No abstract

Background and Aims: The intratumoral microbiome has been reported to regulate the development and progression of cancers. We aimed to characterize intratumoral microbial heterogeneity (IMH) and establish microbiome-based molecular subtyping of HBV-related HCC to elucidate the correlation between IMH and HCC tumorigenesis. Approach and Results: A case-control study was designed to investigate microbial landscape and characteristic microbial signatures of HBV-related HCC tissues adopting metagenomics next-generation sequencing. Microbiome-based molecular subtyping of HCC tissues was established by nonmetric multidimensional scaling. The tumor immune microenvironment of 2 molecular subtypes was characterized by EPIC and CIBERSORT based on RNA-seq and verified by immunohistochemistry. The gene set variation analysis was adopted to explore the crosstalk between the immune and metabolism microenvironment. A prognosis-related gene risk signature between 2 subtypes was constructed by the weighted gene coexpression network analysis and the Cox regression analysis and then verified by the Kaplan-Meier survival curve. IMH demonstrated in HBV-related HCC tissues was comparably lower than that in chronic hepatitis tissues. Two microbiome-based HCC molecular subtypes, defined as bacteria- and virus-dominant subtypes, were established and significantly correlated with discrepant clinical-pathologic features. Higher infiltration of M2 macrophage was detected in the bacteria-dominant subtype with to the virus-dominant subtype, accompanied by multiple upregulated metabolism pathways. Furthermore, a 3-gene risk signature containing CSAG4, PIP4P2, and TOMM5 was filtered out, which could predict the clinical prognosis of HCC patients accurately using the Cancer Genome Atlas data. Conclusions: Microbiome-based molecular subtyping demonstrated IMH of HBV-related HCC was correlated with a disparity in clinical-pathologic features and tumor microenvironment (TME), which might be proposed as a biomarker for prognosis prediction of HCC.

Aims and objectives Acute-on-chronic hepatitis B liver failure (ACHBLF) is a critical clinical syndrome with a high short-term mortality evolved from chronic hepatitis B (CHB)-related liver disease. Prediction of mortality risk and early intervention can improve the prognosis of patients. This study aimed to develop and validate the nomogram for short-time mortality estimation in ACHBLF patients defined according to Asian Pacific Association for the Study of the Liver (APASL). Methods A study of 105 ACHBLF patients with 90-day follow up was performed to develop the nomogram. Patients were randomly assigned to derivation cohort (n = 75) and validation cohort (n = 35) according to 7:3. Concordance index (C-index), calibration curve and decision curve analysis (DCA) were used to evaluate the nomogram. We also compared the nomogram with APASL ACLF research consortium (AARC) score, model for end-stage liver disease (MELD) score, MELD with serum sodium (MELD-Na) score and albumin-bilirubin (ALBI) score. The nomogram was validated using an external cohort including 40 patients. Results The 28-day and 90-day mortality of 105 patients were respectively 49.52% and 55.24%. Albumin (ALB), international normalized ratio (INR) and estimated glomerular filtration rate (eGFR) were independent predictors for 28-day mortality; INR and eGFR were independent predictors for 90-day mortality. C-index of Nomogram-1 for 28-day mortality and Nomogram-2 for 90-day mortality were respectively 0.82 and 0.81. Calibration curve and Hosmer–Lemeshow test (Nomogram-1, 0.323; Nomogram-2, 0.231) showed optimal agreement between observed and predicted death. Areas under receiver operator characteristic curve(AUROC) of Nomogram-1(0.772) and Nomogram-2(0.771) were larger compared with AARC, MELD, MELD-Na and ALBI score. The results were well estimated in the external validation cohort. Conclusions This study highlighted the predictive value of eGFR, and the nomogram based on INR and eGFR could effectively estimate individualized risk for short-term mortality of ACHBLF patients defined according to APASL.

BackgroundThe efficacy of current therapeutic schedule is limited owing to fibroproliferative tumor microenvironment (TME) of cholangiocarcinoma, compelling a search for new therapeutic targets.MethodsGene expression profiles and methylation profiles were obtained from UCSC Xena. Consensus clustering was performed on the transcriptome data of cholangiocarcinoma to determine the different immune subtypes. The differentially expressed genes (DEGs) between hot tumor and cold tumors were identified. ESTIMATE was used to assess immune score, and the cases were separated into relatively superior and inferior immune score groups. Single-sample gene set enrichment analysis was applied to assess 28 immune cells in the cholangiocarcinoma microenvironment. Unsupervised consensus was applied for methylation profiling to distribute the high and low methylation groups. The correlation between DNA methylation and mRNA expression was investigated, and the relationship between the ATP2B1 gene and the immune microenvironment was explored. Finally, 77 cases of intrahepatic cholangiocarcinoma (ICC) were collected for verification.ResultsSeven subtypes were related to patient outcomes (P=0.005). The proportions of CD8+ T cells in the “hot” immune type was significantly greater than that in the “cold” immune type (P<0.05). Next, DEGs and DNA methylation-governed genes were intersected, and ATP2B1 was identified as a prognosis factor in ICC (P=0.035). ATP2B1 expression was positively correlated with immune scores (P=0.005, r=0.458), the levels of infiltrating CD8+ T cells (P=0.004, r=0.47), and CD4+ T cells (P=0.027, r=0.37). Immunohistochemistry confirmed that the amounts of CD8+ and CD4+ T cells were significantly higher in ICC tissue samples than in tissues with ATP2B1 overexpression (P<0.05).ConclusionsATP2B1 overexpression can activate immune signals and prompt cold tumor response.