Origin recognition complex subunit 1 regulates cell growth and metastasis in glioma by altering activation of ERK and JNK signaling pathway

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Origin recognition complex subunit 1 regulates cell growth and metastasis in glioma by altering activation of ERK and JNK signaling pathway Wenmin Xiong, Chen Xie, Yang Qiu, Ziwei Tu, Qiaoying Gong∗ Department of Radiotherapy of Head and Neck, Tumor Hospital of Jiangxi Province, No. 519, Beijing East Road, Qingshanhu District, Nanchang City, 330000, Jiangxi Province, PR China

A R T I C LE I N FO

A B S T R A C T

Keywords: ORC1 Glioma Proliferation Apoptosis Invasion Migration

Origin recognition complex subunit 1(ORC1) is reported to be closely associated with the cell cycle. However, studies on the role of ORC1 in glioma remain undefined. The aim of the present study was to determine whether ORC1 affects cell migration, invasion, apoptosis, and proliferation and to explore the possible underlying mechanism. GEO database analysis indicated that ORC1 was significantly upregulated in glioma, while Gene set enrichment analysis (GSEA) analysis indicated that ORC1 primarily regulated the cell cycle and affects apoptotic signaling pathways. Analysis of protein-protein interaction (PPI) and gene ontology (GO) to further study the relevant mechanisms revealed that the function of the interaction between proteins and ORC1 was primarily concentrated in the regulation of cell cycle, and apoptosis played a critical role in the whole PPI network. Western blot assay and RT-PCR assay indicated that ORC1 was significantly upregulated in glioma tissues. Western blot assay and RT-PCR indicated that ORC1 was significantly upregulated in glioma cell lines. Cell migration, invasion, apoptosis, and proliferation were detected using Transwell and wound healing assays, flow cytometry, colony formation, and CCK8, respectively. Furthermore, OCR1 inhibition reduced invasion and migration, promoted cell apoptosis. In addition, OCR1 overexpression promoted cell proliferation and induced G2 phase arrest. Moreover, OCR1 downregulation suppressed activation of the ERK/JNK signaling pathway. The effects of ORC1 on biological processes were reversed by ERK and JNK inhibitors. These results indicate that ORC1 could be a novel prognostic marker of glioma via the activation of the ERK/JNK signaling pathway.

1. Introduction Glioma is considered the tumor with the highest malignancy in the central nervous system. It exhibits increased invasion and proliferation ability and accounts for about 40% of intracranial tumors, astrocytoma, ependymoma, mixed gliomas, and oligodendroglioma [1,2]. Glioma is classified into WHO grade I-IV and is located in the brain; hence, surgery to remove a brain tumor is difficult, and tumors recur easily after surgery [3]. In recent years, surgery, radiotherapy, and chemotherapy for brain cancer have advanced significantly; however, patients with gliomas have no obvious improvement in the five-year survival rate following these interventions [4]. The major cause of treatment failure is thought to be the invasive growth of gliomas and to tumor recurrence and metastasis [5]. Therefore, gene therapy has been developed as a new strategy for patients with gliomas and can deliver foreign genetic material into specific cell types; several types of therapies are possible, antibody-directed enzyme prodrug therapy (ADEPT), antitumor gene immunotherapy, anti-angiogenic therapy, and antisense gene therapy

∗

[6,7]. The identification, in the present study, of proteins that confer distinct invasive properties to cells may be of great value in developing novel therapeutic methods and understanding glioma invasion. The initial step of DNA replication involves the origin recognition complex (ORC) in eukaryotes, consisting of Orc1/2/3/4/5/6. It was found in saccharomyces, with chromosomal replication origins [8]. It has been shown that ORC1/2/3/4/5/6 are expressed in different human tissues, e.g., lung [9], bones [10], kidney [11] and uterus [12]. Expression levels of ORC2-5 were not found to vary during the cell cycle [13]. However, ORC1 was found to be synthesized in the G1 phase and to be degraded in the S phase. These cell cycle-specific oscillations in the expression of ORC1 were closely associated with cell proliferation and cell cycle. It was also determined that ORC1 was responsible for cell cycle progression. Thus, ORC1 may be involved in cell proliferation, apoptosis, invasion, migration and other biological processes.

Corresponding author. E-mail address: [email protected] (Q. Gong).

https://doi.org/10.1016/j.mcp.2019.101496 Received 7 October 2019; Received in revised form 18 December 2019; Accepted 18 December 2019 0890-8508/ © 2019 Published by Elsevier Ltd.

Please cite this article as: Wenmin Xiong, et al., Molecular and Cellular Probes, https://doi.org/10.1016/j.mcp.2019.101496

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2. Materials and methods

were retrieved from the Tumor Hospital of Jiangxi Province (Jiangxi, China) as fresh-frozen specimens (mean age, 45.23 ± 8.71 years; 11 males and 10 females) from May 2016 to June 2018. Patient clinical characteristics are shown in Table 2. All patients provided written informed consent, and the study conducted in accordance with the Declaration of Helsinki. Both clinical data and detailed follow-up data were obtained for all patients. All the specimens collected were handled according to the protocols approved by the Ethics Committee of Tumor Hospital of Jiangxi Province. The following eligibility criteria were included in our study: (1) the histopathological classification and grading of glioma met WHO criteria; (2) surgical extraction of tumor lesions; (3) no preoperative anti-cancer treatment such as chemotherapy and radiotherapy; (4) complete postoperative follow-up data; (5) no other primary or familial malignancies. All patients underwent TNM staging according to the 7th edition of AJCC system.

