Dataset Information

Screening and identification of key biomarkers in lung squamous cell carcinoma by bioinformatics analysis.

ABSTRACT: The high mortality rate of lung squamous cell carcinoma (LUSC) is in part due to the lack of early detection of its biomarkers. The identification of key molecules involved in LUSC is therefore required to improve clinical diagnosis and treatment outcomes. The present study used the microarray datasets GSE31552, GSE6044 and GSE12428 from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were conducted to construct the protein-protein interaction network of DEGs and hub genes module using STRING and Cytoscape. The 67 DEGs identified consisted of 42 upregulated genes and 25 downregulated genes. The pathways predicted by KEGG and GO enrichment analyses of DEGs mainly included cell cycle, cell proliferation, glycolysis or gluconeogenesis, and tetrahydrofolate metabolic process. Further analysis of the University of California Santa Cruz and ONCOMINE databases identified 17 hub genes. Overall, the present study demonstrated hub genes that were closely associated with clinical tissue samples of LUSC, and identified TYMS, CCNB2 and RFC4 as potential novel biomarkers of LUSC. The findings of the present study contribute to an improved understanding of the molecular mechanisms of carcinogenesis and progression of LUSC, and assist with the identification of potential diagnostic and therapeutic targets of LUSC.

SUBMITTER: Man J

PROVIDER: S-EPMC6781567 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Screening and identification of key biomarkers in lung squamous cell carcinoma by bioinformatics analysis.

Man Jun J Zhang Xiaomei X Dong Huan H Li Simin S Yu Xiaolin X Meng Lihong L Gu Xiaofeng X Yan Hong H Cui Jinwei J Lai Yuxin Y

Oncology letters 20190916 5

The high mortality rate of lung squamous cell carcinoma (LUSC) is in part due to the lack of early detection of its biomarkers. The identification of key molecules involved in LUSC is therefore required to improve clinical diagnosis and treatment outcomes. The present study used the microarray datasets GSE31552, GSE6044 and GSE12428 from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) en ...[more]

PMID: 31612029

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Project description:Lung cancer is the leading cause of cancer-related mortality worldwide. Despite progress in the treatment of non-small-cell lung cancer, there are limited treatment options for lung squamous cell carcinoma (LUSC), compared with lung adenocarcinoma. The present study investigated the disease mechanism of LUSC in order to identify key candidate genes for diagnosis and therapy. A total of three gene expression profiles (GSE19188, GSE21933 and GSE74706) were analyzed using GEO2R to identify common differentially expressed genes (DEGs). The DEGs were then investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. A protein-protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes/Proteins, and visualized using Cytoscape software. The expression levels of the hub genes identified using CytoHubba were validated using the University of California, Santa Cruz (UCSC) database and the Human Protein Atlas. A Kaplan-Meier curve and Gene Expression Profiling Interactive Analysis were then employed to evaluate the associated prognosis and clinical pathological stage of the hub genes. Furthermore, non-coding RNA regulatory networks were constructed using the Gene-Cloud Biotechnology information website. A total of 359 common DEGs (155 upregulated and 204 downregulated) were identified, which were predominantly enriched in 'mitotic nuclear division', 'cell division', 'cell cycle' and 'p53 signaling pathway'. The PPI network consisted of 257 nodes and 2,772 edges, and the most significant module consisted of 66 upregulated genes. A total of 19 hub genes exhibited elevated RNA levels, and 10 hub genes had elevated protein levels compared with normal lung tissues. The upregulation of five hub genes (CCNB1, CEP55, FOXM1, MKI67 and TYMS; defined in Table I) were significantly associated with poor overall survival and unfavorable clinical pathological stages. Various ncRNAs, such as C1orf220, LINC01561 and MGC39584, may also play important roles in hub-gene regulation. In conclusion, the present study provides further understanding of the pathogenesis of LUSC, and reveals CCNB1, CEP55, FOXM1, MKI67 and TYMS as potential biomarkers or therapeutic targets.

Project description:The aim of the present study was to identify the differentially expressed genes (DEGs) in esophageal squamous-cellcarcinoma (ESCC) and provide potential therapeutic targets. The microarray dataset GSE20347 was downloaded from the Gene Expression Omnibus (GEO) database, and included 17 tissue samples and 13 normal adjacent tissue samples from patients with ESCC. A total of 22,277 DEGs were identified. A heat map for the DEGs was constructed with the Morpheus online tool and the top 200 genes (100 upregulated and 100 downregulated) were selected for further bioinformatics analysis, including analysis of gene ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, protein-protein interaction networks and Spearman's correlation tests. The results of the GO analysis indicated that the upregulated DEGs were most significantly enriched in membrane-bounded vesicles in the cellular component (CC) category, but were not significantly enriched in any GO terms of the categories biological process (BP) or molecular function (MF); furthermore, the downregulated DEGs were most significantly enriched in regulation of DNA metabolic processes, nucleotide binding and chromosomes in the categories BP, MF and CC, respectively. The KEGG analysis indicated that the downregulated DEGs were enriched in the regulation of cell cycle pathways. The top 10 hub proteins in the protein-protein interaction network were cyclin-dependent kinase 4, budding uninhibited by benzimidazoles 1, cyclin B2, heat shock protein 90AA1, aurora kinase A, H2A histone family member Z, replication factor C subunit 4, and minichromosome maintenance complex component 2, -4 and -7. These proteins are mainly involved in regulating tumor progression. The genes in the four top modules were mainly implicated in regulating cell cycle pathways. Secreted Ly-6/uPAR-related protein (SLURP) was the hub gene, and SLURP and its interacting genes were most enriched in the chromosomal part in the CC category, organelle organization in the BP category and protein binding in the MF category, and were involved in pathways including DNA replication, cell cycle and P53 signaling. The expression of SLURP-1 in fifteen patients with esophageal carcinoma was detected using quantitative polymerase chain reaction analysis, and the results indicated that SLURP-1 expression was significantly decreased in the tumor samples relative to that in normal adjacent tissues. These results suggest that several hub proteins and the hub gene SLURP-1 may serve as potential therapeutic targets, and that gene dysfunction may be involved in the tumorigenesis of ESCC.

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Screening and identification of key biomarkers in lung squamous cell carcinoma by bioinformatics analysis.

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Screening and identification of key biomarkers in lung squamous cell carcinoma by bioinformatics analysis.

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