VEGFA, MYC, and JUN are abnormally elevated in the synovial tissue of patients with advanced osteoarthritis

doi:10.21203/rs.3.rs-4646415/v1

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VEGFA, MYC, and JUN are abnormally elevated in the synovial tissue of patients with advanced osteoarthritis

https://doi.org/10.21203/rs.3.rs-4646415/v1

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Osteoarthritis (OA), a disease that affects more than 500 million people worldwide, profoundly affects quality of life and the ability to work. The MAPK signaling pathway plays an essential role in various types of inflammatory diseases, including OA. To address the lack of studies focused on synovial cells in OA, we evaluated the expression patterns and roles of the MAPK signaling pathway components in OA synovial tissues using bioinformatics. The expression levels of JUN, MYC, and VEGFA were significantly higher in the synovial tissues of patients with OA than in control tissues. These loci were closely related to abnormal proliferation, inflammation, and angiogenesis in the synovial tissues of patients with OA. We speculate that Myc and VEGFA activate the p38-MAPK signaling pathway to further activate Jun, thereby promoting abnormal inflammation, proliferation, and angiogenesis in OA synovial tissue. Our study found that MYC and VEGFA expression have a combined effect on MAPK activation, and that the upregulation and activation of JUN is associated with the upregulation of MYC and/or VEGFA. Our findings may provide a new combination therapy for the clinical treatment of OA and offer new insight into the pathogenesis of OA.

Osteoarthritis

MAPK

MYC

VEGFA

JUN

synovial tissue

Osteoarthritis (OA) is the most common chronic degenerative joint disease. The main clinical symptoms include chronic pain, joint instability, stiffness, and radiographic joint space narrowing [1]. OA pathogenesis mainly includes different degrees of synovial inflammation, the degeneration of the knee ligaments and meniscuses, the degeneration and destruction of articular cartilage, the thickening of subchondral bone, secondary bone hyperplasia, joint capsule hypertrophy, and inflammation of the infrapatellar fat pad [1–5]. According to the latest Global Burden of Disease study, the global age-standardized prevalence of knee OA is 3.8%; among 291 diseases evaluated, knee OA was the 11th largest contributor to disability worldwide (when measured in years lived with disability) and ranked 38th in disability-adjusted life years. OA is the most common form of arthritis, affecting more than 500 million people worldwide (approximately 7% of the global population), with a particularly high incidence in older people (> 65 years) [6–8]. However, treatment methods and drugs for OA are very limited; except for joint replacement in patients with advanced disease, current therapies only alleviate and slow the progression of the disease, and there is currently no cure [9–12].

The molecular mechanism underlying the occurrence and development of OA is still unclear [13–16]. Under the influence of multiple risk factors, including age, obesity, trauma, and mechanical load, OA can activate synovial inflammation by various mechanisms, such as mitochondrial dysfunction, injury-related molecular patterns, cytokines, metabolites, and crystals in the synovium [17–25]. Synovial inflammation leads to further changes in the biological function of the synovium and damages the cartilage and bone tissue, eventually leading to the irreversible development of OA [26, 27]. Baseline synovitis detected by magnetic resonance imaging or ultrasound is associated with the radiographic progression of OA, as defined by worsening of the Kellgren and Lawrence (KL) Grade or joint space narrowing [8, 28–34]. The mitogen-activated protein kinase (MAPK) signaling pathway is found in all eukaryotes MAPK is a member of the intracellular serine-threonine protein kinase superfamily and is the central node in various signal transduction pathways [35, 36]. and it is plays an important role in a variety of inflammatory diseases.Jun belongs to the activator protein 1 (AP-1) family of proteins [48]. It plays a key role in regulating cell proliferation and apoptosis [49] and contributes to the regulation of a variety of other cellular processes including survival, differentiation, migration, and transformation [50]. It is also involved in the occurrence and development of OA, where it may drive chondrocyte hypertrophy and the differentiation of osteoprogenitor cells into osteoblasts, mediate the synthesis of cartilage-specific extracellular matrix components, and alter angiogenesis in bones [51]. In addition to Jun, c-Myc and vascular endothelial growth factor A (VEGFA) may have key roles in OA. C-Myc, a member of the Myc family, is a helix-loop-helix leucine zipper pleiotropic transcription factor involved in a variety of cellular processes including cell growth, apoptosis, metabolism, differentiation, and DNA repair [52]. Myc overexpression is associated with OA as well as small cell lung cancer, myeloid leukemia, breast cancer, and cervical cancer [53]. Silencing the c-Myc-encoding gene reduces the effects of IL-1β on cell cycle progression and apoptosis in the chondrocytes of rats with OA [54]. VEGFA is a member of the vascular endothelial growth factor family and has a wide range of functions including the stimulation of angiogenesis, monocyte chemotaxis, vascular permeability, and vasodilation [55; 56]; it is also an important mediator of osteogenesis [57]. High VEGFA expression is associated with OA, tumor angiogenesis, rheumatoid arthritis, psoriasis, atherosclerosis, brain edema, age-related macular degeneration, diabetic retinopathy, retinopathy of prematurity, and sepsis [55, 58]. VEGFs appear to be involved in specific pathological processes in OA, including cartilage degeneration, osteophyte formation, subchondral bone cysts and sclerosis, synovitis, and pain. In addition, extensive research has shown that the inhibition of VEGF signaling slows the progression of OA [59].

