Dataset Information

Screening and identification of key biomarkers in bladder carcinoma: Evidence from bioinformatics analysis.

ABSTRACT: Bladder cancer (BC) is one of the most common urogenital malignancies. However, present studies of its multiple gene interaction and cellular pathways remain unable to accurately verify the genesis and the development of BC. The aim of the present study was to investigate the genetic signatures of BC and identify its potential molecular mechanisms. The gene expression profiles of GSE31189 were downloaded from the Gene Expression Omnibus database. The GSE31189 dataset contained 92 samples, including 52 BC and 40 non-cancerous urothelial cells. To further examine the biological functions of the identified differentially expressed genes (DEGs), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and a protein-protein interaction (PPI) network was mapped using Cytoscape software. In total, 976 DEGs were identified in BC, including 457 upregulated genes and 519 downregulated genes. GO and KEGG pathway enrichment analyses indicated that upregulated genes were significantly enriched in the cell cycle and the negative regulation of the apoptotic process, while the downregulated genes were mainly involved in cell proliferation, cell adhesion molecules and oxidative phosphorylation pathways (P<0.05). From the PPI network, the 12 nodes with the highest degrees were screened as hub genes; these genes were involved in certain pathways, including the chemokine-mediated signaling pathway, fever generation, inflammatory response and the immune response nucleotide oligomerization domain-like receptor signaling pathway. The present study used bioinformatics analysis of gene profile datasets and identified potential therapeutic targets for BC.

SUBMITTER: Yan M

PROVIDER: S-EPMC6096082 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Screening and identification of key biomarkers in bladder carcinoma: Evidence from bioinformatics analysis.

Yan Meiqin M Jing Xuan X Liu Yina Y Cui Xiangrong X

Oncology letters 20180621 3

Bladder cancer (BC) is one of the most common urogenital malignancies. However, present studies of its multiple gene interaction and cellular pathways remain unable to accurately verify the genesis and the development of BC. The aim of the present study was to investigate the genetic signatures of BC and identify its potential molecular mechanisms. The gene expression profiles of GSE31189 were downloaded from the Gene Expression Omnibus database. The GSE31189 dataset contained 92 samples, includ ...[more]

PMID: 30127900

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Project description:BackgroundIn osteosarcoma, the lung is the most common metastatic organ. Intensive work has been made to illuminate the pathogeny, but the specific metastatic mechanism remains unclear. Thus, we conducted the study to seek to find the key genes and critical functional pathways associated with progression and treatment in lung metastasis originating from osteosarcoma.MethodsTwo independent datasets (GSE14359 and GSE85537) were screened out from the Gene Expression Omnibus (GEO) database and the overlapping differentially expressed genes (DEGs) were identified using GEO2R online platform. Subsequently, the Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were conducted using DAVID. Meanwhile, the protein-protein interaction (PPI) network constructed by STRING was visualized using Cytoscape. Afterwards, the key module and hub genes were extracted from the PPI network using the MCODE and cytoHubba plugin. Moreover, the raw data obtained from GSE73166 and GSE21257 were applied to verify the expression differences and conduct the survival analyses of hub genes, respectively. Finally, the interaction network of miRNAs and hub genes constructed by ENCORI was visualized using Cytoscape.ResultsA total of 364 DEGs were identified, comprising 96 downregulated genes and 268 upregulated genes, which were mainly involved in cancer-associated pathways, adherens junction, ECM-receptor interaction, focal adhesion, MAPK signaling pathway. Subsequently, 10 hub genes were obtained and survival analysis demonstrated SKP2 and ASPM were closely related to poor prognosis of patients with osteosarcoma. Finally, hsa-miR-340-5p, has-miR-495-3p, and hsa-miR-96-5p were found to be most closely associated with these hub genes according to the interaction network of miRNAs and hub genes.ConclusionThe key genes and functional pathways identified in the study may contribute to understanding the molecular mechanisms involved in the carcinogenesis and progression of lung metastasis originating from osteosarcoma, and provide potential diagnostic and therapeutic targets.

Dataset Information

Screening and identification of key biomarkers in bladder carcinoma: Evidence from bioinformatics analysis.

Publications

Screening and identification of key biomarkers in bladder carcinoma: Evidence from bioinformatics analysis.

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