The immune reprogramming mediated by MZB1 reveals the immune and prognostic features of clear cell renal cell carcinoma

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Objective: Immune reprogramming plays a crucial role in establishing the tumor immune microenvironment (TIME). This study ims to explore potential regulatory factors of TIME and their impact on the prognosis and immunotherapy of clear cell renal cell carcinoma (ccRCC). Methods: We obtained the RNA sequencing data of 529 ccRCC samples from The Cancer Genome Atlas (TCGA) database. The ESTIMATE algorithm and Kaplan-Meier survival curve analysis were applied to investigate the relationship between immune cell and stromal cell infiltration levels in all ccRCC samples and patient overall survival (OS). Immune genes significantly associated with ccRCC prognosis were identified through univariate Cox regression analysis and protein-protein interaction network analysis. The individual key immune genes were identified by the gene alteration analysis for further study, such as clinical feature correlation analysis, gene set enrichment analysis (GSEA), estimation of tumor-infiltrating immune cell (TIC) proportions, immune checkpoint correlation analysis, and drug sensitivity analysis. These processes were designed to discover the potential regulatory effects of the key immune genes in TIME. Finally, the expression of the key immune gene was confirmed using the UALCAN and Human Protein Atlas (HPA) databases. Results: We obtained seven key genes significantly associated with the prognosis of ccRCC via comprehensive analysis, which were IL6, PLG, IGLL5, MZB1, CCL13, CD19, and POU2AF1. The gene alteration analyses indicated that MZB1 presented the highest mutation rate and was associated with the survival in 354 patients with ccRCC. And thus, we took the MZB1 for further study. Other analyses showed that MZB1 expression was up-regulated in ccRCC tumor samples and negatively correlated with survival. In the immune microenvironment of ccRCC, we found a higher level of immune infiltration of several TICs such as CD8 + T cells, Tregs, and macrophages. Furthermore, MZB1 expression was positively correlated with the infiltration level of eight TICs, including B memory cells, CD4 + T cells, CD8 + T cells, plasma cells, and Tregs. It also exhibited a positive correlation with six common immune checkpoint molecules, including PDCD-1, CTLA-4, and LAG3, including PDCD-1, CTLA-4, and LAG3. Drug sensitivity analysis suggested that high expression of MZB1 reduced the sensitivity to PD-1 immune checkpoint inhibitors, such as nivolumab and pembrolizumab. The GSEA enrichment analysis demonstrated that the MZB1 high-expression group was mainly associated with immune-related pathways such as NF-κB signaling, interferon reaction (IFNα, IFNγ), and IL2-STAT5 signaling. In contrast, the enrichment results of the MZB1 low-expression group were mainly associated with tumor metabolism, such as the bile acid metabolism, the fatty acid metabolism, the oxidative phosphorylation and other metabolic pathways. Finally, we found that MZB1 protein showed high expression in ccRCC patients in the UALCAN database, regrettably, the HPA immunohistochemistry database did not detect the expression of MZB1. Conclusion: MZB1 promotes the formation of the tumor immune-suppressive microenvironment by mediating immune reprogramming, including the recruitment of immunosuppressive TICs and the expression of immune checkpoint, and it is prospective to be a prognostic factor for ccRCC immunotherapy.
