Xilang Chen

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) is characterized by an immune-suppressive microenvironment, which contributes to tumor progression, metastasis, and immunotherapy resistance. Identification of HCC-intrinsic factors regulating the immunosuppressive microenvironment is urgently needed. Here, we aimed to elucidate the role of SYR-Related High-Mobility Group Box 18 (SOX18) in inducing immunosuppression and to validate novel combination strategies for SOX18-mediated HCC progression and metastasis. METHODS: The role of SOX18 in HCC was investigated in orthotopic allografts and diethylinitrosamine/carbon tetrachloride-induced spontaneous models by using murine cell lines, adeno-associated virus 8, and hepatocyte-specific knockin and knockout mice. The immune cellular composition in the HCC microenvironment was evaluated by flow cytometry and immunofluorescence. RESULTS: SOX18 overexpression promoted the infiltration of tumor-associated macrophages (TAMs) and regulatory T cells (Tregs) while diminishing cytotoxic T cells to facilitate HCC progression and metastasis in cell-derived allografts and chemically induced HCC models. Mechanistically, transforming growth factor-beta 1 (TGF-β1) upregulated SOX18 expression by activating the Smad2/3 complex. SOX18 transactivated chemokine (C-X-C motif) ligand 12 (CXCL12) and programmed death ligand 1 (PD-L1) to induce the immunosuppressive microenvironment. CXCL12 knockdown significantly attenuated SOX18-induced TAMs and Tregs accumulation and HCC dissemination. Antagonism of chemokine receptor 4 (CXCR4), the cognate receptor of CXCL12, or selective knockout of CXCR4 in TAMs or Tregs likewise abolished SOX18-mediated effects. TGFβR1 inhibitor Vactosertib or CXCR4 inhibitor AMD3100 in combination with anti-PD-L1 dramatically inhibited SOX18-mediated HCC progression and metastasis. CONCLUSIONS: SOX18 promoted the accumulation of immunosuppressive TAMs and Tregs in the microenvironment by transactivating CXCL12 and PD-L1. CXCR4 inhibitor or TGFβR1 inhibitor in synergy with anti-PD-L1 represented a promising combination strategy to suppress HCC progression and metastasis.

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with high incidence, recurrence, and metastasis rates. The emergence of immunotherapy has improved the treatment of advanced HCC, but problems such as drug resistance and immune-related adverse events still exist in clinical practice. The immunosuppressive tumor microenvironment (TME) of HCC restricts the efficacy of immunotherapy and is essential for HCC progression and metastasis. Therefore, it is necessary to elucidate the mechanisms behind immunosuppressive TME to develop and apply immunotherapy. This review systematically summarizes the pathogenesis of HCC, the formation of the highly heterogeneous TME, and the mechanisms by which the immunosuppressive TME accelerates HCC progression and metastasis. We also review the status of HCC immunotherapy and further discuss the existing challenges and potential therapeutic strategies targeting immunosuppressive TME. We hope to inspire optimizing and innovating immunotherapeutic strategies by comprehensively understanding the structure and function of immunosuppressive TME in HCC.

HMGB1-induced KLF7 overexpression facilitates HCC progression and metastasis by upregulating TLR4 and PTK2. Genetic ablation of KLF7 via AAV gene therapy and combined blockade of TLR4 and PTK2 represents promising therapy strategies for KLF7-positive HCC patients.

We demonstrated the essentiality of ELF4 in the metastatic process of CRC, and targeting the ELF4-relevant positive feedback circuit might represent a novel therapeutic strategy.

Background: Cuproptosis is a newly defined form of cell death, whether cuproptosis involved in hepatocellular carcinoma (HCC) remains elusive. Method: We obtained patients’ RNA expression data and follow-up information from University of California Santa Cruz (UCSC) and The Cancer Genome Atlas (TCGA). We analyzed the mRNA level of Cuproptosis-related genes (CRGs) and performed univariate Cox analysis. Liver hepatocellular carcinoma (LIHC) was chosen for further investigation. Real-Time quantitative PCR (RT-qPCR), Western blotting (WB), Immunohistochemical (IHC), and Transwell assays were used to determine expression patterns and functions of CRGs in LIHC. Next, we identified CRGs-related lncRNAs (CRLs) and differentially expressed CRLs between HCC and normal cases. Univariate Cox analysis, least absolute shrinkage selection operator (LASSO) analysis and Cox regression analysis were used to construct the prognostic model. Univariate and multivariate Cox analysis was used to assess whether the risk model can act as an independent risk factor of overall survival duration. Different risk groups performed immune correlation analysis, tumor mutation burden (TMB), and Gene Set Enrichment Analysis (GSEA) analysis were performed in different risk groups. Finally, we assessed the performance of the predictive model in drug sensitivity. Results: CRGs expression levels have significant differences between tumor and normal tissues. High expression of Dihydrolipoamide S-Acetyltransferase ( DLAT ) correlated to metastasis of HCC cells and indicated poor prognosis for HCC patients. Our prognostic model consisted of four cuproptosis-related lncRNA (AC011476.3, AC026412.3, NRAV, MKLN1-AS). The prognostic model performed well in predicting survival rates. The results from Cox regression analysis suggested that risk score can serve as an independent prognostic element for survival durations. Survival analysis revealed that low risk patients have extended survival periods compared with those with high risk. The results of the immune analysis indicated that risk score has a positive correlation with B cell and CD4 + T cell Th2, while has a negative relationship with endothelial cell and hematopoietic cells. Besides, immune checkpoint genes have higher expression folds in the high-risk set than in the low-risk set. The high-risk group had higher rates of genetic mutation than the low-risk set while having a shorter survival time. GSEA revealed the signaling pathways enriched in the high-risk group were mostly immune-related, while metabolic-related pathways were enriched in the low-risk group. Drugs sensitivity analysis indicated that our model has the ability to predict the efficacy of clinical treatment. Conclusion: The Cuproptosis-related lncRNAs prognostic formula is a novel predictor of HCC patients’ prognosis and drug sensitivity.