Therefore, Jun, c-Myc, and VEGFA may play a key role in OA. Nevertheless, up until the present moment, the majority of investigations have predominantly centered around osteocytes, with comparatively fewer studies directed towards the synovium. Concurrently, in an endeavor to establish greater clinical relevance and facilitate the expeditious evolution of osteoarthritis (OA) diagnostic and therapeutic methodologies, the present study procured specimens from 20 OA patients alongside 10 samples of normative human synovial tissue, obtained through knee arthroscopy, to undergo iterative validation processes. This undertaking entailed an assessment of the expression profiles and functional attributes pertaining to Jun, c-Myc, and VEGFA within human synovial tissues.

Dataset acquisition

A search against the Gene Expression Omnibus (GEO) database, created by the National Center for Biotechnology Information, was performed with "osteoarthritis" as the key word. The screening requirements were as follows: (1) the species was Homo sapiens; (2) a healthy control group and an OA group were included, each with sample sizes not less than three; (3) the OA group was not treated with drugs or other therapies; and (4) complete, original gene expression data files and complete chip annotation data were available.

Principal component analysis

R Studio was used to preprocess the data. After the conversion of probes and gene names, the average value for a gene corresponding to multiple probes was obtained. After normalizing the dataset using the “limma” package in R, a principal component analysis was performed using the "FactoMineR" and "factoextra" packages.

Differential expression analysis

R Studio was used to compare expression levels between OA synovial tissues and normal synovial tissues to obtain differentially expressed genes (DEGs). The original data set was preprocessed using the “limma” package in R. A fold change (FC) value ≥ 2, log₂(FC) > 1, and P < 0.05 were used as screening criteria to filter out DEGs in OA synovial tissues.

Intersection analysis

An intersection analysis was performed to identify DEGs obtained from the three gene expression datasets (i.e., DEGs shared between the healthy control group and the OA group). The results were displayed in an UpSet graph.

PPI network construction and visualization

The common DEGs in the OA synovial tissues were imported into the STRING online database to study protein–protein interactions (PPIs). The species was set to Homo sapiens, with default conditions used for other parameters. Nodes with no connections to other proteins were removed. The results were imported into Cytoscape for visualization, and the number of proteins interacting with each protein was calculated and expressed as a degree value.

Biomarker analysis

Using clinical information for samples and the expression levels of indicators, the key targets obtained by the PPI network analysis were analyzed for biomarker identification. Receiver operating characteristic (ROC) curves for the key genes were drawn using the R package “pROC,” and the areas under the curve (AUC) were calculated. AUC > 0.50 indicated that genes had diagnostic value for OA, with values closer to 1.0 indicating a higher diagnostic value.

Gene ontology functional enrichment analysis

Common DEGs in OA synovial tissues were imported into the DAVID database for a gene ontology (GO) enrichment analysis. The species was set as Homo sapiens, with P < 0.05 as the screening criterion. The results were divided into three parts: cellular component (CC), molecular function (MF), and biological process (BP).

