Burden of liver cancer due to hepatitis C from 1990 to 2019 at the global, regional, and national levels

BackgroundLiver cancer due to hepatitis C (LCDHC) is one of the leading causes of cancer-related deaths worldwide, and the burden of LCDHC is increasing. We aimed to report the burden of LCDHC at the global, regional, and national levels in 204 countries from 1990 to 2019, stratified by etiology, sex, age, and Sociodemographic Index.MethodsData on LCDHC were available from the Global Burden of Disease, Injuries, and Risk Factors (GBD) study 2019. Numbers and age-standardized mortality, incidence, and disability-adjusted life year (DALY) rates per 100,000 population were estimated through a systematic analysis of modeled data from the GBD 2019 study. The trends in the LCDHC burden were assessed using the annual percentage change.ResultsGlobally, in 2019, there were 152,225 new cases, 141,810 deaths, and 2,878,024 DALYs due to LCDHC. From 1990 to 2019, the number of incidences, mortality, and DALY cases increased by 80.68%, 67.50%, and 37.20%, respectively. However, the age-standardized incidence, mortality, and DALY rate had a decreasing trend during this period. In 2019, the highest age-standardized incidence rates (ASIRs) of LCDHC were found in high-income Asia Pacific, North Africa and the Middle East, and Central Asia. At the regional level, Mongolia, Egypt, and Japan had the three highest ASIRs in 2019. The incidence rates of LCDHC were higher in men and increased with age, with a peak incidence in the 95+ age group for women and the 85–89 age group for men in 2019. A nonlinear association was found between the age-standardized rates of LCDHC and sociodemographic index values at the regional and national levels.ConclusionsAlthough the age-standardized rates of LCDHC have decreased, the absolute numbers of incident cases, deaths, and DALYs have increased, indicating that LCDHC remains a significant global burden. In addition, the burden of LCDHC varies geographically. Male and older adult/s individuals have a higher burden of LCDHC. Our findings provide insight into the global burden trend of LCDHC. Policymakers should establish appropriate methods to achieve the HCV elimination target by 2030 and reducing the burden of LCDHC

Identification and validation of potential diagnostic signature and immune cell infiltration for HIRI based on cuproptosis-related genes through bioinformatics analysis and machine learning

Background and aimsCuproptosis has emerged as a significant contributor in the progression of various diseases. This study aimed to assess the potential impact of cuproptosis-related genes (CRGs) on the development of hepatic ischemia and reperfusion injury (HIRI).MethodsThe datasets related to HIRI were sourced from the Gene Expression Omnibus database. The comparative analysis of differential gene expression involving CRGs was performed between HIRI and normal liver samples. Correlation analysis, function enrichment analyses, and protein-protein interactions were employed to understand the interactions and roles of these genes. Machine learning techniques were used to identify hub genes. Additionally, differences in immune cell infiltration between HIRI patients and controls were analyzed. Quantitative real-time PCR and western blotting were used to verify the expression of the hub genes.ResultsSeventy-five HIRI and 80 control samples from three databases were included in the bioinformatics analysis. Three hub CRGs (NLRP3, ATP7B and NFE2L2) were identified using three machine learning models. Diagnostic accuracy was assessed using a receiver operating characteristic (ROC) curve for the hub genes, which yielded an area under the ROC curve (AUC) of 0.832. Remarkably, in the validation datasets GSE15480 and GSE228782, the three hub genes had AUC reached 0.904. Additional analyses, including nomograms, decision curves, and calibration curves, supported their predictive power for diagnosis. Enrichment analyses indicated the involvement of these genes in multiple pathways associated with HIRI progression. Comparative assessments using CIBERSORT and gene set enrichment analysis suggested elevated expression of these hub genes in activated dendritic cells, neutrophils, activated CD4 memory T cells, and activated mast cells in HIRI samples versus controls. A ceRNA network underscored a complex regulatory interplay among genes. The genes mRNA and protein levels were also verified in HIRI-affected mouse liver tissues.ConclusionOur findings have provided a comprehensive understanding of the association between cuproptosis and HIRI, establishing a promising diagnostic pattern and identifying latent therapeutic targets for HIRI treatment. Additionally, our study offers novel insights to delve deeper into the underlying mechanisms of HIRI

Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning

Background and aimsCuproptosis has been identified as a key player in the development of several diseases. In this study, we investigate the potential role of cuproptosis-related genes in the pathogenesis of nonalcoholic fatty liver disease (NAFLD).MethodThe gene expression profiles of NAFLD were obtained from the Gene Expression Omnibus database. Differential expression of cuproptosis-related genes (CRGs) were determined between NAFLD and normal tissues. Protein–protein interaction, correlation, and function enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was analyzed in both NAFLD patients and controls. Quantitative real-time PCR was employed to validate the expression of hub genes.ResultsFour datasets containing 115 NAFLD and 106 control samples were included for bioinformatics analysis. Three hub CRGs (NFE2L2, DLD, and POLD1) were identified through the intersection of three machine learning algorithms. The receiver operating characteristic curve was plotted based on these three marker genes, and the area under the curve (AUC) value was 0.704. In the external GSE135251 dataset, the AUC value of the three key genes was as high as 0.970. Further nomogram, decision curve, calibration curve analyses also confirmed the diagnostic predictive efficacy. Gene set enrichment analysis and gene set variation analysis showed these three marker genes involved in multiple pathways that are related to the progression of NAFLD. CIBERSORT and single-sample gene set enrichment analysis indicated that their expression levels in macrophages, mast cells, NK cells, Treg cells, resting dendritic cells, and tumor-infiltrating lymphocytes were higher in NAFLD compared with control liver samples. The ceRNA network demonstrated a complex regulatory relationship between the three hub genes. The mRNA level of these hub genes were further confirmed in a mouse NAFLD liver samples.ConclusionOur study comprehensively demonstrated the relationship between NAFLD and cuproptosis, developed a promising diagnostic model, and provided potential targets for NAFLD treatment and new insights for exploring the mechanism for NAFLD

Increased Cord Blood Betatrophin Levels in the Offspring of Mothers with Gestational Diabetes.

