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. 2017 May 31;16(1):553–564. doi: 10.3892/mmr.2017.6662

Identification of critical genes in nucleus pulposus cells isolated from degenerated intervertebral discs using bioinformatics analysis

Zhuangchen Zhu 1,*,✉, Guang Chen 1,*, Wei Jiao 1, Defeng Wang 1, Yan Cao 1, Qingfu Zhang 1, Junqin Wang 1
PMCID: PMC5482069  PMID: 28586059

Abstract

Intervertebral disc (IVD) degeneration is a pathological process, which may lead to lower back pain. The present study aimed to investigate the pathogenesis of IVD degeneration. GSE42611 was downloaded from Gene Expression Omnibus, including 4 nucleus pulposus samples isolated from degenerated IVDs and 4 nucleus pulposus samples separated from normal IVDs. The differentially expressed genes (DEGs) between the degenerated and normal samples were screened using the limma package in R. Functional and pathway enrichment analyses were conducted separately for the upregulated and downregulated genes, using Database for Annotation, Visualization and Integrated Discovery software. In addition, protein-protein interaction (PPI) networks were constructed using the Search Tool for the Retrieval of Interacting Genes database and Cytoscape software. Finally, module analyses were conducted for the PPI networks using the MCODE plug-in in Cytoscape. A total of 558 DEGs were identified in the degenerated nucleus pulposus cells: 253 upregulated and 305 downregulated. Pathway enrichment analysis revealed that downregulated thrombospondin 1 (THBS1) was enriched in extracellular matrix-receptor interaction. Interleukin (IL)-6 in the PPI network for the upregulated genes and vascular endothelial growth factor A (VEGFA) in the PPI network for the downregulated genes had higher degrees. Additionally, four modules (µM1, µM2, µM3 and µM4) were identified from the PPI network for the upregulated genes. Four modules (dM1, dM2, dM3 and dM4) were identified from the PPI network for the downregulated genes. In the dM2 module, collagen genes and integrin subunit α4 (ITGA4) may interact with each other. Additionally, functional enrichment indicated that collagen genes were enriched in extracellular matrix organization. In conclusion, IL-6, VEGFA, THBS1, ITGA4 and collagen genes may contribute to the progression of IVD degeneration. These results suggested that the manipulation of these genes and their products may have potential as a novel therapeutic strategy for the treatment of patients with IVD.

Keywords: intervertebral disc degeneration, differentially expressed genes, functional and pathway enrichment analysis, protein-protein interaction network

Introduction

Intervertebral disc (IVD) degeneration, also termed degenerative disc disorder or degenerative disc disease, is a pathological process that may induce acute or chronic lower back pain (1,2). Lower back pain is one of the primary health problems in developed countries (3). The risk factors for disc degeneration include genetic inheritance and environmental risk factors, including smoking cigarettes and repetitive and high mechanical loading (4). IVD degeneration is a rapidly progressing disease without an effective therapeutic method (5). Therefore, it is necessary to explore the mechanisms of IVD degeneration in order to be able to develop a novel treatment scheme.

IVD degeneration and the underlying molecular mechanisms have been previously investigated. The aggrecanases ADAM metallopeptidase with thrombospondin type 1 motif (ADAMTS)-1, -4, -5, -9 and -15 may promote extracellular matrix (ECM) alterations during IVD degeneration, and may be used for preventing IVD degeneration and its morbidity (6). In disc cells, reduced expression of SRY-type high mobility group box 9 (SOX9) may be associated with disc degeneration and disc ageing via inhibition of type II collagen expression (7). The growth differentiation factor-5 (GDF-5) cDNA and the recombinant GDF-5 protein may promote the expression of ECM protein-coding genes in mouse IVD cells (8). Previous studies have detected overexpressed tumor necrosis factor α (TNF-α) and interleukin (IL)-1 in aged and degenerative IVDs obtained from human and animal models (9,10). IL-1 has been identified to be involved in IVD degeneration via directly inhibiting matrix synthesis and promoting matrix degradation (11,12). Cytokines of IL-1 and TNF-α may be associated with the pathogenesis of IVD degeneration; however, IL-1 may have a greater contribution to IVD degeneration and may be a more suitable therapeutic target for the disease (13).

