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International Journal of Endocrinology
Volume 2015 (2015), Article ID 164087, 7 pages
Research Article

Identification of Differentially Expressed Genes in Pituitary Adenomas by Integrating Analysis of Microarray Data

1Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
2Department of Cardiology, Beijing Chuiyangliu Hospital, Beijing, China
3Beijing Neurosurgical Institute, Center of Brain Tumor, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China

Received 22 September 2014; Revised 16 December 2014; Accepted 16 December 2014

Academic Editor: Maria L. Dufau

Copyright © 2015 Peng Zhao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Pituitary adenomas, monoclonal in origin, are the most common intracranial neoplasms. Altered gene expression as well as somatic mutations is detected frequently in pituitary adenomas. The purpose of this study was to detect differentially expressed genes (DEGs) and biological processes during tumor formation of pituitary adenomas. We performed an integrated analysis of publicly available GEO datasets of pituitary adenomas to identify DEGs between pituitary adenomas and normal control (NC) tissues. Gene function analysis including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) networks analysis was conducted to interpret the biological role of those DEGs. In this study we detected 3994 DEGs (2043 upregulated and 1951 downregulated) in pituitary adenoma through an integrated analysis of 5 different microarray datasets. Gene function analysis revealed that the functions of those DEGs were highly correlated with the development of pituitary adenoma. This integrated analysis of microarray data identified some genes and pathways associated with pituitary adenoma, which may help to understand the pathology underlying pituitary adenoma and contribute to the successful identification of therapeutic targets for pituitary adenoma.