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Abstract

Introduction

Cartilage defects (CDs) are orthopedic conditions with limited regenerative potential. This study aimed to identify endoplasmic reticulum (ER) stress-related biomarkers and construct a diagnostic model to enhance the early detection of CD.

Methods

This study analyzed the transcriptomic dataset GSE129147 to identify ER stress-related differentially expressed genes (ERSRDEGs) between CD and control tissues using the limma package (version 3.58.1). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were employed for functional enrichment. Immune infiltration was assessed using cell-type identification, which involved estimating the relative subsets of RNA transcripts and single-sample gene set enrichment analysis. Diagnostic models were constructed using logistic regression, support vector machine, and least absolute shrinkage and selection operator regression.

Results

Twenty ERSRDEGs were identified, with CYBB, ATP6V1A, and TNFRSF12A significantly upregulated in CD samples. GO and KEGG analyses highlighted oxidative stress response and extracellular matrix remodeling as key mechanisms in CD pathogenesis. Immune analysis revealed an increase in regulatory T cells and a reduction in CD8+ T cells. TNFRSF12A showed strong immune associations and, together with TWIST1 and ATP6V1A, formed the final preliminary diagnostic model. The preliminary LASSO model achieved satisfactory predictive accuracy (AUC: 0.7–0.9).

Discussion

These findings suggest that ER stress and immune imbalance jointly contribute to cartilage degeneration. The identified genes, particularly TNFRSF12A, TWIST1, and ATP6V1A, not only serve as potential biomarkers but also provide preliminary evidence for new mechanistic insights into stress–immune crosstalk in CD.

Conclusion

This study reveals the key roles of ER stress and immune dysregulation in CDs. Moreover, the ERSRDEG-based diagnostic model provides preliminary bioinformatics evidence and potential molecular indicators for targeted diagnostics and therapies.

