Dataset Information

Bioinformatics Analysis to Screen the Key Prognostic Genes in Tumor Microenvironment of Bladder Cancer.

ABSTRACT: Bladder cancer (BLCA) is the fifth most common cancer and has the features of low survival rate and high morbidity and mortality. The Cancer Genome Atlas (TCGA) is a pool of global gene expression profile and contains huge amounts of cancer genomics data, which makes it possible to inquire the relationship between gene expression and prognosis of a series of malignant tumors including BLCA. Immune and stromal cells are two major components of tumor microenvironment (TME) which play an important role in judging the prognosis of tumor and influencing the progression of malignant, inflammatory, and metabolic disorders. In our study, we conducted a quantitative analysis of immune and stromal elements based on the ESTIMATE algorithm and thus divided BLCA cases into high and low groups. Then the differentially expressed genes closely related to tumor prognosis between groups were identified and had been shown to correlate with immune response and stromal alterations, which was further confirmed by functional enrichment analysis and protein-protein interaction networks. We validated those genes through BLCA dates downloaded from ArrayExpress and thus got the marker genes to predict prognosis of BLCA. Additionally, immune cell infiltration analysis explored the correlation between the verified genes and immune cells. In conclusion, we identified a series of TME-related genes that assess the prognosis and explored the interaction between TME and tumor prognosis to guide clinical individualized treatment.

SUBMITTER: Zhang Z

PROVIDER: S-EPMC7048919 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Bioinformatics Analysis to Screen the Key Prognostic Genes in Tumor Microenvironment of Bladder Cancer.

Zhang Zhao Z Chen Dongshan D Li Zeyan Z Li Zeyan Z Liu Zhao Z Yan Lei L Xu Zhonghua Z

BioMed research international 20200217

Bladder cancer (BLCA) is the fifth most common cancer and has the features of low survival rate and high morbidity and mortality. The Cancer Genome Atlas (TCGA) is a pool of global gene expression profile and contains huge amounts of cancer genomics data, which makes it possible to inquire the relationship between gene expression and prognosis of a series of malignant tumors including BLCA. Immune and stromal cells are two major components of tumor microenvironment (TME) which play an important ...[more]

PMID: 32149116

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Project description:Objectives: Bladder cancer (BLCA) is the most common malignant tumor in the urinary system, while the prognosis of muscle-invasive bladder cancer (MIBC) is poor. Cuproptosis might be a promising therapeutic approach to trigger tumor cell death. This study aimed to figure out the role of cuproptosis in BLCA and constructed a new cuproptosis scoring system to guide clinical diagnosis and individualize treatments. Methods: Consensus clustering was used to classify 490 patients with BLCA from TCGA and GEO cohorts. Survival outcomes and functional enrichment analyses were performed between the different subtypes. The cuproptosis scoring system was constructed by LASSO-Cox analysis. ESTIMATE, CIBERSORT, and ssGSEA were used to investigate the tumor microenvironment (TME). Drug sensitivity was evaluated with pRRophetic. An immunotherapy cohort was used to investigate the treatment response. The cuproptosis scoring system was verified in our own cohort with quantitative real-time PCR. Results: An overview of 12 cuproptosis genes (CuGs) in the TCGA database was depicted. Based on the mRNA expression profiles of CuGs, patients were classified into two cuproptosis molecular patterns. Based on the differential genes between the two cuproptosis patterns, the patients were classified into two cuproptosis gene clusters. There were distinct survival outcomes, signaling pathways, and TME between the two subtypes. A 7-gene cuproptosis scoring system was constructed. Patients with high cuproptosis scores showed worse OS and more immunosuppressing TME than those with low cuproptosis scores. The two cuproptosis score groups had distinct mutation profiles. Patients with high cuproptosis scores tended to be sensitive to chemotherapy drugs, but insensitive to immune checkpoint inhibitors (ICIs) treatment. Conclusion: This study depicted the landscape of cuproptosis in BLCA. We constructed a cuproptosis scoring system to predict the prognosis of BLCA patients. There were significant differences in survival outcomes, TME, mutation profiles, and drug sensitivities in high and low cuproptosis score patients. The cuproptosis scoring system could help oncologists comprehensively understand the tumor characteristic of BLCA and make individualized treatment strategies.

Dataset Information

Bioinformatics Analysis to Screen the Key Prognostic Genes in Tumor Microenvironment of Bladder Cancer.

Publications

Bioinformatics Analysis to Screen the Key Prognostic Genes in Tumor Microenvironment of Bladder Cancer.

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