KEGG pathway enrichment analysis

The common DEGs in the OA synovial tissues were imported into the DAVID database for a Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The species was set as Homo sapiens, and P < 0.05 was used as the screening criterion to identify related pathways.

Specimen collection

We obtained synovial tissue from 20 patients (nine male and 11 female) with OA who underwent knee arthroplasty at the Joint and Microsurgical Surgery Department of the First Affiliated Hospital of Anhui Medical University. Of the patients, four were at KL Grade 2, six were at KL Grade 3, and 10 were at KL Grade 4; none of the cases had used drug intervention before surgery. Meanwhile, the synovial tissues of 10 healthy people (six men and four women) were obtained from knee arthroscopy of sprain patients in the Arthroscopy Department of the First Affiliated Hospital of Anhui Medical University. No drug intervention was used before arthroscopy. This work was approved by the Human Research Ethics Committee of Anhui Medical University (Ethics number: S20210085, date: 2021/03/31).

Quantitative real-time PCR analysis

The total RNA was extracted using TRIzol reagent (Thermo Fisher, Waltham, MA, USA) according to the manufacturer’s protocol. Total RNA (500 ng) was reverse-transcribed into cDNA using a PrimeScript RT Reagent Kit (Takara, Kusatsu, Japan). Quantitative real-time PCR (qRT-PCR) was performed using SYBR Green PCR Mix (Thermo Fisher). Primer sequences are listed in Table 1. ACTB served as an internal reference, and the relative expression levels of messenger RNAs (mRNAs) were quantified using the 2^−ΔΔCt method.

Table 1

Primers used for RT-qPCR
Gene symbol	Primer	Sequence
JUN	Forward	TCCAAGTGCCGAAAAAGGAA
JUN	Reverse	CGAGTTCTGAGCTTTCAAGGT
MYC	Forward	GTCAAGAGGCGAACACACAAC
MYC	Reverse	TTGGACGGACAGGATGTATGC
VEGFA	Forward	AGGGCAGAATCATCACGAAGT
VEGFA	Reverse	AGGGTCTCGATTGGATGGCA
ACTB	Forward	CATGTACGTTGCTATCCAGGC
ACTB	Reverse	CTCCTTAATGTCACGCACGAT

Western blot

Tissues were lysed on ice using NP40 buffer containing a protease and phosphatase inhibitor cocktail (Beyotime Biotechnology, China) for 30 min. The protein concentration was determined using the BCA protein assay kit (Beyotime Biotechnology). Total protein was further separated by SDS-PAGE before transferring to polyvinylidene difluoride membranes (Merck, Rahway, NJ, USA). The membranes were blocked with 5% non-fat milk at room temperature for 1 h, and then incubated with primary antibodies (C-MYC, VEGFA, JUN, p38-MAPK, β-actin; Cell Signaling Technology) overnight at 4°C. After five washes, the membranes were incubated with HRP-conjugated secondary antibodies at room temperature for 1 h. Protein bands were visualized using ECL solution (NCM Biotech, Suzhou, China) and detected with an automatic chemiluminescence imaging analysis system (Bio-Rad Laboratories, Hercules, CA, USA). The intensity of each band was quantified using ImageJ software (National Institute of Mental Health, Bethesda, MD, USA).

Hematoxylin-eosin staining and immunohistochemistry

Human OA synovium or normal synovium were fixed with 4% paraformaldehyde overnight and embedded in paraffin before sectioning into 5-µm slices. The sections were then deparaffinized with xylene before being rehydrated in water using an ethanol gradient. After staining with hematoxylin and eosin, they were incubated with primary antibodies for over 4 h at 4°C. Finally, the sections were washed and incubated with appropriate secondary antibody for 1 h. Antigen-positive cells were visualized using the DAB Substrate kit (Beyotime Biotechnology).

Statistical methods

Comparisons between multiple groups were performed using one-way analysis of variance (ANOVA) in GraphPad Prism 7 (GraphPad Software, La Jolla, CA, USA). The T test was used to compare the two sets of data. Data were presented as means ± SD. P-values < 0.05 (two-sided) were considered significant (*P < 0.05, **P < 0.01, ***P < 0.001).