In 2013, Markova et al (14) established a rat disc organ culture model that mimicked IVD degeneration via culturing rat IVDs in the presence of IL-1β, TNF-α and serum-limiting conditions. They obtained 1036 differentially expressed genes (DEGs) between experimental and control groups following gene expression analysis for microarray data. The present study used the data from Markova et al (14) and the DEGs between degenerated and normal nucleus pulposus cells were identified, and their possible functions were predicted using enrichment analysis. Additionally, protein-protein interaction (PPI) networks were visualized and module analysis was conducted to screen for key genes in degenerated nucleus pulposus cells.

Materials and methods

Microarray data

Microarray data obtained from GSE42611 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42611), which was downloaded from the database of Gene Expression Omnibus (GEO), were sequenced on the platform of GPL6247 Affymetrix Rat Gene 1.0 ST Array [transcript (gene) version]. GSE42611 included 4 nucleus pulposus samples isolated from degenerated IVDs and 4 nucleus pulposus samples separated from normal IVDs. The procedure that had been used to obtain the rat lumbar disc specimens (n=4 specimens/group) was as follows, according to the method of Ponnappan et al (8): Whole lumbar IVDs with endplates had been dissected and preserved in organ culture. Lumbar discs in the experimental group had been cultivated in Dulbecco's modified Eagle's medium (DMEM) containing 100 ng/ml TNF-α, 10 ng/ml IL-1β, 50 µg/ml L-ascorbate, 40 mM NaCl, 1% fetal bovine serum (FBS), antibiotics and antimycotics. Lumbar discs in the control group had been cultured in DMEM containing 50 µg/ml L-ascorbate, 40 mM NaCl, 10% FBS and antibiotics without cytokines. The discs had been cultured for a total of 10 days (14). GSE42611 used in this study was downloaded from a public database; therefore, patient consent or ethics committee approval were not required.

Data preprocessing and DEGs screening

GSE42611 was downloaded and the microarray data was preprocessed using the Affy package (15) in R. The process of data preprocessing included background correction, quantile normalization, summarization and probe ID to gene symbol transformation. Linear models for microarray data in the limma package (16) in R were used to analyze the DEGs between degenerated and normal nucleus pulposus cells. P-values of the DEGs were calculated separately and adjusted using the t-test method and the Benjamini & Hochberg method (17). P<0.05 and |log2 fold-change (FC)|>1 were used as the thresholds.

Functional and pathway enrichment analysis

The Database for Annotation, Visualization and Integrated Discovery (DAVID; david.abcc.ncifcrf.gov) software was used to interpret functions of extensive genes obtained from previous genome studies (18). The Gene Ontology database (GO; www.geneontology.org) contained structured ontologies or vocabularies that depict basic characteristics of genes and gene products (19). The Kyoto Encyclopedia of Genes and Genomes database (KEGG; www.genome.jp/kegg/) synthesizes information of biological systems from genomic, chemical and systemic functional aspects (20). Using the DAVID software, functional and pathway enrichment analyses were conducted separately, for upregulated and downregulated genes. P≤0.05 and >2 enriched genes were set as the thresholds.

PPI network construction and module analysis

The Search Tool for the Retrieval of Interacting Genes (STRING; string-db.org) database provide comprehensive and easily accessible interaction information derived from experiments and predictions (21). Cytoscape software (www.cytoscape.org) was used to integrate high-throughput expression data and biomolecular interaction networks into a unified framework (22). The PPIs obtained for the DEGs were searched using the STRING database (21), with the required confidence (combined score) >0.4 as the threshold. Using Cytoscape software version 2.8 (22), the PPIs were used to established a PPI network. In the network, the proteins were termed nodes and the number of edges involved were their degrees. Finally, the MCODE plug-in (23) in Cytoscape was used to perform module analysis of the PPI networks. The parameters were set at the default thresholds.

Results

DEG analysis

P<0.05 and |log2FC|>1 were set as thresholds and the DEGs between degenerated and normal nucleus pulposus cells were analyzed. There were 558 DEGs identified in the degenerated nucleus pulposus cells compared with normal nucleus pulposus cells, including 253 upregulated and 305 downregulated genes. There were more downregulated genes compared with upregulated genes.

Functional and pathway enrichment analysis

The upregulated genes in the degenerated nucleus pulposus cells were significantly enriched in 255 GO terms and 9 KEGG pathways. The top 10 functions are presented in Table IA, including response to wounding (P=2.35×10−8), inflammatory response (P=5.99×10−8) and response to organic substance (P=1.56×10−7).

Table I.

