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Exploring the FGFR3-related oncogenic mechanism in bladder cancer using bioinformatics strategy.

ABSTRACT: Aberrant activation of fibroblast growth factor receptor 3 (FGFR3) is frequently observed in bladder cancer, but how it involved in carcinogenesis is not well understood. The current study was aimed to investigate the underlying mechanism on the progression of bladder cancer.The GSE41035 dataset downloaded from Gene Expression Omnibus was used to identify the differentially expressed genes (DEGs) between bladder cancer cell line RT112 with or without depletion of FGFR3, and gene ontology enrichment analysis was performed. Then, FGFR3-centered protein-protein interaction (PPI) and regulatory networks were constructed. Combined with the data retrieved from GSE31684, prognostic makers for bladder cancer were predicted.We identified a total of 2855 DEGs, and most of them were associated with blood vessel morphogenesis and cell division. In addition, KIAA1377, POLA2, FGFR3, and EPHA4 were the hub genes with high degree in the FGFR3-centered PPI network. Besides, 17 microRNAs (miRNAs) and 6 transcriptional factors (TFs) were predicted to be the regulators of the nodes in PPI network. Moreover, CSTF2, POLA1, HMOX2, and EFNB2 may be associated with the prognosis of bladder cancer patient.The current study may provide some insights into the molecular mechanism of FGFR3 as a mediator in bladder cancer.

SUBMITTER: Cao W

PROVIDER: S-EPMC5359882 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Exploring the FGFR3-related oncogenic mechanism in bladder cancer using bioinformatics strategy.

Cao Wei W Ma Enguang E Zhou Li L Yuan Tan T Zhang Chunying C

World journal of surgical oncology 20170320 1

<h4>Background</h4>Aberrant activation of fibroblast growth factor receptor 3 (FGFR3) is frequently observed in bladder cancer, but how it involved in carcinogenesis is not well understood. The current study was aimed to investigate the underlying mechanism on the progression of bladder cancer.<h4>Methods</h4>The GSE41035 dataset downloaded from Gene Expression Omnibus was used to identify the differentially expressed genes (DEGs) between bladder cancer cell line RT112 with or without depletion ...[more]

PMID: 28320388

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Dataset Information

Exploring the FGFR3-related oncogenic mechanism in bladder cancer using bioinformatics strategy.

Publications

Exploring the FGFR3-related oncogenic mechanism in bladder cancer using bioinformatics strategy.

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