Recycling senescent cell lipids for targeted senotherapy

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Recycling senescent cell lipids for targeted senotherapy

Data availability

The main data supporting the findings of this study are presented in the paper and its supplementary information. The raw mass spectrometry proteomics data generated in this study have been deposited in the iProX database (https://www.iprox.cn/), under accession number IPX0012242000. Source data are provided with this paper.

References

  1. Di Micco, R., Krizhanovsky, V., Baker, D. & d’Adda di Fagagna, F. Cellular senescence in ageing: from mechanisms to therapeutic opportunities. Nat. Rev. Mol. Cell Biol. 22, 75–95 (2021).

    Google Scholar 

  2. Coryell, P. R., Diekman, B. O. & Loeser, R. F. Mechanisms and therapeutic implications of cellular senescence in osteoarthritis. Nat. Rev. Rheumatol. 17, 47–57 (2021).

    Google Scholar 

  3. Mehdizadeh, M., Aguilar, M., Thorin, E., Ferbeyre, G. & Nattel, S. The role of cellular senescence in cardiac disease: basic biology and clinical relevance. Nat. Rev. Cardiol. 19, 250–264 (2022).

    Google Scholar 

  4. Schmitt, C. A., Wang, B. & Demaria, M. Senescence and cancer—role and therapeutic opportunities. Nat. Rev. Clin. Oncol. 19, 619–636 (2022).

    Google Scholar 

  5. Sanfeliu-Redondo, D., Gibert-Ramos, A. & Gracia-Sancho, J. Cell senescence in liver diseases: pathological mechanism and theranostic opportunity. Nat. Rev. Gastroenterol. Hepatol. 21, 477–492 (2024).

    Google Scholar 

  6. López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M. & Kroemer, G. Hallmarks of aging: an expanding universe. Cell 186, 243–278 (2023).

    Google Scholar 

  7. Chaib, S., Tchkonia, T. & Kirkland, J. L. Cellular senescence and senolytics: the path to the clinic. Nat. Med. 28, 1556–1568 (2022).

    Google Scholar 

  8. Colville, A. et al. Death-seq identifies regulators of cell death and senolytic therapies. Cell Metab. 35, 1814–1829 (2023).

    Google Scholar 

  9. Jeon, O. et al. Local clearance of senescent cells attenuates the development of post-traumatic osteoarthritis and creates a pro-regenerative environment. Nat. Med. 23, 775–781 (2017).

    Google Scholar 

  10. de Magalhães, J. P. Cellular senescence in normal physiology. Science 384, 1300–1301 (2024).

    Google Scholar 

  11. Reyes, N. S. et al. Sentinel p16INK4a+ cells in the basement membrane form a reparative niche in the lung. Science 378, 192–201 (2022).

    Google Scholar 

  12. Wang, X. et al. Signalling by senescent melanocytes hyperactivates hair growth. Nature 618, 808–817 (2023).

    Google Scholar 

  13. Rabinovitch, M. Are senolytic agents guilty of overkill or inappropriate age discrimination?. Circulation 147, 667–668 (2023).

    Google Scholar 

  14. Reimann, M., Lee, S. & Schmitt, C. A. Cellular senescence: neither irreversible nor reversible. J. Exp. Med. 221, e20232136 (2024).

    Google Scholar 

  15. Hornburg, D. et al. Dynamic lipidome alterations associated with human health, disease and ageing. Nat. Metab. 5, 1578–1594 (2023).

    Google Scholar 

  16. Tsugawa, H. et al. A lipidome landscape of aging in mice. Nat. Aging 4, 709–726 (2024).

    Google Scholar 

  17. Byrns, C. N. et al. Senescent glia link mitochondrial dysfunction and lipid accumulation. Nature 630, 475–483 (2024).

    Google Scholar 

  18. Kaffe, E. et al. Bioactive signalling lipids as drivers of chronic liver diseases. J. Hepatol. 80, 140–154 (2024).

    Google Scholar 

  19. Zeng, Q. et al. Lipids and lipid metabolism in cellular senescence: Emerging targets for age-related diseases. Ageing Res. Rev. 97, 102294 (2024).

    Google Scholar 

  20. Jeon, Y. G., Kim, Y. Y., Lee, G. & Kim, J. B. Physiological and pathological roles of lipogenesis. Nat. Metab. 5, 735–759 (2023).

    Google Scholar 

  21. Yang, L., Zhao, X., Ma, Z., Ma, S. & Zhou, F. An overview of functional biolubricants. Friction 11, 23–47 (2023).

    Google Scholar 

  22. Gebeshuber, I. C. & Van Aken, G. Editorial: Friction and Lubricants Related to Human Bodies. Lubricants 2017, 4 (2017). 5.