Ethics approval

This study was approved by the Ethics Committee of Anhui Medical University. In accordance with the principles of the Declaration of Helsinki, all patients provided informed written consent prior to participation.

Raw data processing

In a search of the GEO database, three datasets met the requirements for inclusion in the analyses. Information on the datasets is shown in Table 2.

Table 2

Dataset Information
data set	platform	sample source	normal control	OA
GSE55457	GPL96	synovial tissue	10	10
GSE55235	GPL96	synovial tissue	10	10
GSE12021	GPL96	synovial tissue	9	10

Principal component analysis and Differentially expressed genes

Illustrated in Fig. 1 is the application of principal component analysis to three distinct datasets, namely GSE55457 (depicted in Fig. 1A), GSE55235 (depicted in Fig. 1B), and GSE12021 (depicted in Fig. 1C). In each of these datasets, the assessment of intra-group distances pertaining to samples from the normal control and osteoarthritis (OA) groups revealed minimal dispersion, accompanied by distinct demarcations between the said groups. This observation is suggestive of substantial dissimilarity between the normal control and OA cohorts. As such, these three datasets hold promise for subsequent investigative endeavors.

DEGs identified in the GSE55457 (Fig. 2A), GSE55235 (Fig. 2B), and GSE12021 (Fig. 2C) datasets are shown in volcano plots, where blue indicates genes that are downregulated compared with levels in the healthy control group (Log2FC < − 1, P < 0.05) and red indicates genes that are upregulated compared with levels in the healthy control group (Log2FC > 1, P < 0.05). There were 410 downregulated genes and 218 upregulated genes in GSE55457, 395 downregulated genes and 662 upregulated genes in GSE55235, and 403 downregulated genes and 262 upregulated genes in GSE12021. The results of an intersection analysis are shown in Fig. 2D. There were 64 upregulated genes and 84 downregulated genes shared among all three datasets.

PPI network analysis

Exploration of the interdependent relationships among differentially expressed genes (DEGs), which exhibit overlaps, was facilitated through queries within the String database. Subsequently, a protein-protein interaction (PPI) network was meticulously constructed and visually represented employing Cytoscape software. Within this network framework, the quantum of associations that individual proteins engendered with their counterparts was quantified as their Degree values. Notably, these Degree values were color-coded, transitioning from a gradient ranging from red to gray, symbolizing descending order of magnitude. Evidently, the chromatic gradient manifested red hues for higher Degree values. The outcome of this network analysis prominently highlighted escalated Degree values for pertinent proteins such as MYC, IL6, VEGFA, JUN, ATF3, and PTGS2 (Fig. 3). This augmented numerical magnitude strongly implies a heightened propensity for reciprocal interactions among these aforementioned proteins.

Core protein expression analysis and Biomarker analysis

Heatmaps depicting the expression profiles of pivotal genes, namely MYC, IL6, VEGFA, JUN, ATF3, and PTGS2, within the datasets GSE55457 (depicted in Fig. 4A), GSE55235 (depicted in Fig. 4B), and GSE12021 (depicted in Fig. 4C), were generated. These heatmaps effectively portray the gene expression dynamics across distinct datasets, whereby the spectrum of expression intensities ranging from minimal to maximal is graphically represented through a color gradient spanning from blue to red. A discernible trend is evident from these visualizations, illustrating that the expression levels of IL6, PTGS2, and VEGFA in the context of osteoarthritis (OA) surpass those within the normal control group. Conversely, for the genes JUN, MYC, and ATF3, a marginally reduced expression magnitude is observed within the normal control group as compared to the OA cohort.

Indicators with AUC values > 0.5 for the three datasets were as follows: GSEA55457 (Fig. 5A), MYC (AUC = 0.88), IL6 (AUC = 0.79), VEGFA (AUC = 0.89), JUN (AUC = 0.97), ATF3 (AUC = 0.89), and PTGS2 (AUC = 0.76); GSEA55235 (Fig. 5B), MYC (AUC = 1), IL6 (AUC = 0.94), VEGFA (AUC = 0.99), JUN (AUC = 1), ATF3 (AUC = 1), and PTGS2 (AUC = 0.98); GSEA12021 (Fig. 5C), MYC (AUC = 0.867), IL6 (AUC = 0.811), VEGFA (AUC = 0.889), JUN (AUC = 0.967), ATF3 (AUC = 0.878), and PTGS2 (AUC = 0.967).