AIM:Exposing a fetus to hyperglycemia can increase the risk for later-life metabolic disorders. Betatrophin has been proposed as a key regulator of pancreatic beta cell proliferation and lipid regulation. Highly responsive to nutritional signals, serum betatrophin concentrations have been found to be altered by various physiological and pathological conditions. We hypothesized that betatrophin levels are increased in the cord blood in offspring exposed to intrauterine hyperglycemia. METHODS:This was a cross-sectional study including 54 mothers who underwent uncomplicated Cesarean delivery in a university hospital. Maternal gestational glucose concentration was determined at 24-48 weeks gestation after a 75-g OGTT. Cord blood and placental tissue was collected immediately post delivery. Metabolic parameters were determined in the Clinical Laboratory. Cord blood betatrophin levels were assayed using a commercially available ELISA kit. Placental mitochondrial content was determined by real-time PCR. RESULTS:Cord blood betatrophin levels were increased in the gestational diabetes mellitus (GDM) group compared with the normoglycemic group. Furthermore, betatrophin levels were positively correlated with maternal gestational 2h post-OGTT glucose, cord blood insulin, HOMA-IR, and inversely correlated with placental mitochondrial content. CONCLUSIONS:Cord blood betatrophin may function as a potential biomarker of maternal intrauterine hyperglycemia and fetal insulin resistance, which may presage for long-term metabolic impact of GDM on offspring

Transcriptome sequencing and metabolome analysis reveal the metabolic reprogramming of partial hepatectomy and extended hepatectomy

Abstract Surgical resection remains a critical treatment option for many patients with primary and secondary hepatic neoplasms. Extended hepatectomy (eHx) may be required for some patients with large tumors, which may cause liver failure and death. Partial hepatectomy (pHx) and eHx mouse models were constructed, liver tissues were sampled at 18, 36, and 72 h posthepatectomy. Transcriptome and metabolome analyses were employed to explore the different potential mechanisms in regeneration and injury between pHx and eHx. The results showed that eHx was associated with more severe liver injury and lower survival rates than pHx. Transcriptomics data showed there were 1842, 2129, and 1277 differentially expressed genes (DEGs) in eHx and 962, 1305, and 732 DEGs in pHx at 18, 36, and 72 h posthepatectomy, respectively, compared with the those in the sham groups. Compared with pHx, the number of DEGs in the eHx group reached a maximum of 230 at 18 h after surgery and decreased sequentially to 87 and 43 at 36 and 72 h. Metabolomics analysis identified a total of 1399 metabolites, and 48 significant differentially produced metabolites (DPMs) were screened between eHx and pHx. Combined analysis of DEGs and DPMs indicated that cholesterol metabolism and insulin resistance may be two important pathways for liver regeneration and mouse survival postextended hepatectomy. Our results showed the global influence of pHx and eHx on the transcriptome and metabolome in mouse liver, and revealed cholesterol metabolism and insulin resistance pathways might be involved in regeneration post-pHx and -eHx

Correlation analysis between maternal gestational OGTT glycemia and cord blood betatrophin.

<p>Correlation was adjusted for pregestational BMI, gestational weight gain, cord blood HOMA-IR, newborn birth weight, sex, parity, and gestational age at delivery and maternal age. Data represents both cohorts (n = 54).</p

CBX8 exhibits oncogenic properties and serves as a prognostic factor in hepatocellular carcinoma

Polycomb group family is a class of proteins that have important roles in both physiological and pathological processes, and its family member Chromobox homolog 8 (CBX8) regulates cell differentiation, aging, and cell cycle progression in numerous carcinomas; however, the effects and underlying mechanisms of CBX8 in hepatocellular carcinoma (HCC) are rarely reported. We found that CBX8 expression in clinical HCC specimens correlates inversely with patient survival. In HCC cells, we found that enforced overexpression of CBX8 induces epithelial-mesenchymal transition, invasive migration, and stem cell-like traits, which are associated with increased tumor growth and metastasis in mice. Conversely, CBX8 silencing inhibits the aggressive phenotype of HCC cells that have high CBX8 expression. Mechanistically, CBX8 modulates H3K27me3 in the gene promoter of bone morphogenetic protein 4 (BMP4), which is associated with active BMP4 transcription and, consequently, the activation of Smads and mitogen-activated protein kinases. BMP4 expression reverses the effects of CBX8 silencing in inhibiting epithelial-mesenchymal transition, stemness, and metastasis. Our results establish CBX8 as a critical driver of HCC stem cell-like and metastatic behaviors and characterize its role in modulating BMP4 expression. These findings have implications for the targeting of CBX8 as an approach to HCC prognosis and treatment

Maternal and newborn characteristics.

<p>Maternal and newborn characteristics.</p