A New Inflammation-Related Risk Model for Predicting Hepatocellular Carcinoma Prognosis.

Background: Hepatocellular carcinoma (HCC) is characterized by a poor prognosis. Inflammation has a vital role in the formation and development of HCC. However, the prediction of HCC prognosis using inflammation-related genes (IRGs) remains elusive. In this study, we constructed a new IRG risk model to predict the HCC prognosis. Results: HCC-related RNA expression profiles and their corresponding clinical data were downloaded from TCGA and ICGC databases to explore the IRGs' predicting ability. Seven hundred thirty-seven IRGs from GeneCards were used as candidate genes to construct the model. The associations of overall survival (OS) with IRGs were evaluated using the log-rank test and univariate Cox analysis, and 32 out of 737 IRGs showed predicting the potential for HCC prognosis. These IRGs were further analyzed using the least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses. Finally, 6 IRGs were included in an IRG risk model. Based on the cut-off of the risk score calculated according to the IRG risk model, HCC samples were divided into the high-risk and the low-risk groups. The OS of patients was lower in the high-risk group than in the low-risk group (P < 0.05). The area under the receiver operating characteristic curve (AUC) of the risk score was 0.78 for 3-year survival. Univariate Cox and multivariate Cox analyses revealed that the risk score was an independent risk factor for HCC prognosis. The KEGG and GO enrichment analysis results further showed that the risk scores were closely related to inflammatory and immune pathways. In addition, the ssGSEA demonstrated that several immune cells and some immune-related pathways were negatively correlated with the risk score. Conclusions: The new IRG risk score was an independent risk factor for HCC prognosis and could be used to assess the immune status of the HCC microenvironment.

Diagnostic and prognostic values of pyroptosis-related genes for the hepatocellular carcinoma.

BACKGROUND: Due to the high heterogeneity, the early diagnosis and prognostic prediction of hepatic cellular cancer (HCC) is challenging. In this study, we explored the diagnostic and prognostic value of pyroptosis-related genes (PRGs) in HCC. We downloaded the mRNA expression profiles of HCC and the corresponding clinical data from the TCGA and ICGC databases. Fifty-one PRGs were extracted from Genecards, MsigDB, and relevant literature. The area under the receiver operating characteristic (AUC) was used to explore the diagnostic value of the PRGs. RESULTS: The results revealed that BAK1, BAX, CHMP2A, CHMP4C, CHMP6, GSDMC, and GSDMD had higher diagnostic values for HCC (AUCs > 0.8, P < 0.05). Then, univariate and multivariate analyses of 51 PRGs were performed for HCC samples, and 4 PRGs (TP53, GPX4, GSDMC, BAK1) associated with HCC prognosis were obtained and used to construct a pyroptosis-related risk model. HCC samples were divided into high-risk and low-risk groups based on the risk score's cut-off. Kaplan-Meier curve and Log-rank test were used to compare the overall survival (OS) of two risk groups. The OS was lower in the high-risk group than in the low-risk group. In addition, the time-dependent receiver operating characteristics revealed that the risk model could be used to predict the prognosis of HCC more accurately. The risk score also resulted as an independent risk factor for HCC prognosis (TCGA: HR = 2.45, 95% CI 1.53-3.92; ICGC: HR = 2.19, 95% CI 1.39-3.46). Moreover, the AUC of the risk score for diagnosing HCC was relatively higher (TCGA: AUC = 0.840, P < 0.05; ICGC: AUC = 0.795, P < 0.05). CONCLUSIONS: In a word, BAK1, BAX, CHMP2A, CHMP4C, CHMP6, GSDMC, GSDMD, and the pyroptosis-related risk model could be used to diagnose the HCC, and the risk score also resulted as an independent risk factor for the HCC prognosis.

Characteristics of peripheral blood Gamma-glutamyl transferase in different liver diseases.

ABSTRACT: Gamma-glutamyl transferase (GGT) is a marker of oxidative stress and cholestasis. Because of its low specificity, clinicians usually ignore its diagnostic value.To compare and analyze the clinical features of GGT in primary biliary cholangitis (PBC), drug-induced liver injury (DILI), alcoholic liver disease (ALD), and non-alcoholic fatty liver disease (NAFLD) from the perspective of different causes instead of the severity of the disease.We observed the distribution characteristics and the rate of abnormality of GGT in the above 4 diseases. The relationship between GGT and alanine aminotransferase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), total serum bilirubin, triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol, high-density lipoprotein cholesterol was analyzed using Spearman correlation.The highest level of GGT was up to 1000.00 to 2000.00 U/L in PBC and DILI, and the highest level of GGT was more than 2000.00 U/L in ALD, yet the difference was not statistically significant (P > .05). The highest level of GGT was only about 200.00 U/L in NAFLD and was the lowest in 4 liver diseases. Also, GGT was positively correlated with ALP, TC in PBC and DILI. Also, in ALD, GGT was positively correlated with ALT, AST, ALP, TG, and TC. In NAFLD, GGT was positively correlated with ALT, AST, and TG.The abnormal GGT in PBC and cholestasis DILI was associated with cholestasis; in ALD, it was associated with oxidative stress and cholestasis, and in NAFLD, it was associated with oxidative stress. GGT levels had different characteristics in different liver diseases, which were closely related to the pathogenesis of liver diseases.

pH-Mediated Clustering of Exosomes: Breaking Through the Size Limit of Exosome Analysis in Conventional Flow Cytometry.

Exosomes have recently emerged as some of the most promising biomarkers for disease diagnosis. Due to their small sizes and composition heterogeneity, exosomes are difficult to detect by currently available platforms. Here, we report a pH-mediated assembly system that converts single nanosized exosomes into microsized clusters, which can be directly analyzed by conventional flow cytometry (FCM), breaking through the size limit of exosome analysis. We demonstrated the clinical utility of the pH-mediated clustering system by profiling the exosomal proteins from blood plasma samples of 33 cancer patients and 11 benign controls. The results indicated that the combination of MUC-1 and PD-L1 could serve as a new biomarker panel for the early diagnosis of liver cancer with high clinical accuracy. This pH-mediated assembly strategy allows rapid, sensitive, and high-throughput analysis of exosome biomarkers by conventional FCM, which can be easily refined for use in both basic and clinical settings.

Assessment of cholestasis in drug-induced liver injury by different methods.

Cholestasis in drug-induced liver injury (DILI) can be assessed by biochemical and pathologic methods, but the agreement between the 2 methods remains unclear.The aim of this study was to identify the accurate method for assessment of cholestasis in DILI.The DILI standard established and revised by the Council for International Organizations of Medical Sciences (CIOMS) (R values were calculated by liver function at different time points), cholestatic liver disease guideline (European Association for the Study of the Liver, EASL), and liver pathology were used to assess, compare, and analyze the cholestasis in 133 patients with DILI.The R values at different time points in CIOMS standard had no statistical difference for the assessment of cholestatic DILI (a = 0.05, χ = 1.51, P = .679). There were statistical differences among the results of CIOMS, EASL, and pathology (a = 0.05, χ = 99.97, P < .001). EASL standard had no statistical difference with pathology (a = 0.003, χ = 8.00, P = .005).CIOMS and EASL standards based on biochemical parameters underestimated cholestatic DILI, as compared to liver pathology.