Cardiac glycosides are broad-spectrum senolytics

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Abstract

Senescence is a cellular stress response that results in the stable arrest of old, damaged or pre-neoplastic cells. Oncogene-induced senescence is tumour suppressive but can also exacerbate tumorigenesis through the secretion of proinflammatory factors from senescent cells. Drugs that selectively kill senescent cells, termed ‘senolytics’, have proved beneficial in animal models of many age-associated diseases. In the present study, we show that the cardiac glycoside ouabain is a senolytic agent with broad activity. Senescent cells are sensitized to ouabain-induced apoptosis, a process mediated in part by induction of the proapoptotic Bcl-2 family protein NOXA. We demonstrate that cardiac glycosides synergize with anti-cancer drugs to kill tumour cells and eliminate senescent cells that accumulate after irradiation or in old mice. Ouabain also eliminates senescent pre-neoplastic cells. The findings of the present study suggest that cardiac glycosides may be effective anti-cancer drugs by acting through multiple mechanisms. