Graphical abstract
Keywords
Categories
How to Cite
Abstract
Background: It is reported that matrisome exerts a significant function in the pathogenesis of knee osteoarthritis (KOA). Thus, this study was conducted to screen the matrisome-associated diagnostic genes for KOA.
Results: A total of 158 matrisome-related genes in KOA were obtained, then 5 diagnostic genes were screened, namely collagen type 1 alpha 1 (COL1A1), high temperature requirement factor A1 (HTRA1), SPARC (osteonectin), cwcv and kazal-like domains proteoglycan 1 (SPOCK1), sulfatase 1 (SULF1) and extracellular matrix protein 1 (ECM1). These 5 diagnostic genes were both obviously overexpressed in KOA groups relative to those in the healthy group, and both strongly associated with most immune cells, such as macrophage, eosinophil, and activated B cell. The targeted drugs for the 5 diagnostic genes contained 9-Octadecenamide, Diacerein, and Rifaximin. The mRNA and protein expression levels of the 5 diagnostic genes were consistent with the bioinformatics analysis results. Also, the viability of monosodium iodoacetate (MIA)-treated SW1353 cells was significantly decreased after upregulation of ECM1, while apoptosis showed the opposite trend. Moreover, MIA remarkably increased the phosphorylation levels of PI3K and Akt in SW1353 cells.
Conclusions: Five matrisome-associated diagnostic genes were identified with better diagnostic values, including COL1A1, HTRA1, SPOCK1, SULF1 and ECM1. ECM1 exacerbates the progression of KOA, and PI3K-Akt signaling pathway is involved in the progression of KOA. The drugs, containing 9-Octadecenamide, Diacerein, and Rifaximin, etc., might be used for KOA treatment by targeting COL1A1, HTRA1, SPOCK1, SULF1 and ECM1.
References
Giorgino R, Albano D, Fusco S, et al. Knee osteoarthritis: Epidemiology, pathogenesis, and mesenchymal stem cells: What else is new? An update. International Journal of Molecular Sciences 2023;24(7):6405. https://doi.org/10.3390/ijms24076405 PMid: 37047377
Zhu S, Qu W, He C. Evaluation and management of knee osteoarthritis. Journal of Evidence-Based Medicine 2024;17(3):675-687. https://doi.org/10.1111/jebm.12627 PMid: 38963824
Sharma L. Osteoarthritis of the knee. The New England Journal of Medicine 2021;384(1):51-59. https://doi.org/10.1056/NEJMcp1903768 PMid: 33406330
Qiao H, Hao X, Wang G. Effects of mind-body exercise on knee osteoarthritis: a systematic review and meta-analysis of randomized controlled trials. BMC Musculoskeletal Disorders 2024;25(1):229. https://doi.org/10.1186/s12891-024-07278-4 PMid: 38515124
Gelber AC. Knee osteoarthritis. Annals of Internal Medicine 2024;177(9):ITC129-ITC144. https://doi.org/10.7326/annals-24-01249 PMid: 39250809
Li H, Kong W, Liang Y, et al. Burden of osteoarthritis in China, 1990-2019: Findings from the Global Burden of Disease Study 2019. Clinical Rheumatology 2024;43(3):1189-1197. https://doi.org/10.1007/s10067-024-06885-9 PMid: 38289570
Jang S, Lee K, Ju JH. Recent updates of diagnosis, pathophysiology, and treatment on osteoarthritis of the knee. International Journal of Molecular Sciences 2021;22(5):2619. https://doi.org/10.3390/ijms22052619 PMid: 33807695
Tore NG, Oskay D, Haznedaroglu S. The quality of physiotherapy and rehabilitation program and the effect of telerehabilitation on patients with knee osteoarthritis. Clinical Rheumatology 2023;42(3):903-915.https://doi.org/10.1007/s10067-022-06417-3 PMid: 36279075