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2025-11-14
2025-12-19

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References

  1. Howell M. Liao Q. Gee C.W. Surgical management of osteochondral defects of the knee: An educational review. Curr. Rev. Musculoskelet. Med. 2021 14 1 60 66 10.1007/s12178‑020‑09685‑1 33587261
    [Google Scholar]
  2. Acevedo Rua L. Mumme M. Manferdini C. Darwiche S. Khalil A. Hilpert M. Buchner D.A. Lisignoli G. Occhetta P. von Rechenberg B. Haug M. Schaefer D.J. Jakob M. Caplan A. Martin I. Barbero A. Pelttari K. Engineered nasal cartilage for the repair of osteoarthritic knee cartilage defects. Sci. Transl. Med. 2021 13 609 eaaz4499 10.1126/scitranslmed.aaz4499 34516821
    [Google Scholar]
  3. Xiong Y. Mi B.B. Lin Z. Hu Y.Q. Yu L. Zha K.K. Panayi A.C. Yu T. Chen L. Liu Z.P. Patel A. Feng Q. Zhou S.H. Liu G.H. The role of the immune microenvironment in bone, cartilage, and soft tissue regeneration: From mechanism to therapeutic opportunity. Mil. Med. Res. 2022 9 1 65 10.1186/s40779‑022‑00426‑8 36401295
    [Google Scholar]
  4. Tetteh E.S. Bajaj S. Ghodadra N.S. Cole B.J. Basic science and surgical treatment options for articular cartilage injuries of the knee. J. Orthop. Sports Phys. Ther. 2012 42 3 243 253 10.2519/jospt.2012.3673 22383075
    [Google Scholar]
  5. Gao H. Pan Q. Dong W. Yao Y. Progress in osteochondral regeneration with engineering strategies. Ann. Biomed. Eng. 2022 50 10 1232 1242 10.1007/s10439‑022‑03060‑6 35994165
    [Google Scholar]
  6. Guo X. Xi L. Yu M. Fan Z. Wang W. Ju A. Liang Z. Zhou G. Ren W. Regeneration of articular cartilage defects: Therapeutic strategies and perspectives. J. Tissue Eng. 2023 14 20417314231164765 10.1177/20417314231164765 37025158
    [Google Scholar]
  7. Yang C. Chen R. Chen C. Yang F. Xiao H. Geng B. Xia Y. Tissue engineering strategies hold promise for the repair of articular cartilage injury. Biomed. Eng. Online 2024 23 1 92 10.1186/s12938‑024‑01260‑w 39261876
    [Google Scholar]
  8. Nordberg R.C. Bielajew B.J. Takahashi T. Dai S. Hu J.C. Athanasiou K.A. Recent advancements in cartilage tissue engineering innovation and translation. Nat. Rev. Rheumatol. 2024 20 6 323 346 10.1038/s41584‑024‑01118‑4 38740860
    [Google Scholar]
  9. Li Y. He J. Zhou J. Li Z. Liu L. Hu S. Guo B. Wang W. A conductive photothermal non-swelling nanocomposite hydrogel patch accelerating bone defect repair. Biomater. Sci. 2022 10 5 1326 1341 10.1039/D1BM01937F 35103257
    [Google Scholar]
  10. Wan Y.T.O. Lui T.H. Arthroscopic debridement and microfracture of osteochondral lesion of the talar head. Arthrosc. Tech. 2019 8 9 e969 e973 10.1016/j.eats.2019.05.006 31687328
    [Google Scholar]
  11. Elghawy A.A. Sesin C. Rosselli M. Osteochondral defects of the talus with a focus on platelet-rich plasma as a potential treatment option: A review. BMJ Open Sport Exerc. Med. 2018 4 1 000318 10.1136/bmjsem‑2017‑000318 29464105
    [Google Scholar]
  12. Logroscino G. Saracco M. Goderecci R. Paglia A. Calvisi V. Arthroscopy in osteochondral pathology of the elbow: Indications, treatment and complications. J. Biol. Regul. Homeost. Agents 2019 33 2 1 7 [XIX.] 31168996
    [Google Scholar]
  13. Puddu L. Altamore F. Santandrea A. Mercurio D. Caggiari G. Della Sala S. Marinetti A. Tessarolo F. Rigoni M. Manunta A.F. Cortese F. Surgical treatment of talar osteo-chondral lesions with micro-fractures, mesenchymal cells grafting on membrane, or allograft: Mid-term clinical and magnetic resonance assessment. J. Orthop. 2020 21 416 420 10.1016/j.jor.2020.08.012 32921950