2.1. Database analysis The mRNA expression data of glioblastoma cell lines were obtained from the Gene Expression Omnibus (GEO) profiles database (http:// www.ncbi.nlm.nih.gov/geo/, GSE15824). The mRNA expression levels of 2893 differentially expressed genes (DEGs) were evaluated using the ‘limma’ package in R (https://www.r-project.org/). The expression levels were color coded and visualized using the heat map method. The significantly dysfunctional genes are shown in rows and the samples in columns. Red, black, and green indicate the levels of expression: upregulated, not varied, and down-regulated. 2.2. Gene set enrichment analysis (GSEA)

2.7. Cell treatments

The biological processes/signaling pathways of gene sets were investigated using gene set enrichment analysis (GSEA v2.2, http://www. broad.mit.edu/gsea/). GSEA can generate a gene set enrichment score (ES) to estimate genes from a predefined gene set. The significance threshold was determined by permutation analysis (1000 permutations). At P-value < 0.05, a gene set was considered to be significantly enriched.

ORC1 knockdown cells were generated by transfecting commercial shRNA in a lentiviral vector (PLKO.1-EGFP) for ORC1 (Research Service Biotechnology co. LTD. Shanghai, China). Control cells were generated by transfecting with virus delivering a scramble short hairpin retrovirus. Overexpression cell lines were generated by transfecting ORC1 cDNA (R&S Biotechnology co. LTD) cloned into the pLV-IRES-eGFP plasmid (Invitrogen, Carlsbad, CA, USA) by EcoR I/BamH I restriction enzyme sites. The transfection of U87-MG and T98G cells using lentiviral expressing shRNA-ORC1 and ORC1 were prepared as previously described [15]. The black pLV-IRES-eGFP (Vector-NC) and recombinant lentivirus pLKO.1-EGFP-scramble shRNA (shRNA-NC) served as negative controls. After T89G cells were pre-treated with 10 μmol/mL ERK and JNK inhibitor (astragaloside IV; Biolaibo Technology co., LTD, Beijing, China) for 6 h, lentiviruses expressing ORC1 were then transfected into cells. The sequences of ORC1 overexpression or inhibitons in Table 3. Astragaloside IV (the inhibitors of ERK and JNK) was purchase from Biolaibo Technology co., LTD (M00922; Beijing, China). After T98G cell was pre-treated 30 μM of Astragaloside IV for 6 h, ORC1 overexpression was transfected into cells.

2.3. Gene ontology analysis GO analysis to explore DEG enrichment for functional annotation in glioma was performed using the Database for Integrated Discovery, Visualization and Annotation (DAVID) online analysis tool (https:// david.ncifcrf.gov/). The database provides a complete functional annotation tool set, which helps researchers to identify cellular component (CC), molecular function (MF) and biological process (BP) terms enriched significantly, enrichment analysis of DEGs, with P < 0.05 as the cut-off criterion. 2.4. PPI network construction and hub genes identification STRING (http://www.string-db.org/), a search tool, is used to retrieve interacting genes and identify the interactions of gene products, providing experimental and predicted interaction information based on previous studies [14]. The protein interactions were analyzed by STRING web, and the required confidence (combined score) ≥ 0.4 served as the cut-off criterion, and PPI network was visualized by Cytoscape software. Subsequently, for the calculation of node degree, node betweenness, and closeness, the Network Analyzer plug-in was used. Degree stands for the number of inter-connections to filter hub genes of PPI in a network. Node betweenness reflects the capability of nodes to manage the rate of information flow in the network. Closeness is the inverse of the sum of the distance from a node to other nodes. The higher scores reveal that the node is more central in the network. Accordingly, the central node may be the core protein and key candidate genes with important physiological regulation function in glioma.

2.8. CCK8 assay CCK8 assay was used to assay cell viability as previously described [16,17]. 2 × 103 cells were seeded into 96-well plates and incubated for 0, 24, 48 and 72 h. Then, 10 μL CCK8 reagent was added dropwise into each well and incubated in the dark for 2 h. Finally, the optical density (OD) in each well was measured using Sunrise microplate reader (Tecan Group, Ltd., Mannedorf, Switzerland) at a 450 nm wavelength. 2.9. Colony formation assay Forty-eight h after transfection with shRNA-ORC1 or ORC1, 5 × 102 cells per well were cultured for 14 days in 6-well plates [18]. The cells were subsequently rinsed twice with phosphate buffer saline (PBS), fixed with 4% paraformaldehyde and stained with 0.5% crystal violet for 15 min. The number of colonies was then counted in 10 random view fields using a microscope and their average was calculated. The experiment was performed in triplicate.

2.5. Cell culture Human normal astrocytes (HEB), and the human glioma cell lines (SWO-38, SHG-44, and T98G) were purchased from Shanghai Beinuo Biotech Co., Ltd. U87-MG (AC319) were purchased from ATCC (Manassas, VA, USA). Cells were cultured in Dulbecco's modified Eagle Medium (DMEM), containing streptomycin 100 U/mL, penicillin and 10% fetal calf serum in an incubator at 37 °C in 5% CO2 (HyClone Laboratories Inc., South Logan, UT, USA).

2.10. Wound healing assay Wound healing assays were used to assess cell migration. In brief, 6 × 104 transfected U87-MG or T98G cells were seeded into 6-well plates. At 90–100% confluency, a 20 μL pipette tip was used to scratch the monolayer [19], which was then washed with PBS. The cell cultures were incubated at 37 °C in serum-free DMEM. The wound size, observed through a light microscope (magnification, × 20), at 0 and 48 h

2.6. Patient tissue samples A total of 21 confirmed different pathological grade glioma samples 2

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Table 1 (continued)

