Dataset Information

CALD1, CNN1, and TAGLN identified as potential prognostic molecular markers of bladder cancer by bioinformatics analysis.

ABSTRACT:

Background

Bladder cancer (BC) is one of the most common malignant neoplasms in the genitourinary tract. We employed the GSE13507 data set from the Gene Expression Omnibus (GEO) database in order to identify key genes related to tumorigenesis, progression, and prognosis in BC patients.

Methods

The data set used in this study included 10 normal bladder mucosae tissue samples and 165 primary BC tissue samples. Differentially expressed genes (DEGs) in the 2 types of samples were identified by GEO2R. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the online website DAVID. The online website STRING was used to construct a protein-protein interaction network. Moreover, the plugins in MCODE and cytoHubba in Cytoscape were employed to find the hub genes and modules in these DEGs.

Results

We identified 154 DEGs comprising 135 downregulated genes and 19 upregulated genes. The GO enrichment results were mainly related to the contractile fiber part, extracellular region part, actin cytoskeleton, and extracellular region. The KEGG pathway enrichment results mainly comprised type I diabetes mellitus, asthma, systemic lupus erythematosus, and allograft rejection. A module was identified from the protein-protein interaction network. In total, 15 hub genes were selected and 3 of them comprising CALD1, CNN1, and TAGLN were associated with both overall survival and disease-free survival.

Conclusion

CALD1, CNN1, and TAGLN may be potential biomarkers for diagnosis as well as therapeutic targets in BC patients.

SUBMITTER: Liu Y

PROVIDER: S-EPMC6336601 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

CALD1, CNN1, and TAGLN identified as potential prognostic molecular markers of bladder cancer by bioinformatics analysis.

Liu Yun Y Wu Xia X Wang Guokun G Hu Shisong S Zhang Yuandong Y Zhao Shenglong S

Medicine 20190101 2

<h4>Background</h4>Bladder cancer (BC) is one of the most common malignant neoplasms in the genitourinary tract. We employed the GSE13507 data set from the Gene Expression Omnibus (GEO) database in order to identify key genes related to tumorigenesis, progression, and prognosis in BC patients.<h4>Methods</h4>The data set used in this study included 10 normal bladder mucosae tissue samples and 165 primary BC tissue samples. Differentially expressed genes (DEGs) in the 2 types of samples were iden ...[more]

PMID: 30633156

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Project description:Bladder cancer is one of the most common malignant tumors of the urinary system that seriously threatens the health of a population. In recent years, the application of immunotherapy has significantly changed the treatment of bladder cancer, but only some patients can benefit from the treatment with immune-checkpoint inhibitors. Many problems are unsolved in the field of bladder cancer immunotherapy, especially in the search for genes that are critical to the level of immune cell infiltration and new effective therapeutic targets. We attempted to use bioinformatics analysis to identify immune gene markers related to the prognosis of bladder cancer and to establish a prognostic signature for bladder cancer patients based on their immune gene expression profiles. We used univariate Cox proportional hazards regression analysis, the least absolute shrinkage and selection operator (LASSO) Cox regression, and multivariate Cox proportional hazards regression analysis from The Cancer Genome Atlas bladder cancer cohort (TCGA-BLCA). Fifteen genes related to prognosis were screened using the survival analysis, correlation analysis, cancer and adjacent cancer differential expression analysis, and mutation analysis. The potential biological role of these genes was determined using survival analysis and principal component analysis (PCA). The receiver operating characteristic (ROC) curve assesses the prognostic value of the predictive signature. The gene ontology (GO), Kyoto Encyclopedia of Gene and Genome (KEGG), Gene set enrichment analysis (GSEA), and other methods were used to reveal the differential gene enrichment in the signaling pathways and cellular processes of high- and low-risk groups. The single-sample GSEA (ssGSEA) method was used to quantify the infiltration levels of 24 immune cells in the tumor immune microenvironment and these immune genes were found to be closely related to the tumor immune microenvironment. In summary, we screened 15 immune genes that were closely related to bladder cancer overall survival (OS) and may be potential prognostic indicators of bladder cancer. They may have research and clinical application value in bladder cancer immunotherapy. We used 15 immune genes to construct a new immune-related gene signature that was verified and could be helpful in improving individualized prognosis of patients with bladder cancer.

Dataset Information

CALD1, CNN1, and TAGLN identified as potential prognostic molecular markers of bladder cancer by bioinformatics analysis.

Background

Methods

Results

Conclusion

Publications

CALD1, CNN1, and TAGLN identified as potential prognostic molecular markers of bladder cancer by bioinformatics analysis.

Similar Datasets

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