Identification of driver genes and key pathways of non-functional pituitary adenomas predicts the therapeutic effect of STO-609

Bo Wu; Shanshan Jiang; Xinhui Wang; Sheng Zhong; Yiming Bi; Dazhuang Yi; Ge Liu; Fangfei Hu; Gaojing Dou; Yong Chen; Yi Wu; Jiajun Dong

doi:10.1371/journal.pone.0240230

. 2020 Oct 29;15(10):e0240230. doi: 10.1371/journal.pone.0240230

Identification of driver genes and key pathways of non-functional pituitary adenomas predicts the therapeutic effect of STO-609

Bo Wu ^1,^2,^#, Shanshan Jiang ^3,^#, Xinhui Wang ^1,⁴, Sheng Zhong ⁵, Yiming Bi ⁶, Dazhuang Yi ⁶, Ge Liu ⁷, Fangfei Hu ⁷, Gaojing Dou ^1,⁸, Yong Chen ⁶, Yi Wu ^9,^‡,^*, Jiajun Dong ^9,^‡,^*

Editor: Tomasz Boczek¹⁰

PMCID: PMC7595405 PMID: 33119597

Abstract

Objective

Our study is to identify DEGs (Differentially Expressed Genes), comprehensively investigate hub genes, annotate enrichment functions and key pathways of Non-functional pituitary adenomas (NFPAs), and also to verify STO-609 therapeutic effect.

Methods

The gene expression level of NFPA and normal tissues were compared to identify the DEGs (Differential expressed genes) based on gene expression profiles (GSE2175, GSE26966 and GSE51618). Enrichment functions, pathways and key genes were identified by carrying out GO (Gene Ontology), KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis and PPI (Protein-Protein Interation) network analysis. Moreover, experiments in vitro were conducted to verify the anti-NFPAs effects of STO-609.

Results

169 over-expression genes and 182 low expression genes were identified among 3 datasets. Dopaminergic synapse and vibrio cholerae infection pathways have distinctly changed in NFPA tissues. The Ca²⁺/CaM pathway played important roles in NFPA. Four hub proteins encoded by genes CALM1, PRDM10, RIPK4 and MAD2L1 were recognized as hub proteins. In vitro, assays showed that STO-609 induced apoptosis of NFPA cells to inhibit the hypophysoma cellular viability, diffusion and migration.

Conclusion

Four hub proteins, encoded by gene CALM1, PRDM10, RIPK4 and MAD2L1, played important roles in NFPA development. The Ca²⁺/CaM signaling pathway had significant alternations during NFPA forming process, the STO-609, a selective CaM-KK inhibitor, inhibited NFPA cellular viability, proliferation and migration. Meanwhile, NFPA was closely related to parkinson’s disease (PD) in many aspects.

Introduction

Human pituitary adenomas, accounting for 10% of intracranial tumors, are common intracranial primary neoplasms [1]. Pituitary adenomas (PA) encompass two types, one is functional endocrine, symptomatic or functional active type, and the other one is non-functioning, null cell or functionally inactive type [2]. Non-functional Pituitary Adenomas (NFPAs) comprises approximately 30% of PA [3]. The levels of hormones in the blood do not alter significantly in NFPA patients, accordingly the patients don’t have any clinical symptoms caused by hormone hypersecretion. Although NFPAs are histologically benign tumors [4], which is defined as level I according to WHO (2016) pathologic grading criteria [5], it is difficult to diagnose them in the primary stage due to the lack of clinical manifestations of hormone hypersecretion and the absence of specific serological markers. Along with the condition development, tumors suppress adjacent tissue and then clinical symptoms appear, which accounts for patients compression symptoms [6]. These complications will seriously affect the nervous system function and reduce the quality of life. In addition, the overall risk of malignant tumors in patients with NFPA is higher [7].

The diagnostic approaches regarding to NFPAs include perimetry, the evaluation of all anterior pituitary hormone systems, and the sellar region of tumor in MRI [8]. Except for a few functional PA, which can be controlled by drugs, it hasn’t been any effective drug treatment for NFPAs so far. Treatments for NFPAs are surgical treatment and radiotherapy. The standard treatment for NFPA is surgical resection, endoscopic trans-sphenoidal approach is the most accepted approach to reduce the tumor size and to improve clinical symptoms [9, 10]. NFPAs are mostly benign, however, the tumor sometimes suppresses and invades the surrounding tissue. Thus tumors are difficult to be resected completely and tend to relapse after initial surgery [11]. The recurrence rate after operation is up to 30%. Radiation therapy is usually used in the treatment of persistent or recurrent adenomas, however, the treatment effect is still unsatisfactory [8]. So novel therapeutic methods and medicines are needed urgently.

After decades studies, the molecular pathogenesis of NFPAs is still turbid. Our knowledge regarding to NFPAs is still superficial and provincial [12], there is a lack of definite index to guide the clinical practice. In addition, trans-sphenoidal surgery, the most accepted treatment approach for NFPAs, still contains many surgical complications, such as postoperative endocrine deficits, postoperative infection, cerebrospinal fluid leak etc. However, there is still no potent drug for NFPAs. The genes, proteins interaction and small molecules drugs research regarding to NFPAs have been rarely conducted in the past decades. So conducting a study which comprehensively depicts molecular pathogenesis of NFPAs as well as identifies novel drugs for NFPAs is necessary and crucial.

Our study used bioinformatics methods, especially combining with microarray technology, GO, KEGG analysis and PPI network analysis, employing 3 datasets (GSE2175, GSE26966 and GSE51618) to screen out the DEGs. Then, hub genes and key pathways were screened, which could be exploited to select novel molecular targets for NFPA diagnosis and treatment. Meanwhile, a series of assays in vitro were conducted to verify the anti-NFPAs effect of STO-609, which is a selective and cell-permeable inhibitor of the Ca2+/calmodulin-dependent protein kinase kinase (CaM-KK) [13]. STO-609 operates downstream of CALMA, and inhibits the Ca²⁺/CaM signaling pathway on account of the ATP-competitive inhibition to CaM-KK [14], as shown in Fig 1.

Materials and methods

Microarray data

Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo) database is a public database, which stores a great quantity of studies related to high throughput functional genomic researches [15]. Profiles GSE2175, GSE26966 and GSE51618 were obtained from this database. The GSE2175 dataset contains 5 samples, from which we choose a normal one and a pathological one [16]. The GSE26966 dataset contains 23 samples, from which we choose 13 effective ones (9 normal and 4 pathological) [17]. And the GSE51618 dataset contains 3 normal samples and 7 pathological samples.

Identification of DEGs

Genespring software (version 11.5, Agilent, USA) was used for data analysis. We compared expression level of genes of NFPAs and normal tissue for DEGs. In GeneSpring, hierarchical clustering analysis and principal component analysis (PCA) were applied to ensure probe quality control. Probes that intensity values below 20th percentile were eliminated using the “filter probesets by expression” option. Classical t test was performed with a change > 2 fold and P < 0.05 was defined to be statistically significant. For three datasets, we did the same operation three times. Then, website tool was used to draw Venn diagrams of three groups of DEGs. (http://bioinformatics.psb.ugent.be/webtools/Venn/).