Table 1 Go analysis. Category

Term

PValue

BP BP BP BP BP BP BP BP

GO:0000082~G1/S transition of mitotic cell cycle GO:0006270~DNA replication initiation GO:0006468~protein phosphorylation GO:0006260~DNA replication GO:0051301~cell division GO:0038095~Fc-epsilon receptor signaling pathway GO:0051726~regulation of cell cycle GO:0045893~positive regulation of transcription, DNAtemplated GO:0000086~G2/M transition of mitotic cell cycle GO:0007094~mitotic spindle assembly checkpoint GO:0000083~regulation of transcription involved in G1/ S transition of mitotic cell cycle GO:0043066~negative regulation of apoptotic process GO:0007093~mitotic cell cycle checkpoint GO:0000910~cytokinesis GO:0007067~mitotic nuclear division GO:0050852~T cell receptor signaling pathway GO:0043123~positive regulation of I-kappaB kinase/NFkappaB signaling GO:0016032~viral process GO:0031145~anaphase-promoting complex-dependent catabolic process GO:1902895~positive regulation of pri-miRNA transcription from RNA polymerase II promoter GO:0008283~cell proliferation GO:0042981~regulation of apoptotic process GO:0000070~mitotic sister chromatid segregation GO:0045930~negative regulation of mitotic cell cycle GO:0010800~positive regulation of peptidyl-threonine phosphorylation GO:0045931~positive regulation of mitotic cell cycle GO:0042177~negative regulation of protein catabolic process GO:0018105~peptidyl-serine phosphorylation GO:0008284~positive regulation of cell proliferation GO:0051092~positive regulation of NF-kappaB transcription factor activity GO:0000079~regulation of cyclin-dependent protein serine/threonine kinase activity GO:0045944~positive regulation of transcription from RNA polymerase II promoter GO:0032508~DNA duplex unwinding GO:0019049~evasion or tolerance of host defenses by virus GO:0008630~intrinsic apoptotic signaling pathway in response to DNA damage GO:0036092~phosphatidylinositol-3-phosphate biosynthetic process GO:0006915~apoptotic process GO:0030335~positive regulation of cell migration GO:0007249~I-kappaB kinase/NF-kappaB signaling GO:0006954~inflammatory response GO:0006977~DNA damage response, signal transduction by p53 class mediator resulting in cell cycle arrest GO:1901203~positive regulation of extracellular matrix assembly GO:0051098~regulation of binding GO:0006974~cellular response to DNA damage stimulus GO:0071260~cellular response to mechanical stimulus GO:0007049~cell cycle GO:1900034~regulation of cellular response to heat GO:0016202~regulation of striated muscle tissue development GO:0051437~positive regulation of ubiquitin-protein ligase activity involved in regulation of mitotic cell cycle transition GO:0045143~homologous chromosome segregation GO:0043551~regulation of phosphatidylinositol 3-kinase activity GO:0000122~negative regulation of transcription from RNA polymerase II promoter GO:0010628~positive regulation of gene expression GO:0007183~SMAD protein complex assembly

2.23E-11 4.85E-09 1.45E-08 2.18E-08 3.72E-07 1.37E-06 4.75E-06 6.66E-06

BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP BP

BP BP BP BP BP

Category

Term

PValue

BP BP

GO:0000076~DNA replication checkpoint GO:0033598~mammary gland epithelial cell proliferation GO:0030071~regulation of mitotic metaphase/anaphase transition GO:0007062~sister chromatid cohesion GO:0002223~stimulatory C-type lectin receptor signaling pathway GO:0000187~activation of MAPK activity GO:0016572~histone phosphorylation GO:0042493~response to drug GO:0033209~tumor necrosis factor-mediated signaling pathway GO:2001275~positive regulation of glucose import in response to insulin stimulus GO:0097296~activation of cysteine-type endopeptidase activity involved in apoptotic signaling pathway GO:0070306~lens fiber cell differentiation GO:0042993~positive regulation of transcription factor import into nucleus GO:0007050~cell cycle arrest GO:0045216~cell-cell junction organization GO:0031293~membrane protein intracellular domain proteolysis GO:0001556~oocyte maturation GO:0008156~negative regulation of DNA replication GO:0032332~positive regulation of chondrocyte differentiation GO:0042787~protein ubiquitination involved in ubiquitin-dependent protein catabolic process GO:0017015~regulation of transforming growth factor beta receptor signaling pathway GO:0051403~stress-activated MAPK cascade GO:0007492~endoderm development GO:0002028~regulation of sodium ion transport GO:1900182~positive regulation of protein localization to nucleus GO:0071480~cellular response to gamma radiation GO:0010165~response to X-ray GO:0051439~regulation of ubiquitin-protein ligase activity involved in mitotic cell cycle GO:0001666~response to hypoxia GO:0045737~positive regulation of cyclin-dependent protein serine/threonine kinase activity GO:0051090~regulation of sequence-specific DNA binding transcription factor activity GO:0007569~cell aging GO:0070423~nucleotide-binding oligomerization domain containing signaling pathway GO:0046686~response to cadmium ion GO:0030878~thyroid gland development GO:0005829~cytosol GO:0005654~nucleoplasm GO:0072686~mitotic spindle GO:0000784~nuclear chromosome, telomeric region GO:0005634~nucleus GO:0005813~centrosome GO:0005737~cytoplasm GO:0000922~spindle pole GO:0005622~intracellular GO:0005667~transcription factor complex GO:0000942~condensed nuclear chromosome outer kinetochore GO:0000776~kinetochore GO:0042555~MCM complex GO:0008385~IkappaB kinase complex GO:0005942~phosphatidylinositol 3-kinase complex GO:0051233~spindle midzone GO:0016020~membrane GO:0005515~protein binding GO:0016301~kinase activity GO:0019901~protein kinase binding GO:0046982~protein heterodimerization activity GO:0008134~transcription factor binding GO:0004672~protein kinase activity

0.016087 0.016087

BP BP BP BP BP BP BP

7.73E-06 8.44E-06 1.31E-05

BP 2.92E-05 3.61E-05 1.23E-04 1.32E-04 2.19E-04 3.02E-04

BP BP BP BP BP BP

3.15E-04 5.40E-04 7.39E-04

BP BP BP

7.92E-04 8.66E-04 0.001159 0.001254 0.001353

BP BP

0.001455 0.0019

BP BP BP BP

0.002036 0.002306 0.002429

BP BP BP

0.002813 0.003048

BP BP

0.003569 0.004046

BP

0.004063

BP BP

0.004409 BP BP CC CC CC CC CC CC CC CC CC CC CC

0.005336 0.006034 0.006544 0.006939 0.006974 0.008075 0.008075 0.008451 0.009061 0.009484 0.010068 0.010084