The top 10 enriched functions for the differentially expressed genes in the degenerated nucleus pulposus cells

A, Top 10 functions enriched for the upregulated genes in the degenerated nucleus pulposus cells
ID Description P-value Number of genes Gene
GO:0009611 Response to wounding 2.35×10−8 24 KNG1, CXCL1, NFKBIZ, IL6, GIP, KNG2, OLR1, C3, CXCL3, KNG1L1, CXCL2, CLU, HP, GLI3, TIMP1, SOD2, ORM1, CASP4, HIF1A, CCL20, PTGES, HMOX1, JAK2, TFPI2
GO:0006954 Inflammatory response 5.99×10−8 17 KNG1, CXCL1, NFKBIZ, IL6, KNG2, OLR1, C3, CXCL3, CXCL2, KNG1L1, HP, ORM1, CASP4, HIF1A, CCL20, PTGES, HMOX1
GO:0010033 Response to organic substance 1.56×10−7 35 FOSL2, OSMR, IL6ST, TLR2, NFKBIA, HP, GNG12, MMP3, GLI3, TIMP1, GCH1, IRAK3, PTGES, HMOX1, CSF2RB, ANGPT1, PPP3CA, SKIL, PIK3R3, NR1H3, IL6, SGK1, GIP, BCKDHB, MMP14, CYP7B1, HIF1A, ATP2A2, ABCB1B, CXCL16, JAK2, CTSC, PTPN1, CAR4, STEAP2
GO:0006952 Defense response 1.68×10−7 22 KNG1, CXCL1, NFKBIZ, IL6, KNG2, OLR1, FGR, C3, CXCL3, KNG1L1, CXCL2, TLR2, HP, GCH1, ORM1, CASP4, HIF1A, CCL20, PTGES, CXCL16, HMOX1, NOS2
GO:0042311 Vasodilation 2.48×10−6   7 KNG1, EDNRB, KNG2, KNG1L1, ITGA1, SOD2, GCH1
GO:0034097 Response to cytokine stimulus 3.62×10−6 11 IRAK3, IL6, FOSL2, OSMR, IL6ST, PTGES, CXCL16, SKIL, MMP3, TIMP1, GCH1
GO:0009719 Response to endogenous stimulus 4.73×10−6 24 SGK1, IL6, FOSL2, GIP, BCKDHB, TLR2, HP, GNG12, MMP14, MMP3, GLI3, TIMP1, HIF1A, ATP2A2, ABCB1B, HMOX1, ANGPT1, JAK2, PTPN1, PPP3CA, PIK3R3, STEAP2, CAR4, NR1H3
GO:0009725 Response to hormone stimulus 8.64×10−6 22 SGK1, IL6, FOSL2, GIP, BCKDHB, TLR2, HP, GNG12, MMP14, GLI3, TIMP1, HIF1A, ATP2A2, ABCB1B, HMOX1, ANGPT1, JAK2, PTPN1, STEAP2, CAR4, PIK3R3, NR1H3
GO:0055066 Di-, tri-valent inorganic cation homeostasis 1.15×10−5 14 KNG1, IL6ST, HEXB, SOD2, SLC11A2, EDNRB, HIF1A, MT1A, ATP2A2, HMOX1, MT2A, PKD2, JAK2, CP
GO:0055080 Cation homeostasis 1.82×10−5 15 KNG1, SGK1, IL6ST, HEXB, SOD2, SLC11A2, EDNRB, HIF1A, MT1A, ATP2A2, HMOX1, MT2A, PKD2, JAK2, CP
B, Top 10 enriched functions for the downregulated genes in the degenerated nucleus pulposus cells
ID Description P-value Number of genes Gene
