The causal effect of gut microbiota on hepatic encephalopathy: a mendelian randomization analysis.

BACKGROUND: There is growing evidence for a relationship between gut microbiota and hepatic encephalopathy (HE). However, the causal nature of the relationship between gut microbiota and HE has not been thoroughly investigated. METHOD: This study utilized the large-scale genome-wide association studies (GWAS) summary statistics to evaluate the causal association between gut microbiota and HE risk. Specifically, two-sample Mendelian randomization (MR) approach was used to identify the causal microbial taxa for HE. The inverse variance weighted (IVW) method was used as the primary MR analysis. Sensitive analyses were performed to validate the robustness of the results. RESULTS: The IVW method revealed that the genus Bifidobacterium (OR = 0.363, 95% CI: 0.139-0.943, P = 0.037), the family Bifidobacteriaceae (OR = 0.359, 95% CI: 0.133-0.950, P = 0.039), and the order Bifidobacteriales (OR = 0.359, 95% CI: 0.133-0.950, P = 0.039) were negatively associated with HE. However, no causal relationship was observed among them after the Bonferroni correction test. Neither heterogeneity nor horizontal pleiotropy was found in the sensitivity analysis. CONCLUSION: Our MR study demonstrated a potential causal association between Bifidobacterium, Bifidobacteriaceae, and Bifidobacteriales and HE. This finding may provide new therapeutic targets for patients at risk of HE in the future.

Inflammation-related nomogram for predicting survival of patients with unresectable hepatocellular carcinoma received conversion therapy.

BACKGROUND: The efficacy of conversion therapy for patients with unresectable hepatocellular carcinoma (HCC) is a common clinical concern. AIM: To analyse the prognostic factors of overall survival (OS) in patients with unresectable HCC who received conversion therapy. METHODS: One hundred and fifty patients who met the inclusion criteria were enrolled and divided into a training cohort (n = 120) and a validation cohort (n = 30). Using the independent risk factors in the training cohort, a nomogram model was constructed to predict OS for patients treated with transarterial chemoembolization following hepatic resection. The nomogram was internally validated with the bootstrapping method. The predictive performance of nomogram was assessed by Harrell's concordance index (C-index), calibration plot and time-dependent receiver operating characteristic curves and compared with six other conventional HCC staging systems. RESULTS: Multivariate Cox analysis identified that albumin, blood urea nitrogen, gamma-glutamyl transpeptidase to platelet ratio, platelet to lymphocyte ratio, macrovascular invasion and tumour number were the six independent prognostic factors correlated with OS in nomogram model. The C-index in the training cohort and validation cohort were 0.752 and 0.807 for predicting OS, which were higher than those of the six conventional HCC staging systems (0.563 to 0.715 for the training cohort and 0.458 to 0.571 for the validation cohort). The calibration plots showed good consistency between the nomogram prediction of OS and the actual observations of OS. Decision curve analyses indicated satisfactory clinical utility. With a total nomogram score of 196, patients were accurately classified into low-risk and high-risk groups. Furthermore, we have deployed the model into online calculators that can be accessed for free at https://ctmodelforunresectablehcc.shinyapps.io/DynNomapp/. CONCLUSION: The nomogram achieved optimal individualized prognostication of OS in HCC patients who received conversion therapy, which could be a useful clinical tool to help guide postoperative personalized interventions and prognosis judgement.

Identification of circRNAs involved in the development of hepatocellular carcinoma after insufficient radiofrequency ablation.

Previous studies have reported that circular RNAs (circRNAs) play a key role in the pathogenesis and progression of various diseases. In the present study, we aimed to identify potential circRNAs associated with the progression of hepatocellular carcinoma (HCC) after insufficient radiofrequency ablation (IRFA). A xenograft mouse IRFA model was initially established, and immunohistochemical staining (IHC) and polymerase chain reaction (PCR) were performed to confirm the expression of programmed cell death-ligand 1 (PD-L1) and vascular endothelial growth factor receptor-1 (VEGFR-1). CircRNA expression alterations were screened by next-generation sequencing (RNA-seq). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to predict the function of genes coding differentially expressed circRNAs. The selected circRNAs were validated utilizing PCR and Sanger sequencing. The relationships between circRNAs, microRNAs, PD-L1, and VEGFR-1 were predicted by bioinformatics. Overall, a total of 612 circRNAs were differentially expressed in IRFA-treated subcutaneous tumorigenesis tissue. Among them, 435 circRNAs were significantly upregulated and 177 circRNAs were downregulated. GO and KEGG analyses were employed to predict the functions of these circRNAs. Thereafter, quantitative reverse transcription PCR (qRT-PCR) assays determined that these seven circRNAs were overexpressed in the IRFA group, which was consistent with the RNA-seq results. Based on the bioinformatic analysis, seven circRNAs confirmed by Sanger sequencing were predicted to likely regulate PD-L1 and VEGFR-1 expression levels by functioning as sponges for microRNAs (miRNAs) and forming a circRNA-miRNA-PD-L1/VEGFR-1 regulatory network. Finally, IHC and qRT-PCR of PD-L1 and VEGFR-1 confirmed the activation of this pathway. Taken together, we report that differentially expressed circRNAs might simultaneously regulate PD-L1 and VEGFR-1 in the IRFA tissues, which provides a novel view of circRNAs in HCC progression after the IRFA procedure.