Dataset Information

Identification and Immunocorrelation of Prognosis-Related Genes Associated With Development of Muscle-Invasive Bladder Cancer.

ABSTRACT: Improved understanding of the molecular mechanisms and immunoregulation of muscle-invasive bladder cancer (MIBC) is essential to predict prognosis and develop new targets for therapies. In this study, we used the cancer genome atlas (TCGA) MIBC and GSE13507 datasets to explore the differential co-expression genes in MIBC comparing with adjacent non-carcinoma tissues. We firstly screened 106 signature genes by Weighted Gene Co-expression Network Analysis (WGCNA) and further identified 15 prognosis-related genes of MIBC using the univariate Cox progression analysis. Then we systematically analyzed the genetic alteration, molecular mechanism, and clinical relevance of these 15 genes. We found a different expression alteration of 15 genes in MIBC comparing with adjacent non-carcinoma tissues and normal tissues. Meanwhile, the biological functions and molecular mechanisms of them were also discrepant. Among these, we observed the ANLN was highly correlated with multiple cancer pathways, molecular function, and cell components, revealing ANLN may play a pivotal role in MIBC development. Next, we performed a consensus clustering of 15 prognosis-related genes; the results showed that the prognosis, immune infiltration status, stage, and grade of MIBC patients were significantly different in cluster1/2. We further identified eight-genes risk signatures using the least absolute shrinkage and selection operator (LASSO) regression analysis based on the expression values of 15 prognosis-related genes, and also found a significant difference in the prognosis, immune infiltration status, stage, grade, and age in high/low-risk cohort. Moreover, the expression of PD-1, PD-L1, and CTLA4 was significantly up-regulated in cluster1/high-risk-cohort than that in cluster2/low-risk-cohort. High normalized enrichment score of the Mitotic spindle, mTORC1, Complement, and Apical junction pathway suggested that they might be involved in the distinct tumor immune microenvironment (TIME) of cluster1/2 and high-/low-risk-cohort. Our study identified 15 prognosis-related genes of MIBC, provided a feasible stratification method to help for the future immunotherapy strategies of MIBC patients.

SUBMITTER: Li J

PROVIDER: S-EPMC7884823 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification and Immunocorrelation of Prognosis-Related Genes Associated With Development of Muscle-Invasive Bladder Cancer.

Li Jingxian J Lou Yantao Y Li Shuai S Sheng Fei F Liu Shuaibing S Du E E Zhang Zhihong Z

Frontiers in molecular biosciences 20210129

Improved understanding of the molecular mechanisms and immunoregulation of muscle-invasive bladder cancer (MIBC) is essential to predict prognosis and develop new targets for therapies. In this study, we used the cancer genome atlas (TCGA) MIBC and GSE13507 datasets to explore the differential co-expression genes in MIBC comparing with adjacent non-carcinoma tissues. We firstly screened 106 signature genes by Weighted Gene Co-expression Network Analysis (WGCNA) and further identified 15 prognosi ...[more]

PMID: 33604353

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Project description:Background: Bladder urothelial carcinoma (BLCA) is one of the most common malignant tumors with high morbidity and recurrence rate. The study aims to establish a prediction model to elaborate the relation between inflammatory response and prognosis of BLCA and thus to evaluate the potential prognostic value of inflammatory response-related genes (IRGs) in therapeutic choices. Methods: The study utilized the gene expression profiles from the The Cancer Genome Atlas and Gene Expression Omnibus (GSE32894) datasets. Differentially expressed IRGs between normal and tumor tissues were identified, and 10 of them were correlated with overall survival (OS) (p < 0.05). Then, the LASSO-Cox regression analysis was applied to optimize the signature. RNA sequencing data of patients with BLCA from GSE32894 were applied as a validation set. Cox regression analyses of the seven-gene signature were performed to examine the efficiency of signature in predicting prognosis. Receiver operating characteristic curve analysis was applied to measure the predictive performance of the risk score for OS. Analysis of independent prognostic factors, downstream functional enrichment, drug sensitivity, and immune features were included in this study. Results: The IRG signature (LDLR, ROS1, MMP14, TNFAIP6, MYC, PTGER4, and RIPK2) was used to divide patients into high- and low-risk groups. Cox regression analyses revealed that the risk score was an independent predictive factor. Functional enrichment analysis revealed that genes were enriched in prognosis-related molecular functions and immune-related biological processes. Drug sensitivity and tumor microenvironment correlation analysis indicated that the signature was related to immunotherapy effect. Conclusion: The study defined a new prognostic signature consisting of seven IRGs, which could effectively predict the prognosis of patients with BLCA and reveal relationship of immune features in BLCA with different risk scores. The study also provided a possible indicator for targeted therapy.

Project description:Background:Bladder cancer (BCa) is a common urothelial malignancy. The Cancer Genome Atlas (TCGA) database allows for an opportunity to analyze the relationship between gene expression and clinical outcomes in bladder cancer patients. This study is aimed at identifying prognosis-related genes in the bladder cancer microenvironment. Methods:Immune scores and stromal scores were calculated by applying the ESTIMATE algorithm. We divided bladder cancer patients into high and low groups based on their immune/stromal scores. Then, differentially expressed genes (DEGs) were identified in bladder cancer patients based on the TCGA database. We evaluated the correlation between immune/stromal scores and clinical characteristics as well as prognosis. Finally, we validated identified genes associated with bladder cancer prognosis through a cohort study in the Gene Expression Omnibus (GEO) database. Results:A higher stromal score was associated with female (vs. malep = 0.037), age > 65 (vs.age ? 65?p = 0.015), T3/4 (vs. T1/2,p < 0.001), N status(p = 0.016), and pathological high grade (vs. low gradeP < 0.001). By analyzing DEGs, there were 1125 genes commonly upregulated, and 209 genes were commonly downregulated. Protein-protein interaction networks further showed the important protein that may be involved in the biological behavior and prognosis of BCa, such as FN1, CXCL12, CD3E, LCK, and ZAP70. A total of 14 DEGs were found to be associated with overall survival of bladder cancer. After validation by a cohort of 165 BCa cases with detailed follow-up information from GSE13507, 10 immune-associated DEGs were demonstrated to be predictive of prognosis in BCa. Among them, 5 genes have not been reported previously associated with the prognosis of BCa, including BTBD16, OLFML2B, PRRX1, SPINK4, and SPON2. Conclusions:Our study elucidated tight associations between stromal score and clinical characteristics as well as prognosis in BCa. Moreover, we obtained a group of genes closely related to the prognosis of BCa in the tumor microenvironment.

Dataset Information

Identification and Immunocorrelation of Prognosis-Related Genes Associated With Development of Muscle-Invasive Bladder Cancer.

Publications

Identification and Immunocorrelation of Prognosis-Related Genes Associated With Development of Muscle-Invasive Bladder Cancer.

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