    [Google Scholar]
  14. Redondo M. Beer A. Yanke A. Cartilage restoration: Microfracture and osteochondral autograft transplantation. J. Knee Surg. 2018 31 3 231 238 10.1055/s‑0037‑1618592 29396963
    [Google Scholar]
  15. Chen X. Shi C. He M. Xiong S. Xia X. Endoplasmic reticulum stress: Molecular mechanism and therapeutic targets. Signal Transduct. Target. Ther. 2023 8 1 352 10.1038/s41392‑023‑01570‑w 37709773
    [Google Scholar]
  16. Oakes S.A. Papa F.R. The role of endoplasmic reticulum stress in human pathology. Annu. Rev. Pathol. 2015 10 1 173 194 10.1146/annurev‑pathol‑012513‑104649 25387057
    [Google Scholar]
  17. Aşık M.D. Gürsoy S. Akkaya M. Kozacı L.D. Doğan M. Bozkurt M. Microarray analysis of cartilage: Comparison between damaged and non-weight-bearing healthy cartilage. Connect. Tissue Res. 2020 61 5 456 464 10.1080/03008207.2019.1611797 31142155
    [Google Scholar]
  18. Liu M. Gong S. Sheng X. Zhang Z. Wang X. Bioinformatic identification of important roles of COL1A1 and TNFRSF12A in cartilage injury and osteoporosis. J. Int. Soc. Sports Nutr. 2025 22 1 2454641 10.1080/15502783.2025.2454641 39847474
    [Google Scholar]
  19. Davis S. Meltzer P.S. GEOquery: A bridge between the Gene Expression Omnibus (GEO) and BioConductor. Bioinformatics 2007 23 14 1846 1847 10.1093/bioinformatics/btm254 17496320
    [Google Scholar]
  20. Stelzer G. Rosen N. Plaschkes I. Zimmerman S. Twik M. Fishilevich S. Stein T. I. Nudel R. Lieder I. Mazor Y. The GeneCards suite: From gene data mining to disease genome sequence analyses Curr. Protoc. Bioinformatics 2016 54 1.30.1 1.30.33 10.1002/cpbi.5 27322403
    [Google Scholar]
  21. Ritchie M.E. Phipson B. Wu D. Hu Y. Law C.W. Shi W. Smyth G.K. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015 43 7 47 10.1093/nar/gkv007 25605792
    [Google Scholar]
  22. Chen H. Su X. Li Y. Dang C. Luo Z. Identification of metabolic reprogramming-related genes as potential diagnostic biomarkers for diabetic nephropathy based on bioinformatics. Diabetol. Metab. Syndr. 2024 16 1 287 10.1186/s13098‑024‑01531‑5 39609849
    [Google Scholar]
  23. Wu L. Zheng H. Guo X. Li N. Qin L. Li X. Lou G. Integrative analyses of genes associated with oxidative stress and cellular senescence in triple-negative breast cancer. Heliyon 2024 10 14 34524 10.1016/j.heliyon.2024.e34524 39130410
    [Google Scholar]
  24. Shen J. Yao E. Tian W. He J. Gu Y. Zhao D. Glycolytic pathways: The hidden regulators in Parkinson’s disease. Heliyon 2025 11 3 41831 10.1016/j.heliyon.2025.e41831 39959499
    [Google Scholar]
  25. Zhu N. Wang X. Zhu H. Zheng Y. Exploring the role of alternative lengthening of telomere-related genes in diagnostic modeling for non-alcoholic fatty liver disease. Sci. Rep. 2024 14 1 30309 10.1038/s41598‑024‑81129‑z 39638831
    [Google Scholar]
  26. Mao W. Zong G. Gao Y. Qu S. Cheng X. Integrative analyses of mitophagy-related genes and mechanisms associated with type 2 diabetes in muscle tissue. Curr. Issues Mol. Biol. 2024 46 9 10411 10429 10.3390/cimb46090619 39329971
    [Google Scholar]
  27. Mi H. Muruganujan A. Ebert D. Huang X. Thomas P.D. PANTHER version 14: More genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Res. 2019 47 D1 D419 D426 10.1093/nar/gky1038 30407594
    [Google Scholar]
  28. Li R. Zhou C. Ye K. Chen H. Peng M. Identification of genes involved in energy metabolism in preeclampsia and discovery of early biomarkers. Front. Immunol. 2025 16 1496046 10.3389/fimmu.2025.1496046 39967661
    [Google Scholar]