Gene ontology and pathway enrichment analysis

The Database for Annotation, Visualization and Integrated Discovery (DAVID, http://david.abcc.ncifcrf.gov/) provides tools to help users learn the biological meaning behind DEGs. Biological processes (BP), molecular functions (MF) and cellular components (CC) of genes were analyzed with GO analysis, and enrichment pathways of those genes were identified with KEGG analysis.

Integration of PPI network construction and modules selection

STRING (Search Tool for the Retrieval of Interacting Genes, http://string.embl.de/) database provides an available option for users to evaluate the proteins interaction information on line. Then, the information was analyzed in Cytoscape software. Main modules were screened with scores > 3.6 and number of nodes>11 by Molecular Complex Detection (MCODE). Genes belong to modules were also performed with GO and KEGG analysis.

Cell lines and reagents

HP75, a non-functional pituitary adenoma cell line, was cultured in DMEM (BioWhittaker, Cambrex Corp., Nottingham, UK) containing 15% horse serum (TCS Cellworks, Buckingham, UK), and 2.5% fetal calf serum (Life Technologies, Paisley, UK) at 37°C in an easeful air atmosphere containing 5% carbon dioxide. AtT-20 (mouse normal pituitary cells) and GT1-1 (mouse pituitary adenoma cells) were cultured in DMEM, containing 10% FCS, at 37°C in the same air environment. STO-609, a selective inhibitor of CaM-KK, which inhibited the Ca²⁺/CaM signaling pathway, was purchased from Apexbio Inc. (Apexbio, Houston, USA). STO-609 was dissolved in DMSO to obtain the stock solution, then appropriate culture medium was respectively added to the stock solution to configure cell culture medium with different STO-609 concentration.

CCK-8 assay

The cells, HP75 and GT1-1, viability were assessed by Cell Counting Kit-8 (CCK-8) (Dojindo Laboratories, Kumamoto, Japan). We seeded the cells into 96-well plates for overnight, and the density is 1.0×10⁵ cells/well. After washing culture medium, different doses of STO-609 were used to the cells and cultured for 24h, control group and solvent control group were classed by using normal saline (NS) and DMSO respectively, and 6 wells were prepared for doses of STO-609 (concentration gradients were 0.4μmol/L, 0.8μmol/L, 1.6μmol/L, 3.2μmol/L, 6.4μmol/L, 12.8μmol/L, 25.6μmol/L and 51.2μmol/L). Cells were cultured for 1h after added CCK-8 into wells with a quantity of 10μl/well. The wave length of 450 nm was applied to measure OD value of each well on the microplate reader (Multiskan, Thermo, USA).

Colony-forming assay

HP75 and GT1-1 were inoculated in a six-well cell culture plate with density of 50 cells per square centimetre, and the surface area of each well of the culture plate was 9.6 cm². After 24h in culture, we configured cell culture medium with STO-609 concentration of 0.25μmol/L and 1μmol/L. The concentration of DMSO was less than 0.1%. In this concentration, the influence of DMSO on cells was negligible. After 10 days, we counted and described colonies refer to Franken et al. [18]. Moreover, colonies were dyed by 5% crystal violet for half an hour after fixed in 4% paraformaldehyde.

In vitro scratch assay

GT1-1 cells were seeded into PermanoxTM plates (24-well) and cultured. The cell-free area was made with a 1ml pipette. After 24h in culture, different doses of STO-609 were used to treat the cells at 0, 12, 24 hours, we captured the scraped area images with phase contrast microscopy, and measured the wounds and scratch width.

Apoptosis assays

The HP75 cells in the log growth phase were inoculated into 6-well plates, and the density was 2 × 10⁵ cells/well. Different doses of STO-609 were used to treat cells. After 24h in culture, cells were harvested and Annexin-V-FITC/PI labeling was conducted. Then, the stained cells were analyzed flow cytometer and calculated with FACSDiva version 6.2.

Statistical analysis

SPSS18.0(SPSS Inc., Chicago, Illinois, USA) was applied for all statistics data. The independent-samples t test method was used for quantitative data of bioinformatical analysis, while Analysis of Variance (ANOVA) was conducted to analyse multiple comparison data of cell assays. Dunnett-t test was performed as post hoc test after ANOVA. Significance level was marked with P values < 0.05.

Results

Identification of DEGs

There are 12500, 3102 and 1341 DEGs were identified from GSE2175, GSE26966, and GSE51618 profiles. Then Venn plot showed that 351 DEGs in NFPA tissues in all three datasets, among which were 169 up-regulated and 182 down-regulated. The Venn plot of DEGs was exhibited on Fig 2A, and the details were placed on S1 Table. The hub genes expression heat maps were also exposed on Fig 2C and 2D.

Gene ontology and pathway enrichment analysis of DEGs

In order to obtain further insight of DEGs, we respectively put the up-regulated and down-regulated DEGs into DAVID, and the details of results were showed in Fig 2B, 2E and 2F and Table 1. GO analysis results demonstrated that up-regulated DEGs were enriched in regulation of myocardial contraction by calcium signal and regulation of growth in BP analysis, while CC analysis displayed the enrichment in endoplasmic reticulum membrane, membrane and nucleoplasm. As for MF analysis, microtubule binding and protein binding are enriched with up-regulated DEGS. Meanwhile, the down-regulated DEGs in BP analysis were enriched in cell migration and transforming growth factor β receptor signaling pathway. Besides, the CC analysis showed the enrichment of these down-regulated DEGs in extracellular region, integral component of plasma membrane and neuronal cell body. For MF analysis, the enrichment was in protein homodimerization activity. In addition, the KEGG analysis results respectively demonstrated the enriched pathways of up- and down-regulated DEGs: dopaminergic synapse was where up-regulated DEGs mainly enriched, while vibrio cholerae infection was the point of down-regulated DEGs. The GSEA analysis results revealed that the pathway of parkinson’s disease (PD) and the pathway of vibrio choleras infection were significantly altered.

Table 1. Functional and pathway enrichment analysis of up-regulated and down-regulated genes in NFPAs.