Deng M, Hu Y, Zhang Z, et al. Unicondylar knee replacement versus total knee replacement for the treatment of medial knee osteoarthritis: a systematic review and meta-analysis. Archives of Orthopaedic and Trauma Surgery 2021;141(8):1361-1372. https://doi.org/10.1007/s00402-021-03790-7 PMid: 33512583
Theocharis AD, Skandalis SS, Gialeli C, et al. Extracellular matrix structure. Advanced Drug Delivery Reviews 2016;97:4-27. https://doi.org/10.1016/j.addr.2015.11.001 PMid: 26562801
Famá EAB, Pinhal MAS. Extracellular matrix components in preeclampsia. Clinica Chimica Acta 2025;568:120132. https://doi.org/10.1016/j.cca.2025.120132 PMid: 39798685
Li SH, Wu QF. MicroRNAs target on cartilage extracellular matrix degradation of knee osteoarthritis. European Review for Medical and Pharmacological Sciences 2021;25(3):1185-1197. https://doi.org/10.26355/eurrev_202102_24821 PMid: 33629288
Arteel GE, Naba A. The liver matrisome - looking beyond collagens. JHEP Reports 2020;2(4):100115. https://doi.org/10.1016/j.jhepr.2020.100115 PMid: 32637906
Downs M, Sethi MK, Raghunathan R, et al. Matrisome changes in Parkinson's disease. Analytical and Bioanalytical Chemistry 2022;414(9):3005-3015. https://doi.org/10.1007/s00216-022-03929-4 PMid: 35112150
Wise CA, Sepich D, Ushiki A, et al. The cartilage matrisome in adolescent idiopathic scoliosis. Bone Research 2020;8:13. https://doi.org/10.1038/s41413-020-0089-0 PMid: 32195011
Rafaeva M, Erler JT. Framing cancer progression: Influence of the organ- and tumour-specific matrisome. The FEBS Journal 2020;287(8):1454-1477. https://doi.org/10.1111/febs.15223 PMid: 31972068
Sung JY, Cheong JH. The matrisome is associated with metabolic reprograming in stem-like phenotypes of gastric cancer. Cancers 2022;14(6):1438. https://doi.org/10.3390/cancers14061438 PMid: 35326589
Miosge N, Hartmann M, Maelicke C, et al. Expression of collagen type I and type II in consecutive stages of human osteoarthritis. Histochemistry and Cell Biology 2004;122(3):229-236. https://doi.org/10.1007/s00418-004-0697-6 PMid: 15316793
Xia B, Di C, Zhang J, et al. Osteoarthritis pathogenesis: A review of molecular mechanisms. Calcified Tissue International 2014;95(6):495-505. https://doi.org/10.1007/s00223-014-9917-9 PMid: 25311420
Meszaros E, Malemud CJ. Prospects for treating osteoarthritis: enzyme-protein interactions regulating matrix metalloproteinase activity. Therapeutic Advances in Chronic Disease 2012;3(5):219-229. https://doi.org/10.1177/2040622312454157 PMid: 23342237
Chen W, Liu W, Jiang T, et al. Tongbi Huoluo Decoction alleviates cartilage degeneration in knee osteoarthritis by inhibiting degradation of extracellular matrix. Chinese Medicine 2023;18(1):91. https://doi.org/10.1186/s13020-023-00802-z PMid: 37507774
Han W, Chen X, Wang X, et al. TLR-4, TLR-5 and IRF4 are diagnostic markers of knee osteoarthritis in the middle-aged and elderly patients and related to disease activity and inflammatory factors. Experimental and Therapeutic Medicine 2020;20(2):1291-1298. https://doi.org/10.3892/etm.2020.8825 PMid: 32765669
Hassan MA, Hameed AS, Hameed EK. Serum fibulin-3 as a diagnostic and prognostic biomarker in patients with knee osteoarthritis. Irish Journal of Medical Science 2024;193(6):2923-2927. https://doi.org/10.1007/s11845-024-03780-9 PMid: 39127857
