Microarray data analysis reveals differentially expressed genes in prolactinoma.

Gene expression profiles of prolactinomas were compared with those of normal pituitary glands to identify differentially expressed genes (DEGs). Protein-protein interaction (PPI) analysis and protein complex prediction were performed to reveal the cross-talk between these genes and molecular mechanisms underlying the disease. Microarray data were downloaded from Gene Expression Omnibus. DEGs were screened using GEO2R and false discovery rate (FDR) < 0.05 was set as the cut-off. Protein-protein interaction (PPI) network was constructed with information from STRING and significant KEGG pathways were unveiled. Protein complexes were predicted using ClusterONE from Cytoscape and then validated in terms of pathways, protein domain, cellular localization and literatures. A total of 1712 genes (1911 probes) were found to be differentially expressed in prolactinoma. Interactions were identified among 121 protein products. Nineteen significant pathways (FDR< 0.05) were acquired and pathways in cancer was the top one. Pathways linked to myeloid leukemia and tryptophan metabolism were also enriched in the DEGs. Four protein complexes were predicted and then validated. They were associated with focal adhesion, cytoskeleton, metabolism of tryptophan, arginine and proline as well as aldehyde dehydrogenases. They might play important roles in the pathogenesis of prolactinoma. In present study, not only DEGs were provided, but also PPIs and protein complexes were discussed. These findings promoted the knowledge about prolactinoma and provided novel candidate targets for the therapy development of prolactinoma.

BACKGROUND

prolactinoma, differentially expressed genes, protein-protein interaction network, protein complex.