Expression	Category	Term	Count	%	PValue
Up-regulated	GOTERM_BP_DIRECT	GO:0010882~regulation of cardiac muscle contraction by calcium ion signaling	3	1.29	3.11E-03
	GOTERM_BP_DIRECT	GO:0040008~regulation of growth	5	2.15	4.24E-03
	GOTERM_BP_DIRECT	GO:0051301~cell division	12	5.15	4.52E-03
	GOTERM_BP_DIRECT	GO:0006811~ion transport	7	3.00	5.14E-03
	GOTERM_BP_DIRECT	GO:0070886~positive regulation of calcineurin-NFAT signaling cascade	3	1.29	5.24E-03
	GOTERM_CC_DIRECT	GO:0005789~endoplasmic reticulum membrane	27	11.59	2.26E-05
	GOTERM_CC_DIRECT	GO:0016020~membrane	46	19.74	3.83E-04
	GOTERM_CC_DIRECT	GO:0005654~nucleoplasm	53	22.75	1.08E-03
	GOTERM_CC_DIRECT	GO:0000922~spindle pole	7	3.00	2.28E-03
	GOTERM_CC_DIRECT	GO:0000139~Golgi membrane	16	6.87	6.66E-03
	GOTERM_MF_DIRECT	GO:0008017~microtubule binding	10	4.29	1.42E-03
	GOTERM_MF_DIRECT	GO:0005515~protein binding	134	57.51	2.21E-03
	GOTERM_MF_DIRECT	GO:0051010~microtubule plus-end binding	3	1.29	8.23E-03
	GOTERM_MF_DIRECT	GO:0004385~guanylate kinase activity	3	1.29	9.80E-03
	GOTERM_MF_DIRECT	GO:0003677~DNA binding	33	14.16	1.29E-02
	KEGG_PATHWAY	hsa04728:Dopaminergic synapse	9	3.86	4.65E-04
	KEGG_PATHWAY	hsa04022:cGMP-PKG signaling pathway	10	4.29	5.83E-04
	KEGG_PATHWAY	hsa04713:Circadian entrainment	7	3.00	2.31E-03
	KEGG_PATHWAY	hsa04723:Retrograde endocannabinoid signaling	7	3.00	3.15E-03
	KEGG_PATHWAY	hsa05034:Alcoholism	9	3.86	3.73E-03
Down-regulated	GOTERM_BP_DIRECT	GO:0016477~cell migration	13	5.33	2.85E-06
	GOTERM_BP_DIRECT	GO:0007179~transforming growth factor beta receptor signaling pathway	8	3.28	2.05E-04
	GOTERM_BP_DIRECT	GO:0002053~positive regulation of mesenchymal cell proliferation	5	2.05	3.42E-04
	GOTERM_BP_DIRECT	GO:0060397~JAK-STAT cascade involved in growth hormone signaling pathway	4	1.64	8.98E-04
	GOTERM_BP_DIRECT	GO:0071603~endothelial cell-cell adhesion	3	1.23	1.01E-03
	GOTERM_CC_DIRECT	GO:0005576~extracellular region	38	15.57	2.59E-04
	GOTERM_CC_DIRECT	GO:0005887~integral component of plasma membrane	32	13.11	1.84E-03
	GOTERM_CC_DIRECT	GO:0043025~neuronal cell body	12	4.92	2.28E-03
	GOTERM_CC_DIRECT	GO:0031012~extracellular matrix	11	4.51	4.50E-03
	GOTERM_CC_DIRECT	GO:0009986~cell surface	15	6.15	9.15E-03
	GOTERM_MF_DIRECT	GO:0042803~protein homodimerization activity	25	10.25	2.80E-05
	GOTERM_MF_DIRECT	GO:0005179~hormone activity	7	2.87	1.40E-03
	GOTERM_MF_DIRECT	GO:0008201~heparin binding	8	3.28	4.92E-03
	GOTERM_MF_DIRECT	GO:0043621~protein self-association	4	1.64	2.17E-02
	GOTERM_MF_DIRECT	GO:0019003~GDP binding	4	1.64	3.29E-02
	KEGG_PATHWAY	hsa04151:PI3K-Akt signaling pathway	17	6.97	1.25E-04
	KEGG_PATHWAY	hsa05110:Vibrio cholerae infection	5	2.05	1.04E-02
	KEGG_PATHWAY	hsa00270:Cysteine and methionine metabolism	4	1.64	2.32E-02
	KEGG_PATHWAY	hsa04261:Adrenergic signaling in cardiomyocytes	7	2.87	3.09E-02
	KEGG_PATHWAY	hsa04015:Rap1 signaling pathway	8	3.28	5.38E-02

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Integration of PPI network construction and modules selection

The hub nodes with degrees more than 12 were defined as hub proteins, which played important roles in NFPA listing in Table 2. Four hub proteins encoded by genes CALM1 (calmodulin 1), PRDM10 (PR/SET domain 10), RIPK4 (receptor interacting serine/threonine kinase 4) and MAD2L1 (mitotic arrest deficient 2 like 1), played significant roles in NFPA. Among these proteins with high node degree in NFPAs, PRDM10 got the highest degree of 57. Based on the PPI network of DEGs, a notable module was screened out through MCODE, including 349 nodes and 594 edges with a 3.4 average node degree, which was shown in Fig 3, and the functional annotation and enrichment of modules genes was listed respectively in Table 3. Functions of genes in module 1 were mainly enriched in spindle pole, cell division and microtubule cytoskeleton; in module 2, the enrichment showed primarily in cellular response to hypoxia, response to drug and pathways in cancer; and in module 3, genes were mainly correlated to Wnt signaling pathway and beta-catenin destruction complex disassembly.

Table 2. Top 20 hub genes which were screened with degrees more than 12.

Gene symbol	Degree	Betweenness Centrality	Gene symbol	Degree	Betweenness Centrality
PRDM10	57	0.42790519	KIF11	16	0.01211223
RIPK4	33	0.19695202	PBK	16	0.03231519
CALM1	28	0.10316316	KIF2C	15	0.01750419
BCL2	28	0.09331486	PRC1	15	0.00761907
CCNB1	22	0.07022771	CAMK2G	14	0.02860711
CDKN2A	19	0.03962583	RFC3	14	0.02189282
POMC	18	0.0389501	WNT5A	13	0.05815162
MAD2L1	17	0.00857124	GNB5	13	0.04135738
MCM2	17	0.02005968	NTS	13	0.06497129
CCNB2	16	0.01160158	CASK	13	0.03506031

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Table 3. The functional annotation and enrichment of modules genes.

Module	Term	Count	PValue	FDR	Genes
module1	GO:0000922~spindle pole(CC)	4	2.42E-05	2.13E-02	CCNB1, KIF11, MAD2L1, PRC1
	GO:0051301~cell division(BP)	5	3.53E-05	3.95E-02	CCNB1, KIF2C, KIF11, MAD2L1, CCNB2
	GO:0015630~microtubule cytoskeleton(CC)	4	4.80E-05	4.22E-02	KIF2C, CCNB2, PRC1, MCM2
module2	hsa05200:Pathways in cancer(KEGG)	8	7.41E-05	8.34E-02	ADCY1, CDKN2A, BCR, CDKN2B, RXRA, BCL2, GNB5, GNAS
	GO:0071456~cellular response to hypoxia(BP)	4	2.58E-04	3.71E-01	BCL2, PPARGC1A, SLC9A1, PCK1
	GO:0042493~response to drug(BP)	5	5.95E-04	8.55E-01	ADCY1, BCL2, GNAS, PPARGC1A, SLC9A1
module3	hsa04310:Wnt signaling pathway(KEGG)	7	4.55E-09	3.09E-06	WNT5A, DKK2, FRAT1, FRAT2, WIF1, LRP5, APC
	GO:1904886~beta-catenin destruction complex disassembly(BP)	4	2.33E-07	2.95E-04	FRAT1, FRAT2, LRP5, APC
	GO:0016055~Wnt signaling pathway(BP)	5	2.97E-06	3.76E-03	WNT5A, DKK2, WIF1, LRP5, APC

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STO-609 reduced proliferation of NFPA cells

CAM pathway activated PI3K which stimulated important signaling pathways of NFPAs as reported. Therefore, CALM1 was regarded as the vital therapeutic target for NFPAs. To estimate effects of STO-609 in NFPA cells, CCK-8 assay and colony-forming assay were performed. As Fig 4A showed, the cellular viability of AtT-20 cells was slowly declined following the augment of drug concentrations, and HP75 and GT1-1 groups decreased more significantly compared to AtT-20 group. The results of colony-forming assay pointed that compared with the control group, the clonogenicities in petri dish treated by STO-609 were less and smaller (Fig 4B). The numbers of clone formation in drug groups was lower than in control group significantly (Fig 4D and 4E).