Functional enrichment analysis

The results of the GO enrichment analysis are shown in Fig. 6. In the BP category, DEGs were enriched for various terms, including positive regulation of transcription from RNA polymerase II promoter, cytokine-mediated signaling pathway, positive regulation of smooth muscle cell proliferation, fat cell differentiation, and circadian rhythm. Enrichment in the CC category included chromatin, RNA polymerase II transcription factor complex, extracellular space, nucleus, and transcription factor complex. In the MF category, enriched terms included transcriptional activator activity, RNA polymerase II transcription regulatory region sequence-specific binding, transcription factor activity, sequence-specific DNA binding, sequence-specific double-stranded DNA binding, cytokine activity, and protein binding.

Pathway enrichment analysis

The results of the KEGG pathway enrichment analysis are shown in Fig. 7. The DEGs were involved in various pathways including the MAPK signaling pathway, TNF signaling pathway, osteoclast differentiation, rheumatoid arthritis, Kaposi sarcoma-associated herpesvirus infection, IL-17 signaling pathway, breast cancer, NF-κB signaling pathway, colorectal cancer, Epstein-Barr virus infection, AGE-RAGE signaling pathway in diabetic complications, human T-cell leukemia virus 1 infection, C-type lectin receptor signaling pathway, legionellosis, and HIF-1 signaling pathway.

Analysis of DEGs in pathways

Gene information on the MAPK signaling pathway was collected from the GSEA database and KEGG database, and the intersection of genes in the MAPK pathway that had been identified in the three datasets was obtained (Fig. 8A). A total of 12 DEGs in the pathway were obtained and analyzed through a PPI network (Fig. 8B). We found three important targets: JUN, MYC, and VEGFA. These targets play important roles in the pathological process of OA by regulating the MAPK signaling pathway.

Verification of the differential expression of JUN, MYC, and VEGFA

Using 20 OA synovial tissues and 10 normal synovial tissues, the differential expression of three important targets of JUN, MYC, and VEGFA was validated. The results obtained by qRT-PCR were consistent with the results obtained by bioinformatics analysis; the mRNA expression levels of JUN, MYC, and VEGFA in the synovial tissue of OA patients were significantly higher than those of normal synovial tissue (Fig. 9A–C). Using five OA synovial tissues and five normal synovial tissues, western blot and immunohistochemical results showed that the protein expression levels of JUN, MYC, and VEGFA in the synovial tissue of OA patients were significantly higher than those in normal synovial tissue (Fig. 10).

Verification of the differential expression of p38-MAPK

Using five OA synovial tissues and five normal synovial tissues, western blot and immunohistochemical results showed that the expression levels of p38-MAPK in the synovial tissue of OA patients were significantly higher than those in normal synovial tissue (Fig. 11).

As a degenerative disease, OA is associated with a poor quality of life and can eventually lead to a loss of the ability to work [60–62]. However, its pathogenesis and risk factors are not clear. Most research has focused on chondrocytes, osteoblasts, and osteoclasts. The synovium is relatively less well-studied, despite its importance in the occurrence and development of OA. Some studies have shown that the synovial tissues of patients with OA have a higher proliferative capacity than those of healthy individuals, in addition to greater inflammatory changes and obvious synovitis [16, 63, 64]. One study revealed that synovitis mediates the loss of cartilage and worsening pain, every 0.1 mm of cartilage lost over 24 months corresponded to a Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale score of 0.32 (95% CI 0.21–0.44) [65]. Therefore, the pathological changes in synovial tissue and synovial cells may have important implications for cartilage and OA.