GO:0000279 M phase 9.18×10−12 21 KIF11, MKI67, SGOL2, DLGAP5, HAUS1, NUF2, NUSAP1, CENPF, BIRC5, NDC80, CEP55, TACC3, CCNB1, KIF2C, PLK1, TUBB5, BUB1B, MNS1, SKA3, STMN1, CDCA3
GO:0048545 Response to steroid hormone stimulus 2.95×10−9 23 SOCS2, AIF1, CRYAB, IL1RN, TGFB3, IGF1, BIRC5, AQP1, MMP2, ADIPOQ, TIMP3, H19, CCND1, KRT19, CD36,SERPINF1, ADM, AVPR1A, FABP4, RARA, COL1A1, CD24, CCNA2
GO:0009628 Response to abiotic stimulus 1.09×10−8 26 RBP4, APOBEC1, GCLC, AIF1, LXN, IL18, COL3A1, MMP2, CXCL12, TIMP3, KRT8, THBS1, COL11A1, MYOF, PTPRC, CRYAB, ATP1A3, IGF1, SNAI2, CCND1, CD36, ADM, FYN, AVPR1A, TGFB1I1, COL1A1
GO:0022610 Biological adhesion 1.23×10−8 28 IBSP, COL3A1, LMO7, KITLG, ITGBL1, FAT3, CD93, COMP, ACAN, COL12A1, TNN, CD4, EMB, CD24, THBS1, COL11A1, THBS4, PTPRC, ACTN1, ITGA4, PCDH18, THY1, OMD, COL14A1, CD36, PECAM1, DSC2, CDH11
GO:0007155 Cell adhesion 1.23×10−8 28 IBSP, COL3A1, LMO7, KITLG, ITGBL1, FAT3, CD93, COMP, ACAN, COL12A1, TNN, CD4, EMB, CD24, THBS1, COL11A1, THBS4, PTPRC, ACTN1, ITGA4, PCDH18, THY1, OMD, COL14A1, CD36, PECAM1, DSC2, CDH11
GO:0051301 Cell division 2.09×10−8 16 RBP4, HAUS1, NUF2, NUSAP1, BIRC5, CEP55, CCNB1, CCND1, CCNB2, PLK1, BUB1B, SKA3, TOP2A, CCNA2, ASPM, CDCA3
GO:0022402 Cell cycle process 2.49×10−8 24 GAS2L3, KIF11, MKI67, SGOL2, DLGAP5, HAUS1, NUF2, NUSAP1, CENPF, BIRC5, NDC80, CEP55, TACC3, CDKN3, CCNB1, KIF2C, CCND1, PLK1, TUBB5, BUB1B, MNS1, SKA3, STMN1, CDCA3
GO:0030199 Collagen fibril organization 4.36×10−8   8 COL3A1, COL1A2, ACAN, COL1A1, COL11A1, COL5A2, SERPINH1, DPT
GO:0007049 Cell cycle 4.42×10−8 27 GAS2L3, S100A6, HAUS1, CEP55, KIF2C, TUBB5, MNS1, SKA3, CCNA2, CDCA3, KIF11, MKI67, SGOL2, DLGAP5, NUF2, CENPF, NUSAP1, BIRC5, NDC80, TACC3, CDKN3, CCNB1, CCND1, CCNB2, PLK1, BUB1B, STMN1
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The downregulated genes in the degenerated nucleus pulposus cells were significantly enriched in 263 GO terms and 10 KEGG pathways. The top 10 functions included M phase (P=9.18×10−12), cell cycle phase (P=2.81×10−10) and response to steroid hormone stimulus (P=2.95×10−9; Table IB).