CC CC CC CC CC CC MF MF MF MF MF MF

0.010327

0.012089 0.01409 0.014178 0.015732 0.016087

0.01808 0.018398 0.019075 0.019763 0.02007 0.023242 0.023726 0.026014 0.026014 0.026014 0.029957 0.032961 0.035843 0.035843 0.035843 0.037798 0.037798 0.038254 0.039748 0.041695 0.041695 0.041695 0.041695 0.041695 0.043637 0.045576 0.047248 0.047511 0.049443 0.049443 0.049443 0.049443 0.049443 3.14E-11 8.36E-10 9.74E-07 4.03E-06 5.39E-06 1.13E-05 1.34E-05 4.89E-05 0.002606 0.005497 0.007442 0.009983 0.01667 0.018505 0.025814 0.034876 0.045682 7.14E-09 2.03E-08 6.15E-07 3.02E-06 1.95E-05 7.21E-05

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10 min after a 24-h incubation, and gently extracted with a cotton swab. Invaded cells were estimated by observing 5 random fields using a light microscope (magnification, × 20). The experiment was performed in triplicate.

Table 1 (continued) Category

Term

PValue

MF MF MF MF MF MF MF MF

GO:0004674~protein serine/threonine kinase activity GO:0005524~ATP binding GO:0042803~protein homodimerization activity GO:0016303~1-phosphatidylinositol-3-kinase activity GO:0004721~phosphoprotein phosphatase activity GO:0019899~enzyme binding GO:0003682~chromatin binding GO:0035014~phosphatidylinositol 3-kinase regulator activity GO:0046935~1-phosphatidylinositol-3-kinase regulator activity GO:0042802~identical protein binding GO:0047485~protein N-terminus binding GO:0042826~histone deacetylase binding GO:0031625~ubiquitin protein ligase binding GO:0003688~DNA replication origin binding GO:0000983~transcription factor activity, RNA polymerase II core promoter sequence-specific GO:0004707~MAP kinase activity GO:0005159~insulin-like growth factor receptor binding GO:0016538~cyclin-dependent protein serine/threonine kinase regulator activity GO:0008353~RNA polymerase II carboxy-terminal domain kinase activity GO:0046983~protein dimerization activity GO:0003678~DNA helicase activity

9.31E-05 1.07E-04 0.003055 0.003376 0.003692 0.004324 0.007592 0.008033

MF MF MF MF MF MF MF MF MF MF MF MF MF

2.12. Flow cytometry analysis of cell cycle and apoptosis Flow cytometry assay was used to investigate cell cycle progression and apoptosis. The cells were digested after a 24 h treatment and fixed with 70% ethanol for 24 h at 4 °C, followed by Annexin V/PI gauged -double staining, with 50 μg/ml propidium iodide (PI) solution and 100 μg/ml RNase A in PBS (Beyotime Institute of Biotechnology) [20]. Cells were re-suspended in 300 μL binding buffer at 1 × 106 concentration and incubated in the dark for 10 min with 5 μL Annexin Vfluorescein isothiocyanate at ambient temperature and subsequently for 5 min with 5 μL PI on ice. The FACSCalibur system was used to analyze samples with flow cytometer (both BD Biosciences, Franklin Lakes, NJ, USA). The experiment was performed in triplicate.

0.012026 0.016234 0.016268 0.017886 0.01973 0.02194 0.023911 0.027842 0.029801 0.029801

2.13. Western blot assay The RIPA buffer was used to extract total proteins, and the bicinchoninic acid assay was used to calculate protein concentrations (Thermo Fisher Scientific, Inc.). Proteins were separated by SDS-PAGE (Bio-Rad) as previously described [18,20]. Antibodies against ORC1 (dilution, 1:800; cat. No. sc-13231; Santa Cruz Biotechnology, Santa Cruz, CA), pro caspase-3 (dilution, 1:1000; cat. No. ab32105; Abcam, Cambridge, UK), cleaved caspase-3 (dilution, 1:800; cat. No. ab2302; Abcam, Cambridge, UK), Bax (dilution, 1:500; cat. No. sc-20067; Santa); Bcl-2 (dilution, 1:800; cat. No. sc-7382; Santa); CyclinD1 (dilution, 1:1000; cat. No. ab16663; Abcam); p53 (dilution, 1:800; cat. No. sc-47698; Santa); Vimentin (dilution, 1:800; cat. No. ab92547; Abcam, Cambridge, UK); MMP2 (dilution, 1:1000; cat. No. ab37150; Abcam) and GAPDH (dilution 1:1000; cat. no. ab8245; Abcam) were used. The membranes were incubated with the above antibodies overnight at 4 °C. Next, membranes were incubated for 1 h at ambient temperature with goat anti-rabbit horseradish peroxidase-labeled secondary antibody (dilution 1:10,000; cat. no. ab6721; Abcam). Target proteins were detected using Clarity™ Western enhanced chemiluminescence substrate (Bio-Rad Laboratories, Inc., Hercules, CA, USA), according to the manufacturer's protocol. Optical density was measured using AlphaEaseFC software (version 5.0, ProteinSimple, San Jose, CA, USA). GAPDH served as the internal control. The experiment was performed in triplicate.

0.031757 0.036549 0.047267

BP: Biological process; CC: cell componet; MF: molecular function. Table 2 Correlations between ORC1 expression in glioma and clinical characteristics. Group

Gender Male Female Age ≤40 > 40 WHO grade I-II stage III-IV stage

No.

Relative ORC1 expression

p Value

Low

High

11 10

4 6

7 4

0.279

12 9

8 5

4 4

0.604

8 13

3 6

5 7

0.697

χ2 test, *p < 0.05.

following pipette scratch, was used to estimate relative cell migration. The experiment was performed in triplicate.

