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Inhibiting IRE1?-endonuclease activity decreases tumor burden in a mouse model for hepatocellular carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) is a liver tumor that usually arises in patients with cirrhosis. Hepatic stellate cells are key players in the progression of HCC, as they create a fibrotic micro-environment and produce growth factors and cytokines that enhance tumor cell proliferation and migration. We assessed the role of endoplasmic reticulum (ER) stress in the cross-talk between stellate cells and HCC cells. Mice with a fibrotic HCC were treated with the IRE1?-inhibitor 4?8C, which reduced tumor burden and collagen deposition. By co-culturing HCC-cells with stellate cells, we found that HCC-cells activate IRE? in stellate cells, thereby contributing to their activation. Inhibiting IRE1? blocked stellate cell activation, which then decreased proliferation and migration of tumor cells in different in vitro 2D and 3D co-cultures. In addition, we also observed cell-line-specific direct effects of inhibiting IRE1? in tumor cells.

SUBMITTER: Pavlovic N

PROVIDER: S-EPMC7661042 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Inhibiting IRE1α-endonuclease activity decreases tumor burden in a mouse model for hepatocellular carcinoma.

Pavlović Nataša N Calitz Carlemi C Thanapirom Kess K Mazza Guiseppe G Rombouts Krista K Gerwins Pär P Heindryckx Femke F

eLife 20201026

Hepatocellular carcinoma (HCC) is a liver tumor that usually arises in patients with cirrhosis. Hepatic stellate cells are key players in the progression of HCC, as they create a fibrotic micro-environment and produce growth factors and cytokines that enhance tumor cell proliferation and migration. We assessed the role of endoplasmic reticulum (ER) stress in the cross-talk between stellate cells and HCC cells. Mice with a fibrotic HCC were treated with the IRE1α-inhibitor 4μ8C, which reduced tum ...[more]

PMID: 33103995

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Project description:Introduction: Tumor mutation burden (TMB) is an emerging biomarker for immunotherapy of hepatocellular carcinoma (HCC), but its value for clinical application has not been fully revealed.Materials and methods: We used the Wilcox test to identify the differentially expressed immune-related genes (DEIRGs) in groups with high and low TMB as well as screened the immune gene pairs related to prognosis using univariate Cox regression analysis. A LASSO Cox regression prognostic model was developed by combining The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) with the International Cancer Genome Consortium (ICGC) LIRI-JP cohort, and internal (TCGA, ICGC) and external (GSE14520) validation analyses were conducted on the predictive value of the model. We also explored the relationship between the prognostic model and tumor microenvironment via the ESTIMATE algorithm and performed clinical correlation analysis by the chi-square test, revealing its underlying molecular mechanism with the help of Gene Set Enrichment Analysis (GSEA).Results: The prognostic model consisting of 15 immune gene pairs showed high predictive value for short- and long-term survival of HCC in three independent cohorts. Based on univariate multivariate Cox regression analysis, the prognostic model could be used to independently predict the prognosis in each independent cohort. The immune score, stromal score, and estimated score values were lower in the high-risk group than in the low-risk group. As shown by the chi-square test, the prognostic model exhibited an obvious correlation with the tumor stage [American Joint Committee on Cancer tumor-node-metastasis (AJCC-TNM) (p < 0.001), Barcelona Clinic Liver Cancer (BCLC) (p = 0.003)], histopathological grade (p = 0.033), vascular invasion (p = 0.009), maximum tumor diameter (p = 0.013), and background of liver cirrhosis (p < 0.001). GSEA revealed that the high-risk group had an enrichment of many oncology features, including the cell cycle, mismatch repair, DNA replication, RNA degradation, etc.Conclusion: Our research developed and validated a reliable prognostic model associated with TMB for HCC, which may help to further enrich the therapeutic targets of HCC.

Project description:BackgroundHepatocellular carcinoma (HCC) was the sixth common malignancies characteristic with highly aggressive in the world. It was well established that tumor mutation burden (TMB) act as indicator of immunotherapeutic responsiveness in various tumors. However, the role of TMB in tumor immune microenvironment (TIME) is still obscure.MethodThe mutation data was analyzed by employing "maftools" package. Weighted gene co-expression network analysis (WGCNA) was implemented to determine candidate module and significant genes correlated with TMB value. Differential analysis was performed between different level of TMB subgroups employing R package "limma". Gene ontology (GO) enrichment analysis was implemented with "clusterProfiler", "enrichplot" and "ggplot2" packages. Then risk score signature was developed by systematical bioinformatics analyses. K-M survival curves and receiver operating characteristic (ROC) plot were further analyzed for prognostic validity. To depict comprehensive context of TIME, XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, CIBERSORT, and CIBERSORT-ABS algorithm were employed. Additionally, the potential role of risk score on immune checkpoint blockade (ICB) immunotherapy was further explored. The quantitative real-time polymerase chain reaction was performed to detect expression of HTRA3.ResultsTMB value was positively correlated with older age, male gender and early T status. A total of 75 intersection genes between TMB-related genes and differentially expressed genes (DEGs) were screened and enriched in extracellular matrix-relevant pathways. Risk score based on three hub genes significantly affected overall survival (OS) time, infiltration of immune cells, and ICB-related hub targets. The prognostic performance of risks score was validated in the external testing group. Risk-clinical nomogram was constructed for clinical application. HTRA3 was demonstrated to be a prognostic factor in HCC in further exploration. Finally, mutation of TP53 was correlated with risk score and do not interfere with risk score-based prognostic prediction.ConclusionCollectively, a comprehensive analysis of TMB might provide novel insights into mutation-driven mechanism of tumorigenesis further contribute to tailored immunotherapy and prognosis prediction of HCC.

Dataset Information

Inhibiting IRE1?-endonuclease activity decreases tumor burden in a mouse model for hepatocellular carcinoma.

Publications

Inhibiting IRE1α-endonuclease activity decreases tumor burden in a mouse model for hepatocellular carcinoma.

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