Zhang C.L.¹ , Zhao N.¹ , Wu S.Y.³ , Song J.² , Kang Y.J.² , Liu S.² , Zhang D.W.²

1. College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
2. The 2nd Affiliated Hospital, Harbin Medical University, Harbin, 150081, China
3. Software College, East China University of Technology, Nanchang, 330013, China
Author    Correspondence author
Cancer Genetics and Epigenetics, 2015, Vol. 3, No. 12   doi: 10.5376/cge.2015.03.00012
Received: 02 Oct., 2015    Accepted: 13 Nov., 2015    Published: 18 Nov., 2015

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Zhang C.1, Zhao N.1, Wu S.3, Song J.2, Kang Y.2, Liu S.2, and Zhang D.2, 2015, The Identification of Differentially Expressed Genes of Human Prolactinoma by Microarray, Vol.3, No.12, 1-8 (doi: 10.5376/cge.2015.03.00012)

Prolactinoma is the most common intracranial neoplasms. Although prolactinoma is always treated with anticarcinogen, many patients recurrence after curing. This indicates that we need to identify a new mechanism for the treatment of prolactinoma. In order to recognize new biomarkers, we identify the differentially expressed genes (DEGs) by the microarray. A total of 86 DEGs are identified including 35 up-regulated genes and 51 down-regulated genes. The set of DEGs can distinguish tumor samples and normal samples significantly. The genes are mainly enriched in 33 Go terms and 2 kegg pathways associated with prolactinoma. In order to recognize the function of DEGs, we import these genes into protein-protein interaction network to analyze these genes. For example, MDM2, LYN, CDH1, GH1, ACTG1 and FUS play an important role in prolactinoma. In summary, the gene set we recognize can provide potential effect for treatment of prolactinoma.

Microarray; Bioinformatics;Biomarker;Prolactinoma; Differentially expressed gene