STO-609 inhibits migration of NFPA cells

To evaluate migration of GT1-1 cell lines, the widths of cell-free area were measured. After 24h, the results exposed that the widths of scratch in control group were thinner than that in STO-609 group (P < 0.05). Meanwhile, the wounds in the drug group were quite wider than in control group after 48h (P < 0.05) (Fig 4C).

STO-609 induces apoptosis of HP75 cells

Flow cytometer was used to analyze the cells treated with different doses of STO-609 to expose the mechanism of STO-609 in NFPA. In the control group, the proportion of normal, necrotic, late apoptosis and early apoptosis was 88.51%, 3.45%, 4.53% and 3.51%, respectively; 66.35%, 1.66%, 16.46%, and 15.53% in low dose group; 34.81%, 2.58%, 47.84%, and 14.77% in high dose group (Fig 4G and 4H).

Discussion

Although NFPAs are benign, it is difficult to diagnose and detect them in their early stages. As the disease develops, single surgical resection is difficult to remove the tumor completely. Clinical diagnosis, treatment and prognosis would be significantly improved if the appropriate targets are identified. Few related genes and molecular pathways have been studied by previous researchers, there is an urgent need for comprehensive analysis regarding to NFPAs.

Our study used bioinformatics analysis techniques to screen hub genes and pathways, which provides promising targets for the diagnosis and treatment of NFPA. A previous study pointed that: MYO5A, a deferential expressed gene between invasive and non-invasive NFPA, might be a crucial biomarker for tumor invasiveness [19]. This study used similar bioinformatics methods but combined with more complicated and refined algorithms, to identify possible markers between NFPA and normal pituitary tissues.

We downloaded three datasets: GSE2175, GSE26966 and GSE51618, screened normal tissues and NFPA tissues samples from them, and identified the DEGs between normal tissues and NFPA tissues. The result showed that there were 351 DEGs among which 169 were up regulated and 182 were down regulated. The functions and corresponding signaling pathways of DEGs were investigated by GO, KEGG and GSEA analysis. The results implied that NFPA cells shared similar characteristics of universal cancer cells (cell regulation of growth changed, cell division and ion transport strengthen, the extracellular matrix changed and cell interaction). In addition, DEGs were closely related to dopaminergic synapses, neuronal cell bodies, regulations of cardiac muscle contraction by calcium ion signaling and adrenergic signaling in cardiomyocytes. Besides, GSEA analysis results revealed that NFPAs were closely related to Parkinson’s disease (PD) and vibrio cholerae infection. Dopamine agonists were vital medium in medical management of pituitary adenomas and they were also used in the treatment of PD [20]. Previous study also suggested that dopamine inhibited PRL releasing by decreasing intracellular cAMP levels and calcium uptake and reduced the effects of cholera toxin, which stimulated the formation of cAMP [21]. Meanwhile, some pituitary macroadenoma patients complicated with unknown reason movement disorders [22]. Based on the facts above and our results, we hypothesized that NFPA and PD might be homologous. It was decreased dopamine levels in the NFPA patients, which accounted for dopaminergic neuron synapse pathway compensatorily activated in most NFPA patients, that led to PD. In other words, NFPA patients took a rather higher risk suffering PD. However, the detailed mechanisms needed to be elucidated by further studies.

PPI network exposed that four hub proteins encoded by genes (CALM1, PRDM10, RIPK4 and MAD2L1) had never been reported related to NFPA. CALM1, which encoded calmodulin (CaM), played an important role in cell functions such as phosphorylation of tau protein, constitution of various biological membrane structures, signal transduction and synthesis and release of neurotransmitters. It could also affect steroidogenesis mediated by cAMP synthesis [23, 24]. In NFPA cells, CALM1 was differential expressed significantly. And many abnormal regulated pathways (involved Dopaminergic synapse, cGMP-PKG signaling pathway, Alcoholism, cAMP signaling pathway) were driven by this gene. Evidences also suggested that CALM1 was closely related to neurodegenerative disease such as PD. There were also four important signaling pathways that had been reported about NFPA: MAPK, p53, TGFβ and Jak-STAT [25–28]. These four pathways were closely related to the stimulation of PI3K (phosphoinositide-3-kinase) and the outcome of its product PIP3 (phosphatidylinositol 3,4,5-trisphosphate). Initially, it was CaM that triggered activation of PI3K [29–32]. Accordingly, CALM1 could be considered as the most important therapeutic target for NFPAs. Meanwhile, the Ca²⁺/CaM signaling pathway was aberrantly regulated in NFPAs, which was involved in lots of physiological functions of cells: transcriptional activation, protein synthesis, glycogen metabolism, cell division and so forth. It prompted us to hypothesize that STO-609, a selective inhibitor of CaM-KK, which could block the Ca²⁺/CaM signaling pathway and the function of CALM1, might have anti-NFPAs therapeutic effects and it had also been verified by the following assays in these studies.

PRDM10, PR/SET domain 10, was a part of the PRDM (PRDI-BF1 and RIZ homology domain containing) family participating in transcriptional regulation through chromatin remodeling. The protein encoded by PRDM10 was a transcription factor participating in regulation of transcription and protein binding, which had been reported play a significant role during development of the central nervous system, and in the pathogenesis of neuronal storage disease [33–35]. It is suggested that PRDM 10 might be involved in normal tissue differentiation during mouse embryonic development [35]. There were few reports in the past about PRDM10, and it had not been specially described in any other neoplasm but for undifferentiated pleomorphic sarcoma [33]. In our study, it showed that this gene, which was the core of the interaction with multiple genes, had a pivotal position in NFPA tissues. The expression of this gene was abnormally regulated, in view of PRDM10 was a driver gene of NFPA, we hypothesized its abnormal activation would promote the initiation of NFPA, it might play roles during the course of NFPA development. PRDM10 might be a biomarker in the early diagnosis of NFPA.

RIPK4, receptor interacting serine/threonine kinase 4, encoded a protein which was a serine/threonine protein kinase that interacted with protein kinase C-delta and required for keratinocyte differentiation. RIPK4, the new member in RIP kinase family, might manage NF-kappa B-dependent pro-survival or pro-inflammatory signals negatively. It was reported that this gene was neurodegenerative disease related in a mouse neural stem cells experiment [36], and could also be a novel putative tumor suppressor in human hepatocarcinogenesis [37]. Our study showed that its molecular functions which mainly involved in protein binding, ATP binding, protein serine/threonine kinase activity and protein kinase activity, played important roles in the proceeding of NFPA. Overexpression of RIPK4 led to activation of JNK and NF-kappa B, which resulted in abnormal cell cycle and proliferation [38]. It was reported that up-regulation of RIPK4 might help the development of certain tumors, such as skin, ovarian, cervical squamous cell carcinoma, and cervical cancer [39–41]. Our results suggested that RIPK4 was a driver gene of NFPA, and it might be a novel monitor marker, target or factor for diagnosis, therapy and even prognostic analysis.

