CYP2C19 Genotype Could be a Predictive Factor for Aggressive Manifestations of Hepatocellular Carcinoma Related with Chronic Hepatitis B Infection in Thailand

CYP2C19 loss-of-function variants are independent risk factors for premature cerebral infarction: a hospital based retrospective study

OBJECTIVE

Cytochrome P450 2C19 (CYP2C19) plays an vital role in the course of cardiovascular and cerebrovascular diseases by affecting lipid metabolism. Triglyceride-glucose (TyG) is a comprehensive index composed of triglyceride and blood glucose, has relationship with some diseases. There was no research report on the association CYP2C19 polymorphisms, TyG with premature cerebral infarction (CI) (onset ≤ 65 years old) susceptibility.

METHODS

This study retrospectively analyzed 1953 CI patients aged ≤ 65 years old from December 2018 to March 2024, and 1919 age-matched individuals with non-CI as controls. The relationship between CYP2C19 polymorphisms, TyG and premature CI risk were analyzed.

RESULTS

The proportion of hypertension, and diabetes mellitus in patients with premature CI was higher than those in controls. The serum total cholesterol (TC), triglycerides (TG), low-density lipoprotein-cholesterol (LDL-C), and TyG levels in patients with premature CI were significantly higher than those in controls (all p < 0.05). The patients had lower CYP2C19 *1 allele frequency (63.3% vs. 69.6%, p < 0.001) and higher CYP2C19 *2 allele frequency (31.3% vs. 25.4%, p < 0.001) than controls. Logistic regression analysis showed that smoking history (odds ratio (OR): 1.193, 95% confidence interval (CI): 1.002-1.422, p = 0.048), hypertension (OR: 3.371, 95% CI: 2.914-3.898, p < 0.001), diabetes mellitus (OR: 1.911, 95% CI: 1.632-2.237, p < 0.001), CYP2C19 intermediate metabolizer (IM) + poor metabolizer (PM) phenotypes (OR: 1.424, 95% CI: 1.243-1.631, p < 0.001), and dyslipidemia (OR: 1.294, 95% CI: 1.077-1.554, p = 0.006) were independent risk factors for premature CI.

CONCLUSIONS

History of smoking, hypertension, diabetes mellitus, dyslipidemia, and CYP2C19 IM + PM phenotypes were independently associated with premature CI susceptibility.

Prevalence of Hepatocellular Carcinoma in Hepatitis B Population within Southeast Asia: A Systematic Review and Meta-Analysis of 39,050 Participants

BACKGROUND AND AIM

Hepatocellular carcinoma (HCC) is a significant complication of hepatitis B and still poses a global public health concern. This systematic review and meta-analysis provide adequate details on the prevalence of HCC in the HBV population within Southeast Asian countries.

METHOD

Following the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) criteria, a thorough search for literature discussing the prevalence of HCC in the HBV population within southeast Asia was performed. Eligible studies were subjected to a meta-analysis utilising a DerSimonian and Laird approach and a random effect model. A protocol was registered with PROSPERO (CRD42023423953).

RESULT

Our study meticulously recovered 41 articles from seven countries in Southeast Asia, namely Cambodia, Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam. A total of 39,050 HBV patients and 7479 HCC cases in southeast Asia were analysed. The pooled prevalence of HCC in HBV cases within southeast Asia was 45.8% (95% CI, 34.3-57.8%, I2 = 99.51%, p < 0.001). Singapore (62.5%, CI: 42.4-79.1) had the highest pooled prevalence of HCC in the HBV population compared to Vietnam, with the lowest estimate (22.4%, CI: 9.9-44.9). There was a drop in the pooled prevalence of HCC in HBV from 2016 until now (37.6%, CI: 19.2-60.5).

CONCLUSION

The findings of this review reveal a high pooled prevalence of HCC in the HBV population and therefore stir the need for routine screening, management, and surveillance.

Construction of HBV-HCC prognostic model and immune characteristics based on potential genes mining through protein interaction networks

OBJECTIVE

To search for human protein-coding genes related to hepatocellular carcinoma (HCC) in the context of hepatitis B virus (HBV) infection, and perform prognosis risk assessment.

METHODS

Genes related to HBV-HCC were selected through literature screening and protein-protein interaction (PPI) network database analysis. Prognosis potential genes (PPGs) were identified using Cox regression analysis. Patients were divided into high-risk and low-risk groups based on PPGs, and risk scores were calculated. Kaplan-Meier plots were used to analyze overall survival rates, and the results were predicted based on clinicopathological variables. Association analysis was also conducted with immune infiltration, immune therapy, and drug sensitivity. Experimental verification of the expression of PPGs was done in patient liver cancer tissue and normal liver tissue adjacent to tumors.

RESULTS

The use of a prognosis potential genes risk assessment model can reliably predict the prognosis risk of patients, demonstrating strong predictive ability. Kaplan-Meier analysis showed that the overall survival rate of the low-risk group was significantly higher than that of the high-risk group. There were significant differences between the two subgroups in terms of immune infiltration and IC50 association analysis. Experimental verification revealed that CYP2C19, FLNC, and HNRNPC were highly expressed in liver cancer tissue, while UBE3A was expressed at a lower level.

CONCLUSION

PPGs can be used to predict the prognosis risk of HBV-HCC patients and play an important role in the diagnosis and treatment of liver cancer. They also reveal their potential role in the tumor immune microenvironment, clinical-pathological characteristics, and prognosis.

Identification of Key Functional Modules and Immunomodulatory Regulators of Hepatocellular Carcinoma

Despite the advances in the treatment of hepatocellular carcinoma (HCC), the prognosis of HCC patients remains unsatisfactory due to postsurgical recurrence and treatment resistance. Therefore, it is important to reveal the mechanisms underlying HCC and identify potential therapeutic targets against HCC, which could facilitate the development of novel therapies. Based on 12 HCC samples and 12 paired paracancerous normal tissues, we identified differentially expressed mRNAs and lncRNAs using the "limma" package in R software. Moreover, we used the weighted gene coexpression network analysis (WGCNA) to analyze the expression data and screened hub genes. Furthermore, we performed pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. In addition, the relative abundance of a given gene set was estimated by single-sample Gene Set Enrichment Analysis. We identified 687 differentially expressed mRNAs and 260 differentially expressed lncRNAs. A total of 6 modules were revealed by WGCNA, and MT1M and MT1E genes from the red module were identified as hub genes. Moreover, pathway analysis revealed the top 10 enriched KEGG pathways of upregulated or downregulated genes. Additionally, we also found that CD58 might act as an immune checkpoint gene in HCC via PD1/CTLA4 pathways and regulate the levels of tumor-infiltrating immune cells in HCC tissues, which might be an immunotherapeutic target in HCC. Our research identified key functional modules and immunomodulatory regulators for HCC, which might offer novel diagnostic biomarkers and/or therapeutic targets for cancer immunotherapy.