Dataset Information

Genome-scale analysis identifies NEK2, DLGAP5 and ECT2 as promising diagnostic and prognostic biomarkers in human lung cancer.

ABSTRACT: This study aims to identify promising biomarkers for the early detection of lung cancer and evaluate the prognosis of lung cancer patients. Genome-wide mRNA expression data obtained from the Gene Expression Omnibus (GSE19188, GSE18842 and GSE40791), including 231 primary tumor samples and 210 normal samples, were used to discover differentially expressed genes (DEGs). NEK2, DLGAP5 and ECT2 were found to be highly expressed in tumor samples. These results were experimentally confirmed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The elevated expression of the three candidate genes was also validated using the Cancer Genome Atlas (TCGA) datasets, which consist of 349 tumor and 58 normal tissues. Furthermore, we performed receiver operating characteristics (ROC) analysis to assess the diagnostic value of these lung cancer biomarkers, and the results suggested that NEK2, DLGAP5 and ECT2 expression levels could robustly distinguish lung cancer patients from normal subjects. Finally, Kaplan-Meier analysis revealed that elevated NEK2, DLGAP5 and ECT2 expression was negatively correlated with both overall survival (OS) and relapse-free survival (RFS). Taken together, these findings indicate that these three genes might be used as promising biomarkers for the early detection of lung cancer, as well as predicting the prognosis of lung cancer patients.

SUBMITTER: Shi YX

PROVIDER: S-EPMC5556079 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Genome-scale analysis identifies NEK2, DLGAP5 and ECT2 as promising diagnostic and prognostic biomarkers in human lung cancer.

Shi Yuan-Xiang YX Yin Ji-Ye JY Shen Yao Y Zhang Wei W Zhou Hong-Hao HH Liu Zhao-Qian ZQ

Scientific reports 20170814 1

This study aims to identify promising biomarkers for the early detection of lung cancer and evaluate the prognosis of lung cancer patients. Genome-wide mRNA expression data obtained from the Gene Expression Omnibus (GSE19188, GSE18842 and GSE40791), including 231 primary tumor samples and 210 normal samples, were used to discover differentially expressed genes (DEGs). NEK2, DLGAP5 and ECT2 were found to be highly expressed in tumor samples. These results were experimentally confirmed by quantita ...[more]

PMID: 28808310

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Project description:BACKGROUND We aimed to screen and identify central genetic and molecular targets involved in advancement of lung adenocarcinoma (LUAD) and to perform an integrated analysis and clinical validation. MATERIAL AND METHODS The GEO2R technique was utilized to assess differentially expressed genes (DEGs) among the gene sets GSE75037, GSE85716, and GSE118370. Subsequently, gene Ontology (GO) analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) analytical methods were executed to determine related biofunctions and signaling pathways, which were annotated with tools from the Database for Annotation, Visualization and Integrated Discovery (DAVID) resource. Then, a protein-protein interaction (PPI) network complex consisting of all detected DEGs was built with the STRING web interface. Cytohubba and MCODE plug-ins for Cytoscape software and Gene Expression Profiling Interactive Analysis (GEPIA) were employed to identify the hub genes. Finally, the mRNA expression of the identified hub genes was quantitatively validated by The Cancer Genome Atlas (TCGA) database analysis and real-time quantitative polymerase chain reaction (RT-qPCR). RESULTS We screened 146 upregulated DEGs and 431 downregulated DEGs with the criteria of |logFC| >1 and P<0.05, and the GO analysis indicated that DEGs were implicated in mitotic nuclear division (biological process, BP), the nucleus (cellular component, CC), and protein binding (molecular function, MF) and were associated with multiple KEGG pathways, such as the p53 signaling pathway in cancer. Then, the top 8 genes that predicted significantly different outcomes in LUAD patients were filtered from the DEGs and selected as hub genes. The TCGA database analysis and RT-qPCR results demonstrated that these genes were differentially expressed with the same trends in LUAD tissues compared with normal tissues. CONCLUSIONS Overall, we propose that 8 genes (PECAM1, CDK1, MKI67, SPP1, TOP2A, CHEK1, CCNB1, and RRM2) might be novel hub genes strongly associated with the progression and prognosis of LUAD.

Dataset Information

Genome-scale analysis identifies NEK2, DLGAP5 and ECT2 as promising diagnostic and prognostic biomarkers in human lung cancer.

Publications

Genome-scale analysis identifies NEK2, DLGAP5 and ECT2 as promising diagnostic and prognostic biomarkers in human lung cancer.

Similar Datasets

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