MAD2L1, mitotic arrest deficient 2 like 1, was part of the mitotic spindle assembly checkpoint that prevented the onset of anaphase until all chromosomes were properly aligned at the metaphase plate. MAD2L1 jointly contributed to the regulation of mitotic checkpoint and maintained chromosomal integrity [42, 43], interacting with a variety of other molecules such as PTTG1, WT1, AURORA, AURORB and H3K4 [42, 44–46]. Meanwhile, co-depletion of MAD2L1 and BUBR1 induced cell cycle arrest and death in addition to aneuploidy [47]. Aneuploidy occurred during tumorigenesis initiation and contributed to tumor formation. Spatial organization of the mitotic regulatory event, and precise timing are vital key in activation of mitotic checkpoint, which ensured accurate chromosome segregation and catalytic activation of the spindle assembly checkpoint depended on regulated protein-protein interactions. MAD2L1 involved in these processes, the abnormal expression of MAD2L1 might result in checkpoint control loss, chromosome instability, or early onset of malignancy [43, 48, 49]. In our study, this gene was significantly up-regulated, which revealed that MAD2L1 was a driver gene of NFPA, as well as a potential a bio-markers for diagnosis and therapy of NFPA.

The effects of STO-609 were evaluated in this study with a series of assays in vitro. The results pointed that the cellular viability in HP75 and GT1-1 cell lines was revealed dose-depended decreased when treated with STO-609. In comparison to control group, clonogenicities of STO-609 group were less and smaller significantly, which showed a consistency with CCK-8 assay. That also pointed out that STO-609 stunted the proliferation of NFPA cells. The scratch assay suggested that the wounds in control group decreased more sharply than that in STO-609 group significantly after 48h. That implied that migration of hypophysoma cells was strongly restrained by STO-609. Moreover, apoptosis assays were calculated by flow cytometer to study the deeper mechanism of STO-609 anti-hypophysoma effect. The result that percentages of apoptosis cells increased as the augment of STO-609 dose revealed that STO-609 could induce the apoptosis of NFPA cells.

Conclusion

Our study selected out the DEGs and key pathways in the NFPA tissue. The DEGs in this study contribute to synthetic insight of NFPA pathogenesis in molecular level. Four hub proteins encoded by genes: CALM1, PRDM10, RIPK4 and MAD2L1 were aberrantly expressed and could be potentially applied as diagnostic bio-markers, therapeutic targets and prognostic bio-markers. The enrichment functions and pathways were related to Ca²⁺/CaM signaling pathway and parkinson’s disease. STO-609, a potent inhibitor regarding to the Ca²⁺/CaM signaling pathway and CALM1, suppressed proliferation and migration of NFPA cells via inducing NFPA cells apoptosis. STO-609 was a promising drug in NFPA treatment.

Supporting information

S1 Table. Venn plot analysis results of DEGs among three datasets.

(XLSX)

Click here for additional data file.^{(193.4KB, xlsx)}

Abbreviations

BP: Biological processes
CALM1: Calmodulin 1
CaM-KK: Calmodulin-dependent protein kinase kinase
CC: Cell component
CCK-8: Cell Counting Kit-8
DAVID: Database for Annotation, Visualization and Intergrated Discovery
DEG: Differential expressed genes
DMEM: Dulbecco’s modified Eagle’s medium
FBS: Fetal bovine serum
GEO: Gene Expression Omnibus
GO: Gene ontology
GSEA: Gene Set Enrichment Analysis
KEGG: Kyoto encyclopedia of Genes and Genomes
MAD2L1: Mitotic arrest deficient 2 like 1
MF: Molecular function
NFPAs: Non-functional pituitary adenomas
NS: Normal saline
PA: Pituitary adenomas
PCA: Principal component analysis
PD: Parkinson’s disease
PRDM10: PR/SET domain 10
PRL: Prolactin
PPI: Protein-protein interation
RIPK4: Receptor interacting serine/threonine kinase 4
STRING: Search Tool for Retrieval of Interacting Genes
WHO: World Health Organization

Data Availability

All relevant data are within the manuscript and its Supporting Information files. The gene datasets applied in this study are also publicly available from the Gene Expression Omnibus repository (http://www.ncbi.nlm.nih.gov/geo).

Funding Statement

This study was supported by the Science and Technology Planning Project of Jiangmen, China (2018630100110019805).

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PLoS One. 2020 Oct 29;15(10):e0240230. doi: 10.1371/journal.pone.0240230.r001

Author response to previous submission

22 Dec 2019

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PLoS One. doi: 10.1371/journal.pone.0240230.r002

Decision Letter 0

Tomasz Boczek

20 Feb 2020

PONE-D-19-34884

Identification of Driver Genes and Key Pathways of Non-functional Pituitary Adenomas Predicts the Therapeutic Effect of STO-609

PLOS ONE

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Reviewer #1: In this manuscript, the authors aim to identify novel molecular pathways and genes regulating non-functional pituitary adenomas (NFPA) which are usually benign tumors, to identify therapeutic targets. They utilize three GEO data sets from gene expression profiling of non-invasive and invasive NFPAs to perform data mining analyses to identify differentially expressed genes, hierarchical clustering, gene ontology, hub gene expression, biological function and pathway analyses. From these analyses, they identify CALM1, PRDM10, and MAD2L1 were recognized as hub genes upregulated in invasive NFPAs while RIPK4 was identified as a downregulated hub gene. Since CALM1, the gene encoding for the intracellular Ca2+ receptor calmodulin (CaM), is one of the upregulated hub genes, the authors utilize STO-609, a selective inhibitor of CaMKKs, the upstream regulator of the CaMK signaling cascade that is regulated by Ca2+/CaM binding, to modulate CaM function in one human NFPA cell line and one mouse pituitary adenoma cell line. They report that treatment of these cells with STO-609 results in a loss of cell viability and migration potential. This is an interesting story, where the data mining and the identification of the four hub genes and a potential similarity to Parkinson disease are interesting. However the manuscript suffers from some very serious flaws:

1. The whole paper is poorly written with bad sentence construction, grammatical and spelling mistakes, wrong word usage and use of colloquial phrases such as “It’s”, “what’s more”, etc. The impact of the potentially exciting discovery of the data mining results they describe for figures 1-3 is lost due to the poor English writing. The authors should extensively edit the paper for English language.

2. There are many abbreviations in this paper, which makes it hard to follow the content at times. Authors should include a table of all the abbreviations used in the paper.

3. The rationale for the STO-609 studies is not clear at all. This should be made in the last paragraph of the introduction as well as in the results section which describes these studies. Moreover, STO-609 does not affect the function of Calmodulin. A statement that STO-609 blocks CALM1 function appears repeatedly in the text in the introduction and discussion without any references to back this claim. This reviewer is not aware of any studies showing this in the literature. If the authors have evidence, they should cite the appropriate papers to back up this claim.