  29. Zhou J. Huo H. He R. Lu Y. Peng Y. Zou X. Jiang S. Age-related stress gene expression in neonatal sepsis involves regulatory networks and immune cell infiltration. Sci. Rep. 2025 15 1 18814 10.1038/s41598‑025‑01442‑z 40442112
    [Google Scholar]
  30. Zheng D. Yang K. Chen X. Li Y. Chen Y. Analysis of immune–stromal score-based gene signature and molecular subtypes in osteosarcoma: Implications for prognosis and tumor immune microenvironment. Front. Genet. 2021 12 699385 10.3389/fgene.2021.699385 34630511
    [Google Scholar]
  31. Kanehisa M. Goto S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000 28 1 27 30 10.1093/nar/28.1.27 10592173
    [Google Scholar]
  32. Li Z. Zhao W. Ji W. Li Z. Wang K. Jiang T. A neutrophil extracellular traps-related gene trait revealed the prospective therapy strategy of coronary atherosclerosis. J. Inflamm. Res. 2024 17 9925 9951 10.2147/JIR.S489847 39624399
    [Google Scholar]
  33. Yu G. Wang L.G. Han Y. He Q.Y. clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS 2012 16 5 284 287 10.1089/omi.2011.0118 22455463
    [Google Scholar]
  34. Yan T. Su T. Zhu M. Qing Q. Huang B. Liu J. Ma T. Oxidative stress gene expression in ulcerative colitis: Implications for colon cancer biomarker discovery. Sci. Rep. 2025 15 1 22641 10.1038/s41598‑025‑05108‑8 40595862
    [Google Scholar]
  35. Sanz H. Valim C. Vegas E. Oller J.M. Reverter F. SVM-RFE: Selection and visualization of the most relevant features through non-linear kernels. BMC Bioinformatics 2018 19 1 432 10.1186/s12859‑018‑2451‑4 30453885
    [Google Scholar]
  36. Engebretsen S. Bohlin J. Statistical predictions with glmnet. Clin. Epigenetics 2019 11 1 123 10.1186/s13148‑019‑0730‑1 31443682
    [Google Scholar]
  37. Lou Y.X. Hua Y. Wu T.T. Sun W. Yang Y. Kong X.Q. Caspase‐7 and vitamin D receptor gene as key genes of hypertension caused by pyroptosis in human. J. Clin. Hypertens 2025 27 4 70047 10.1111/jch.70047 40259750
    [Google Scholar]
  38. Wu J. Zhang H. Li L. Hu M. Chen L. Xu B. Song Q. A nomogram for predicting overall survival in patients with low‐grade endometrial stromal sarcoma: A population‐based analysis. Cancer Commun. 2020 40 7 301 312 10.1002/cac2.12067 32558385
    [Google Scholar]
  39. Van Calster B. Wynants L. Verbeek J.F.M. Verbakel J.Y. Christodoulou E. Vickers A.J. Roobol M.J. Steyerberg E.W. Reporting and interpreting decision curve analysis: A guide for investigators. Eur. Urol. 2018 74 6 796 804 10.1016/j.eururo.2018.08.038 30241973
    [Google Scholar]
  40. Liu B. Ao Y. Liu C. Bai F. Zhou Z. Huang J. Wang Q. Creation of an innovative diagnostic framework for hepatocellular carcinoma employing bioinformatics techniques focused on senescence-related and pyroptosis-related genes. Front. Oncol. 2025 15 1485421 10.3389/fonc.2025.1485421 40018411
    [Google Scholar]
  41. Robin X. Turck N. Hainard A. Tiberti N. Lisacek F. Sanchez J.C. Müller M. pROC: An open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 2011 12 1 77 10.1186/1471‑2105‑12‑77 21414208
    [Google Scholar]
  42. Ke X. Huang M. Zheng Y. Chen G. Polygenic insight identifies precision biomarkers decoding protein catabolism and autophagy pathways in obstructive sleep apnea. Sci. Rep. 2025 15 1 28347 10.1038/s41598‑025‑13687‑9 40759999
    [Google Scholar]
  43. He M.H. Zhang X.H. Zhang J.H. Pan J. Yang C. Evaluating the role of astragalus polysaccharide in modulating immune infiltration and enhancing prognostic biomarkers in pediatric acute myeloid leukemia. Front. Pharmacol. 2025 16 1538888 10.3389/fphar.2025.1538888 40260377
    [Google Scholar]