2.14. Quantitative real time PCR 2.11. Transwell invasion assay Total RNA was isolated from tissue samples and cells using TRIzol® (Invitrogen; Thermo Fisher Scientific, Inc.) according to the manufacturer's protocol. One step Prime Script miRNA and mRNA cDNA Synthesis Kit, were used to perform reverse transcription (Takara Biotechnology Co. Ltd, Dalian, China). Quantitative real-time PCR was performed using SYBR Premix Ex Taq II (Takara Biotechnology). For sample loading normalization, GAPDH was employed. The primer sequences were synthesized by Sangon (Shanghai, China), and included

Cell invasion was detected by Transwell invasion. In brief, Transwell chambers were coated with 80 μL Matrigel (BD Biosciences, Franklin Lakes, NJ, USA) [19], and kept for 30 min at 37 °C. About 2 × 105 transfected U87-MG or T98G cells in 300 μL serum-free medium were seeded in the upper chamber. The lower chamber was filled with 500 μL medium containing 10% FBS. The upper chamber cells were stained with 0.5% crystal violet at ambient temperature for Table 3 The sequences of ORC1 overexpression or inhibitons. Name

sequence

ORC1 overexpression

Sense: 5′-ATGGCACACTACCCCACAAG-3′ Antisense: 5′-TTACTCGTCTTTCAGCGCAT-3′ Sense: 5′CCTGGTGCACAGGAAATATCTCGAGATATTTCCTGTGCACCAGGTTTTTG-3′ Antisense: 5′CAAAAACCTGGTGCACAGGAAATATCTCGAGATATTTCCTGTGCACCAGG-3′

ORC1 inhibition

4

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3.4. PPI network and identification of key genes

ORC1 forward, 5′- TTGCCAACACAATGGACCTG-3′ and reverse, 5′CTGCTGCAGCTGGCTATATG-3′ (110 bp); Bax forward, 5′-GGATGCGT CCACCAAGAAG-3′ and reverse, 5′- GTTGAAGTTGCCGTCAGAAAA-3′ (163 bp) [21]; Bcl-2 forward, 5′-GCCTTCTTTGAGTTCGGTGG-3′ and reverse, 5′-GAAATCAAACAGAGGCCGCA-3′(192 bp) [21]; CyclinD1 forward, 5′-ACAGATCATCCGCAAACACG-3′ and reverse, 5′-ATCACTC TGGAGAGGAAGCG-3′ (186 bp); p53 forward, 5′-CTGGCATTTGCACC TACCTC-3′ and reverse, 5′-TAACCAGCTGCCCAACTGTA-3′ (176 bp); Vimentin forward, 5′- CCCTCACCTGTGAAGTGGAT -3′ and reverse, 5′TGACGAGCCATTTCCTCCTT -3′ (163 bp); MMP-2 forward, 5′- CTACT GAGTGGCCGTGTTTG-3′ and reverse, 5′- TCCCTGAGGTTCTCTTG CTG-3′ (174 bp). The reverse transcription conditions included: 5 min at 85 °C, 30 min at 42 °C and 5 min at 25 °C. Based on an ABI PRISM 7500 sequence detection system, SYBR Green (Roche Diagnostics GmbH, Mannheim, Germany) was employed for a qPCR assay. The qPCR state preceded the 30 sec 33-cycle denaturation, both at 98 °C, with 30 s each of annealing at 56 °C and extension at 72 °C. Target gene expression was normalized with that of the internal control to achieve mRNA relative expression via 2−ΔΔCq formula [22]. The experiment was performed in triplicate.

To predict protein interactions, 35 DEGs were mapped into the STRING database to construct a PPI network. The PPI network was consisted of 34 nodes and 210 edges and visualized by Cytoscape (Fig. 2A). CDK1, PLK1, CCND1, CDC25C, CDC6, ATM, MCM3, ORC1, BCL2L1 and BUB1 were verified to be the top 10 protein nodes in the core of the PPI network, exhibiting the largest connection degrees (Fig. 2B). 3.5. ORC1 was upregulation in glioblastoma tissues and cell lines The results of Western blot and RT-PCR assays showed that ORC1 was highly expressed in glioblastoma tissues, compared to that in normal tissues (Fig. 3A and B). ORC1 overexpression has no concern with gender, age and WHO grade (Table 2). The results of the survival analysis showed that ORC1 overexpression was not associated with poor survival (Fig. 3C). Furthermore, ORC1 was significantly upregulated in glioblastoma cell lines via RT-PCR and Western blot assays (Fig. 3D and E). Transfection with ORC1 shRNA or ORC1 cDNA resulted in changes in ORC1 mRNA and protein expression of U87-MG and T98G cells. Our results showed that ORC1 was significantly downregulation in U87-MG cells carrying with ORC1 shRNA and upregulation in T98G cells carrying with ORC1 cDNA by Western blot and RT-PCR assays (Fig. 3F).

2.15. Statistical analysis Statistical analysis was performed using the statistical package (SPSS) V17. The data are presented as the means ± standard deviations (SD). We defined the relative ORC1 expression > 5.8 as high expression and 5.8 is derived from the mean values of all samples. The correlations between ORC1 expression and clinicopathological characteristics was examined by χ2 test. Survival analysis was performed by the Kaplan–Meier method and compared by the log-rank test. One-way variance analysis (ANOVA) of data prior to the least-significant difference test established results with P values below 0.05 as statistically significant.

3.6. shRNA-mediated knockdown of ORC1 suppresses cell proliferation and induces G1 phase cell cycle arrest and apoptosis ORC1 inhibition resulted in a significant decrease in the proliferation of U87-MG cells by CCK8 and colony formation assays, meanwhile, ORC1 overexpression resulted in a significant increase in the proliferation of T98G cells (Fig. 4A–D). Flow cytometry analysis was used to confirm the effect of ORC1 on cell cycle and cell apoptosis in T98G and U87-MG cells. The apoptosis of U87-MG cells was significantly upregulated following transfection with shRNA-ORC1 and down-regulated following transfection of U87-MG cells with ORC1 cDNA (Fig. 4E and F). No obvious differences were observed in the apoptosis rate between the control and ORC1inhibition transfected U87-MG cells and ORC1 overexpression transfected T98G cells. According to cell cycle analysis, knockdown of ORC1 significantly increased the number of U87-MG cells in the G1 phase (Fig. 4G and H) and overexpression of ORC1 significantly increased the number of T89G cells in the G2 phase (Fig. 4I and J).