4. Nevertheless, the authors are justified in testing STO-609 against NFPAs. However, this needs to be well-justified.

5. None of the figures are legible. All figures appear blurry, pixelated, and I could not understand what any of them show. Given this, it was hard to judge this paper.

6. Specifically, in figure 4A and B, none of the X-axis values which indicate STO-609 concentrations used for the dose-response curve on cell viability, are legible. So I am not able to judge if the treatment worked or not.

7. The authors do not indicate how STO-609 was solubilized, and prepared for the in vitro assays. They talk about a “solvent DMSO control” in the Materials and Methods section but never show this in Figure 4. Thus, it is hard to understand whether the effects they see of STO-609 on these cells is due to solvent toxicity or STO-609.

8. When performing experiments to understand the effects of a drug on cancer cells, it is important to test if that drug does the same to normal cells. The authors should test STO-609 on normal pituitary cells. There is such a cell line available from the ATCC – AtT-20 mouse normal pituitary cells.

9. Discussion makes several statements and claims without any references. Also, the potential link between Parkinson’s disease and NFPA would be interesting. But since none of the figures are legible, it is not possible to reach this conclusion from the data provided. Moreover, the discussion of this connection should be written in a more focused manner.

10. Table 2: What do the authors mean by the column titled “Betweenness”? This is an incorrect term anyways.

Reviewer #2: Despite that, the subject is very interesting but the presented studies are weakly performed and described. Therefore it is difficult to agree with the authors' conclusions in the present form of the manuscript.

1. Why authors choose only one Ca2+/CaM kinase inhibitor? Its cause that results are very unbelievable.

2. The authors omitted a description of cell treatment, probably, therefore, the concentrations of agent added to the cell culture is not described in the materials and methods.

3. The authors did not describe the surface of the dishes used in the colony-forming assay. Additionally, the results of that experiment are presented unreadable. Therefore it is impossible to assess how many colonies grown up? The authors should present the absolute colony numbers per plate (with plate surface) or per cm2. Did the authors check the percentage of grown colonies in control? If it is less than 50% then the cells are not suitable for this assay. Additionally, the figures (4B) presented cell treated with 0.25 mikrom/L looks similar to 1 mikrom/L. Where did the authors saw the differences presented in the graphs?

4. Similar 4C - the pictures do not presented the results showed in the graphs.

In those reasons demonstrated studies are not convincing and required future analysis that could confirm the authors' supposition.

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2020 Oct 29;15(10):e0240230. doi: 10.1371/journal.pone.0240230.r003

Author response to Decision Letter 0

5 Aug 2020

Reviewers' comments:

Reviewer 1:

In this manuscript, the authors aim to identify novel molecular pathways and genes regulating non-functional pituitary adenomas (NFPA) which are usually benign tumors, to identify therapeutic targets. They utilize three GEO data sets from gene expression profiling of non-invasive and invasive NFPAs to perform data mining analyses to identify differentially expressed genes, hierarchical clustering, gene ontology, hub gene expression, biological function and pathway analyses. From these analyses, they identify CALM1, PRDM10, and MAD2L1 were recognized as hub genes upregulated in invasive NFPAs while RIPK4 was identified as a downregulated hub gene. Since CALM1, the gene encoding for the intracellular Ca2+ receptor calmodulin (CaM), is one of the upregulated hub genes, the authors utilize STO-609, a selective inhibitor of CaMKKs, the upstream regulator of the CaMK signaling cascade that is regulated by Ca2+/CaM binding, to modulate CaM function in one human NFPA cell line and one mouse pituitary adenoma cell line. They report that treatment of these cells with STO-609 results in a loss of cell viability and migration potential. This is an interesting story, where the data mining and the identification of the four hub genes and a potential similarity to Parkinson disease are interesting. However the manuscript suffers from some very serious flaws:

The whole paper is poorly written with bad sentence construction, grammatical and spelling mistakes, wrong word usage and use of colloquial phrases such as “It’s”, “what’s more”, etc. The impact of the potentially exciting discovery of the data mining results they describe for figures 1-3 is lost due to the poor English writing. The authors should extensively edit the paper for English language [a].

There are many abbreviations in this paper, which makes it hard to follow the content at times. Authors should include a table of all the abbreviations used in the paper [b].

The rationale for the STO-609 studies is not clear at all. This should be made in the last paragraph of the introduction as well as in the results section which describes these studies. Moreover, STO-609 does not affect the function of Calmodulin. A statement that STO-609 blocks CALM1 function appears repeatedly in the text in the introduction and discussion without any references to back this claim. This reviewer is not aware of any studies showing this in the literature. If the authors have evidence, they should cite the appropriate papers to back up this claim [c].

Nevertheless, the authors are justified in testing STO-609 against NFPAs. However, this needs to be well-justified [d].

None of the figures are legible. All figures appear blurry, pixelated, and I could not understand what any of them show. Given this, it was hard to judge this paper [e].

Specifically, in figure 4A and B, none of the X-axis values which indicate STO-609 concentrations used for the dose-response curve on cell viability, are legible. So I am not able to judge if the treatment worked or not [f].

The authors do not indicate how STO-609 was solubilized, and prepared for the in vitro assays. They talk about a “solvent DMSO control” in the Materials and Methods section but never show this in Figure 4. Thus, it is hard to understand whether the effects they see of STO-609 on these cells is due to solvent toxicity or STO-609 [g].

When performing experiments to understand the effects of a drug on cancer cells, it is important to test if that drug does the same to normal cells. The authors should test STO-609 on normal pituitary cells. There is such a cell line available from the ATCC – AtT-20 mouse normal pituitary cells [h].

Discussion makes several statements and claims without any references. Also, the potential link between Parkinson’s disease and NFPA would be interesting. But since none of the figures are legible, it is not possible to reach this conclusion from the data provided. Moreover, the discussion of this connection should be written in a more focused manner [i].

Table 2: What do the authors mean by the column titled “Betweenness”? This is an incorrect term anyways [j].

Response: Thanks for your comments. We are deeply impressed with your encyclopedic scholarship and conscientious attitude, and we are honored to get your comments.

a, Thanks for your professional comments. This manuscript was polished by a native English speaker, and inopportune expressions was corrected.

b, We had provided the Abbreviations document. Thanks for your comments.

c, Thanks for your professional comments. As we described in this manuscript, STO-609 was an inhibitor of Ca2+/calmodulin-dependent protein kinase kinase (CaM-KK2), which is an important downstream role of Calmodulin. So, STO-609 affect the function of Calmodulin indirectly. The statement that STO-609 blocks CALM1 function in this manuscript was expressed more accurate, and the rationale for the STO-609 studies also was made more clear in the last paragraph of the introduction as well as in the results section which describes these studies. Thanks for your comments again.

