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PURPOSE: To identify immune-related co-expressed genes that promote CD8+ T cell infiltration in bladder cancer, and to explore the interactions among relevant genes in the tumor microenvironment. METHOD: We obtained bladder cancer gene matrix and clinical information data from TCGA, GSE32894 and GSE48075. The "estimate" package was used to calculate tumor purity and immune score. The CIBERSORT algorithm was used to assess CD8+ T cell proportions. Weighted gene co-expression network analysis was used to identify the co-expression modules with CD8+ T cell proportions and bladder tumor purity. Subsequently, we performed correlation analysis among angiogenesis factors, angiogenesis inhibitors, immune inflammatory responses, and CD8+ T cell related genes in tumor microenvironment. RESULTS: A CD8+ T cell related co-expression network was identified. Eight co-expressed genes (PSMB8, PSMB9, PSMB10, PSME2, TAP1, IRF1, FBOX6, ETV7) were identified as CD8+ T cell-related genes that promoted infiltration of CD8+ T cells, and were enriched in the MHC class I tumor antigen presentation process. The proteins level encoded by these genes (PSMB10, PSMB9, PSMB8, TAP1, IRF1, and FBXO6) were lower in the high clinical grade patients, which suggested the clinical phenotype correlation both in mRNA and protein levels. These factors negatively correlated with angiogenesis factors and positively correlated with angiogenesis inhibitors. PD-1 and PD-L1 positively correlated with these genes which suggested PD-1 expression level positively correlated with the biological process composed by these co-expression genes. In the high expression group of these genes, inflammation and immune response were more intense, and the tumor purity was lower, suggesting that these genes were immune protective factors that improved the prognosis in patients with bladder cancer. CONCLUSION: These co-expressed genes promote high levels of infiltration of CD8+ T cells in an immunoproteasome process involved in MHC class I molecules. The mechanism might provide new pathways for treatment of patients who are insensitive to PD-1 immunotherapy due to low degrees of CD8+ T cell infiltration.
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BACKGROUND: Papillary renal cell carcinoma (PRCC) accounts for 15% of all renal cell carcinomas. The molecular mechanisms of renal papillary cell carcinoma remain unclear, and treatments for advanced disease are limited. RESULT: We built the computing model as follows: Risk score = 1.806 * TPX2 - 0.355 * TXNRD2 - 0.805 * SLC6A20. The 3-year AUC of overall survival was 0.917 in the training set (147 PRCC samples) and 0.760 in the test set (142 PRCC samples). Based on the robust model, M2 macrophages showed positive correlation with risk score, while M1 macrophages were the opposite. PRCC patients with low risk score showed higher tumor mutation burden. TPX2 is a risk factor, and co-expression factors were enriched in cell proliferation and cancer-related pathways. Finally, the proliferation and invasion of PRCC cell line were decreased in the TPX2 reduced group, and the differential expression was identified. TPX2 is a potential risk biomarker which involved in cell proliferation in PRCC. CONCLUSION: We conducted a study to develop a three gene model for predicting prognosis in patients with papillary renal cell carcinoma. Our findings may provide candidate biomarkers for prognosis that have important implications for understanding the therapeutic targets of papillary renal cell carcinoma. METHOD: Gene expression matrix and clinical data were obtained from TCGA (The Cancer Genome Atlas), GSE26574, GSE2048, and GSE7023. Prognostic factors were identified using "survival" and "rbsurv" packages, and a risk score was constructed using Multivariate Cox regression analysis. The co-expression networks of the factors in model were constructed using the "WGCNA" package. The co-expression genes of factors were enriched and displayed the biological process. Based on this robust risk model, immune cells infiltration proportions and tumor mutation burdens were compared between risk groups. Subsequently, using the PRCC cell line, the role of TPX2 was determined by Cell proliferation assay, 5-Ethynyl-20-deoxyuridine assay and Transwell assay.