Additionally, the upregulated genes were significantly enriched in cytokine-cytokine receptor interaction (P=2.86×10−4), apoptosis (P=3.95×10−4) and chemokine (P=1.60×10−3; Table IIA) signaling pathways.

Table II.

Enriched pathways for the differentially expressed genes in the degenerated nucleus pulposus cells.

A, Pathways enriched for the upregulated genes
ID Description P-value Number of genes Gene
rno04060 Cytokine-cytokine receptor interaction 2.86×10−4 12 TNFRSF9, IL6, ZCCHC2, IL23R, TNFSF11, OSMR, IL6ST, CXCL16, MET, CXCL2, CSF2RB, IL13RA1
rno04210 Apoptosis 3.95×10−4   8 CFLAR, IRAK3, CSF2RB, NFKBIA, NFKB1, PPP3CA, BIRC3, PIK3R3
rno04062 Chemokine signaling pathway 1.60×10−3 10 CXCL1, FGR, CCL20, CXCL16, CXCL2, NFKBIA, JAK2, NFKB1, GNG12, PIK3R3
rno04621 NOD-like receptor signaling pathway 3.04×10−3   6 CXCL1, IL6, CXCL2, NFKBIA, NFKB1, BIRC3
rno04630 Jak-STAT signaling pathway 6.77×10−3   8 IL6, IL23R, OSMR, IL6ST, CSF2RB, JAK2, PIK3R3, IL13RA1
rno04620 Toll-like receptor signaling pathway 1.45×10−2   6 IL6, MAP3K8, TLR2, NFKBIA, NFKB1, PIK3R3
rno05200 Pathways in cancer 3.02×10−2 11 IL6, HIF1A, EPAS1, MET, NFKBIA, NFKB1, NOS2, RUNX1, BIRC3, PIK3R3, GLI3
rno00230 Purine metabolism 3.71×10−2   7 XDH, GDA, PDE7A, PDE4B, PDE10A, AMPD3, NT5E
rno05222 Small cell lung cancer 4.41×10−2   5 NFKBIA, NFKB1, NOS2, BIRC3, PIK3R3
B, Pathways enriched for the downregulated genes
rno04512 ECM-receptor interaction 1.17×10−11 16 IBSP, COL3A1, ITGA4, COL5A2, HMMR, CD36, COMP, COL6A3, COL1A2, COL6A2, COL6A1, TNN, COL1A1, THBS1, COL11A1, THBS4
rno04510 Focal adhesion 1.90×10−9 20 IBSP, COL3A1, IGF1, ACTN1, ITGA4, COL5A2, CCND1, FYN, COMP, VEGFA, COL6A3, COL1A2, COL6A2, COL6A1, TNN, COL1A1, THBS1, COL11A1, FIGF, THBS4
rno04640 Hematopoietic cell lineage 3.12×10−3   7 CD36, KITLG, CD4, ANPEP, CD24, ITGA4, CSF1R
rno05200 Pathways in cancer 5.58×10−3 14 FGF7, TGFB3, EGLN3, KITLG, IGF1, BIRC5, FZD4, MMP2, CCND1, VEGFA, RARA, FGF1, FIGF, CSF1R
rno04670 Leukocyte transendothelial migration 1.97×10−2   7 CYBB, PECAM1, ACTN1, ITGA4, MMP2, CXCL12, THY1
rno05219 Bladder cancer 2.86×10−2   4 CCND1, VEGFA, MMP2, FIGF
rno04110 Cell cycle 2.93×10−2   7 CCNB1, CCND1, CCNB2, PLK1, TGFB3, BUB1B, CCNA2
rno04115 p53 signaling pathway 3.38×10−2   5 CCNB1, CCND1, CCNB2, SERPINE1, IGF1
rno04610 Complement and coagulation cascades 4.07×10−2   5 C1QA, C3AR1, C5AR1, MASP1, SERPINE1
rno03320 PPAR signaling pathway 4.25×10−2   5 LPL, CD36, FABP4, ADIPOQ, PLTP
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The pathways enriched for the downregulated genes included ECM-receptor interaction [P=1.17×10−11, involving thrombospondin 1 (THBS1)], focal adhesion (P=1.90×10−9) and hematopoietic cell lineage (P=3.12×10−3; Table IIB).

PPI network construction and module analysis

PPI networks were constructed by Cytoscape software following a PPI search of the DEGs. The PPI networks for the upregulated (Fig. 1) and the downregulated (Fig. 2) genes separately had 360 and 1,112 interactions. Notably, IL-6 (degree=39) in the PPI network for the upregulated genes and vascular endothelial growth factor A (VEGFA; degree=37) in the PPI network for the downregulated genes had higher degrees. Using the MCODE plug-in in Cytoscape, four modules (µM1, µM2, µM3 and µM4) were identified from the PPI network for the upregulated genes (Fig. 3). Meanwhile, four modules (dM1, dM2, dM3 and dM4) were identified from the PPI network for the downregulated genes (Fig. 4). It is of note that collagen, type I, α1 (COL1A1), COL1A2, COL3A1, COL5A2, COL6A1, COL6A2, COL6A3, COL11A1, COL12A1 and integrin α4 (ITGA4) may interact with each other in the dM2 module.

Figure 1.

Figure 1.

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Protein-protein interaction network constructed for the upregulated genes.

Figure 2.

Figure 2.

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Protein-protein interaction network constructed for the downregulated genes.

Figure 3.

Figure 3.

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Four modules (µM1, µM2, µM3 and µM4) identified from the protein-protein interaction network constructed for the upregulated genes.

Figure 4.

Figure 4.

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Four modules (dM1, dM2, dM3 and dM4) identified from the protein-protein interaction network constructed for the downregulated genes.

