Pleiotrophin, the angiogenic and mitogenic growth factor: levels in serum and synovial fluid in rheumatoid arthritis and osteoarthritis

Fadda, Samia H.; Bassyouni, Iman H.; Khalifa, Rania; Elsaid, Nora Y.

doi:10.1007/s00393-016-0234-8

Cited by 3 publications

(3 citation statements)

References 26 publications

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“…PTN is a heparin-binding growth factor, with potent mitogenic and angiogenic activity, and a crucial regulator of cancer metastasis, bone development, and bone repair (Liedert et al, 2014). Previous studies have reported that PTN levels are increased in the serum, chondrocytes, and subchondral bone of patients with OA, indicating that PTN might be a crucial factor during disease progression (Kaspiris et al, 2013;Fadda et al, 2018). PTN also promotes endothelial cell proliferation and migration and induces angiogenesis by interacting with two main receptors, PTPRZ and αVβ3 (Fukada et al, 2006;Wang, 2020).…”

Section: Discussionmentioning

confidence: 99%

Single-cell RNA sequencing analysis of human chondrocytes reveals cell–cell communication alterations mediated by interactive signaling pathways in osteoarthritis

Kang

Zhang²,

Wang

et al. 2023

Front. Cell Dev. Biol.

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Objective: Osteoarthritis (OA) is a common joint disorder characterized by degenerative articular cartilage, subchondral bone remodeling, and inflammation. Increasing evidence suggests that the substantial crosstalk between cartilage and synovium is closely related to Osteoarthritis development, but the events that cause this degeneration remain unknown. This study aimed to explore the alterations in intercellular communication involved in the pathogenesis of Osteoarthritis using bioinformatics analysis.Methods: Single-cell transcriptome sequencing (scRNA-seq) profiles derived from articular cartilage tissue of patients with Osteoarthritis were downloaded from a public database. Chondrocyte heterogeneity was assessed using computational analysis, and cell type identification and clustering analysis were performed using the “FindClusters” function in the Seurat package. Intercellular communication networks, including major signaling inputs and outputs for cells, were predicted, and analyzed using CellChat.Results: Seven molecularly defined chondrocytes clusters (homeostatic chondrocytes, hypertrophic chondrocyte (HTC), pre-HTC, regulatory chondrocytes, fibro-chondrocytes (FC), pre-FC, and reparative chondrocyte) with different compositions were identified in the damaged cartilage. Compared to those in the intact cartilage, the overall cell–cell communication frequency and communication strength were remarkably increased in the damaged cartilage. The cellular communication among chondrocyte subtypes mediated by signaling pathways, such as PTN, VISFATIN, SPP1, and TGF-β, was selectively altered in Osteoarthritis. Moreover, we verified that SPP1 pathway enrichment scores increased, but VISFATIN pathway enrichment scores decreased based on the bulk rna-seq datasets in Osteoarthritis.Conclusion: Our results revealed alterations in cell–cell communication among OA-related chondrocyte subtypes that were mediated by specific signaling pathways, which might be a crucial underlying mechanism associated with Osteoarthritis progression.

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Section: Discussionmentioning

confidence: 99%

Single-cell RNA sequencing analysis of human chondrocytes reveals cell–cell communication alterations mediated by interactive signaling pathways in osteoarthritis

Kang

Zhang²,

Wang

et al. 2023

Front. Cell Dev. Biol.

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“…MK and PTN were also shown to be associated with autoimmune diseases such as RA [10,11], MS [12,13], cancers [2,9], and the inhibition of HIV infection [14][15][16]. Therefore, assessing the production of MK and PTN by innate APCs in these situations and regulating their production by these cells is potentially important for the better management of these diseases.…”

Section: Discussionmentioning

confidence: 99%

“…MK and PTN were also shown to be associated with different diseases, including cancers [2,9] and autoimmune diseases such as rheumatoid arthritis (RA) [10,11], systemic lupus erythematosus (SLE) [3], and multiple sclerosis (MS) [12,13]. We and others have shown that MK and PTN binding to their receptors can inhibit HIV infection by interfering with the capacity of the virus to bind to target cells [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Differential Production of Midkine and Pleiotrophin by Innate APCs upon Stimulation through Nucleic Acid-Sensing TLRs