Leek JT, Johnson WE, Parker HS, et al. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics 2012;28(6):882-883. https://doi.org/10.1093/bioinformatics/bts034 PMid: 22257669
Ritchie ME, Phipson B, Wu D, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research 2015;43(7):e47. https://doi.org/10.1093/nar/gkv007 PMid: 25605792
Hu Y, Shao X, Xing L, et al. Single-cell sequencing of lung macrophages and monocytes reveals novel therapeutic targets in COPD. Cells 2023;12(24):2771. https://doi.org/10.3390/cells12242771 PMid: 38132091
Li Z, Song G, Guo D, et al. Identification of GINS2 prognostic potential and involvement in immune cell infiltration in hepatocellular carcinoma. Journal of Cancer 2022;13(2):610-622. https://doi.org/10.7150/jca.53841 PMid: 35069907
Langfelder P, Horvath S. WGCNA: An R package for weighted correlation network analysis. BMC Bioinformatics 2008;9:559. https://doi.org/10.1186/1471-2105-9-559 PMid: 19114008
Tian Z, He W, Tang J, et al. Identification of important modules and biomarkers in breast cancer based on WGCNA. OncoTargets and Therapy 2020;13:6805-6817. https://doi.org/10.2147/ott.S258439 PMid: 32764968
Chang YT, Hong ZJ, Tsai HH, et al. Hub metastatic gene signature and risk score of breast cancer patients with small tumor sizes using WGCNA. Breast Cancer 2024;31(6):1114-1129. https://doi.org/10.1007/s12282-024-01627-w PMid: 39190284
Naba A, Clauser KR, Hoersch S, et al. The matrisome: In silico definition and in vivo characterization by proteomics of normal and tumor extracellular matrices. Molecular & Cellular Proteomics 2012;11(4):M111.014647. https://doi.org/10.1074/mcp.M111.014647 PMid: 22159717
Yu G, Wang LG, Han Y, et al. clusterProfiler: An R Package for Comparing Biological Themes Among Gene Clusters. OMICS: A Journal of Integrative Biology 2012;16(5):284-287. https://doi.org/10.1089/omi.2011.0118 PMid: 22455463
Mering C, Huynen M, Jaeggi D, et al. CJNAR. STRING: a database of predicted functional associations between proteins. Nucleic Acids Research 2003;31(1):258-261. https://doi.org/10.1093/nar/gkg034 PMid: 12519996
Su Y, Zhang Y. Identification of biological processes and genes for gestational diabetes mellitus. Archives of Gynecology and Obstetrics 2015;292(3):635-640. https://doi.org/10.1007/s00404-015-3649-6 PMid: 25736406
Shannon P, Markiel A, Ozier O, et al. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research 2003;13(11):2498-2504. https://doi.org/10.1101/gr.1239303 PMid: 14597658
Kang J, Choi YJ, Kim IK, et al. LASSO-based machine learning algorithm for prediction of lymph node metastasis in T1 colorectal cancer. Cancer Research and Treatment 2021;53(3):773-783. https://doi.org/10.4143/crt.2020.974 PMid: 33421980
Naveed, S. Prediction of breast cancer through random forest. Current Medical Imaging 2023;19(10):1144-1155. https://doi.org/10.2174/1573405618666220930150625 PMid: 36200251
Sanz H, Valim C, Vegas E, et al. SVM-RFE: selection and visualization of the most relevant features through non-linear kernels. BMC Bioinformatics 2018;19(1):432. https://doi.org/10.1186/s12859-018-2451-4 PMid: 30453885
Jiang B, Sun P, Tang J, et al. GLMNet: Graph Learning-Matching Networks for Feature Matching. Pattern Recognition 2022;121:108167. https://doi.org/10.1016/j.patcog.2021.108167
Liaw A, Wiener M. Classification and Regression by randomForest. The R Journal 2002;2-3:18-22.
Functions TM, Wien TU. Package 'e1071'. 2012.