3. Results 3.1. Identification of differentially expressed genes A total of 2893 DEGs, including 398 upregulated genes and 2495 downregulated genes (P < 0.05 and |logFC| > 1 as cutoff criterion), were identified from the GSE15824 dataset by using the ‘limma’ package in R (Fig. 1A). A volcano map was generated to assess the down-regulated and up-regulated mRNA (Fig. 1B).

3.7. shRNA-mediated knockdown of ORC1 suppresses cell migration and invasion

3.2. Gene set enrichment analysis

The migration of ORC1 shRNA transfected U87-MG cells was significantly inhibited and the migration of ORC1 cDNA transfected T98G cells was significantly promoted via wound healing assay (Fig. 5A–D). Next, ORC1 inhibition significantly suppressed the invasion of U87-MG cells and ORC1 overexpression significantly promoted the invasion of T98G cells (Fig. 5E and F). There was no significant difference in the invasion rate between the control and shRNA-NC/or NC groups.

GSEA was used to clarify the signaling pathways and functions of 2893 DEGs in glioblastoma cell lines. Our results showed that 35 DEGs (ATM, ENDOD1, TNFRSF10B, PIK3R3, PIK3R1, PPP3CB, IKBKG, MAP3K14, RELA, IKBKB, BCL2L1, CCND1, CDK1, CDC25B, MCM5, CDC25C, YWHAH, ESPL1, MCM3, CDC6, YWHAE, CDC45, RBL1, SMAD3, TGFB1, PLK1, MAD2L1, ORC1, SKP2, BUB1, CCNE2, E2F3, MAPK9, MAPK1 and BRCA21) were mainly enriched in apoptosis, cell cycle and pathways involved cancer (Fig. 1C).

3.8. Effect of ORC1 on the expression levels of proteins associated with proliferation, cell cycle, apoptosis, migration, and invasion 3.3. Functional annotation analysis of DEGs To further explore the mechanism of ORC1 regulating cell proliferation, cell cycle, apoptosis, migration and invasion in U87-MG and T98G cells, the expression levels of apoptosis-related proteins (caspase3, Bax, Bcl-2, and p53), the proliferation and cell cycle-related protein (CyclinD1), and the migration and invasion-related proteins (Vimentin and MMP-2) was determined by RT-PCR and Western blot assays. As shown in Fig. 6, pro-caspase-3 was significantly down-regulation and

Thirty-five DEGs were used to perform GO functional annotation by DAVID database (https://david.ncifcrf.gov/), and significantly enriched in 89 biological process (BP), 17 cell component (CC) and 27 molecular function (MF) terms (Table 1). CCNE2, CDK1, CDC6, CDC45, CCND1, SKP2, MCM3, ORC1 and MCM5 were enriched in the most significant BP term–G1/S transition of mitotic cell cycle. 5

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Fig. 1. Heat map, volcano map, GSEA analysis of DEGs data from GEO (GSE15824). (A) heat map analysis showed that there were the 7 samples in the GSE15824. DEGs was screened with the Fold change value greater than 2 and P < 0.05 as screening conditions. The cluster heat map showed the 2892 DEGs in glioma cell lines. (B) Volcano plot displayed 398 up-regulated and 2495 down-regulated DEGs. (C–E) GSEA enrichment plots showed that enrichment of apoptosis, cell cycle and cancer pathways was associated with ORC1 gene. DEGs. differentially expressed genes.

Fig. 2. PPI network and Hub gene analysis. (A) Protein-protein interaction network of 44 DEGs genes. (B) The top 30 hub genes in the PPI network.

3.9. ORC1 overexpression promoted the activation of ERK/JNK signaling pathway

cleaved-caspase-3 was significantly up-regulation by ORC1 inhibition in U87-MG cells, meanwhile, pro-caspase-3 was significantly up-regulation and cleaved-caspase-3 was significantly down-regulation by ORC1 overexpression in T98G cells (Fig. 6A and B). The mRNA and protein expression levels of Bax and CyclinD1 were significantly increased in shRNA-ORC1 transfected U87-MG cells compared with control cells and decreased in ORC1 overexpression transfected T98G cells compared with control cells. ORC1 inhibition significantly decreased the mRNA and protein levels of Bcl-2, p53, Vimentin and MMP-2 in U87-MG cells and ORC1 overexpression significantly increased the mRNA and protein levels of Bcl-2, p53, Vimentin and MMP-2 in T98G cells (Fig. 6C–O).

Our results indicated that the phosphorylation levels of ERK and JNK were significantly down-regulated in shRNA-ORC1 transfected U87-MG cells and up-regulated in ORC1 overexpression transfected with T98G cells (Fig. 7). These results revealed that downregulation of ORC1 suppressed the activation of ERK/JNK signaling pathway and upregulation of ORC1 activated ERK/JNK signaling pathway.

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Fig. 3. ORC1 highly expressed in glioma cell lines and tissues. (A) Western blot assay was used to detect the protein expression level of ORC1 in glioma tissues from 21 patients. (B) RT-PCR assay was used to detect the mRNA expression level of ORC1 in glioma tissues from 21 patients. (C) Kaplan-Meier survival analysis was performed to investigate the relationship between ORC1 low expression and ORC1 high expression. (D) Western blot assay was used to detect the protein expression level of ORC1 in glioma cell lines. (E) RT-PCR assay was used to detect the mRNA expression level of ORC1 in glioma cell lines. (F) Western blot and RT-PCR were used to detect the transfection efficiency of U87-MG and T98G cells transfection with lentiviral expressing shRNA-ORC1 and ORC1. GAPDH was used as a load control. Data are presented as the mean ± standard deviation. **P < 0.01 versus normal/Control/HEB group.and RT-PCR were used to detect the mRNA and protein expression level of ORC1 gene. (C–E) Western blot and RT-PCR were used to detect the transfection efficiency of U87-MG and T98G cells transfection with lentiviral expressing shRNA-ORC1 and ORC1. (F and G) CCK8 assay was used to detect cell viability after U87-MG and T98G cells transfection with lentiviral expressing shRNA-ORC1 and ORC1 at 0, 24, 48 and 72 h. GAPDH was used as a load control. Data are presented as the mean ± standard deviation. **P < 0.01versus Control group and shRNA-NC group, and **P < 0.01versus Control group and Vector-NC group.

