Dataset Information

Screening and identification of key biomarkers in nasopharyngeal carcinoma: Evidence from bioinformatic analysis.

ABSTRACT: As for the lack of simple and effective diagnostic methods at the early of the nasopharyngeal carcinoma (NPC), the mortality rate of NPC still remains high. Therefore, it is meaningful to explore the precise molecular mechanisms involved in the proliferation, carcinogenesis, and recurrence of NPC and thus find an effective diagnostic way and make a better therapeutic strategy.Three gene expression data sets (GSE64634, GSE53819, and GSE12452) were downloaded from Gene Expression Omnibus (GEO) and analyzed using the online tool GEO2R to identify differentially expressed genes (DEGs). Gene ontology functional analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of the DEGs were performed in Database for Annotation, Visualization and Integrated Discovery. The Search Tool for the Retrieval of Interacting Genes database was used to evaluate the interactions of DEGs and to construct a protein-protein interaction network using Cytoscape software. Hub genes were validated with the cBioPortal database.The overlap among the 3 data sets contained 306 genes were identified to be differentially expressed between NPC and non-NPC samples. A total of 13 genes (DNAAF1, PARPBP, TTC18, GSTA3, RCN1, MUC5AC, POU2AF1, FAM83B, SLC22A16, SPEF2, ERICH3, CCDC81, and IL33) were identified as hub genes with degrees ?10.The present study was attempted to identify and functionally analyze the DEGs that may be involved in the carcinogenesis or progression of NPC by using comprehensive bioinformatics analyses and unveiled a series of hub genes and pathways. A total of 306 DEGs and 13 hub genes were identified and may be regarded as diagnostic biomarkers for NPC. However, more experimental studies are needed to carried out elucidate the biologic function of these genes results for NPC.

SUBMITTER: Zhang JZ

PROVIDER: S-EPMC6890310 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Screening and identification of key biomarkers in nasopharyngeal carcinoma: Evidence from bioinformatic analysis.

Zhang Ji-Zhou JZ Wu Zeng-Hong ZH Cheng Qing Q

Medicine 20191101 48

As for the lack of simple and effective diagnostic methods at the early of the nasopharyngeal carcinoma (NPC), the mortality rate of NPC still remains high. Therefore, it is meaningful to explore the precise molecular mechanisms involved in the proliferation, carcinogenesis, and recurrence of NPC and thus find an effective diagnostic way and make a better therapeutic strategy.Three gene expression data sets (GSE64634, GSE53819, and GSE12452) were downloaded from Gene Expression Omnibus (GEO) and ...[more]

PMID: 31770211

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Project description:BackgroundPapillary renal cell carcinoma (PRCC) is the most common type of renal cell carcinoma after clear cell renal cell carcinoma (ccRCC). Its pathological classification is controversial, and its molecular mechanism is poorly understood. Therefore, the identification of key genes and their biological pathways is of great significance to elucidate the molecular mechanisms of PRCC occurrence and progression.MethodsThe PRCC-related datasets GSE7023, GSE48352 and GSE15641 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, and gene ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Cytoscape and STRING were used to construct the protein-protein interaction network (PPI) and perform module analysis to identify hub genes and key pathways. A heatmap of hub genes was constructed using the UCSC cancer genomics browser. Overall survival and recurrence-free survival of patients stratified by the expression levels of hub genes were analysed using Kaplan-Meier Plotter. The online database UALCAN was applied to analyse gene expression based on tissue type, stage, subtype and race.ResultsA total of 214 DEGs, specifically, 205 downregulated genes and 9 upregulated genes, were identified. The DEGs were mainly enriched in angiogenesis, kidney development, oxidation-reduction process, metabolic pathways, etc. The 17 hub genes identified were mainly enriched in the biological processes of angiogenesis, cell adhesion, platelet degranulation, and leukocyte transendothelial migration. Survival analysis showed that EGF, KDR, CXCL12, REN, PECAM1, CDH5, THY1, WT1, PLAU and DCN might be related to the carcinogenesis, metastasis or recurrence of PRCC. UALCAN analysis showed that low expression of PECAM1 and PLAU in PRCC tissues was related to stage, subtype and race.ConclusionsThe DEGs and hub genes identified in the present study provide insight into the specific molecular mechanisms of PRCC occurrence and development and may be potential molecular markers and therapeutic targets for the accurate classification and efficient diagnosis and treatment of PRCC.

Project description:BACKGROUND:Ovarian cancer (OC) is the deadliest cause in the gynecological malignancies. Most OC patients are diagnosed in advanced stages with less than 40% of women cured. However, the possible mechanism underlying tumorigenesis and candidate biomarkers remain to be further elucidated. RESULTS:Gene expression profiles of GSE18520, GSE54388, and GSE27651 were available from Gene Expression Omnibus (GEO) database with a total of 91 OC samples and 22 normal ovarian (OV) tissues. Three hundred forty-nine differentially expressed genes (DEGs) were screened between OC tissues and OV tissues via GEO2R and online Venn software, followed by KEGG pathway and gene ontology (GO) enrichment analysis. The enriched functions and pathways of these DEGs contain male gonad development, cellular response to transforming growth factor beta stimulus, positive regulation of transcription from RNA polymerase II promoter, calcium independent cell-cell adhesion via plasma membrane cell adhesion molecules, extracellular matrix organization, pathways in cancer, cell cycle, cell adhesion molecules, PI3K-AKT signaling pathway, and progesterone mediated oocyte maturation. The protein-protein network (PPI) was established and module analysis was carried out using STRING and Cytoscape. Next, with PPI network analyzed by four topological methods in Cytohubba plugin of Cytoscape, 6 overlapping genes (DTL, DLGAP5, KIF15, NUSAP1, RRM2, and TOP2A) were eventually selected. GEPIA and Oncomine were implemented for validating the gene expression and all the six hub genes were highly expressed in OC specimens compared to normal OV tissues. Furthermore, 5 of 6 genes except for DTL were associated with worse prognosis using Kaplan Meier-plotter online tool and 3 of 6 genes were significantly related to clinical stages, including RRM2, DTL, and KIF15. Additionally, cBioPortal showed that TOP2A and RRM2 were the targets of cancer drugs in patients with OC, indicating the other four genes may also be potential drug targets. CONCLUSION:Six hub genes (DTL, DLGAP5, KIF15, NUSAP1, RRM2, and TOP2A) present promising predictive value for the development and prognosis of OC and may be used as candidate targets for diagnosis and treatment of OC.

Dataset Information

Screening and identification of key biomarkers in nasopharyngeal carcinoma: Evidence from bioinformatic analysis.

Publications

Screening and identification of key biomarkers in nasopharyngeal carcinoma: Evidence from bioinformatic analysis.

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