The top 5 functions enriched for the upregulated genes in modules included taxis (µM1; P=1.03×10−8), response to organic substance (µM2; P=1.21×10−4), response to cytokine stimulus (µM3; P=5.04×10−4) and chemical homeostasis (µM4, P=1.22×10−3; Table IIIA). The pathways enriched for the upregulated genes in modules included the chemokine signaling pathway (µM1; P=1.10×10−4) and the Jak-STAT signaling pathway (µM2; P=7.69 ×10−4; Table IIIB). Additionally, the top 5 functions enriched for the downregulated genes in modules, included M phase (dM1; P=2.70×10−16), extracellular matrix organization (dM2; P=1.79×10−7, including COL3A1, COL1A2, COL1A1, COL11A1 and COL5A2), G-protein coupled receptor protein signaling pathway (dM3; P=7.27×10−4) and wound healing (dM4; P=1.56 ×10−4; Table IVA). The pathways enriched for the downregulated genes in modules included cell cycle (dM1; P=4.40×10−5), ECM-receptor interaction (dM2; P=1.37×10−15, including COL3A1, COL6A3, COL1A2, COL6A2, COL6A1, ITGA4, COL1A1, COL11A1 and COL5A2) and neuroactive ligand-receptor interaction (dM3; P=9.49×10−4; Table IVB).

Table III.

Top 5 functions and pathways enriched for the upregulated genes in µM1, µM2, µM3 and µM4 modules.

A, Top 5 functions enriched for the upregulated genes in µM1, µM2, µM3 and µM4 modules
Module ID Description P-value Number of genes Gene
µM1 GO:0042330 Taxis 1.03×10−8 5 CXCL1, CCL20, CXCL16, CXCL3, CXCL2
GO:0006935 Chemotaxis 1.03×10−8 5 CXCL1, CCL20, CXCL16, CXCL3, CXCL2
GO:0006952 Defense response 3.82×10−8 6 KNG1, CXCL1, CCL20, CXCL16, CXCL3, CXCL2
GO:0007626 Locomotory behavior 4.20×10−7 5 CXCL1, CCL20, CXCL16, CXCL3, CXCL2
GO:0006954 Inflammatory response 4.97×10−7 5 KNG1, CXCL1, CCL20, CXCL3, CXCL2
µM2 GO:0010033 Response to organic substance 1.21×10−4 6 IL6, OSMR, IL6ST, HMOX1, PTPN1, PIK3R3
GO:0042127 Regulation of cell proliferation 5.31×10−4 5 IL6, OSMR, IL6ST, HMOX1, SOD2
GO:0010035 Response to inorganic substance 5.55×10−4 4 IL6, HMOX1, NFKB1, SOD2
GO:0007167 Enzyme-linked receptor protein signaling pathway 6.31×10−4 4 IL6ST, MET, PTPN1, PIK3R3
GO:0031667 Response to nutrient levels 6.44×10−4 4 IL6, IL6ST, HMOX1, SOD2
µM3 GO:0034097 Response to cytokine stimulus 5.04×10−4 3 FOSL2, MMP3, TIMP1
GO:0009719 Response to endogenous stimulus 1.26×10−2 3 FOSL2, MMP3, TIMP1
GO:0006508 Proteolysis 2.26×10−2 3 ADAMTS1, MMP3, ADAMTS4
GO:0010033 Response to organic substance 3.18×10−2 3 FOSL2, MMP3, TIMP1
GO:0007568 Aging 4.87×10−2 2 FOSL2, TIMP1
µM4 GO:0048878 Chemical homeostasis 1.22×10−3 4 SLC11A2, SGK1, HIF1A, EPAS1
GO:0043619 Regulation of transcription from RNA polymerase II promoter in response to oxidative stress 2.48×10−3 2 HIF1A, EPAS1
GO:0043618 Regulation of transcription from RNA polymerase II promoter in response to stress 2.97×10−3 2 HIF1A, EPAS1
GO:0043620 Regulation of transcription in response to stress 2.97×10−3 2 HIF1A, EPAS1
GO:0042592 Homeostatic process 3.58×10−3 4 SLC11A2, SGK1, HIF1A, EPAS1
B, Pathways enriched for the upregulated genes in µM1 and µM2 modules
Module ID Description P-value Number of genes Gene
µM1 rno04062 Chemokine signaling pathway 1.10×10−4 4 CXCL1, CCL20, CXCL16, CXCL2
rno04621 NOD-like receptor signaling pathway 4.36×10−2 2 CXCL1, CXCL2
µM2 rno04630 Jak-STAT signaling pathway 7.69×10−4 4 IL6, OSMR, IL6ST, PIK3R3
µM2 rno04060 Cytokine-cytokine receptor interaction 2.12×10−3 4 IL6, OSMR, IL6ST, MET
rno04620 Toll-like receptor signaling pathway 6.74×10−3 3 IL6, NFKB1, PIK3R3
rno05200 Pathways in cancer 8.17×10−3 4 IL6, MET, NFKB1, PIK3R3
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Table IV.

