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Background and Aims: NASH-HCC is inherently resistant to immune checkpoint blockade, but its tumor immune microenvironment is largely unknown., Approach and Results: We applied the imaging mass cytometry to construct a spatially resolved single-cell atlas from the formalin-fixed and paraffin-embedded tissue sections from patients with NASH-HCC, virus-HCC (HBV-HCC and HCV-HCC), and healthy donors. Based on 35 biomarkers, over 750,000 individual cells were categorized into 13 distinct cell types, together with the expression of key immune functional markers. Higher infiltration of T cells, myeloid-derived suppressor cell (MDSCs), and tumor-associated macrophages (TAMs) in HCC compared to controls. The distribution of immune cells in NASH-HCC is spatially heterogeneous, enriched at adjacent normal tissues and declined toward tumors. Cell-cell connections analysis revealed the interplay of MDSCs and TAMs with CD8 + T cells in NASH-HCC. In particular, exhausted programmed cell death 1 (PD-1 + )CD8 + T cells connected with programmed cell death-ligand 1 (PD-L1 + )/inducible T cell costimulator (ICOS + ) MDSCs and TAMs in NASH-HCC, but not in viral HCC. In contrast, CD4 + /CD8 + T cells with granzyme B positivity were reduced in NASH-HCC. Tumor cells expressed low PD-L1 and showed few connections with immune cells., Conclusions: Our work provides the first detailed spatial map of single-cell phenotypes and multicellular connections in NASH-HCC. We demonstrate that interactions between MDSCs and TAMs with effector T cells underlie immunosuppression in NASH-HCC and are an actionable target., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

Ethnopharmacological Relevance: Xiaoyaosan is a traditional Chinese herbal formula that has long been used to treat liver cirrhosis, liver failure, and hepatocarcinoma (HCC). However, little is known about its mechanism of action and targets in treating chronic liver disease., Aim of the Study: This study aimed to detect the critical transition of HCC progression and to explore the regulatory mechanism and targets of Xiaoyaosan treating liver cirrhosis (cirrhosis) using integrative medicinal research involving system biology and pharmacology., Materials and Methods: We recruited chronic liver disease participants to obtain gene expression data and applied the dynamic network biomarker (DNB) method to identify molecular markers and the critical transition. We combined network pharmacology and DNB analysis to locate the potential DNBs (targets). Then we validated the DNBs in the liver cirrhosis rat models using Xiaoyaosan treatment. The expression of genes encoding the four DNBs, including Cebpa, Csf1, Egfr, and Il7r, were further validated in rat liver tissue using Western blot analysis., Results: We found EGFR, CEBPA, Csf1, Ccnb1, Rrmm2, C3, Il7r, Ccna2, and Peg10 overlap in the DNB list and Xiaoyaosan-Target-Disease (XTD) network constructed using network pharmacology databases. We investigated the diagnostic ability of each member in the DNB cluster and found EGFR, CEBPA, CSF1, and IL7R had high diagnostic abilities with AUC >0.7 and P-value < 0.05. We validated these findings in rats and found that liver function improved significantly and fibrotic changes were relieved in the Xiaoyaosan treatment group. The expression levels of CSF1 and IL7R in the Xiaoyaosan group were significantly lower than those in the cirrhosis model group. In contrast, CEBPA expression in the Xiaoyaosan group was significantly higher than that in the cirrhosis model group. The expression of EGFR in the Xiaoyaosan group was slightly decreased than in the model group but not significantly., Conclusion: Using the DNB method and network pharmacology approach, this study revealed that CEBPA, IL7R, EGFR, and CSF1 expression was remarkably altered in chronic liver disease and thus, may play an important role in driving the progression of cirrhosis. Therefore, CEBPA, IL7R, EGFR, and CSF1 may be important targets of Xiaoyaosan in treating cirrhosis and can be considered for developing novel therapeutics., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Hepatitis B virus (HBV)-induced hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths in Asia and Africa. Developing effective and non-invasive biomarkers of HCC for individual patients remains an urgent task for early diagnosis and convenient monitoring. Analyzing the transcriptomic profiles of peripheral blood mononuclear cells from both healthy donors and patients with chronic HBV infection in different states (i.e. HBV carrier, chronic hepatitis B, cirrhosis, and HCC), we identified a set of 19 candidate genes according to our algorithm of dynamic network biomarkers. These genes can both characterize different stages during HCC progression and identify cirrhosis as the critical transition stage before carcinogenesis. The interaction effects (i.e. co-expressions) of candidate genes were used to build an accurate prediction model: the so-called edge-based biomarker. Considering the convenience and robustness of biomarkers in clinical applications, we performed functional analysis, validated candidate genes in other independent samples of our collected cohort, and finally selected COL5A1, HLA-DQB1, MMP2, and CDK4 to build edge panel as prediction models. We demonstrated that the edge panel had great performance in both diagnosis and prognosis in terms of precision and specificity for HCC, especially for patients with alpha-fetoprotein-negative HCC. Our study not only provides a novel edge-based biomarker for non-invasive and effective diagnosis of HBV-associated HCC to each individual patient but also introduces a new way to integrate the interaction terms of individual molecules for clinical diagnosis and prognosis from the network and dynamics perspectives., (© The Author(s) 2019. Published by Oxford University Press on behalf of Journal of Molecular Cell Biology, IBCB, SIBS, CAS.)