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Fig. 4. ORC1 affected the viability, proliferation, apoptosis and cell cycle of U87-MG and T98G cells. After U87-MG and T98G cells transfection with lentiviral expressing shRNA-ORC1 or ORC1. (A) CCK8 assay was used to detect cell viability after U87-MG cells transfection with lentiviral expressing shRNA-ORC1 at 0, 24, 48 and 72 h. (B) CCK8 assay was used to detect cell viability after T98G cells transfection with lentiviral expressing ORC1 at 0, 24, 48 and 72 h. (C and D) Colony formation assay was used to detect cell proliferation. (E and F) Flow cytometry assay was used to detect cell apoptosis. (G and H) Flow cytometry assay was used to the cell cycle distributions in shRNA-ORC1 transfected U87-MG cells. (I and J) Flow cytometry assay was used to the cell cycle distributions in ORC1 transfected T98G cells. Data are presented as the mean ± standard deviation. **P < 0.01 versus Control group and shRNA-NC/Vector-NC group. 8

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Fig. 5. ORC1 affected the migration and invasion U87-MG and T98G cells. (A and B) Wound healing assay was used to detect the migration ability after U87-MG cells transfection with lentiviral expressing shRNA-ORC1 at 0 and 48 h. (C and D) Wound healing assay was used to detect the migration ability after T98G cells transfection with lentiviral expressing ORC1 at 0 and 48 h. (E and F) Transwell assay was used to detect the invasion ability after U87-MG and T98G cells transfection with lentiviral expressing shRNA-ORC1 or ORC1. Data are presented as the mean ± standard deviation. **P < 0.01 versus Control group and shRNA-NC group, and **P < 0.01 versus Control group and Vector-NC group.

(GSE15824) were primarily enriched in apoptosis, cell cycle, and pathways involved in cancer by GSEA analysis (Fig. 1). GO analysis showed that CCNE2, CDK1, CDC6, CCND1, SKP2 and ORC1 were enriched in significant functions and closely associated with the G1/S transition of the cell cycle (Table 1). We found that CDK1, PLK1, CCND1, CDC25C, CDC6, ATM, MCM3, and ORC1 were the top eight protein nodes with the highest connection degrees in PPI network (Fig. 2). CDK1 [24],PLK1 [25], CCND1 [26], CDC25C [26], CDC6 [27], ATM [28] and MCM3 [29] have been reported to be involved in glioma, but ORC1 has never been reported. Therefore, ORC1 was further studied. In eukaryotes, ORC is highly conserved and consists of six-subunits [30]. ORC1, as the largest ORC subunit, can bind DNA and induce cell apoptosis [31]. ORC1 is indispensable to pre-replicative complex assembly, DNA replication discharging, and accurate genome duplication [32]. Our results showed that ORC1 was overexpressed in glioblastoma cell lines and tissues and has no concern with gender, age, WHO grade and poor survival (Table 2) (Figs. 2 and 3). This may be due

3.10. The functions of ORC1 in regulating biological processes were reversed by a ERK and JNK inhibitor After T89G cells were pretreated with ERK and JNK inhibitor (astragaloside IV) for 6 h, the functions of ORC1 overexpression increasing cell viability and proliferation were reversed (Fig. 8A and B). Astragaloside IV inhibited apoptosis and cell cycle progression in ORC1 overexpression transfected T98 cells (Fig. 8C and D). In addition, the invasion and migration of T98G cells transfected with ORC1 were inhibited by astragaloside IV (Fig. 8E and F). 4. Discussion Glioma is characterized by invasive growth leading to poor prognosis and low survival rate [23]. Thus, there is increased interest in finding an effective target for cancer treatment at the gene level. Based on bioinformatics analysis, a total of 35 DEGs from GEO data 9

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Fig. 6. ORC1 affected the expression levels of pro caspase3, cleaved caspase-3, Bax, Bcl-2, CyclinD1, p53, E-cadherin and MMP-2 genes. After U87-MG and T98G cells transfection with lentiviral expressing shRNA-ORC1 or ORC1, (A and B) Western blot assay was used to detect the expression levels of pro caspase3 and cleaved caspase-3 protein. (C–F) Western blot and RT-PCR assays were used to detect the mRNA and protein expression levels of Bax and Bcl-2. (G–J) Western blot and RTPCR assays were used to detect the mRNA and protein expression levels of CyclinD1 and p53. (K–N) Western blot and RT-PCR assays were used to detect the mRNA and protein expression levels of Vimentin and MMP-2. (O) Protein bands of pro caspase-3, cleaved caspase-3, Bax, Bcl-2, cyclinD1, p53, Vimentin, MMP-2 and GAPDH. GAPDH was used as a load control. Data are presented as the mean ± standard deviation. **P < 0.01 versus Control group and shRNA-NC group, and **P < 0.01 versus Control group and Vector-NC group.