    Google Scholar 

  23. DeMoya, C. D. et al. Advances in viscosupplementation and tribosupplementation for early-stage osteoarthritis therapy. Nat. Rev. Rheumatol. 20, 432–451 (2024).

    Google Scholar 

  24. Robinson, W. et al. Low-grade inflammation as a key mediator of the pathogenesis of osteoarthritis. Nat. Rev. Rheumatol. 12, 580–592 (2016).

    Google Scholar 

  25. Seror, J. et al. Supramolecular synergy in the boundary lubrication of synovial joints. Nat. Commun. 6, 6497 (2015).

    Google Scholar 

  26. Zhou, Q. et al. Lipidomics unravels lipid changes in osteoarthritis articular cartilage. Ann. Rheum. Dis. S0003-4967(25)00054-8. Advance online publication (2025).

  27. Wei, G. et al. Risk of metabolic abnormalities in osteoarthritis: a new perspective to understand its pathological mechanisms. Bone Res 11, 63 (2023).

    Google Scholar 

  28. Monnaert, V. et al. Behavior of alpha-, beta-, and gamma-cyclodextrins and their derivatives on an in vitro model of blood-brain barrier. J. Pharmacol. Exp. Ther. 310, 745–751 (2004).

    Google Scholar 

  29. Wang, B. et al. The senescence-associated secretory phenotype and its physiological and pathological implications. Nat. Rev. Mol. Cell Biol. 25, 958-978 (2024).

  30. Davies, M. E., Sharma, H. & Pigott, R. ICAM-1 expression on chondrocytes in rheumatoid arthritis: induction by synovial cytokines. Mediators Inflamm. 1, 71–74 (1992).

    Google Scholar 

  31. Suryadevara, V. et al. SenNet recommendations for detecting senescent cells in different tissues. Nat. Rev. Mol. Cell Biol. 25, 1001-1023 (2024).

  32. Gorgoulis, V. et al. p53-Dependent ICAM-1 overexpression in senescent human cells identified in atherosclerotic lesions. Lab. Invest. 85, 502–511 (2005).

    Google Scholar 

  33. Swahn, H. et al. Senescent cell population with ZEB1 transcription factor as its main regulator promotes osteoarthritis in cartilage and meniscus. Ann. Rheum. Dis. 82, 403–415 (2023).

    Google Scholar 

  34. Fan, Y. et al. Unveiling inflammatory and prehypertrophic cell populations as key contributors to knee cartilage degeneration in osteoarthritis using multi-omics data integration. Ann. Rheum. Dis. 83, 926–944 (2024).

    Google Scholar 

  35. Zhang, B. C. et al. Cholesterol-binding motifs in STING that control endoplasmic reticulum retention mediate anti-tumoral activity of cholesterol-lowering compounds. Nat. Commun. 15, 2760 (2024).

    Google Scholar 

  36. Hu, X. et al. Bitter taste TAS2R14 activation by intracellular tastants and cholesterol. Nature 631, 459–466 (2024).

    Google Scholar 

  37. Roh, K. et al. Lysosomal control of senescence and inflammation through cholesterol partitioning. Nat. Metab. 5, 398–413 (2023).

    Google Scholar 

  38. Doktorova, M. et al. Preparation of asymmetric phospholipid vesicles for use as cell membrane models. Nat. Protoc. 13, 2086–2101 (2018).

    Google Scholar 

  39. Bozelli, J. C. Jr, Hou, Y. H. & Epand, R. M. Thermodynamics of methyl-β-cyclodextrin-induced lipid vesicle solubilization: effect of lipid headgroup and backbone. Langmuir 33, 13882–13891 (2017).

    Google Scholar 

  40. Lin, W. & Klein, J. Recent progress in cartilage lubrication. Adv. Mater. 33, e2005513 (2021).

    Google Scholar 

  41. Sett, R., Paul, B. K. & Guchhait, N. Unsaturation of the phospholipid side-chain influences its interaction with cyclodextrins: a spectroscopic exploration using a phenazinium dye. Colloids Surf. B. Biointerfaces 180, 150–158 (2019).

    Google Scholar 

  42. Szente, L. & Fenyvesi, É Cyclodextrin-lipid complexes: cavity size matters. Struct. Chem. 28, 479–492 (2017).

    Google Scholar 

  43. Abe, M. & Kobayashi, T. Imaging cholesterol depletion at the plasma membrane by methyl-β-cyclodextrin. J. Lipid Res. 62, 100077 (2021).