We analyzed 30 patients with OA and 29 normal controls based on three datasets in GEO and identified 662 upregulated genes and 410 downregulated genes in OA. After obtaining the intersection of the three sets, we detected 64 upregulated genes and 84 downregulated genes in OA. The six proteins encoded by MYC, IL6, VEGFA, JUN, ATF3, and PTGS2 had more interactions based on a PPI network analysis and were closely associated with OA based on a ROC curve analysis. These are candidate biomarkers and may have important roles in OA. GO and KEGG pathway enrichment analyses revealed that the DEGs were involved in the MAPK signaling pathway. Based on the intersection between the MAPK signaling pathway and our DEG set, we obtained 12 indicators related to MAPK with significant expression differences in OA. Combined with the six key indicators of OA identified in the DEG analysis, three important targets were obtained, namely JUN, MYC, and VEGFA. our investigation has substantiated the pivotal involvements of Jun, c-Myc, and VEGFA in the context of Osteoarthritis (OA), employing rigorous bioinformatics methodologies. This alignment with antecedent research outcomes reinforces the robustness of our findings. Nonetheless, it is noteworthy that prior inquiries have predominantly directed their focus towards chondrocytes or immunologically relevant cell populations, with scant emphasis on analyses pertinent to synovial tissue. In stark contrast, our study uniquely concentrates on the disparate gene expression profiles inherent to synovial tissue, thereby yielding a more authentic portrayal of synovial tissue dynamics. Importantly, the delineation of our investigation is confined to the domain of gene expression profiles specific to synovial tissue, a strategic choice that renders a more accurate depiction of the nuanced alterations within the synovial microenvironment. Concurrently, it's pertinent to acknowledge that the majority of antecedent investigations have been predominantly confined to the realm of bioinformatic outputs, often lacking the pivotal facet of experimental corroboration. In a concerted endeavor to advance the clinical dimensions of Osteoarthritis diagnosis and therapeutic interventions, a cohort of 30 human synovial tissue samples was meticulously procured for rigorous experimental validation. Through the judicious application of a multi-modal approach encompassing Quantitative Polymerase Chain Reaction (QPCR), Western blotting, and immunohistochemistry, we meticulously scrutinized the variations in Jun, c-Myc, and VEGFA expression profiles at both the RNA and protein levels. This comprehensive experimental undertaking effectively addresses the extant dearth in empirical validation, particularly within the context of human samples. Moreover, our empirical findings serve to establish a more robust foundation, thus potentiating enhanced precision in the clinical diagnosis and therapeutic stratagems targeting Osteoarthritis.

In pursuit of a more comprehensive comprehension of the intricate interplay among multiple differentially expressed genes, an exhaustive investigation was conducted. Through an exhaustive analysis of pertinent literature, it became evident that Jun, c-Myc, and VEGFA exhibit pronounced associations with the Mitogen-Activated Protein Kinase (MAPK) pathway. Significantly, the MAPK signaling cascade is intrinsically implicated in the progression of Osteoarthritis (OA). In its basal state, the MAPK pathway comprises three distinct signaling cascades, namely, c-Jun N-terminal kinase (JNK), p38, and extracellular signal-regulated kinase (ERK) pathways [37]. Activation of the MAPK pathway elicits the transcriptional upregulation of proinflammatory cytokines including tumor necrosis factor (TNF), interleukins (IL)-1, IL-6, alongside select chemokines. Furthermore, this activation prompts the expression of matrix metalloproteinases (MMPs) such as MMP-1, MMP-13, and cyclooxygenase-2 [38–40]. Evidently, MAPK activation significantly contributes to cartilage collagen degradation, chondrocyte apoptosis, and inflammatory processes characteristic of OA [41–43]. Perturbation of the MAPK signaling pathway engenders aberrant synovial tissue proliferation, inflammation, and the development of heterogeneous pannus across the synovium. It is noteworthy that p38, an integral component of the MAPK pathway, is implicated in the pathogenesis of OA. Constituting a pivotal link in transmitting extracellular cues to cellular entities, the p38-MAPK pathway orchestrates a cascade involving diverse kinases. Of particular import are MAPKK3 and MAPKK6, major facilitators of p38-MAPK activation [66]. Recent inquiries have highlighted the potential influence of miR-24 on OA cells through modulation of the MAPK pathway via its interaction with c-Myc. This interaction contributes to the modulation of interleukin-1β (IL-1β) production, a process facilitated by the p38-MAPK pathway [67]. Additionally, compelling evidence suggests that the absence of PCAT-1 in head and neck squamous cell carcinoma cells confers growth inhibition and apoptosis induction via the inhibition of c-Myc and concurrent activation of Ask1-mediated p38-MAPK signaling [68]. Further augmenting this narrative, VEGFA, a prominent pro-angiogenic factor governing endothelial cell proliferation, differentiation, and migration, assumes pivotal significance. Operating as a dimeric glycoprotein, VEGFA spurs angiogenesis through its engagement with the tyrosine kinase receptor KDR (VEGFR2), thereby inciting the activation of the p38-MAPK signaling cascade [70]. MIR452 emerges as a noteworthy participant, adept at impeding the KRAS-BRAF-MAPK signaling axis by downregulating VEGFA expression and attenuating VEGFA binding to VEGFR2, thereby curtailing angiogenesis [71]. Notably, the VEGFA/VEGFR2 interplay substantiates the migration of human Dental Pulp Stem Cells (hDPSCs) through the p38-MAPK signaling route [72]. In a distinct avenue of exploration, FGF21 emerges as an agent capable of inhibiting Peripheral Nervous System (PNS) myelination via p38-MAPK-induced activation of c-Jun. This inhibition is substantiated by discernible reductions in c-Jun expression and phosphorylation upon specific inhibition of the p38-MAPK pathway through SB203580 [73, 74]. Collectively, it is conjectured that p38-MAPK wields considerable influence in the context of the disparate expression patterns exhibited by Jun, c-Myc, and VEGFA in the context of OA. To fortify this notion, human synovial tissues were employed for an exhaustive analysis of p38-MAPK protein expression levels. The combined utilization of Western Blot analysis and immunohistochemistry discerned a noteworthy increase of approximately 1.5-fold in p38-MAPK expression within synovial tissues obtained from OA-afflicted patients, in comparison to their normative counterparts. While this substantiated the differentially expressed p38-MAPK in the OA context, no commensurate shifts in the expression profiles of Jun, c-Myc, and VEGFA were observed subsequent to p38-MAPK intervention, thereby precluding a conclusive determination of their interdependent regulatory associations. This critical void forms the crux of our impending research investigations.