d, In order to verify the anti-NFPAs effects of STO-609, we performed a series of assays such as CCK-8 assay, Colony-forming assay, in vitro scratch assay and apoptosis assays. CCK-8 and colony-forming assay were conducted to estimate whether STO-609 inhibited the proliferation of NFPA cells, while in vitro scratch assay could demonstrate whether STO-609 reduced the migration of NFPA cells. In addition, apoptosis assays revealed how STO-609 induced the apoptosis of NFPA cells. These experimental methods were reliable and widely used in studying the effects of drugs on cells. For example, Zhang W, Lei Z etc performed CCK-8, colony-forming assay and cell scratch assay to research the effect of water extract of sporoderm-broken spores of ganoderma lucidum on osteosarcoma cells (Zhang W, Lei Z, Meng J, Li G, Zhang Y, He J, Yan W. Water Extract of Sporoderm-Broken Spores of Ganoderma lucidum Induces Osteosarcoma Apoptosis and Restricts Autophagic Flux. OncoTargets and Therapy 2019;12:11651-11665. doi: 10.2147/OTT.S226850.). The details of assays in vitro were provided and Figures was polished according to your following comments. Thanks for your professional comments.

e, Sorry for blurry figures. All the figures was replaced with clear PDF versions.

f, Sorry for that. We optimized the format of Figure 4, and made it easier to read. Thanks for your comments.

g, Thanks for your comments. Firstly, we dissolved STO-609 in pure DMSO to obtain the mother liquor, then we respectively added appropriate culture medium to the mother liquor to configure cell culture medium with STO-609 concentration of 0.25μmol/L and 1μmol/L. The concentration of DMSO was less than 0.5%. In this concentration, the influence of DMSO on cells was negligible, therefore we decided not to set up the DMSO control group. This statement was added to the manuscript.

h, Thanks for your comments. The ATCC – AtT-20 mouse normal pituitary cells were tested in this manuscript, and the results were added in this manuscript.

i, Thanks for your professional comments. The reference you mentioned was added in discussion. In this study, GSEA analysis was performed for further insight of DEGs, and the results showed that the pathway of Parkinson’s disease (PD) was significantly altered. That implicit the potential link between PD and NFPA. Thus, we hypothesized that NFPA and PD might be homologous and NFPA patients may take a rather higher risk suffering PD. This hypothesis needed further studies to elucidated in future.

j, Thank you for pointing out our mistake. We changed “Betweenness” to “Betweenness Centrality” in Table 2.

Reviewer 2:

Despite that, the subject is very interesting but the presented studies are weakly performed and described. Therefore it is difficult to agree with the authors' conclusions in the present form of the manuscript.

Why authors choose only one Ca2+/CaM kinase inhibitor? Its cause that results are very unbelievable [a].

The authors omitted a description of cell treatment, probably, therefore, the concentrations of agent added to the cell culture is not described in the materials and methods [b].

The authors did not describe the surface of the dishes used in the colony-forming assay. [c] Additionally, the results of that experiment are presented unreadable. Therefore it is impossible to assess how many colonies grown up? The authors should present the absolute colony numbers per plate (with plate surface) or per cm2. Did the authors check the percentage of grown colonies in control? If it is less than 50% then the cells are not suitable for this assay. [d] Additionally, the figures (4B) presented cell treated with 0.25 mikrom/L looks similar to 1 mikrom/L. Where did the authors saw the differences presented in the graphs? [e] Similar 4C - the pictures do not presented the results showed in the graphs [f].

In those reasons demonstrated studies are not convincing and required future analysis that could confirm the authors' supposition.

Response: It’s our honor to obtain your comments, and thank you for your excellent comments that benefit us a lot.

a, Thanks for your comments. This study aims to provide potential biomarkers and drug targets for diagnosis and treatment of NFPAs and verify the anti-NFPAs effects of STO-609 preliminary. Actually, we compared all Ca2+/CaM kinase inhibitors, but chose STO-609 finally because STO-609 had been proved playing roles in several diseases recently such as prostate cancer, gastric carcinoma, et al. Thanks for your comments again.

b, Thanks for your comments. The description of STO-609 concentrations was added in this manuscript.

c, Thanks for your professional comments. In colony-forming assay, we used a six-well cell culture plate rather than petri dishes, and the surface area of each well of the culture plate was 9.6 cm2. This description was added in this manuscript.

d, Thanks for your professional comments. We reanalyzed the results of colony-forming assay, and added the absolute colony numbers (with plate surface) to the manuscript and Figure 4. In addition, the percentage of grown colonies in control group was 70%.

e, The figure and graphs were replaced with clear PDF versions. Thanks for your comments which benefit us a lot.

f, Thanks for your comments. The figure was polished.

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PLoS One. doi: 10.1371/journal.pone.0240230.r004

Decision Letter 1

Tomasz Boczek

15 Sep 2020

PONE-D-19-34884R1

Identification of Driver Genes and Key Pathways of Non-functional Pituitary Adenomas Predicts the Therapeutic Effect of STO-609

PLOS ONE

Dear Dr. Chen,

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We look forward to receiving your revised manuscript.

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Tomasz Boczek, Ph.D.

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

Reviewer #2: No

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: No

**********

6. Review Comments to the Author

Reviewer #1: The manuscript has improved a lot with the revision. A few minor concerns remain which need to be addressed.

1. Pages 5-6, lines 128-129: - This sentence needs to be revised. The reference # 49 does not show that STO-609 blocks CALM1 function. You could say, for instance, that you wanted to use STO-609 to block CaMKK signaling, as it operates downstream of CALMA. Please understand that calmodulin activates many proteins, and CaMKK is only one of them.

2. Page 7 line 177 - Delete the part of the sentence that says STO-609 blocks CALM1 gene function. It does not. Also you need to say here how you made the STO-609 solution.

3. Page 8, line 197-198: - Change "mother liquor" to stock solution. The description of STO-609 stock preparation should be moved earlier to page 7 line 177 - first time you mention about using STO-609 on cells.

Page 8, lines 199-202: I disagree. Even 0.05% DMSO could have an effect on cells. This is an important control. Also, Remove the sentence: "different doses of STO-609 were used to treat those cells".

Page 11, lines 268 -276: It is still not clear why they chose to block CaMKK function using STO-609 while PRDM10 scored the highest.. Please make this clear. You do have a paragraph in the Discussion - page 14 lines 348-350 that provide a good rationale. This can be utilized in the Introduction and the Results sections to provide the rationale for blocking CaMKK.

Pages 11-12, lines 281-282: - Revise these sentences: Meanwhile, only tiny decline was observed in STO-609 group. What’s more, the wounds in the drug group were quite wider than in control group after 48h.

Reviewer #2: Unfortunately, despite the author's corrections, the manuscript still has low quality. The authors' explanation about the reason for choosing the only one inhibitor in the present studies is very unclear. The conclusions from such limited analysis are dubious. The quality of figures and language make reading the text difficult. The result of wound healing is still inconsistent (graphs and images) - Figure 4.

To sum up, I regret to inform you that I do not recommend the manuscript in the present form for publication in PLOS ONE.

**********

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Reviewer #1: No

Reviewer #2: No

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 Oct 29;15(10):e0240230. doi: 10.1371/journal.pone.0240230.r005

Author response to Decision Letter 1

21 Sep 2020

Reviewer #1: (No Response)

Reviewer #2: (No Response)

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: (No Response)

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

Reviewer #2: No

Response: The statistical analysis was updated. Independent-samples t test was conducted to analyze quantitative data of bioinformation analysis, while Analysis of Variance (ANOVA) was performed to analyse multiple comparison data of cell experiments. Besides, we conducted Dunnett-t test as post hoc test after ANOVA. We confirmed that the level of significance was P < 0.05. Thanks a lot for the valuable comments.

