown as a good choice both in terms of predictive efficacy and biomarker stability, when compared to other similar approaches. Further functional analyses of the genetic signatures obtained with BLASSO has not only revealed genes with important roles in cancer, but also genes that should play an unknown or collateral role in the studied disease.