Robin X, Turck N, Hainard A, et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 2011;12:77. https://doi.org/10.1186/1471-2105-12-77 PMid: 21414208
Kattan MW, Marasco J. What is a real nomogram? Seminars in Oncology 2010;37(1):23-26. https://doi.org/10.1053/j.seminoncol.2009.12.003 PMid: 20172360
Tibshirani R. The LASSO method for variable selection in the Cox Model. Statistics in Medicine 1997;16(4):385-395. https://doi.org/10.1002/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3 PMid: 9044528
Zheng Y, Wang J, Ling Z, et al. A diagnostic model for sepsis-induced acute lung injury using a consensus machine learning approach and its therapeutic implications. Journal of Translational Medicine 2023;21(1):620. https://doi.org/10.1186/s12967-023-04499-4 PMid: 37700323
Yoo M, Shin J, Kim J, et al. DSigDB: drug signatures database for gene set analysis. Bioinformatics 2015;31(18):3069-3071. https://doi.org/10.1093/bioinformatics/btv313 PMid: 25990557
Xiao B, Liu L, Li A, et al. Identification and verification of immune-related gene prognostic signature based on ssGSEA for osteosarcoma. Frontiers in Oncology 2020;10:607622. https://doi.org/10.3389/fonc.2020.607622 PMid: 33384961
Qiu C, Shi W, Wu H, et al. Identification of molecular subtypes and a prognostic signature based on inflammation-related genes in colon adenocarcinoma. Frontiers in Immunology 2021;12:769685. https://doi.org/10.3389/fimmu.2021.769685 PMid: 350030
Rockel JS, Sharma D, Espin-Garcia O, et al. Deep learning-based clustering for endotyping and post-arthroplasty response classification using knee osteoarthritis multiomic data. Annals of the Rheumatic Diseases 2025;84(5):844-855. https://doi.org/10.1016/j.ard.2025.01.012 PMid: 39948003
Farrar JT, Young JP, LaMoreaux L, et al. Clinical importance of changes in chronic pain intensity measured on an 11-point numerical pain rating scale. Pain 2001;94(2):149-158. https://doi.org/10.1016/s0304-3959(01)00349-9 PMid: 11690728
Chiu PR, Hu YC, Huang TC, et al. Vitamin C protects chondrocytes against monosodium iodoacetate-induced osteoarthritis by multiple pathways. International Journal of Molecular Sciences 2016;18(1):38. https://doi.org/10.3390/ijms18010038 PMid: 28035982
Wang L, Li S, Luo H, et al. PCSK9 promotes the progression and metastasis of colon cancer cells through regulation of EMT and PI3K/AKT signaling in tumor cells and phenotypic polarization of macrophages. Journal of Experimental & Clinical Cancer Research 2022;41(1):303. https://doi.org/10.1186/s13046-022-02477-0 PMid: 36242053
Darzynkiewicz Z, Bedner E, Smolewski P. Flow cytometry in analysis of cell cycle and apoptosis. Seminars in Hematology 2001;38(2):179-193. https://doi.org/10.1016/s0037-1963(01)90051-4 PMid: 11309699
Hornbeck PV. Enzyme-linked immunosorbent assays. Current Protocols in Immunology 2015;110:2.1.-2.1.23. https://doi.org/10.1002/0471142735.im0201s110 PMid: 26237010
Ma H, Bell KN, Loker RN. qPCR and qRT-PCR analysis: Regulatory points to consider when conducting biodistribution and vector shedding studies. Molecular Therapy Methods & Clinical Development 2021;20:152-168. https://doi.org/10.1016/j.omtm.2020.11.007 PMid: 33473355
Mahmoudian A, King LK, Liew JW, et al. Timing is everything: Towards classification criteria for early-stage symptomatic knee osteoarthritis. Osteoarthritis and Cartilage 2024;32(6):649-653. https://doi.org/10.1016/j.joca.2024.02.888 PMid: 38437945
Nersisyan S, Novosad V, Engibaryan N, et al. ECM-receptor regulatory network and its prognostic role in colorectal cancer. Frontiers in Genetics 2021;12:782699. https://doi.org/10.3389/fgene.2021.782699 PMid: 34938324
Chen C, Chen J, Wang Y, et al. Ganoderma lucidum polysaccharide inhibits HSC activation and liver fibrosis via targeting inflammation, apoptosis, cell cycle, and ECM-receptor interaction mediated by TGF-?/Smad signaling. Phytomedicine 2023;110:154626. https://doi.org/10.1016/j.phymed.2022.154626 PMid: 36603342
