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
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
Microarray dataset of gene expression, GSE26966 [14], was downloaded from the Gene Expression Omnibus (
Robust multi-array average algorithm in the affy package (from
Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted using package GOstats (
For all of the identified DEGs, a PPI network was constructed with information from a well-known online server, Search Tool for the Retrieval of Interacting Genes/ Proteins version 10 (STRING v10) (
In order to find potential novel disease genes, known genes implicated in pituitary tumorigenesis were obtained from the Comparative Toxicogenomics Database (CTD) (the most recently released version was up-dated on February 9 2016,
A total of 604 DEGs were acquired between NFPAs and controls, involving 177 up- and 427 down-regulated genes. The top 10 up-regulated genes and top 10 down-regulated genes are shown in Table 1. The 604 DEGs and 23 samples were clustered, and DEGs could well differentiate the disease samples from the healthy controls (Figure 1).
The top 10 up-regulated genes and top 10 down-regulated genes. Corrected Genes Log2 FC Corrected Gene Title 2.04 1.43E-10 single-stranded DNA binding protein 2 2.68 1.43E-10 cadherin 10, type 2 (T2-cadedrin) 2.18 2.45E-10 family with sequency similarity 171, member A1 2.05 8.76E-10 ephrin-B3 2.16 9.13E-10 phosphate cytidylytransferase 1, choline, β 2.26 1.16E-09 ring finger protein 157 2.46 1.57E-09 cyclin-dependent kinase 18 3.63 2.01E-09 leucine rich repeat and fibronectin type III domain containing 5 4.11 2.92E-09 calcium channel, voltage-dependent, a2/δ subunit 4 2.97 5.94E-09 peroxisome proliferator-activated receptor γ, coactivator 1 β –9.74 1.49E-21 growth hormone 1 –8.67 3.69E-15 chorionic somatomammotropin hormone 1 (placental lactogen) –9.33 4.16E-15 δ-like 1 homolog (Drosophila) –9.17 3.14E-13 chorionic somatomammotropin hormone 2 –2.16 5.43E-12 huntingtin interacting protein 1 related –2.33 4.74E-11 cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4) –2.86 8.06E-11 matrix Gla protein –3.79 9.50E-11 potassium inwardly-rectifying channel, subfamily J, member 6 –2.32 1.03E-10 sprouty homolog 4 (Drosophila) –5.72 1.60E-10 maternally expressed 3 (non-protein coding)
Cluster analysis of DEGs. DEGs: differentially expressed genes; T: tumor samples; N: healthy normal samples. Cluster analysis was performed both at gene level (vertical) and sample level (horizontal).
The GO enrichment analysis and KEGG pathway analysis were performed to reveal the key biological functions altered in NFPAs. As shown in Table 2, 12 pathways were significantly enriched, which were mainly associated with signaling pathway and receptor interaction. In GO enrichment analysis, DEGs were significantly enriched in 1037 biological process terms mainly about cell communication and signaling, 65 cellular component terms mainly related with an extracellular matrix (ECM), plasma membrane, and collagen, as well as 186 molecular function terms mainly associated with transcription factor activity and receptor binding (Table 2). In order to better understand the positions of DEGs in pathways and their roles in the development of NFPAs, we visualized four significant pathways that had been reported to participate in the pathogenesis of NFPAs or PAs, including MAPK signaling pathway [10] (Figure 2), p53 signaling pathway [24] (Figure 3), transforming growth factor β (TGFβ), signaling pathway [25] (Figure 4), and Jak-STAT signaling pathway [8] (Figure 5).
Significantly enriched terms. ID: identifier; DEGs: differentially expressed genes; KEGG: Kyoto Encyclopedia of Genes and Genomes; GO: gene ontology; BP: biological process; CC: cellular component; MF: molecular functions.Category Term ID Corrected Number Number of Term KEGG K04610 3.18E-04 10 69 complement and coagulation cascades K04512 3.97E-04 11 84 extracellular matrix-receptor interaction K04010 4.55E-03 20 271 MAPK signaling pathway K04115 5.32E-02 8 69 p53 signaling pathway K00350 6.79E-03 9 87 transforming growth factor β signaling pathway K04630 7.62E-03 13 155 Jak-STAT signaling pathway K04080 1.14E-02 18 256 neuroactive ligand-receptor interaction K04510 1.27E-02 15 202 focal adhesion K05218 2.08E-02 7 71 Melanoma K05412 2.90E-02 7 76 arrhythmogenic right ventricular cardiomopathy K05210 4.63E-02 7 84 colorectal cancer K04920 4.70E-02 6 67 adipocytokine signaling pathway GO BP GO:0032501 2.26E-24 266 4974 multicellular organismal process (top 10) GO:0010243 6.92E-13 57 596 response to organic nitrogen GO:0007275 4.19E-12 112 2080 multicellular organismal development GO:0048583 2.00E-10 99 1624 regulation of response to stimulus GO:0023051 4.23E-10 110 1866 regulation of signaling GO:0010646 5.12E-10 110 1872 regulation of cell communication GO:0048812 1.38E-09 49 571 neuron projection morphogenesis GO:0048667 3.03E-09 48 566 cell morphogenesis involved in neuron differentiation GO:0007243 3.09E-09 64 