Said,

Al-Dughaishi,

Al-Hatmi

et al. 2023

Journal of Immunology Research

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Midkine (MK) and pleiotrophin (PTN) belong to the same family of cytokines. They have similar sequences and functions. Both have important roles in cellular proliferation, tumors, and diseases. They regulate and are expressed by some immune cells. We have recently demonstrated MK production by some human innate antigen-presenting cells (iAPCs), i.e., monocyte-derived dendritic cells (MDDCs) and macrophages stimulated through Toll-like receptor (TLR)-4, and plasmacytoid dendritic cells (pDCs) stimulated through TLR 7. While PTN production was only documented in tissue macrophages. TLRs 3, 7, 8, and 9 are nucleic acid sensing (NAS) TLRs that detect nucleic acids from cell damage and infection and induce iAPC responses. We investigated whether NAS TLRs can induce MK and PTN production by human iAPCs, namely monocytes, macrophages, MDDCs, myeloid dendritic cells (mDCs), and pDCs. Our results demonstrated for the first time that PTN is produced by all iAPCs upon TLR triggering ( p < 0.01 ). IAPCs produced more PTN than MK ( p < 0.01 ). NAS TLRs and iAPCs had differential abilities to induce the production of MK, which was induced in monocytes and pDCs by all NAS TLRs ( p < 0.05 ) and in MDDCs by TLRs 7/8 ( p < 0.05 ). TLR4 induced a stronger MK production than NAS TLRs ( p ≤ 0.05 ). Monocytes produced higher levels of PTN after differentiation to macrophages and MDDCs ( p < 0.05 ). The production of MK and PTN differs among iAPCs, with a higher production of PTN and a selective induction of MK production by NAS TLR. This highlights the potentially important role of iAPCs in angiogenesis, tumors, infections, and autoimmunity through the differential production of MK and PTN upon TLR triggering.

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Identification and validation of novel characteristic genes based on multi-tissue osteoarthritis

Zheng,

Ouyang,

Chen

et al. 2024

Preprint

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Background Osteoarthritis (OA) is characterized by synovial inflammation, articular cartilage degradation, and subchondral bone changes. Currently, there are no reliable biomarkers for the diagnosis and treatment of OA. Therefore, exploring OA biomarkers is crucial for its prevention, diagnosis, and treatment.Materials and Methods The GSE51588, GSE12021, GSE55457, GSE56409, GSE114007, GSE168505, GSE169077, GSE55235, GSE129147, and GSE48556 datasets of patients with OA and normal control samples were obtained from the GEO database. Differentially expressed genes (DEGs) in OA and normal controls were identified using R language. Protein-protein interaction (PPI) network and module analysis were performed to screen and filter key genes. Enrichment analyses were conducted to determine the biological functions and pathways of key DEGs and predict potential transcription factors. Machine learning models (XGBoost, LASSO regression, and SVM) were used to identify the best characteristic genes, and the intersection of hub genes was used as the final diagnostic genes. ROC analysis and nomogram were used to evaluate the diagnostic value of candidate genes. The expression levels of characteristic genes were validated in external GEO datasets containing cartilage, synovial membrane, and blood samples from patients. The expression levels of the key gene IRS2 in chondrocytes were further confirmed through in vitro experiments.Results Fifteen OA characteristic genes (IRS2, ADM, SIK1, PTN, CX3CR1, WNT5A, IL21R, APOD, CRLF1, FKBP5, PNMAL1, NPR3, RARRES1, ASPN, POSTN) were identified using three machine learning algorithms. Enrichment analysis indicated that abnormal expression of DEGs and hub genes may be mediated by extracellular matrix organization, extracellular structure organization, Relaxin signaling pathway, IL-17 signaling pathway, AGE-RAGE signaling pathway in diabetic complications, and PI3K-Akt signaling pathway, which are involved in OA occurrence. Four diagnostic genes (IRS2, WNT5A, PTN, POSTN) were highly correlated with OA. Validation data set analysis showed that IRS2 was down-regulated, while WNT5A, PTN, and POSTN were up-regulated in the experimental group compared to the normal group. qRT-PCR and WB results verified that the expression level of diagnostic gene IRS2 was consistent with bioinformatics analysis results.Conclusion This study integrates bioinformatics analysis and machine learning algorithms to identify and validate four promising biomarkers: IRS2, WNT5A, PTN, and POSTN. POSTN can be used as a biomarker for OA cartilage, and early diagnosis of PTN in OA deserves attention. WNT5A and IRS2 offer new diagnostic perspectives for OA.

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Pleiotrophin, the angiogenic and mitogenic growth factor: levels in serum and synovial fluid in rheumatoid arthritis and osteoarthritis

Cited by 3 publications

References 26 publications

Single-cell RNA sequencing analysis of human chondrocytes reveals cell–cell communication alterations mediated by interactive signaling pathways in osteoarthritis

Single-cell RNA sequencing analysis of human chondrocytes reveals cell–cell communication alterations mediated by interactive signaling pathways in osteoarthritis

Differential Production of Midkine and Pleiotrophin by Innate APCs upon Stimulation through Nucleic Acid-Sensing TLRs

Identification and validation of novel characteristic genes based on multi-tissue osteoarthritis

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