title: Transcriptome network analysis reveals potential candidate genes for             squamous lung cancer.
abstract: Squamous lung cancer is a common type of lung cancer; however, its mechanism             of oncogenesis is still unknown. The aim of this study was to screen candidate             genes of squamous lung cancer using a bioinformatics strategy and elucidate the             mechanism of squamous lung cancer. Published microarray data of the GSE3268 series             was obtained from Gene Expression Omnibus (GEO). Significance analysis of microarrays             was performed using the software R, and differentially expressed genes by R analysis             were harvested. The relationship between transcription factors and target genes             in cancer were collected from the Transcriptional regulatory element database.             A transcriptome network analysis method was used to construct gene regulation             networks and select the candidate genes for squamous lung cancer. SPI1, FLI1,             FOS, ETS2, EGR1 and PPARG were defined as candidate genes for squamous lung cancer             by the transcriptome network analysis method. Among them, 5 genes had been reported             to be involved in lung cancer, except SPI1 and FLI1. Effective recall on previous             knowledge conferred strong confidence in these methods. It is demonstrated that             transcriptome network analysis is useful in the identification of candidate genes             in disease.
authors.affiliation: Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, PR China. jingbaidoc@gmail.com
authors.forename: Jing
authors.initials: J
authors.lastname: Bai
authors.forename: Sheng
authors.initials: S
authors.lastname: Hu
mesh_terms: D014408:Biomarkers, Tumor; D045744:Cell Line, Tumor; D019295:Computational Biology / Q000379:methods; D053263:Gene Regulatory Networks; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics*; D008957:Models, Genetic; D018307:Neoplasms, Squamous Cell / Q000235:genetics*; D015398:Signal Transduction / Q000235:genetics; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism; D059467:Transcriptome / Q000235:genetics*
chemical_list: D014408:Biomarkers, Tumor; D014157:Transcription Factors