  44. Zheng L. Mou L. Hao L. Chen R. Wang Y. Yu M. Zhang X. Exploring the molecular characteristics of inflammatory bowel disease from the perspective of hypoxia-related genes. Front. Pharmacol. 2025 16 1612676 10.3389/fphar.2025.1612676 40771912
    [Google Scholar]
  45. Yu G. Li F. Qin Y. Bo X. Wu Y. Wang S. GOSemSim: An R package for measuring semantic similarity among GO terms and gene products. Bioinformatics 2010 26 7 976 978 10.1093/bioinformatics/btq064 20179076
    [Google Scholar]
  46. Hei C. Li X. Wang R. Peng J. Liu P. Dong X. Li P.A. Zheng W. Niu J. Yang X. Machine learning analysis of gene expression profiles of pyroptosis-related differentially expressed genes in ischemic stroke revealed potential targets for drug repurposing. Sci. Rep. 2025 15 1 7035 10.1038/s41598‑024‑83555‑5 40016488
    [Google Scholar]
  47. Newman A.M. Liu C.L. Green M.R. Gentles A.J. Feng W. Xu Y. Hoang C.D. Diehn M. Alizadeh A.A. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods 2015 12 5 453 457 10.1038/nmeth.3337 25822800
    [Google Scholar]
  48. Yao Y. Yang X. Fu Y. Zhang Y. Immunological features of various molecular subtypes of cervical cancer and their prognostic implications in the context of disulfidptosis. Front. Oncol. 2025 15 1574911 10.3389/fonc.2025.1574911 40438679
    [Google Scholar]
  49. Wang S. Li X. Bi Y. Yan C. Chen Y. The impact of inflammation and iron metabolism on gene expression alterations in ischemic stroke: A bioinformatics approach. Sci. Rep. 2025 15 1 15233 10.1038/s41598‑025‑00369‑9 40307317
    [Google Scholar]
  50. Pan R. Yang Y. Kong Q. Yu J. Chen J. Hypoxia-related gene expression in major depressive disorder: Identifying diagnostic biomarkers and implications for immune cell infiltration. Brain Res. 2025 1866 149866 10.1016/j.brainres.2025.149866 40840857
    [Google Scholar]
  51. Xiao B. Liu L. Li A. Xiang C. Wang P. Li H. Xiao T. Identification and verification of immune-related gene prognostic signature based on ssGSEA for osteosarcoma. Front. Oncol. 2020 10 607622 10.3389/fonc.2020.607622 33384961
    [Google Scholar]
  52. Murray I.R. Benke M.T. Mandelbaum B.R. Management of knee articular cartilage injuries in athletes: Chondroprotection, chondrofacilitation, and resurfacing. Knee Surg. Sports Traumatol. Arthrosc. 2016 24 5 1617 1626 10.1007/s00167‑015‑3509‑8 25661676
    [Google Scholar]
  53. Alvero A.B. Wright-Chisem J. Vogel M.J. Wright-Chisem A. Mather R.C. Nho S.J. Treatment of hip cartilage defects in athletes. Sports Med. Arthrosc. Rev. 2024 32 2 95 103 10.1097/JSA.0000000000000378 38978203
    [Google Scholar]
  54. Ganokroj P. Adriani M. Whalen R.J. Provencher M.T. Treatment of shoulder cartilage defects in athletes. Sports Med. Arthrosc. Rev. 2024 32 2 87 94 10.1097/JSA.0000000000000404 38978202
    [Google Scholar]
  55. Liu X. Shi Y. Liu R. Song K. Chen L. Structure of human phagocyte NADPH oxidase in the activated state. Nature 2024 627 8002 189 195 10.1038/s41586‑024‑07056‑1 38355798
    [Google Scholar]
  56. Kusuyama J. Alves-Wagner A.B. Conlin R.H. Makarewicz N.S. Albertson B.G. Prince N.B. Kobayashi S. Kozuka C. Møller M. Bjerre M. Fuglsang J. Miele E. Middelbeek R.J.W. Xiudong Y. Xia Y. Garneau L. Bhattacharjee J. Aguer C. Patti M.E. Hirshman M.F. Jessen N. Hatta T. Ovesen P.G. Adamo K.B. Nozik-Grayck E. Goodyear L.J. Placental superoxide dismutase 3 mediates benefits of maternal exercise on offspring health. Cell Metab. 2021 33 5 939 956.e8 10.1016/j.cmet.2021.03.004 33770509
    [Google Scholar]
