MICROARRAY TECHNOLOGY REVEALS POTENTIALLY NOVEL GENES AND PATHWAYS INVOLVED IN NON-FUNCTIONING PITUITARY ADENOMAS
Qiao X, Wang H, Wang X, Zhao B, Liu J,
*Corresponding Author: Jun Liu, M.D., Department of Neurosurgery, The Second Hospital of Jilin University, 218 Ziqiang Road, Changchun, 130021, Jilin Province, People’s Republic of China. Tel: +86-138-0431-7080. E-mail: LiuJun66@126.com
page: 5

INTRODUCTION

As a kind of benign adenomas in the pituitary gland, clinically non-functioning pituitary adenomas (NFPAs) are the most common type of pituitary macroadenomas in adults. The NFPAs account for about 34.0% [1] of all pituitary adenomas (PAs) that occur at a prevalence rate of 75-94 per 100,000 [1,2]. Patients with NFPAs generally suffer from headaches, hypopituitarism, hypogonadism and visual field defects. Late diagnosis due to inconspicuous signs and symptoms, extension to the cavernous sinus and sellar floor, resistance to pharmacological therapy and high recurrence rate, make their treatment disappointing and challenging [3]. Approximately 80.0% of NFPAs originate from gonadotroph cells (gonadotroph pituitary adenoma, GnPA) [4], and other NFPAs are mainly associated with null cells (null cell pituitary adenoma, ncPA). The identification of novel therapeutic targets for human NFPAs depend on a good understanding of the molecular mechanism of NFPAs [5]. Progression in understanding the mechanism of PAs, especially NFPAs, has been achieved over the last several years. According to the reports, germline mutations in AIP or MEN1 genes are associated with young age-onset PAs [6,7]. The HGF and c-MET genes are frequently expressed in PAs, and their expressions are correlated with phos-phorylated Akt expression [8]. Durán-Prado et al. [9] identified that sst5TMD4, a truncated variant of somatostatin receptor 5, appeared in 85.0% PAs rather than normal pituitary, and it may play an inhibitory role in PAs that possess poor response to somatostatin analogs. Raf/ MEK/ ERK and PI3K/Akt/mTOR signaling pathways are perturbed in NFPAs [10]. As a target of the SF1 gene in gonadotroph cells, CYP11A1 is up-regulated in human GnPA, and Cyp11a1 promotes survival and proliferation of primary cells and cell lines of rat PAs [5]. Rotondi et al. [11] suggested that the gonadotroph phenotype was strongly associated with AIP expression in NFPAs. The AIP level is higher in GnPA than that in ncPA, and both AIP and cyclinD1 levels are high in most NFPAs. The AIP level correlates with follicle-stimulating hormone β (FSHβ) and cyclinD1 levels in GnPA. However, AIP is not involved in the aggressiveness of NFPAs [11]. Recently, CCNB1 was found to mediate the proliferation-inhibiting role of miR-410, a small non-coding RNA, in GnPA [12]. Additionally, Chesnokova et al. [13] have identified that human pituitary tumors originated from gonadotroph cells express abundant FOXL2, and both FOXL2 and PTTG promote cluster- ing expression and secretion from gonadotroph cells, thus restraining the proliferation of pituitary cells. Along with the development of microarray, transcriptome analysis has been widely utilized in understanding tumor mechanism. Based on the gene expression microarray dataset GSE26966, Michaelis et al. [14] identified that GADD45β, a downstream effector of p53, is a tumor suppressor in gonadotroph tumor. Its overexpression in mouse gonadotroph cells blocks cell proliferation and promotes apoptosis [14]. Based on the same dataset, Cai et al. [15] identified the coexpressed and altered genes involved in gonadotroph tumors and suggest that ITGA4, MPP2, DLK1, CDKN2A and ASAP2 might be biomarkers. However, pathways or functions of the altered genes were not studied by Michaelis et al. [14], and the protein-protein interactions (PPIs) between genes were not investigated in the two aforementioned studies [14,15]. In particular, Zhao et al. [16] performed an integrated analysis of five available microarray datasets of various PAs, to detect 3994 differentially expressed genes (DEGs) (including 2043 up- and 1951 down-regulated genes), and conducted a PPI network analysis. However, PPIs of more DEGs are needed to be analyzed, and more potential novel PAs-related genes are still unknown. Moreover, molecular mechanisms underlying the pathogenesis of PAs, particular NFPAs, remain unclear, and it is still essential to comprehensively investigate and annotate the alterations in gene expression profiles. In the present study, NFPAs-related microarray data uploaded by Michaelis et al. [14] were analyzed to identify significant DEGs, study NFPAs-related functions and pathways, construct interaction network, and identify potential novel NFPAs-related genes.



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