879 intracellular protein kinase cascade GO:0022008 6.39E-09 63 900 neurogenesis GO CC GO:0005576 1.31E-14 132 2164 extracellular region (top 10) GO:0005615 1.19-E-09 61 848 extracellular space GO:0005587 1.37E-05 4 6 collagen type IV GO:0005581 1.90E-05 12 88 collagen GO:0043005 5.12E-05 39 634 neuron projection GO:0005578 5.72E-05 18 204 proteinaceous extracellular matrix GO:0031012 8.74E-05 9 62 extracellular matrix GO:0016323 1.39E-04 15 158 basolateral plasma membrane GO:0005887 5.55E-04 59 1216 integral to plasma membrane GO:0005584 9.84E-04 2 2 collagen type I GO MF GO:0005201 2.40E-10 17 78 extracellular matrix structural constituent (top 10) GO:0008201 1.20E-07 18 129 heparin binding GO:0097367 1.60E-07 22 191 carbohydrate derivative binding GO:0042803 5.71E-06 38 553 protein homodimerization binding GO:0005179 9.11E-11 14 110 hormone activity GO:0000981 1.75E-05 22 253 sequence specific DNA binding RNA polymerase II transcription factor activity GO:0001077 4.36E-05 10 67 RNA polymerase II core promoter proximal region sequence-specific DNA binding transcription factor activity involved in positive regulation of transcription GO:0019199 5.05E-05 11 82 transmembrane receptor protein kinase activity GO:0005102 1.92E-04 55 1093 receptor binding GO:0048407 2.70E-04 4 11 platelet-derived growth factor binding
The MAPK signaling pathway. Genes down-regulated in NFPAs are shown in green, while up-regulated genes are in red.
The p53 signaling pathway. Genes down-regulated in NFPAs are shown in green, while up-regulated genes are in red.
The TGFβ signaling pathway. Genes down-regulated in NFPAs are shown in green, while up-regulated genes are in red.
Jak-STAT signaling pathway. Genes down-regulated in NFPAs are shown in green, while up-regulated genes are in red.
For the 604 DEGs, the PPI network was constructed using information from STRING v10 (Figure 6). The whole network consisted of 115 up-regulated DEGs, 305 down-regulated DEGs and 1379 PPIs (Figure 6).
The whole PPI network of DEGs. Red nodes represent the genes up-regulated in NFPAs, and green nodes represent the genes down-regulated in NFPAs. Circle nodes stand for known disease genes, whereas triangle nodes stand for potential novel disease genes. Node size positively correlates with node degree, namely, the number of neighbors. PPI: protein-protein interaction; DEGs: differentially expressed genes; NFPAs: non-functioning pituitary adenomas.
Known disease genes were obtained from the CTD database (
The PPI sub-network containing the top 10 DEGs. Red nodes represent the genes up-regulated in NFPAs, and green nodes represent the genes down-regulated in NFPAs. Circle nodes stand for known disease genes, whereas triangle nodes stand for potential novel disease genes. Node size positively correlates with node degree, namely, the number of neighbors. PPI: protein-protein interaction; DEGs: differentially expressed genes; NFPAs: non-functioning pituitary adenomas.
Non-functioning pituitary adenomas comprise about 34.0% of pituitary tumors, while their molecular mechanism is still incompletely understood [5]. In the current study, we comprehensively analyzed the gene expression profile of NFPAs and healthy pituitary glands. As a result, 604 DEGs were identified between NFPAs and controls, including 177 up- and 427 down-regulated genes, which were much less than those identified by Michaelis
In the current study, mean FC of the up-regulated genes was 6.6, and mean FC of the down-regulated genes was –19.2, which were different from those in the previous study by Michaelis
Of the top DEGs,
Expressions of
Furthermore, potential novel genes were identified (Figure 6), especially
We found DEGs were significantly enriched in the p53 (Figure 3) and Jak-STAT signaling pathways (Figure 5), which had been reported to take part in PAs pathogenesis [8,24]. The p53 signaling pathway is involved in biological processes such as cell cycle arrest, apoptosis, senescence, DNA repair and changes in metabolism. Expression level of p53 correlates with the proliferative state of PAs [24]. The Jak-STAT pathway is an important downstream pathway for growth factor receptors and cytokine receptors, and it is involved in the regulation of cell proliferation and survival [34,35]. As all of the DEGs mapped on these pathways were remarkably down-regulated in NFPAs, p53 and Jak-STAT signaling pathways might play roles in the progression of NFPAs.
In addition, DEGs were significantly enriched in GO terms mainly about cell communication, signaling, ECM, plasma membrane, collagen, transcription factor activity and receptor binding (Table 2). The ECM, plasma membrane, and receptor binding are the basis of cell communication and signaling between pituitary cells, which play crucial roles in the development and invasion of PAs [36, 37]. As DEGs mapped on these GO terms were remarkably dysregulated in NFPAs, cell communication and signaling might contribute to the progression of NFPAs.
In conclusion, a number of genes (