Correlation between the DEPDC5 rs1012068 polymorphism and the risk of HBV-related hepatocellular carcinoma

Host and HBV Interactions and Their Potential Impact on Clinical Outcomes

Hepatitis B virus (HBV) is a challenge for global health services, affecting millions and leading thousands to end-stage liver disease each year. This comprehensive review explores the interactions between HBV and the host, examining their impact on clinical outcomes. HBV infection encompasses a spectrum of severity, ranging from acute hepatitis B to chronic hepatitis B, which can potentially progress to cirrhosis and hepatocellular carcinoma (HCC). Occult hepatitis B infection (OBI), characterized by low HBV DNA levels in hepatitis B surface antigen-negative individuals, can reactivate and cause acute hepatitis B. HBV genotyping has revealed unique geographical patterns and relationships with clinical outcomes. Moreover, single nucleotide polymorphisms (SNPs) within the human host genome have been linked to several clinical outcomes, including cirrhosis, HCC, OBI, hepatitis B reactivation, and spontaneous clearance. The immune response plays a key role in controlling HBV infection by eliminating infected cells and neutralizing HBV in the bloodstream. Furthermore, HBV can modulate host metabolic pathways involved in glucose and lipid metabolism and bile acid absorption, influencing disease progression. HBV clinical outcomes correlate with three levels of viral adaptation. In conclusion, the clinical outcomes of HBV infection could result from complex immune and metabolic interactions between the host and HBV. These outcomes can vary among populations and are influenced by HBV genotypes, host genetics, environmental factors, and lifestyle. Understanding the degrees of HBV adaptation is essential for developing region-specific control and prevention measures.

Correlation of DEPDC5 rs1012068 and rs5998152 Polymorphisms with Risk of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

Background

Emerging evidence has shown that two common genetic polymorphisms within the pleckstrin domain-containing protein 5 (DEPDC5), rs1012068 and rs5998152, may be associated with the risk of hepatocellular carcinoma (HCC), especially in those individuals chronically infected with the hepatitis C virus (HCV) or the hepatitis B virus (HBV). However, these findings have not been consistently replicated in the literature due to limited sample sizes or different etiologies of HCC. Thus, the present systematic review and meta-analysis were performed to resolve this inconsistency.

Methods

The databases PubMed, Embase, Web of Science, the China National Knowledge Infrastructure, and Scopus were searched up to December 12, 2022. Data from relevant studies were pooled, and odds ratios and 95% confidence intervals were calculated.

Results

A total of 11 case-control studies encompassing 2,609 cases and 8,171 controls on rs1012068 and three encompassing 411 cases and 1,448 controls on rs5998152 were included. Results indicated that the DEPDC5 rs1012068 polymorphism did not significantly increase HCC risk in the total population (allelic model (OR = 1.32, 95% CI = 1.04-1.67, P = 0.02); the recessive model (OR = 1.42, 95% CI = 0.96-2.10, P = 0.08); the dominant model (OR = 1.43, 95% CI = 1.09-1.87, P = 0.01); the homozygous model (OR = 1.61, 95% CI = 1.01-2.57, P = 0.05); the heterozygous model (OR = 1.39, 95% CI = 1.09-1.79, P = 0.009)). Subgroup analyses based on ethnicity and etiology revealed that the rs1012068 polymorphism, under all five genetic models, was associated with increased HCC risk in Asians or in individuals with chronic HBV infection but not in individuals with chronic HCV infection. A significant association was also observed between rs5998152 and HCV-related HCC risk in Asians chronically infected with HCV under allelic, dominant, and heterozygous models.

Conclusion

Our study suggests that the DEPDC5 rs1012068 polymorphism increases HCC risk, especially in Asians with chronic HBV infection, while the rs5998152 polymorphism increases HCC risk in Asians with chronic HCV infection.

