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Squamous lung cancer is a common type of lung cancer; however, its mechanismof oncogenesis is still unknown. The aim of this study was to screen candidategenes of squamous lung cancer using a bioinformatics strategy and elucidate themechanism of squamous lung cancer. Published microarray data of the GSE3268 serieswas obtained from Gene Expression Omnibus (GEO). Significance analysis of microarrayswas performed using the software R, and differentially expressed genes by R analysiswere harvested. The relationship between transcription factors and target genesin cancer were collected from the Transcriptional regulatory element database.A transcriptome network analysis method was used to construct gene regulationnetworks and select the candidate genes for squamous lung cancer. SPI1, FLI1,FOS, ETS2, EGR1 and PPARG were defined as candidate genes for squamous lung cancerby the transcriptome network analysis method. Among them, 5 genes had been reportedto be involved in lung cancer, except SPI1 and FLI1. Effective recall on previousknowledge conferred strong confidence in these methods. It is demonstrated thattranscriptome network analysis is useful in the identification of candidate genesin disease.

Transcriptome network analysis reveals potential candidate genes for squamous lung cancer