Our study found that the gene and protein expressions of MYC, VEGFA and JUN in the knee synovial tissue of OA group were significantly higher than those of control group. In addition, abnormal expression of JUN, Myc, and VEGFA may be associated with the p38-MAPK signaling pathway, ultimately leading to continued proliferation, inflammation, and angiogenesis of the OA synovium. Therefore, the combination therapy targeting the above three genes may bring certain progress for the clinical treatment of OA.

Declaration of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Author Contributions

SCL and RJJ conceived and designed the study. ZZY, ZWJ and CMN drafted, edited, and revised the manuscript. All authors approved the final version of the manuscript.

Ethics approval

The study was conducted in accordance with the Declara-tion of Helsinki, and approved by the Ethics Committee of Anhui Medical University (S20210085 and date of approval 2021/03/31).Informed Consent Statement: Informed consent was obtained from all subjects involved in the study prior to participation.

Funding

This work was supported by the National Natural Science Foundation of China (grant number: 81472088)

Data Statement

The data that support the findings of this study are available in ncbi at /www.ncbi.nlm.nih.gov/geo, reference number GSE55457，GSE55235，GSE12021. These data were derived from the following resources available in the public domain: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE55457, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE55235, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12021

Acknowledgments

None.

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VEGFA, MYC, and JUN are abnormally elevated in the synovial tissue of patients with advanced osteoarthritis

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Version 1

Abstract

Figures

Introduction

Materials and Methods

Dataset acquisition

Principal component analysis

Differential expression analysis

Intersection analysis

PPI network construction and visualization

Biomarker analysis

Gene ontology functional enrichment analysis

KEGG pathway enrichment analysis

Specimen collection

Quantitative real-time PCR analysis

Western blot

Hematoxylin-eosin staining and immunohistochemistry

Statistical methods

Ethics approval

Results

Raw data processing

Principal component analysis and Differentially expressed genes

PPI network analysis

Core protein expression analysis and Biomarker analysis

Functional enrichment analysis

Pathway enrichment analysis

Analysis of DEGs in pathways

Verification of the differential expression of p38-MAPK

Discussion

Conclusions

Declarations

References

Additional Declarations

Status:

Version 1