  57. Yigittürk O. Turgay F. Kızıldağ S. Özsoylu D. Balcı G.A. Do PON1–Q192R and PON1–L55M polymorphisms modify the effects of hypoxic training on paraoxonase and arylesterase activity? J. Sport Health Sci. 2023 12 2 266 274 10.1016/j.jshs.2020.11.004 33188964
    [Google Scholar]
  58. Hawley Z.C.E. Li X. Bodnar D. Gu Y. Luo Y. Ferretti D. Sheehy A. Driscoll R. Zavodszky M.I. Cao S. Isaza I. Jandreski L. Liu Y. Carlile T. Lo S.C. Grimard A. Bourque S. Utturkar A. Desmarais S. Arnold H.M. Huh D. Guilmette E. Kwon D.Y. Viral-mediated knockdown of Atxn2 attenuates TDP-43 pathology and muscle dysfunction in the PFN1C71G ALS mouse model. Acta Neuropathol. Commun. 2025 13 1 116 10.1186/s40478‑025‑02005‑z 40413526
    [Google Scholar]
  59. Canham L. Sendac S. Diagbouga M.R. Wolodimeroff E. Pirri D. Tardajos Ayllon B. Feng S. Souilhol C. Chico T.J.A. Evans P.C. Serbanovic-Canic J. EVA1A (Eva-1 Homolog A) promotes endothelial apoptosis and inflammatory activation under disturbed flow via regulation of autophagy. Arterioscler. Thromb. Vasc. Biol. 2023 43 4 547 561 10.1161/ATVBAHA.122.318110 36794585
    [Google Scholar]
  60. Zhou L. Li Q. Chen A. Liu N. Chen N. Chen X. Zhu L. Xia B. Gong Y. Chen X. KLF15‐activating Twist2 ameliorated hepatic steatosis by inhibiting inflammation and improving mitochondrial dysfunction via NF‐κB‐FGF21 or SREBP1c‐FGF21 pathway. FASEB J. 2019 33 12 14254 14269 10.1096/fj.201901347RR 31648561
    [Google Scholar]
  61. Bahar E. Kim J.Y. Kim D.C. Kim H.S. Yoon H. Combination of niraparib, cisplatin and twist knockdown in cisplatin-resistant ovarian cancer cells potentially enhances synthetic lethality through ER-stress mediated mitochondrial apoptosis pathway. Int. J. Mol. Sci. 2021 22 8 3916 10.3390/ijms22083916 33920140
    [Google Scholar]
  62. Fu L. Zhang L. Zhang X. Chen L. Cai Q. Yang X. Roles of oxygen level and hypoxia-inducible factor signaling pathway in cartilage, bone and osteochondral tissue engineering. Biomed. Mater. 2021 16 2 022006 10.1088/1748‑605X/abdb73 33440367
    [Google Scholar]
  63. Liu K. Zhang B. Zhang X. Promoting articular cartilage regeneration through microenvironmental regulation. J. Immunol. Res. 2024 2024 1 4751168 10.1155/2024/4751168 39104594
    [Google Scholar]
  64. Li H. Zhao T. Yuan Z. Gao T. Yang Y. Li R. Tian Q. Tang P. Guo Q. Zhang L. Cartilage lacuna-biomimetic hydrogel microspheres endowed with integrated biological signal boost endogenous articular cartilage regeneration. Bioact. Mater. 2024 41 61 82 10.1016/j.bioactmat.2024.06.037 39104774
    [Google Scholar]
  65. Arai Y. Cha R. Nakagawa S. Inoue A. Nakamura K. Takahashi K. Cartilage homeostasis under physioxia. Int. J. Mol. Sci. 2024 25 17 9398 10.3390/ijms25179398 39273346
    [Google Scholar]
  66. Juhász K.Z. Hajdú T. Kovács P. Vágó J. Matta C. Takács R. Hypoxic conditions modulate chondrogenesis through the circadian clock: The role of hypoxia-inducible factor-1α. Cells 2024 13 6 512 10.3390/cells13060512 38534356
    [Google Scholar]
  67. Wu Q. Liu C. Liu D. Wang Y. Qi H. Liu X. Zhang Y. Chen H. Zeng Y. Li J. Polystyrene nanoplastics-induced lung apoptosis and ferroptosis via ROS-dependent endoplasmic reticulum stress. Sci. Total Environ. 2024 912 169260 10.1016/j.scitotenv.2023.169260 38086481
    [Google Scholar]
  68. Luo Z. Tian M. Yang G. Tan Q. Chen Y. Li G. Zhang Q. Li Y. Wan P. Wu J. Hypoxia signaling in human health and diseases: Implications and prospects for therapeutics. Signal Transduct. Target. Ther. 2022 7 1 218 10.1038/s41392‑022‑01080‑1 35798726
    [Google Scholar]
