Feng Zhang, Xia Chen, Ke Wei, Daoming Liu, Xiaodong Xu, Xing Zhang, Hong Shi
Department of Oncology, Linyi People’s Hospital of Shandong Province, Linyi, Shandong, China (mainland)
Med Sci Monit 2017; 23:172-206
Lung squamous cell carcinoma (lung SCC) is a common type of lung cancer, but its mechanism of pathogenesis is unclear. The aim of this study was to identify key transcription factors in lung SCC and elucidate its mechanism.
MATERIAL AND METHODS: Six published microarray datasets of lung SCC were downloaded from Gene Expression Omnibus (GEO) for integrated bioinformatics analysis. Significance analysis of microarrays was used to identify differentially expressed genes (DEGs) between lung SCC and normal controls. The biological functions and signaling pathways of DEGs were mapped in the Gene Otology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, respectively. A transcription factor gene regulatory network was used to obtain insights into the functions of DEGs.
RESULTS: A total of 1,011 genes, including 539 upregulated genes and 462 downregulated genes, were filtered as DEGs between lung SCC and normal controls. DEGs were significantly enriched in cell cycle, DNA replication, p53 signaling pathway, pathways in cancer, adherens junction, and cell adhesion molecules signaling pathways. There were 57 transcription factors identified, which were used to construct a regulatory network. The network consisted of 736 interactions between 49 transcription factors and 486 DEGs. NFIC, BRCA1, and NFATC2 were the top 3 transcription factors that had the highest connectivity with DEGs and that regulated 83, 82, and 75 DEGs in the network, respectively.
CONCLUSIONS: NFIC, BRCA1, and NFATC2 might be the key transcription factors in the development of lung SCC by regulating the genes involved in cell cycle and DNA replication pathways.
Keywords: Gene Expression Regulation, Neoplastic, Gene Expression Profiling, Carcinoma, Squamous Cell - genetics, gene ontology, Gene Regulatory Networks, Lung Neoplasms - genetics, Molecular Sequence Annotation, Transcription Factors - metabolism