    Google Scholar 

  44. Lei, Y. et al. Injectable hydrogel microspheres with self-renewable hydration layers alleviate osteoarthritis. Sci. Adv. 8, eabl6449 (2022).

    Google Scholar 

  45. Bajpayee, A. & Grodzinsky, A. Cartilage-targeting drug delivery: can electrostatic interactions help?. Nat. Rev. Rheumatol. 13, 183–193 (2017).

    Google Scholar 

  46. Xie, R. et al. Biomimetic cartilage-lubricating polymers regenerate cartilage in rats with early osteoarthritis. Nat. Biomed. Eng. 5, 1189–1201 (2021).

    Google Scholar 

  47. Moiseeva, V. et al. Senescence atlas reveals an aged-like inflamed niche that blunts muscle regeneration. Nature 613, 169–178 (2023).

    Google Scholar 

  48. Shaw, P. X. et al. Complement factor H genotypes impact risk of age-related macular degeneration by interaction with oxidized phospholipids. Proc. Natl. Acad. Sci. USA 109, 13757–13762 (2012).

    Google Scholar 

  49. Liuzzi, R., Gallier, S., Ringler, S., Caserta, S. & Guido, S. Visualization of choline-based phospholipids at the interface of oil/water emulsions with TEPC-15 antibody. RSC Adv. 6, 109960–109968 (2016).

    Google Scholar 

  50. Lin, W. et al. Cartilage-inspired, lipid-based boundary-lubricated hydrogels. Science 370, 335–338 (2020).

    Google Scholar 

  51. Dolgin, E. Send in the senolytics. Nat. Biotechnol. 38, 1371–1377 (2020).

    Google Scholar 

  52. McHugh, D. & Gil, J. Senescence and aging: causes, consequences, and therapeutic avenues. J. Cell. Biol. 217, 65–77 (2018).

    Google Scholar 

  53. Zhao, J. et al. Senolytics cocktail dasatinib and quercetin alleviate chondrocyte senescence and facet joint osteoarthritis in mice. Spine J. 25, 184–198 (2025).

    Google Scholar 

  54. Gosset, M. et al. Primary culture and phenotyping of murine chondrocytes. Nat. Protoc. 3, 1253–1260 (2008).

    Google Scholar 

  55. Arra, M. et al. IκB-ζ signaling promotes chondrocyte inflammatory phenotype, senescence, and erosive joint pathology. Bone Res. 10, 12 (2022).

    Google Scholar 

  56. Ji, X. et al. GSTP1-mediated S-glutathionylation of Pik3r1 is a redox hub that inhibits osteoclastogenesis through regulating autophagic flux. Redox Biol. 61, 102635 (2023).

    Google Scholar 

  57. Kongpracha, P. et al. Simple but efficacious enrichment of integral membrane proteins and their interactions for in-depth membrane proteomics. Mol. Cell Proteom. 21, 100206 (2022).

    Google Scholar 

  58. Amor, C. et al. Senolytic CAR T cells reverse senescence-associated pathologies. Nature 583, 127–132 (2020).

    Google Scholar 

  59. Gu, Z., Eils, R. & Schlesner, M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinforma. Oxf. Engl. 32, 2847–2849 (2016).

    Google Scholar 

  60. Wu, T. et al. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innov. Camb. Mass 2, 100141 (2021).

    Google Scholar 

  61. Hao, Y. et al. Dictionary learning for integrative, multimodal and scalable single-cell analysis. Nat. Biotechnol. 42, 293–304 (2024).

    Google Scholar 

  62. Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 16, 1289–1296 (2019).

    Google Scholar 

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Acknowledgements

This work was supported by grants from the National Nature Science Fund of China (82201729 to Z.Q., 82501891 to J.H., 8251101103 to Safwat Adel Abdo Moqbel, 82072413 and 82101649 to Y.Q.), the Natural Science Foundation of Zhejiang Province (LMS25H060001 to Y.Q.), the Key R&D Program of Zhejiang Province (2021C03108 to G.F.), and the Joint Construction Project of Zhejiang Province and Health Ministry (WKJ-ZJ-2029 to G.F.). We thank Safwat Adel Abdo Moqbel for providing financial support during the revision of this article. We thank Professor Ruikang Tang from Zhejiang University for his invaluable help in clarifying and structuring the research ideas for this paper. We thank Ms. Xiaoye Li and the Center for Basic and Translational Research at the Second Affiliated Hospital of Zhejiang University School of Medicine for their laboratory management and technical support. We thank Xiaoxing Wu from the Small Animal Experiment Center of the Second Affiliated Hospital of Zhejiang University School of Medicine for her valuable assistance with our animal studies. We thank Turtle Tech Ltd. (Shanghai, China) for their technical guidance on PCR and for their assistance with primer design and validation. We thank Shanghai Applied Protein Technology Co., Ltd. for their help with proteomics, Jingyao Chen from the core facility plat form of Zhejiang University School of Medicine for their technical support and Shanghai Bioprofile Technology Co., Ltd. for their help with scRNA-seq analysis. We thank Wendi Chen and Jiawen Sun (from Scientific Compass www.shiyanjia.com) for providing invaluable assistance with the material mechanical property testing and the friction experiment related testing, respectively.