  69. Yepuri G. Ramirez L.M. Theophall G.G. Reverdatto S.V. Quadri N. Hasan S.N. Bu L. Thiagarajan D. Wilson R. Díez R.L. Gugger P.F. Mangar K. Narula N. Katz S.D. Zhou B. Li H. Stotland A.B. Gottlieb R.A. Schmidt A.M. Shekhtman A. Ramasamy R. DIAPH1-MFN2 interaction regulates mitochondria-SR/ER contact and modulates ischemic/hypoxic stress. Nat. Commun. 2023 14 1 6900 10.1038/s41467‑023‑42521‑x 37903764
    [Google Scholar]
  70. Akhter N. Wilson A. Arefanian H. Thomas R. Kochumon S. Al-Rashed F. Abu-Farha M. Al-Madhoun A. Al-Mulla F. Ahmad R. Sindhu S. Endoplasmic reticulum stress promotes the expression of TNF-α in THP-1 cells by mechanisms involving ROS/CHOP/HIF-1α and MAPK/NF-κB pathways. Int. J. Mol. Sci. 2023 24 20 15186 10.3390/ijms242015186 37894865
    [Google Scholar]
  71. Pueyo Moliner A. Ito K. Zaucke F. Kelly D.J. de Ruijter M. Malda J. Restoring articular cartilage: Insights from structure, composition and development. Nat. Rev. Rheumatol. 2025 21 5 291 308 10.1038/s41584‑025‑01236‑7 40155694
    [Google Scholar]
  72. Hodgkinson T. Kelly D.C. Curtin C.M. O’Brien F.J. Mechanosignalling in cartilage: An emerging target for the treatment of osteoarthritis. Nat. Rev. Rheumatol. 2022 18 2 67 84 10.1038/s41584‑021‑00724‑w 34934171
    [Google Scholar]
  73. Romero-Castillo L. Pandey R.K. Xu B. Beusch C.M. Oliveira-Coelho A. Zeqiraj K. Svensson C. Xu Z. Luo H. Sareila O. Sabatier P. Ge C. Cheng L. Urbonaviciute V. Krämer A. Lindgren C. Haag S. Viljanen J. Zubarev R.A. Kihlberg J. Linusson A. Burkhardt H. Holmdahl R. Tolerogenic antigen-specific vaccine induces VISTA-enriched regulatory T cells and protects against arthritis in DRB1*04:01 mice. Mol. Ther. 2025 33 8 3528 3545 10.1016/j.ymthe.2025.04.034 40285352
    [Google Scholar]
  74. Nayer B. Tan J.L. Alshoubaki Y.K. Lu Y.Z. Legrand J.M.D. Lau S. Hu N. Park A.J. Wang X.N. Amann-Zalcenstein D. Hickey P.F. Wilson T. Kuhn G.A. Müller R. Vasanthakumar A. Akira S. Martino M.M. Local administration of regulatory T cells promotes tissue healing. Nat. Commun. 2024 15 1 7863 10.1038/s41467‑024‑51353‑2 39251592
    [Google Scholar]
  75. Becker M. Joseph S.S. Garcia-Carrizo F. Tom R.Z. Opaleva D. Serr I. Tschöp M.H. Schulz T.J. Hofmann S.M. Daniel C. Regulatory T cells require IL6 receptor alpha signaling to control skeletal muscle function and regeneration. Cell Metab. 2023 35 10 1736 1751.e7 10.1016/j.cmet.2023.08.010 37734370
    [Google Scholar]
  76. Chen D. Li Y. Wang Q. Zhan P. Identification of key osteoporosis genes through comparative analysis of men’s and women’s osteoblast transcriptomes. Calcif. Tissue Int. 2023 113 6 618 629 10.1007/s00223‑023‑01147‑3 37878026
    [Google Scholar]
  77. Liu Z. Sun Y. Pan J. Guo K. Tang Z. Wang X. Single-cell profiling uncovers synovial fibroblast subpopulations associated with chondrocyte injury in osteoarthritis. Front. Endocrinol. 2024 15 1479909 10.3389/fendo.2024.1479909 39720254
    [Google Scholar]
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Exploring Endoplasmic Reticulum Stress-Related Genes in Cartilage Defects: Implications for Diagnosis and Therapy
Bentham Science Publishers ; https://doi.org/10.2174/0113862073441646251107115725
/content/journals/cchts/10.2174/0113862073441646251107115725
/content/journals/cchts/10.2174/0113862073441646251107115725
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  • Article Type:     Research Article
Keywords: immune infiltration ; endoplasmic reticulum stress ; cartilage regeneration ; Cartilage defects ; bioinformatics analysis ; diagnostic model

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