Developing predictive biomarkers that can detect the tipping point before metastasis of hepatocellular carcinoma (HCC), is critical to prevent further irreversible deterioration. To discover such early-warning signals or biomarkers of pulmonary metastasis in HCC, we analyse time-series gene expression data in spontaneous pulmonary metastasis mice HCCLM3-RFP model with our dynamic network biomarker (DNB) method, and identify CALML3 as a core DNB member. All experimental results of gain-of-function and loss-of-function studies show that CALML3 could indicate metastasis initiation and act as a suppressor of metastasis. We also reveal the biological role of CALML3 in metastasis initiation at a network level, including proximal regulation and cascading influences in dysfunctional pathways. Our further experiments and clinical samples show that DNB with CALML3 reduced pulmonary metastasis in liver cancer. Actually, loss of CALML3 predicts shorter overall and relapse-free survival in postoperative HCC patients, thus providing a prognostic biomarker and therapy target in HCC.

Little is known about how chronic inflammation contributes to the progression of hepatocellular carcinoma (HCC), especially the initiation of cancer. To uncover the critical transition from chronic inflammation to HCC and the molecular mechanisms at a network level, we analyzed the time-series proteomic data of woodchuck hepatitis virus/c-myc mice and age-matched wt-C57BL/6 mice using our dynamical network biomarker (DNB) model. DNB analysis indicated that the 5th month after birth of transgenic mice was the critical period of cancer initiation, just before the critical transition, which is consistent with clinical symptoms. Meanwhile, the DNB-associated network showed a drastic inversion of protein expression and coexpression levels before and after the critical transition. Two members of DNB, PLA2G6 and CYP2C44, along with their associated differentially expressed proteins, were found to induce dysfunction of arachidonic acid metabolism, further activate inflammatory responses through inflammatory mediator regulation of transient receptor potential channels, and finally lead to impairments of liver detoxification and malignant transition to cancer. As a c-Myc target, PLA2G6 positively correlated with c-Myc in expression, showing a trend from decreasing to increasing during carcinogenesis, with the minimal point at the critical transition or tipping point. Such trend of homologous PLA2G6 and c-Myc was also observed during human hepatocarcinogenesis, with the minimal point at high-grade dysplastic nodules (a stage just before the carcinogenesis). Our study implies that PLA2G6 might function as an oncogene like famous c-Myc during hepatocarcinogenesis, while downregulation of PLA2G6 and c-Myc could be a warning signal indicating imminent carcinogenesis.