NPRL2 down-regulation facilitates the growth of hepatocellular carcinoma via the mTOR pathway and autophagy suppression

Hepatocellular carcinoma (HCC) is a highly invasive malignancy. Recently, GATOR1 (Gap Activity TOward Rags 1) complexes have been shown to play an important role in regulating tumor growth. NPRL2 is a critical component of the GATOR1 complex. Therefore, this study used NPRL2 knockdown to investigate how GATORC1 regulates the prognosis and development of HCC via the mammalian target of rapamycin (mTOR) and autophagy signaling pathways. We established HepG2 cells with NPRL2 knockdown using small interfering RNA (siRNA) and short hairpin RNA (shRNA) systems. The siRNA-mediated and shRNA-mediated NPRL2 down-regulation significantly reduced the expression of NPRL2 and two other GATPOR1 complex components, NPRL3 and DEPDC5, in HepG2 cells; furthermore, the efficient down-regulation of NPRL2 protein expression by both the shRNA and siRNA systems enhanced the proliferation, migration, and colony formation in vitro. Additionally, the NPRL2 down-regulation significantly increased HCC growth in the subcutaneous and orthotopic xenograft mouse models. The NPRL2 down-regulation increased the Rag GTPases and mTOR activation and inhibited autophagy in vitro and in vivo. Moreover, the NPRL2 level in the tumors was significantly associated with mortality, recurrence, the serum alpha fetoprotein level, the tumor size, the American Joint Committee on Cancer stage, and the Barcelona Clinic Liver Cancer stage. Low NPRL2, NPRL3, DEPDC5, and LC3, and high p62 and mTOR protein expression in the tumors was significantly associated with disease-free survival and overall survival in 300 patients with HCC after surgical resection. Conclusion: The efficient down-regulation of NPRL2 significantly increased HCC proliferation, migration, and colony formation in vitro, and increased HCC growth in vivo. Low NPRL2 protein expression in the tumors was closely correlated with poorer clinical outcomes in patients with HCC. These results provide a mechanistic understanding of HCC and aid the development of treatments for HCC.

International multicenter validation of GES score for HCC risk stratification in chronic hepatitis C patients

We have recently demonstrated the ability of a simple predictive model (GES) score to determine the risk of hepatocellular carcinoma (HCC) after using direct-acting antivirals. However, our results were restricted to Egyptian patients with hepatitis C virus (HCV) genotype 4. Therefore, we studied a large, independent cohort of multiethnic populations through our international collaborative activity. Depending on their GES scores, patients are stratified into low risk (≤ 6/12.5), intermediate risk (> 6-7.5/12.5), and high risk (> 7.5/12.5) for HCC. A total of 12,038 patients with chronic HCV were analyzed in this study, of whom 11,202 were recruited from 54 centers in France, Japan, India, the U.S., and Spain, and the remaining 836 were selected from the Gilead-sponsored randomized controlled trial conducted across the U.S., Europe, Canada, and Australia. Descriptive statistics and log-rank tests. The performance of the GES score was evaluated using Harrell's C-index (HCI). The GES score proved successful at stratifying all patients into 3 risk groups, namely low-risk, intermediate-risk, and high-risk. It also displayed significant predictive value for HCC development in all participants (p < .0001), with HCI ranging from 0.55 to 0.76 among all cohorts after adjusting for HCV genotypes and patient ethnicities. The GES score can be used to stratify HCV patients into 3 categories of risk for HCC, namely low-risk, intermediate-risk, and high-risk, irrespective of their ethnicities or HCV genotypes. This international multicenter validation may allow the use of GES score in individualized HCC risk-based surveillance programs.

Liver cancer risk-predictive molecular biomarkers specific to clinico-epidemiological contexts

Hepatocellular carcinoma (HCC) risk prediction is increasingly important because of the low annual HCC incidence in patients with the rapidly emerging non-alcoholic fatty liver disease or cured HCV infection. To date, numerous clinical HCC risk biomarkers and scores have been reported in literature. However, heterogeneity in clinico-epidemiological context, e.g., liver disease etiology, patient race/ethnicity, regional environmental exposure, and lifestyle-related factors, obscure their real clinical utility and applicability. Proper characterization of these factors will help refine HCC risk prediction according to certain clinical context/scenarios and contribute to improved early HCC detection. Molecular factors underlying the clinical heterogeneity encompass various features in host genetics, hepatic and systemic molecular dysregulations, and cross-organ interactions, which may serve as clinical-context-specific biomarkers and/or therapeutic targets. Toward the goal to enable individual-risk-based HCC screening by incorporating the HCC risk biomarkers/scores, their assessment in patient with well-defined clinical context/scenario is critical to gauge their real value and to maximize benefit of the tailored patient management for substantial improvement of the poor HCC prognosis.