Top 5 functions and pathways enriched for the downregulated genes in dM1, dM2, dM3 and dM4 modules.

A, Top 5 functions enriched for the downregulated genes
Module ID Description P-value Number of genes Gene
dM1 GO:0000279 M phase 2.70×10−16 12 CCNB1, KIF2C, KIF11, MKI67, PLK1, DLGAP5, NUF2, NUSAP1, BUB1B, CENPF, BIRC5, CEP55
GO:0007049 Cell cycle 6.52×10−15 14 KIF11, MKI67, DLGAP5, NUF2, NUSAP1, CENPF, BIRC5, CEP55, CDKN3, CCNB1, KIF2C, PLK1, BUB1B, CCNA2
GO:0022403 Cell cycle phase 7.11×10−15 12 CCNB1, KIF2C, KIF11, MKI67, PLK1, DLGAP5, NUF2, NUSAP1, BUB1B, CENPF, BIRC5, CEP55
GO:0022402 Cell cycle process 1.48×10−14 13 KIF11, MKI67, DLGAP5, NUF2, NUSAP1, CENPF, BIRC5, CEP55, CDKN3, CCNB1, KIF2C, PLK1, BUB1B
GO:0000087 M phase of mitotic cell cycle 1.70×10−14 10 CCNB1, KIF11, PLK1, DLGAP5, NUF2, NUSAP1, BUB1B, CENPF, BIRC5, CEP55
dM2 GO:0030199 Collagen fibril organization 5.72×10−10   5 COL3A1, COL1A2, COL1A1, COL11A1, COL5A2
GO:0030198 Extracellular matrix organization 1.79×10−7   5 COL3A1, COL1A2, COL1A1, COL11A1, COL5A2
GO:0043588 Skin development 6.89×10−7   4 COL3A1, COL1A2, COL1A1, COL5A2
GO:0043062 Extracellular structure organization 1.10×10−6   5 COL3A1, COL1A2, COL1A1, COL11A1, COL5A2
GO:0001501 Skeletal system development 1.45×10−5   5 COL3A1, COL1A2, COL1A1, COL11A1, COL5A2
dM3 GO:0007186 G-protein coupled receptor protein signaling pathway 7.27×10−4   6 S1PR3, C3AR1, C5AR1, PENK, LPAR1, CXCL12
GO:0007610 Behavior 7.91×10−4   4 C3AR1, C5AR1, PENK, CXCL12
GO:0002430 Complement receptor mediated signaling pathway 9.92×10−4   2 C3AR1, C5AR1
GO:0007204 Elevation of cytosolic calciumion concentration 1.03×10−3   3 C3AR1, C5AR1, LPAR1
GO:0051480 Cytosolic calcium ion homeostasis 1.29×10−3   3 C3AR1, C5AR1, LPAR1
dM4 GO:0042060 Wound healing 1.56×10−4   4 SERPINE1, TGFB3, IGF1, GAS6
GO:0040007 Growth 2.91×10−4   4 SERPINE1, TGFB3, IGF1, GAS6
GO:0042246 Tissue regeneration 3.74×10−4   3 SERPINE1, IGF1, GAS6
GO:0007167 enzyme linked receptor protein signaling pathway 6.31×10−4   4 TGFB3, IGF1, FIGF, CSF1R
GO:0051094 Positive regulation of developmental process 8.57×10−4   4 TGFB3, IGF1, FIGF, CSF1R
dM1 rno04110 Cell cycle 4.40×10-5   4 CCNB1, PLK1, BUB1B, CCNA2
rno04914 Progesterone-mediated oocyte maturation 1.41×10-3   3 CCNB1, PLK1, CCNA2
B, Pathways enriched for the downregulated genes
Module ID Description P-value Number of genes Gene
dM2 rno04512 ECM-receptor interaction 1.37×10−15 9 COL3A1, COL6A3, COL1A2, COL6A2, COL6A1, ITGA4, COL1A1, COL11A1, COL5A2
rno04510 Focal adhesion 1.91×10−12 9 COL3A1, COL6A3, COL1A2, COL6A2, COL6A1, ITGA4, COL1A1, COL11A1, COL5A2
dM3 rno04080 Neuroactive ligand-receptor interaction 9.49×10−4 4 S1PR3, C3AR1, C5AR1, LPAR1
dM4 rno05200 Pathways in cancer 5.33×10−3 4 TGFB3, IGF1, FIGF, CSF1R
rno04510 Focal adhesion 2.26×10−2 3 IGF1, ACTN1, FIGF
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Discussion