Author information

Author notes

  1. These authors contributed equally: Xiaoxiao Ji, Xingzi He, Honglu Cai.

Authors and Affiliations

  1. Department of Orthopedic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China

    Xiaoxiao Ji, Xingzi He, Honglu Cai, Peng Tang, Hao Zhou, Jiajie Wang, Yifan Wu, Jinfeng Zhou, Kaicheng Xu, Changjian Lin, Xiaoyong Wu, Kanbin Wang, Wangmi Liu, Gang Feng, Shigui Yan, Guangyao Jiang, Zihao Qu & Yiying Qi

  2. Orthopedics Research Institute of Zhejiang University, Hangzhou, Zhejiang, China

    Xiaoxiao Ji, Xingzi He, Honglu Cai, Peng Tang, Hao Zhou, Jiajie Wang, Yifan Wu, Jinfeng Zhou, Kaicheng Xu, Changjian Lin, Xiaoyong Wu, Kanbin Wang, Wangmi Liu, Gang Feng, Shigui Yan, Guangyao Jiang, Zihao Qu & Yiying Qi

  3. Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, PR China

    Xiaoxiao Ji, Xingzi He, Honglu Cai, Peng Tang, Hao Zhou, Jiajie Wang, Yifan Wu, Jinfeng Zhou, Kaicheng Xu, Changjian Lin, Xiaoyong Wu, Kanbin Wang, Wangmi Liu, Gang Feng, Shigui Yan, Guangyao Jiang, Zihao Qu & Yiying Qi

  4. Zhejiang Key Laboratory of Motor System Disease Precision Research and Therapy, Hangzhou City, Zhejiang Province, PR China

    Xiaoxiao Ji, Xingzi He, Honglu Cai, Peng Tang, Hao Zhou, Jiajie Wang, Yifan Wu, Jinfeng Zhou, Kaicheng Xu, Changjian Lin, Xiaoyong Wu, Kanbin Wang, Wangmi Liu, Gang Feng, Shigui Yan, Guangyao Jiang, Zihao Qu & Yiying Qi

  5. College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China

    Zhang Lin

  6. State Key Laboratory of Transvascular Implantation Devices, Hangzhou, China

    Yiying Qi

Authors

  1. Xiaoxiao Ji
  2. Xingzi He
  3. Honglu Cai
  4. Peng Tang
  5. Hao Zhou
  6. Jiajie Wang
  7. Yifan Wu
  8. Jinfeng Zhou
  9. Zhang Lin
  10. Kaicheng Xu
  11. Changjian Lin
  12. Xiaoyong Wu
  13. Kanbin Wang
  14. Wangmi Liu
  15. Gang Feng
  16. Shigui Yan
  17. Guangyao Jiang
  18. Zihao Qu
  19. Yiying Qi

Contributions

X.J., X.H., P.T., Y.W., J.Z., K.X., C.L., X.W. and K.W. performed the experimental operations. X.J. and H.C. performed the analysis and visualization of the single-cell data. X.J., Z.Q., J.W. and Z.L. completed the design and preparation of MINH. X.J. and H.Z. completed the related experiments and analysis of p16-3MR mice. Y.Q., Z.Q., G.J., S.Y., W.L. and G.F. supervised this project. X.J. conceived and designed the study. X.J. and Y.Q. completed the conceptual integration and manuscript writing.

Corresponding authors

Correspondence to Guangyao Jiang, Zihao Qu or Yiying Qi.

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Competing interests

The authors declare no competing interests.

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Nature Communications thanks Fernando de la Cuesta and Jing Xie for their contribution to the peer review of this work. A peer review file is available.

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Ji, X., He, X., Cai, H. et al. Recycling senescent cell lipids for targeted senotherapy. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70486-0

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  • DOI: https://doi.org/10.1038/s41467-026-70486-0