Predictive performance and clinical utility of HCC risk scores in chronic hepatitis C: a comparative study

BACKGROUND AND AIM

Many HCC risk prediction scores were developed to guide HCC risk stratification and identify CHC patients who either need intensified surveillance or may not require screening. There is a need to compare different scores and their predictive performance in clinical practice. We aim to compare the newest HCC risk scores evaluating their discriminative ability, and clinical utility in a large cohort of CHC patients.

PATIENTS AND METHODS

The performance of the scores was evaluated in 3075 CHC patients who achieved SVR following DAAs using Log rank, Harrell's c statistic, also tested for HCC-risk stratification and negative predictive values.

RESULTS

HCC developed in 212 patients within 5 years follow-up. Twelve HCC risk scores were identified and displayed significant Log rank (p ≤ 0.05) except Alonso-Lopez TE-HCC, and Chun scores (p = 0.374, p = 0.053, respectively). Analysis of the remaining ten scores revealed that ADRES, GES pre-post treatment, GES algorithm and Watanabe (post-treatment) scores including dynamics of AFP, were clinically applicable and demonstrated good statistical performance; Log rank analysis < 0.001, Harrell's C statistic (0.66-0.83) and high negative predictive values (94.38-97.65%). In these three scores, the 5 years cumulative IR in low risk groups be very low (0.54-1.6), so screening could be avoided safely in these patients.

CONCLUSION

ADRES, GES (pre- and post-treatment), GES algorithm and Watanabe (post-treatment) scores seem to offer acceptable HCC-risk predictability and clinical utility in CHC patients. The dynamics of AFP as a component of these scores may explain their high performance when compared to other scores.

Treated with interferon and the gene polymorphism of CGRP and its receptor

OBJECTIVE

This case-control study aims to investigate the relationship of polymorphisms of four gene loci (CGRP rs155209 and rs3781719, RAMP1 rs3754701 and rs7590387) with the prognosis of interferon therapy for chronic hepatitis B (CHB).

MATERIALS AND METHODS

A total of 317 CHB patients receiving interferon alone for the first time were recruited in northern China, and peripheral blood samples were obtained. The single-nucleotide polymorphisms (SNPs) in rs155209, rs3781719, rs3754701, and rs7590387 were genotyped using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS). Univariate and multivariate logistic regression methods were employed to assess the correlation between CHB prognosis treated with interferon and polymorphisms of these gene loci.

RESULTS

The study clearly demonstrated the relevance of polymorphisms of rs155209, rs3781719, rs3754701, and rs7590387 with DNA response and ALT response after interferon treatment. CHB patients with CGRP rs155209C had a lower risk of developing DNA response (CT vs. TT: OR = 0.159, 95% CI = 0.086-0.294, P_adj < 0.001; CC vs. TT: OR = 0.131, 95% CI = 0.059-0.288, P_adj < 0.001), as well as a lower risk of developing ALT response (CT vs. TT: OR = 0.530, 95% CI = 0.323-0.869, P_adj < 0.05). Moreover, CHB patients with RAMP1 rs3754701T allele were more prone to develop DNA response (AT vs. AA: OR = 2.061, 95% CI = 1.237-3.435, P_adj < 0.05; TT vs. AA: OR = 5.676, 95% CI =1.247-25.837, P_adj < 0.05), and they also more likely to develop ALT response (AT vs. AA: OR = 1.766, 95% CI = 1.098-2.840, P_adj < 0.05). We did not find a significant association between CGRP rs3781719 or RAMP1 rs7590387 and DNA response or ALT response.

CONCLUSION

This study revealed that CGRP rs155209 and RAMP1 rs3754701 polymorphisms, but not CGRP rs3781719 and RAMP1 rs7590387, were correlated with interferon therapy prognosis for CHB in Han Chinese population, and RAMP1 rs3754701T was a protective factor for ALT response and DNA response, but CGRP rs155209C carriers were less prone to DNA and ALT responses.