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The immune reprogramming mediated by MZB1 reveals the immune and prognostic features of clear cell renal cell carcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The immune reprogramming mediated by MZB1 reveals the immune and prognostic features of clear cell renal cell carcinoma Shangjin Chen, Shuangze Zhong, Yuancheng Luo, Hansheng Lin, Guofan Hu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3833766/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective Immune reprogramming plays a crucial role in establishing the tumor immune microenvironment (TIME). This study ims to explore potential regulatory factors of TIME and their impact on the prognosis and immunotherapy of clear cell renal cell carcinoma (ccRCC). Methods We obtained the RNA sequencing data of 529 ccRCC samples from The Cancer Genome Atlas (TCGA) database. The ESTIMATE algorithm and Kaplan-Meier survival curve analysis were applied to investigate the relationship between immune cell and stromal cell infiltration levels in all ccRCC samples and patient overall survival (OS). Immune genes significantly associated with ccRCC prognosis were identified through univariate Cox regression analysis and protein-protein interaction network analysis. The individual key immune genes were identified by the gene alteration analysis for further study, such as clinical feature correlation analysis, gene set enrichment analysis (GSEA), estimation of tumor-infiltrating immune cell (TIC) proportions, immune checkpoint correlation analysis, and drug sensitivity analysis. These processes were designed to discover the potential regulatory effects of the key immune genes in TIME. Finally, the expression of the key immune gene was confirmed using the UALCAN and Human Protein Atlas (HPA) databases. Results We obtained seven key genes significantly associated with the prognosis of ccRCC via comprehensive analysis, which were IL6, PLG, IGLL5, MZB1, CCL13, CD19, and POU2AF1. The gene alteration analyses indicated that MZB1 presented the highest mutation rate and was associated with the survival in 354 patients with ccRCC. And thus, we took the MZB1 for further study. Other analyses showed that MZB1 expression was up-regulated in ccRCC tumor samples and negatively correlated with survival. In the immune microenvironment of ccRCC, we found a higher level of immune infiltration of several TICs such as CD8 + T cells, Tregs, and macrophages. Furthermore, MZB1 expression was positively correlated with the infiltration level of eight TICs, including B memory cells, CD4 + T cells, CD8 + T cells, plasma cells, and Tregs. It also exhibited a positive correlation with six common immune checkpoint molecules, including PDCD-1, CTLA-4, and LAG3, including PDCD-1, CTLA-4, and LAG3. Drug sensitivity analysis suggested that high expression of MZB1 reduced the sensitivity to PD-1 immune checkpoint inhibitors, such as nivolumab and pembrolizumab. The GSEA enrichment analysis demonstrated that the MZB1 high-expression group was mainly associated with immune-related pathways such as NF-κB signaling, interferon reaction (IFNα, IFNγ), and IL2-STAT5 signaling. In contrast, the enrichment results of the MZB1 low-expression group were mainly associated with tumor metabolism, such as the bile acid metabolism, the fatty acid metabolism, the oxidative phosphorylation and other metabolic pathways. Finally, we found that MZB1 protein showed high expression in ccRCC patients in the UALCAN database, regrettably, the HPA immunohistochemistry database did not detect the expression of MZB1. Conclusion MZB1 promotes the formation of the tumor immune-suppressive microenvironment by mediating immune reprogramming, including the recruitment of immunosuppressive TICs and the expression of immune checkpoint, and it is prospective to be a prognostic factor for ccRCC immunotherapy. Biological sciences/Immunology/Immunotherapy Biological sciences/Cancer/Cancer microenvironment Biological sciences/Immunology ccRCC tumor immune microenvironment immune reprogramming immune checkpoints Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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This study ims to explore potential regulatory factors of TIME and their impact on the prognosis and immunotherapy of clear cell renal cell carcinoma (ccRCC).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe obtained the RNA sequencing data of 529 ccRCC samples from The Cancer Genome Atlas (TCGA) database. The ESTIMATE algorithm and Kaplan-Meier survival curve analysis were applied to investigate the relationship between immune cell and stromal cell infiltration levels in all ccRCC samples and patient overall survival (OS). Immune genes significantly associated with ccRCC prognosis were identified through univariate Cox regression analysis and protein-protein interaction network analysis. The individual key immune genes were identified by the gene alteration analysis for further study, such as clinical feature correlation analysis, gene set enrichment analysis (GSEA), estimation of tumor-infiltrating immune cell (TIC) proportions, immune checkpoint correlation analysis, and drug sensitivity analysis. These processes were designed to discover the potential regulatory effects of the key immune genes in TIME. Finally, the expression of the key immune gene was confirmed using the UALCAN and Human Protein Atlas (HPA) databases.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe obtained seven key genes significantly associated with the prognosis of ccRCC via comprehensive analysis, which were IL6, PLG, IGLL5, MZB1, CCL13, CD19, and POU2AF1. The gene alteration analyses indicated that MZB1 presented the highest mutation rate and was associated with the survival in 354 patients with ccRCC. And thus, we took the MZB1 for further study. 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The GSEA enrichment analysis demonstrated that the MZB1 high-expression group was mainly associated with immune-related pathways such as NF-κB signaling, interferon reaction (IFNα, IFNγ), and IL2-STAT5 signaling. In contrast, the enrichment results of the MZB1 low-expression group were mainly associated with tumor metabolism, such as the bile acid metabolism, the fatty acid metabolism, the oxidative phosphorylation and other metabolic pathways. 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