Dataset Information

Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy.

ABSTRACT: Background:Esophageal squamous cell carcinoma (ESCC) is one of leading malignant cancers of gastrointestinal tract worldwide. Until now, the involved mechanisms during the development of ESCC are largely unknown. This study aims to explore the driven-genes and biological pathways in ESCC. Methods:mRNA expression datasets of GSE29001, GSE20347, GSE100942, and GSE38129, containing 63 pairs of ESCC and non-tumor tissues data, were integrated and deeply analyzed. The bioinformatics approaches include identification of differentially expressed genes (DEGs) and hub genes, gene ontology (GO) terms analysis and biological pathway enrichment analysis, construction and analysis of protein-protein interaction (PPI) network, and miRNA-gene network construction. Subsequently, GEPIA2 database and qPCR assay were utilized to validate the expression of hub genes. DGIdb database was performed to search the candidate drugs for ESCC. Results:Finally, 120 upregulated and 26 downregulated DEGs were identified. The functional enrichment of DEGs in ESCC were mainly correlated with cell cycle, DNA replication, deleted in colorectal cancer (DCC) mediated attractive signaling pathway, and Netrin-1 signaling pathway. The PPI network was constructed using STRING software with 146 nodes and 2392 edges. The most significant three modules in PPI were filtered and analyzed. Totally ten genes were selected and considered as the hub genes and nuclear division cycle 80 (NDC80) was closely related to the survival of ESCC patients. DGIdb database predicted 33 small molecules as the possible drugs for treating ESCC. Conclusions:In summary, the data may provide new insights into ESCC pathogenesis and treatments. The candidate drugs may improve the efficiency of personalized therapy in future.

SUBMITTER: Yang W

PROVIDER: S-EPMC6530124 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy.

Yang Wanli W Zhao Xinhui X Han Yu Y Duan Lili L Lu Xin X Wang Xiaoqian X Zhang Yujie Y Zhou Wei W Liu Jinqiang J Zhang Hongwei H Zhao Qingchuan Q Hong Liu L Fan Daiming D

Cancer cell international 20190522

<h4>Background</h4>Esophageal squamous cell carcinoma (ESCC) is one of leading malignant cancers of gastrointestinal tract worldwide. Until now, the involved mechanisms during the development of ESCC are largely unknown. This study aims to explore the driven-genes and biological pathways in ESCC.<h4>Methods</h4>mRNA expression datasets of GSE29001, GSE20347, GSE100942, and GSE38129, containing 63 pairs of ESCC and non-tumor tissues data, were integrated and deeply analyzed. The bioinformatics ap ...[more]

PMID: 31139019

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Project description:BACKGROUND:Ovarian cancer (OC) ranks fifth as a cause of gynecological cancer-associated death globally. Until now, the molecular mechanisms underlying the tumorigenesis and prognosis of OC have not been fully understood. This study aims to identify hub genes and therapeutic drugs involved in OC. METHODS:Four gene expression profiles (GSE54388, GSE69428, GSE36668, and GSE40595) were downloaded from the Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) in OC tissues and normal tissues with an adjusted P-value <?0.05 and a |log fold change (FC)|?>?1.0 were first identified by GEO2R and FunRich software. Next, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) analyses were performed for functional enrichment analysis of these DEGs. Then, the hub genes were identified by the cytoHubba plugin and the other bioinformatics approaches including protein-protein interaction (PPI) network analysis, module analysis, survival analysis, and miRNA-hub gene network construction was also performed. Finally, the GEPIA2 and DGIdb databases were utilized to verify the expression levels of hub genes and to select the candidate drugs for OC, respectively. RESULTS:A total of 171 DEGs were identified, including 114 upregulated and 57 downregulated DEGs. The results of the GO analysis indicated that the upregulated DEGs were mainly involved in cell division, nucleus, and protein binding, whereas the biological functions showing enrichment in the downregulated DEGs were mainly negative regulation of transcription from RNA polymerase II promoter, protein complex and apicolateral plasma membrane, and glycosaminoglycan binding. As for the KEGG-pathway, the upregulated DEGs were mainly associated with metabolic pathways, biosynthesis of antibiotics, biosynthesis of amino acids, cell cycle, and HTLV-I infection. Additionally, 10 hub genes (KIF4A, CDC20, CCNB2, TOP2A, RRM2, TYMS, KIF11, BIRC5, BUB1B, and FOXM1) were identified and survival analysis of these hub genes showed that OC patients with the high-expression of CCNB2, TYMS, KIF11, KIF4A, BIRC5, BUB1B, FOXM1, and CDC20 were statistically more likely to have poorer progression free survival. Meanwhile, the expression levels of the hub genes based on GEPIA2 were in accordance with those based on GEO. Finally, DGIdb database was used to identify 62 small molecules as the potentially targeted drugs for OC treatment. CONCLUSIONS:In summary, the data may produce new insights regarding OC pathogenesis and treatment. Hub genes and candidate drugs may improve individualized diagnosis and therapy for OC in future.

Project description:BackgroundEsophageal squamous cell carcinoma (ESCC) as the main subtype of esophageal cancer (EC) is a leading cause of cancer-related death worldwide. Despite advances in early diagnosis and clinical management, the long-term survival of ESCC patients remains disappointing, due to a lack of full understanding of the molecular mechanisms.MethodsIn order to identify the differentially expressed genes (DEGs) in ESCC, the microarray datasets GSE20347 and GSE26886 from Gene Expression Omnibus (GEO) database were analyzed. The enrichment analyses of gene ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Set Enrichment Analysis (GSEA) were performed for the DEGs. The protein-protein interaction (PPI) network of these DEGs was constructed using the Cytoscape software based on the STRING database to select as hub genes for weighted co-expression network analysis (WGCNA) with ESCC samples from TCGA database.ResultsA total of 746 DEGs were commonly shared in the two datasets including 286 upregulated genes and 460 downregulated genes in ESCC. The DEGs were enriched in biological processes such as extracellular matrix organization, proliferation and keratinocyte differentiation, and were enriched in biological pathways such as ECM-receptor interaction and cell cycle. GSEA analysis also indicated the enrichment of upregulated DEGs in cell cycle. The 40 DEGs were selected as hub genes. The MEblack module was found to be enriched in the cell cycle, Spliceosome, DNA replication and Oocyte meiosis. Among the hub genes correlated with MEblack module, GSEA analysis indicated that DEGs of TCGA samples with DLGAP5 upregulation was enriched in cell cycle. Moreover, the highly endogenous expression of DLGAP5 was confirmed in ESCC cells. DLGAP5 knockdown significantly inhibited the proliferation of ESCC cells.ConclusionsDEGs and hub genes such as DLGAP5 from independent datasets in the current study will provide clues to elucidate the molecular mechanisms involved in development and progression of ESCC.

Dataset Information

Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy.

Publications

Identification of hub genes and therapeutic drugs in esophageal squamous cell carcinoma based on integrated bioinformatics strategy.

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