Main insights of genome wide association studies into HCV-related HCC

Background

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-mortality globally. Hepatocarcinogenesis is a complex multifactorial process. Host genetic background appeared to play a crucial role in the progression of HCC among chronic hepatitis C patients, especially in the era of Genome Wide Association Studies (GWAS) which allowed us to study the association of millions of single nucleotide polymorphisms (SNPs) with different complex diseases. This article aimed to review the discovered SNPs associated with the risk of HCV-related HCC development which was reported in the published GWA studies and subsequent validation studies and also try to explain the possible functional pathways.

Main text

We reviewed the recent GWA studies which reported several new loci associated with the risk of HCV-related HCC, such as (SNPs) in MHC class I polypeptide-related sequence A (MICA), DEP domain-containing 5 (DEPDC5), Tolloid-like protein 1 (TLL1), and human leukocyte antigen (HLA) genes. We also explained the possible underlying biological mechanisms that affect the host immune response pathways. Additionally, we discussed the controversial results reported by the subsequent validation studies of different ethnicities.

Conclusions

Although GWA studies reported strong evidence of the association between the identified SNPs and the risk of HCV-related HCC development, more functional experiments are necessary to confirm the defined roles of these genetic mutations for the future clinical application in different populations.

Clinical and Molecular Prediction of Hepatocellular Carcinoma Risk

Prediction of hepatocellular carcinoma (HCC) risk becomes increasingly important with recently emerging HCC-predisposing conditions, namely non-alcoholic fatty liver disease and cured hepatitis C virus infection. These etiologies are accompanied with a relatively low HCC incidence rate (~1% per year or less), while affecting a large patient population. Hepatitis B virus infection remains a major HCC risk factor, but a majority of the patients are now on antiviral therapy, which substantially lowers, but does not eliminate, HCC risk. Thus, it is critically important to identify a small subset of patients who have elevated likelihood of developing HCC, to optimize the allocation of limited HCC screening resources to those who need it most and enable cost-effective early HCC diagnosis to prolong patient survival. To date, numerous clinical-variable-based HCC risk scores have been developed for specific clinical contexts defined by liver disease etiology, severity, and other factors. In parallel, various molecular features have been reported as potential HCC risk biomarkers, utilizing both tissue and body-fluid specimens. Deep-learning-based risk modeling is an emerging strategy. Although none of them has been widely incorporated in clinical care of liver disease patients yet, some have been undergoing the process of validation and clinical development. In this review, these risk scores and biomarker candidates are overviewed, and strategic issues in their validation and clinical translation are discussed.

Concurrent activation of growth factor and nutrient arms of mTORC1 induces oxidative liver injury

mTORC1 is a protein kinase important for metabolism and is regulated by growth factor and nutrient signaling pathways, mediated by the Rheb and Rag GTPases, respectively. Here we provide the first animal model in which both pathways were upregulated through concurrent mutations in their GTPase-activating proteins, Tsc1 and Depdc5. Unlike former models that induced limited mTORC1 upregulation, hepatic deletion of both Tsc1 and Depdc5 (DKO) produced strong, synergistic activation of the mTORC1 pathway and provoked pronounced and widespread hepatocyte damage, leading to externally visible liver failure phenotypes, such as jaundice and systemic growth defects. The transcriptome profile of DKO was different from single knockout mutants but similar to those of diseased human livers with severe hepatitis and mouse livers challenged with oxidative stress-inducing chemicals. In addition, DKO liver cells exhibited prominent molecular pathologies associated with excessive endoplasmic reticulum (ER) stress, oxidative stress, DNA damage and inflammation. Although DKO liver pathologies were ameliorated by mTORC1 inhibition, ER stress suppression unexpectedly aggravated them, suggesting that ER stress signaling is not the major conduit of how hyperactive mTORC1 produces liver damage. Interestingly, superoxide scavengers N-acetylcysteine (NAC) and Tempol, chemicals that reduce oxidative stress, were able to recover liver phenotypes, indicating that mTORC1 hyperactivation induced liver damage mainly through oxidative stress pathways. Our study provides a new model of unregulated mTORC1 activation through concomitant upregulation of growth factor and nutrient signaling axes and shows that mTORC1 hyperactivation alone can provoke oxidative tissue injury.