Zhong J, Xiang D, Ma X. Prediction and analysis of osteoarthritis hub genes with bioinformatics. Annals of Translational Medicine 2023;11(2):66. https://doi.org/10.21037/atm-22-6450 PMid: 36819525
Li J, Jiang M, Yu Z, et al. Artemisinin relieves osteoarthritis by activating mitochondrial autophagy through reducing TNFSF11 expression and inhibiting PI3K/AKT/mTOR signaling in cartilage. Cellular & Molecular Biology Letters 2022;27(1):62. https://doi.org/10.1186/s11658-022-00365-1 PMid: 3590282
Xu K, He Y, Moqbel SAA, et al. SIRT3 ameliorates osteoarthritis via regulating chondrocyte autophagy and apoptosis through the PI3K/Akt/mTOR pathway. International Journal of Biological Macromolecules 2021;175:351-360. https://doi.org/10.1016/j.ijbiomac.2021.02.029 PMid: 33556400
Chen Y, Pan X, Zhao J, et al. Icariin alleviates osteoarthritis through PI3K/Akt/mTOR/ULK1 signaling pathway. European Journal of Medical Research 2022;27(1):204. https://doi.org/10.1186/s40001-022-00820-x PMid: 36253872
Wang K, Li Y, Lin J. Identification of diagnostic biomarkers for osteoarthritis through bioinformatics and machine learning. Heliyon 2024;10(6):e27506. https://doi.org/10.1016/j.heliyon.2024.e27506 PMid: 38496843
Li X, Sun X, Kan C, et al. COL1A1: A novel oncogenic gene and therapeutic target in malignancies. Pathology- Research and Practice 2022;236:154013. https://doi.org/10.1016/j.prp.2022.154013 PMid: 35816922
Aborehab NM, El Bishbishy MH. Chondroprotection of fruit peels in a monosodium iodoacetate-induced osteoarthritis rat model via downregulation of Col1A1. Archiv der Pharmazie 2022;355(7):e2200028. https://doi.org/10.1002/ardp.202200028 PMid: 35385163
Oka C, Saleh R, Bessho Y, et al. Interplay between HTRA1 and classical signalling pathways in organogenesis and diseases. Saudi Journal of Biological Sciences 2022;29(4):1919-1927. https://doi.org/10.1016/j.sjbs.2021.11.056 PMid: 35531175
Murayama M, Hirata H, Shiraki M, et al. Nupr1 deficiency downregulates HtrA1, enhances SMAD1 signaling, and suppresses age-related bone loss in male mice. Journal of Cellular Physiology 2023;238(3):566-581. https://doi.org/10.1002/jcp.30949 PMid: 36715607
Otsuki S, Taniguchi N, Grogan SP, et al. Expression of novel extracellular sulfatases Sulf-1 and Sulf-2 in normal and osteoarthritic articular cartilage. Arthritis Research & Therapy 2008;10(3):R61. https://doi.org/10.1186/ar2432 PMid:18507859
Feng D, Li H, Ma X, et al. Downregulation of extracellular matrix protein 1 effectively ameliorates osteoarthritis progression in vivo. International Immunopharmacology 2024;126:111291. https://doi.org/10.1016/j.intimp.2023.111291 PMid: 38039715
Xie J, Huang Z, Yu X, et al. Clinical implications of macrophage dysfunction in the development of osteoarthritis of the knee. Cytokine & Growth Factor Reviews 2019;46:36-44. https://doi.org/10.1016/j.cytogfr.2019.03.004 PMid: 30910350
Zhang H, Lin C, Zeng C, et al. Synovial macrophage M1 polarisation exacerbates experimental osteoarthritis partially through R-spondin-2. Annals of the Rheumatic Diseases 2018;77(10):1524-1534. https://doi.org/10.1136/annrheumdis-2018-213450 PMid: 29991473
Blackler G, Lai-Zhao Y, Klapak J, et al. Targeting STAT6-mediated synovial macrophage activation improves pain in experimental knee osteoarthritis. Arthritis Research & Therapy 2024;26(1):73. https://doi.org/10.1186/s13075-024-03309-6 PMid: 38509602
Ravin KA, Loy M. The Eosinophil in Infection. Clinical Reviews in Allergy & Immunology 2016;50(2):214-227. https://doi.org/10.1007/s12016-015-8525-4 PMid: 26690368
Uchida K, Takano S, Inoue G, et al. Increase in mast cell marker expression in the synovium of obese patients with osteoarthritis of the knee. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy 2019;12:377-382. https://doi.org/10.2147/dmso.S201523 PMid: 31114272
Wang Q, Lepus CM, Raghu H, et al. IgE-mediated mast cell activation promotes inflammation and cartilage destruction in osteoarthritis. eLife 2019;8:e39905. https://doi.org/10.7554/eLife.39905 PMid: 31084709
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright (c) 2026 Electronic Journal of Biotechnology