Detection of hepatitis Β virus DNA and mutations in K-ras and p53 genes in human hepatocellular carcinomas

Journal URL: http://www.spandidos-publications.com/ijo/Hepatitis Β virus (HBV) infection is considered as one of the major risk factors in the development of human hepatocellular carcinoma (HCC). Recent studies have also suggested the implication of oncogene and onco-suppressor genes in liver carcinogenesis. We studied 41 cases of HCC for the presence of HBV DNA and point mutations in codon 12 of K-ras and codon 249 of p53. We used 'nested' PCR for the amplification of HBV because of the expected low incidence of the virus DNA in the samples. PCR was also used for the amplification of K-ras and p53 regions that contain the codons of interest, followed by RFLP analysis for the detection of point mutations. HBV DNA was amplified in 22 cases (53.7%), while 5 cases (12.2%) appeared to carry mutations in codon 12 of K-ras and 7 cases (17.1%) had mutations in codon 249 of the p53 gene. These results further support the correlation between HBV infection and HCC and also indicate an implication of K-ras and p53 genes in hepatocarcinogenesis

Machine learning approaches to enhance diagnosis and staging of patients with MASLD using routinely available clinical information

Aims: Metabolic dysfunction Associated Steatotic Liver Disease (MASLD) outcomes such as MASH (metabolic dysfunction associated steatohepatitis), fibrosis and cirrhosis are ordinarily determined by resource-intensive and invasive biopsies. We aim to show that routine clinical tests offer sufficient information to predict these endpoints. Methods: Using the LITMUS Metacohort derived from the European NAFLD Registry, the largest MASLD dataset in Europe, we create three combinations of features which vary in degree of procurement including a 19-variable feature set that are attained through a routine clinical appointment or blood test. This data was used to train predictive models using supervised machine learning (ML) algorithm XGBoost, alongside missing imputation technique MICE and class balancing algorithm SMOTE. Shapley Additive exPlanations (SHAP) were added to determine relative importance for each clinical variable. Results: Analysing nine biopsy-derived MASLD outcomes of cohort size ranging between 5385 and 6673 subjects, we were able to predict individuals at training set AUCs ranging from 0.719-0.994, including classifying individuals who are At-Risk MASH at an AUC = 0.899. Using two further feature combinations of 26-variables and 35-variables, which included composite scores known to be good indicators for MASLD endpoints and advanced specialist tests, we found predictive performance did not sufficiently improve. We are also able to present local and global explanations for each ML model, offering clinicians interpretability without the expense of worsening predictive performance. Conclusions: This study developed a series of ML models of accuracy ranging from 71.9—99.4% using only easily extractable and readily available information in predicting MASLD outcomes which are usually determined through highly invasive means

Diagnostic performance of FibroTest, SteatoTest and ActiTest in patients with NAFLD using the SAF score as histological reference

BACKGROUND: Blood tests of liver injury are less well validated in non‐alcoholic fatty liver disease (NAFLD) than in patients with chronic viral hepatitis. AIMS: To improve the validation of three blood tests used in NAFLD patients, FibroTest for fibrosis staging, SteatoTest for steatosis grading and ActiTest for inflammation activity grading. METHODS: We pre‐included new NAFLD patients with biopsy and blood tests from a single‐centre cohort (FibroFrance) and from the multicentre FLIP consortium. Contemporaneous biopsies were blindly assessed using the new steatosis, activity and fibrosis (SAF) score, which provides a reliable and reproducible diagnosis and grading/staging of the three elementary features of NAFLD (steatosis, inflammatory activity) and fibrosis with reduced interobserver variability. We used nonbinary‐ROC (NonBinAUROC) as the main endpoint to prevent spectrum effect and multiple testing. RESULTS: A total of 600 patients with reliable tests and biopsies were included. The mean NonBinAUROCs (95% CI) of tests were all significant (P < 0.0001): 0.878 (0.864–0.892) for FibroTest and fibrosis stages, 0.846 (0.830–0.862) for ActiTest and activity grades, and 0.822 (0.804–0.840) for SteatoTest and steatosis grades. FibroTest had a higher NonBinAUROC than BARD (0.836; 0.820–0.852; P = 0.0001), FIB4 (0.845; 0.829–0.861; P = 0.007) but not significantly different than the NAFLD score (0.866; 0.850–0.882; P = 0.26). FibroTest had a significant difference in median values between adjacent stage F2 and stage F1 contrarily to BARD, FIB4 and NAFLD scores (Bonferroni test P < 0.05). CONCLUSIONS: In patients with NAFLD, SteatoTest, ActiTest and FibroTest are non‐invasive tests that offer an alternative to biopsy, and they correlate with the simple grading/staging of the SAF scoring system across the three elementary features of NAFLD: steatosis, inflammatory activity and fibrosis

Machine learning approaches to enhance diagnosis and staging of patients with MASLD using routinely available clinical information