The present study identified a total of 558 DEGs in degenerated nucleus pulposus cells compared with normal nucleus pulposus cells, including 253 upregulated and 305 downregulated genes. Using the MCODE plug-in in Cytoscape, four modules (µM1, µ0M2, µM3 and µM4) were identified from the PPI network for the upregulated genes. Additionally, four modules (dM1, dM2, dM3 and dM4) were identified from the PPI network for the downregulated genes.

A previous study demonstrated that genetic variations of IL-6 may be associated with IVD degeneration, accompanied by sciatica (24). VEGFA was overexpressed in the nucleus pulposus and affects the survival of nucleus pulposus cells in an autocrine/paracrine manner (25). Injuries of IVDs may lead to increased VEGF levels, indicating that VEGF may be associated with discogenic back pain (26). Under co-culture conditions, VEGF induction may contribute to neo-vascularization of IVD tissue and may function in the resorption of herniated discs (27). The findings of the present study indicated that IL-6 (degree=39) in the PPI network for the upregulated genes and VEGFA (degree=37) in the PPI network for the downregulated genes had higher degrees. Therefore, IL6 and VEGFA may be key genes involved in IVD degeneration. A previous study observed the immunolocalization of THBS in human IVD (28). THBS1 and THBS2 are promising susceptibility genes in lumbar-disc herniation (LDH) that mediate the expression levels of matrix metalloproteinases (MMPs) 2 and 9, which are critical effectors of ECM remodeling (29). Mice with THBS1 or THBS2 deficiency exhibit abnormal spine curvature (30). Pathway enrichment performed in the present study revealed that downregulated THBS1 was enriched in ECM-receptor interactions, suggesting that THBS1 may have an important role in IVD degeneration.

The sequence variation of the regulatory region of COL1A1 is closely associated with lumbar disc disease (LDD) in young military recruits who are newly diagnosed (31). Ribosomal protein L8, ribosomal protein S16 and ribosomal protein S23 have been identified to contribute to protein synthesis, and COL3A1 was involved in skeletal system processes in disc degeneration (DD), indicating that they may be used for diagnosis and therapy of DD (32). Polymorphisms of the COL9 and COL11 genes contribute to the progression of degenerative lumbar spinal stenosis (33). COL11A1 expression level was reduced in the IVD of patients with LDH and it had a negative association with the severity of disc degeneration in patients with LDH (34). In the dM2 module identified by the present study, COL1A1, COL1A2, COL3A1, COL5A2, COL6A1, COL6A2, COL6A3, COL11A1, COL12A1 and ITGA4 may interact with each other. Functional enrichment indicated that collagen genes were enriched in ECM organization. Therefore, collagen genes may contribute to the progression of IVD degeneration. Additionally, ITGA4 may also be implicated in IVD degeneration via interaction with collagen genes.

In conclusion, the present study investigated the underlying mechanisms of IVD degeneration via bioinformatics analysis. A total 558 DEGs were screened in the degenerated nucleus pulposus cells. IL6, VEGFA, THBS1, ITGA4 and collagen genes may be involved in the progression of IVD degeneration. These results suggested that the manipulation of these genes and their products may have potential as a novel therapeutic strategy for the treatment of patients with IVD. However, these findings were obtained by bioinformatics prediction and require further confirmation via further experimental studies.

Acknowledgements

The present study was supported by the Shandong Province Pharmaceutical Technology Development Program (grant no. 2015-261), the Projects of Medical and Health Technology Development Program in Shandong Province, China (grant no. 2014WS0502), the Taishan Medical University Cultivate High-level Task Projects (grant no. 2014GCC02) and the Projects of Health Science and Technology Association in Shandong Province, China (grant no. 2016BJ0009).

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