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.