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copy edit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

Response: Thanks for the professional comments. We had already re-polished the language in this manuscript to meet the requirements of PLOS ONE.

6. Review Comments to the Author

Reviewer #1: The manuscript has improved a lot with the revision. A few minor concerns remain which need to be addressed.

1.Pages 5-6, lines 128-129: - This sentence needs to be revised. The reference # 49 does not show that STO-609 blocks CALM1 function. You could say, for instance, that you wanted to use STO-609 to block CaMKK signaling, as it operates downstream of CALMA. Please understand that calmodulin activates many proteins, and CaMKK is only one of them.

Response: Thanks a lot for your detailed comments. This sentence was revised according to this suggestion.

2.Page 7 line 177 - Delete the part of the sentence that says STO-609 blocks CALM1 gene function. It does not. Also you need to say here how you made the STO-609 solution.

Response: This part was revised according to your comments. Thank you for the valuable suggestions.

Page 8, lines 199-202: I disagree. Even 0.05% DMSO could have an effect on cells. This is an important control. Also, Remove the sentence: "different doses of STO-609 were used to treat those cells".

Response: These sections were all revised with your comments. Besides, the point of view that the influence of 0.1% DMSO on cells is negligible is supported by researches as following:

[1]Qi W, Ding D, Salvi R J. Cytotoxic effects of dimethyl sulphoxide (DMSO) on cochlear organotypic cultures[J]. Hearing Research, 2008, 236(1-2):52-60

[2]Nirogi R, Kandikere V, Bhyrapuneni G, et al. Effect of dimethyl sulfoxide on in vitro cytochrome P4501A2 mediated phenacetin O-deethylation in human liver microsomes[J]. Drug Metabolism & Disposition the Biological Fate of Chemicals, 2011, 39(11):2162

These suggestions benefited us a lot in improving this manuscript. It is our great honor to obtain your valuable and professional comments.

Reviewer #2: Unfortunately, despite the author's corrections, the manuscript still has low quality.[a] The authors' explanation about the reason for choosing the only one inhibitor in the present studies is very unclear. The conclusions from such limited analysis are dubious.[b] The quality of figures and language make reading the text difficult.[c] The result of wound healing is still inconsistent (graphs and images) - Figure 4.[d]

To sum up, I regret to inform you that I do not recommend the manuscript in the present form for publication in PLOS ONE.[a]

Response: a, In this study, bioinformatical methods were conducted to identify DEGs, comprehensively investigate hub genes, annotate enrichment functions and key pathways of NFPAs, and performed a series of cell assays to verify the therapeutic effect of STO-609 on NFPAs. The bioinformatical methods and cell assays in this study were scientific and reliable, which were widely used in researches as following:

[1]Zhong S, Wu B, Li J et al. T5224, RSPO2 and AZD5363 are novel drugs against functional pituitary adenoma [J]. Aging, 2019;11(20):9043-9059.

[2]Zhong S, Wu B, Han Y et al. Identification of Driver Genes and Key Pathways of Pediatric Brain Tumors and Comparison of Molecular Pathogenesis Based on Pathologic Types [J]. World Neurosurgery, 2017;107:990-1000.

[3]Shen S, Kong J, Qiu Y et al. Identification of core genes and outcomes in hepatocellular carcinoma by bioinformatics analysis [J]. Journal of Cellular Biochemistry, 2019;120(6):10069-10081.

b, Thanks for your comments. This study aims to provide potential biomarkers and drug targets for diagnosis and treatment of NFPAs and verify the anti-NFPAs effects of STO-609 preliminary. After comparing all Ca2+/CaM kinase inhibitors, we found STO-609 was a selective and cell-permeable inhibitor of the CaM-KK, and was proved playing roles in prostate cancer, gastric carcinoma, et al. We conjectured STO-609 was also a potential drug for NFPAs, therefore we regarded STO-609 as the major object in this research. Other Ca2+/CaM kinase inhibitors were outside the scope of this study. We believe other Ca2+/CaM kinase inhibitors could be interesting directions in further researches.

c, This language in this manuscript was polished to meet the requirements of PLOS ONE. Besides, we improved the resolution of figures to make them more clear for publication. Thanks for your comments.

d, We increased the images resolution of the microscopy images in Fig.4 and believed that this version was clear enough to compare the widths of scratch. Thank you for the useful suggestions.

Dear reviewers,

Thanks sincerely for your hard work dealing with this manuscript. These professional comments and suggestions really helped us a lot to improve the quality of this manuscript. We believe these opinions will benefit us on our researches in the future.

If there is any problem, please don’t hesitate to contact us. We will reply you as soon as possible. Best wishes to you and all whom you love.

Best regards,

Yong Chen

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PLoS One. doi: 10.1371/journal.pone.0240230.r006

Decision Letter 2

Tomasz Boczek

23 Sep 2020

Identification of Driver Genes and Key Pathways of Non-functional Pituitary Adenomas Predicts the Therapeutic Effect of STO-609

PONE-D-19-34884R2

Dear Dr. Chen,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Tomasz Boczek, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0240230.r007

Acceptance letter

Tomasz Boczek

8 Oct 2020

PONE-D-19-34884R2

Identification of Driver Genes and Key Pathways of Non-functional Pituitary Adenomas Predicts the Therapeutic Effect of STO-609

Dear Dr. Chen:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Tomasz Boczek

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Venn plot analysis results of DEGs among three datasets.

(XLSX)

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Data Availability Statement

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PERMALINK

Identification of driver genes and key pathways of non-functional pituitary adenomas predicts the therapeutic effect of STO-609

Bo Wu

Shanshan Jiang

Xinhui Wang

Sheng Zhong

Yiming Bi

Dazhuang Yi

Ge Liu

Fangfei Hu

Gaojing Dou

Yong Chen

Yi Wu

Jiajun Dong

Roles

Abstract

Objective

Methods

Results

Conclusion

Introduction

Fig 1. The overall framework of this study.

Materials and methods

Microarray data

Identification of DEGs

Gene ontology and pathway enrichment analysis

Integration of PPI network construction and modules selection

Cell lines and reagents

CCK-8 assay

Colony-forming assay

In vitro scratch assay

Apoptosis assays

Statistical analysis

Results

Identification of DEGs

Gene ontology and pathway enrichment analysis of DEGs

Table 1. Functional and pathway enrichment analysis of up-regulated and down-regulated genes in NFPAs.

Integration of PPI network construction and modules selection

Table 2. Top 20 hub genes which were screened with degrees more than 12.

Fig 3. Top 3 modules from the protein-protein interaction network.

Table 3. The functional annotation and enrichment of modules genes.

STO-609 reduced proliferation of NFPA cells

STO-609 inhibits migration of NFPA cells

STO-609 induces apoptosis of HP75 cells

Discussion

Conclusion

Supporting information

Abbreviations

Data Availability

Funding Statement

References

Author response to previous submission

Decision Letter 0

Tomasz Boczek

Roles

Author response to Decision Letter 0

Decision Letter 1

Tomasz Boczek

Roles

Author response to Decision Letter 1

Decision Letter 2

Tomasz Boczek

Roles

Acceptance letter

Tomasz Boczek

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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