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Identification of differentially coexpressed genes in gonadotrope tumors and normal pituitary using bioinformatics
Tao Cai1, Jie Xiao, Zhi-Fei Wang
1Department of Otolaryngology, The First Xiangya Hospital of Central South University, Changsha, Hunan Province, China.
Abstract:
To investigate the underlying molecular mechanisms of pituitary tumor by using the microarray expression profiles of pituitary tumor and normal tissue samples. The gene expression profile of GSE26966 was downloaded from Gene Expression Omnibus, including nine normal samples and 14 pituitary tumor samples. The differentially coexpressed genes (DEGs) were identified by Affy package in R Software. The functional and pathway enrichment analysis of the screened DEGs were performed by DAVID. Then, differential coexpression networks were contructed and further analyzed. Functional and pathway enrichment analysis of the 1220 identified DEGs revealed that phosphatidylinositol signaling system, p53 signaling pathway and inositol phosphate metabolism were disturbed in pituitary tumors. The degree of DLK1, CDKN2A and ITGA4 in the constructed differential coexpression network was 46, 45 and 44, respectively. In addition, MPP2 and ASAP2 were the obvious hub genes in the constructed differential coexpression network. Through exploring genes in the differential coexpression networks, the results suggested that DLK1, CDKN2A, ITGA4, MPP2 and ASAP2 may potentially be used as biomarkers for pituitary tumor.