\ua9 2024 McTeer et al.Aims Metabolic dysfunction Associated Steatotic Liver Disease (MASLD) outcomes such as MASH (metabolic dysfunction associated steatohepatitis), fibrosis and cirrhosis are ordinarily determined by resource-intensive and invasive biopsies. We aim to show that routine clinical tests offer sufficient information to predict these endpoints. Methods Using the LITMUS Metacohort derived from the European NAFLD Registry, the largest MASLD dataset in Europe, we create three combinations of features which vary in degree of procurement including a 19-variable feature set that are attained through a routine clinical appointment or blood test. This data was used to train predictive models using supervised machine learning (ML) algorithm XGBoost, alongside missing imputation technique MICE and class balancing algorithm SMOTE. Shapley Additive exPlanations (SHAP) were added to determine relative importance for each clinical variable. Results Analysing nine biopsy-derived MASLD outcomes of cohort size ranging between 5385 and 6673 subjects, we were able to predict individuals at training set AUCs ranging from 0.719-0.994, including classifying individuals who are At-Risk MASH at an AUC = 0.899. Using two further feature combinations of 26-variables and 35-variables, which included composite scores known to be good indicators for MASLD endpoints and advanced specialist tests, we found predictive performance did not sufficiently improve. We are also able to present local and global explanations for each ML model, offering clinicians interpretability without the expense of worsening predictive performance. Conclusions This study developed a series of ML models of accuracy ranging from 71.9—99.4% using only easily extractable and readily available information in predicting MASLD outcomes which are usually determined through highly invasive means

Adiponectin, leptin, and IGF-1 are useful diagnostic and stratification biomarkers of NAFLD

[EN] Background: Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease where liver biopsy remains the gold standard for diagnosis. Here we aimed to evaluate the role of circulating adiponectin, leptin, and insulin-like growth factor 1 (IGF-1) levels as non-invasive NAFLD biomarkers and assess their correlation with the metabolome. Materials and Methods: Leptin, adiponectin, and IGF-1 serum levels were measured by ELISA in two independent cohorts of biopsy-proven obese NAFLD patients and healthy-liver controls (discovery: 38 NAFLD, 13 controls; validation: 194 NAFLD, 31 controls) and correlated with clinical data, histology, genetic parameters, and serum metabolomics. Results: In both cohorts, leptin increased in NAFLD vs. controls (discovery: AUROC 0.88; validation: AUROC 0.83; p < 0.0001). The leptin levels were similar between obese and non-obese healthy controls, suggesting that obesity is not a confounding factor. In the discovery cohort, adiponectin was lower in non-alcoholic steatohepatitis (NASH) vs. non-alcoholic fatty liver (AUROC 0.87; p < 0.0001). For the validation cohort, significance was attained for homozygous for PNPLA3 allele c.444C (AUROC 0.63; p < 0.05). Combining adiponectin with specific serum lipids improved the assay performance (AUROC 0.80; p < 0.0001). For the validation cohort, IGF-1 was lower with advanced fibrosis (AUROC 0.67, p<0.05), but combination with international normalized ratio (INR) and ferritin increased the assay performance (AUROC 0.81; p < 0.01). Conclusion: Serum leptin discriminates NAFLD, and adiponectin combined with specific lipids stratifies NASH. IGF-1, INR, and ferritin distinguish advanced fibrosis.CR was funded by FEDER through the COMPETE program and by national funds through Fundação para a Ciência e a Tecnologia (PTDC/MED-FAR/29097/2017—LISBOA-01- 0145-FEDER-029097) and by European Horizon 2020 (H2020- MSCA-RISE-2016-734719). This work was also supported by Fundação para a Ciência e Tecnologia (PD/BD/135467/2017) and Portuguese Association for the Study of Liver/MSD 2017. JB was funded by Spanish Carlos III Health Institute (ISCIII) (PI15/01132, PI18/01075 and Miguel Servet Program CON14/00129 and CPII19/00008), co-financed by Fondo Europeo de Desarrollo Regional (FEDER), Instituto de Salud Carlos III (CIBERehd, Spain), La Caixa Scientific Foundation (HR17-00601), Fundación Científica de la Asociación Española Contra el Cáncer, and European Horizon 2020 (ESCALON project: H2020-SC1-BHC-2018-2020)

Upregulation of Hemoglobin Expression by Oxidative Stress in Hepatocytes and Its Implication in Nonalcoholic Steatohepatitis

Recent studies revealed that hemoglobin is expressed in some non-erythrocytes and it suppresses oxidative stress when overexpressed. Oxidative stress plays a critical role in the pathogenesis of non-alcoholic steatohepatitis (NASH). This study was designed to investigate whether hemoglobin is expressed in hepatocytes and how it is related to oxidative stress in NASH patients. Analysis of microarray gene expression data revealed a significant increase in the expression of hemoglobin alpha (HBA1) and beta (HBB) in liver biopsies from NASH patients. Increased hemoglobin expression in NASH was validated by quantitative real time PCR. However, the expression of hematopoietic transcriptional factors and erythrocyte specific marker genes were not increased, indicating that increased hemoglobin expression in NASH was not from erythropoiesis, but could result from increased expression in hepatocytes. Immunofluorescence staining demonstrated positive HBA1 and HBB expression in the hepatocytes of NASH livers. Hemoglobin expression was also observed in human hepatocellular carcinoma HepG2 cell line. Furthermore, treatment with hydrogen peroxide, a known oxidative stress inducer, increased HBA1 and HBB expression in HepG2 and HEK293 cells. Importantly, hemoglobin overexpression suppressed oxidative stress in HepG2 cells. We concluded that hemoglobin is expressed by hepatocytes and oxidative stress upregulates its expression. Suppression of oxidative stress by hemoglobin could be a mechanism to protect hepatocytes from oxidative damage in NASH