ORC1 suppressed cell migration and invasion (Fig. 5). These results show that ORC1 could affect migration, invasion, apoptosis, and proliferation in glioma cells. Changes in the expression of ORC1 may affect cell cycle. G1/S phase, as an important cell-cycle checkpoint, is closely related to the occurrence and development of tumors [36,37]. CyclinD1 and p53 are very important transcription factors regulating G1/S phase of the cell cycle [38]. Moreover, CyclinD1 and p53 have been used to study cell proliferation, cell apoptosis and cell cycle in a variety of cancers [39–42]. CyclinD1 is considered an oncogene and p53 is considered a tumor suppressor gene. Thus, the mRNA and protein expression levels of CyclinD1 and p53 were determined by RT-PCR and Western blot assays. shRNA-mediated knockdown of ORC1 up-regulated CyclinD1 expression level and down-regulated p53 expression level in U87-MG cells. The mRNA and protein expression levels of CyclinD1 and p53 in overexpressing ORC1 transfected T98G cells exhibited an opposite trend (Fig. 6). Bax, a pro-apoptotic factor of the Bcl-2 family, can

to the small number of cases. Furthermore, down-regulation or upregulation of ORC1 significantly regulated cell viability by the CCK8 assay (Fig. 4). This was an indication that ORC1 played an important role in cell proliferation. Thus, colony formation, cell apoptosis and cell cycle were further examined by colony formation assay and flow cytometry analysis. We found that shRNA-mediated knockdown of ORC1 suppressed cell proliferation, induced G1 phase cell cycle arrest and apoptosis (Fig. 4). It is well known that ORC1 overexpression could trigger DNA re-replication stress and thus induce G2 phase cell cycle arrest. Our results showed that ORC1 overexpression promoted cell proliferation and induced G2 phase cell cycle arrest (Fig. 4). The growth pattern of tumors has three phases: expansive growth, exophytic growth, and invasive growth [33–35]. Invasive growth, a growth pattern observed in most malignant tumors, is caused by tumor cell division, hyperplasia, and migration. Accordingly, we further investigated the effects of ORC1 on invasion and migration by transwell and wound healing assays. Similarly, we found that shRNA-mediated knockdown of

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Fig. 7. ORC1 affected the activation of ERK and JNK signaling pathways. (A–C) Western blot assay was used to detect the phosphorylation levels of ERK and JNK. GAPDH was used as a load control. Data are presented as the mean ± standard deviation. **P < 0.01 versus Control group and shRNA-NC group, and **P < 0.01 versus Control group and Vector-NC group.

The results showed ORC1 overexpression promoted cell proliferation, invasion and migration and inhibited apoptosis in glioma cells via activating ERK and JNK signaling pathways. In conclusion, shRNA-mediated knockdown of ORC1 regulated the expression levels of related genes to promote cell apoptosis, affect cell cycle distribution, suppress cell proliferation, and reduce migration and invasion through the suppression of JNK and ERK signaling pathways. ORC1 may be considered an oncogene involved in glioma.

promote the release of cytochrome C to activate caspase-3, which induces cell apoptosis. Bcl-2, as an anti-apoptotic factor of Bcl-2 family, suppressed cell apoptosis by decreasing Bax expression levels [43,44]. Our results indicated that shRNA-mediated knockdown of ORC1 upregulated the expression levels of cleaved caspase-3 and Bax, and downregulated the expression levels of Bcl-2 (Fig. 6). These results suggested that ORC1 regulated cell proliferation and apoptosis by regulating the expression levels of proliferation and apoptosis-related genes, including caspase-3, Bax, Bcl-2, CyclinD1 and p53. MMP-2, one of the matrix metalloproteinases (MMPs), that degrade the basement membrane allowing tumor invasion and metastasis, is associated with aggressiveness and poor prognosis of many cancers [45]. The Vimentin is the migration and invasion-related protein and closely related to patient's survival [46]. shRNA-mediated knockdown of ORC1 suppressed the expression levels of Vimentin and MMP-2. These results indicated that ORC1 affected invasion and migration of cells in glioma. According to our study, ORC1 played an important role in the migration, invasion, apoptosis and proliferation of glioma cells. To explore the mechanism of ORC1, glioma cells were transfected with shRNAORC1 or ORC1. ERK signaling pathway regulates transition through the G1-S phase of the cell cycle and is involved in cell proliferation and differentiation [47]. The activation of ERK up-regulates or down-regulates the expression levels of CyclinD1, p53 and Bcl-2 to affect glioma growth [47,48]. JNK signaling pathway is vital for the cell cycle, proliferation, migration, invasion and apoptosis. It has been reported that the activation of JNK significantly upregulates the expression levels of Bax and Caspase-3 to affect cell apoptosis, and regulates the expression levels of MMP2 and Vimentin to affect cell migration and invasion in glioma [49,50]. The results showed that the phosphorylation levels of ERK and JNK proteins were suppressed by shRNA-mediated knockdown of ORC1 in U87-MG cells (Fig. 7). These results indicated that ORC1 affected JNK and ERK signaling pathways. Whether ORC1 affecting glioma growth by activating ERK and JNK signaling pathways needs to be further verified. Astragaloside IV is a saponin isolated from Astragalus and inhibits the activation of ERK and JNK signaling pathways. Our results showed that the effects of ORC1 overexpression on promoting biological processes were reversed by astragaloside IV (Fig. 8).

Funding No funding was received. Availability of data and materials The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request. Ethics approval and consent to participate All patients provided written informed consent, and the study conducted in accordance with the Declaration of Helsinki. Both clinical data and detailed follow-up data were obtained for all patients. All the specimens collected were handled according to the protocols approved by the Ethics Committee of Tumor Hospital of Jiangxi Province. Authors' contributions Wenmin Xiong and Chen Xie wrote the main manuscript and analyzed the data. Yang Qiu and Ziwei Tu performed the experiments. Qiaoying Gong designed the study. All authors read and approved the final manuscript. Declaration of competing interest The authors declare that they have no competing interests. 11

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Fig. 8. The functions of ORC1 in regulating biological processes were reversed by ERK and JNK inhibitor. After T98G cells with Astragaloside IV were transfected with ORC1 overexpression, (A) CCK8 assay was used to detect cell viability; (B) Colony formation was used to detect cell proliferation; (C and D) Flow cytometry assay was used to detect cell apoptosis rate and cell cycle distributions; (E) Wound healing assay was used to detect the migration ability; (F) Transwell assay was used to detect the invasion ability. Data are presented as the mean ± standard deviation. **P < 0.01 versus vector group, and ##P < 0.01 versus ORC1 group.

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Acknowledgements [23]

GSE15824 dataset (http://www.ncbi.nlm.nih.gov/geo/) was used to perform our study.

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