Bioinformatics analysis of microarray data to identify the candidate biomarkers of lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the major subtype of lung cancer and the most lethal malignant disease worldwide. However, the molecular mechanisms underlying LUAD are not fully understood. Four datasets (GSE118370, GSE85841, GSE43458 and GSE32863) were obtained from the gene expression omnibus (GEO)....

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Bibliographic Details
Published in:PeerJ (San Francisco, CA) CA), 2019-07, Vol.7, p.e7313, Article e7313
Main Authors: Guo, Tingting, Ma, Hongtao, Zhou, Yubai
Format: Article
Language:English
Subjects:
Adenocarcinoma
Biochemistry
Bioinformatical analysis
Bioinformatics
Biological markers
Biology
Biomarker
Biomarkers
Cancer therapies
Carcinogenesis
Cell growth
Computational biology
Data Mining and Machine Learning
Datasets
Differentially expressed genes
Disease prevention
DNA microarrays
Gene expression
Genes
Genomics
Kinases
Leukocyte migration
Lung adenocarcinoma
Lung cancer
Malaria
Medical prognosis
Metastasis
Microarray
Molecular modelling
Mortality
Novels
Oncology
Ontology
Peptides
Prion diseases
Protein-protein interactions
Proteins
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Summary:Lung adenocarcinoma (LUAD) is the major subtype of lung cancer and the most lethal malignant disease worldwide. However, the molecular mechanisms underlying LUAD are not fully understood. Four datasets (GSE118370, GSE85841, GSE43458 and GSE32863) were obtained from the gene expression omnibus (GEO). Identification of differentially expressed genes (DEGs) and functional enrichment analysis were performed using the limma and clusterProfiler packages, respectively. A protein-protein interaction (PPI) network was constructed via Search Tool for the Retrieval of Interacting Genes (STRING) database, and the module analysis was performed by Cytoscape. Then, overall survival analysis was performed using the Kaplan-Meier curve, and prognostic candidate biomarkers were further analyzed using the Oncomine database. Totally, 349 DEGs were identified, including 275 downregulated and 74 upregulated genes which were significantly enriched in the biological process of extracellular structure organization, leukocyte migration and response to peptide. The mainly enriched pathways were complement and coagulation cascades, malaria and prion diseases. By extracting key modules from the PPI network, 11 hub genes were screened out. Survival analysis showed that except VSIG4, other hub genes may be involved in the development of LUAD, in which MYH10, METTL7A, FCER1G and TMOD1 have not been reported previously to correlated with LUAD. Briefly, novel hub genes identified in this study will help to deepen our understanding of the molecular mechanisms of LUAD carcinogenesis and progression, and to discover candidate targets for early detection and treatment of LUAD.
ISSN:2167-8359
2167-8359
DOI:10.7717/peerj.7313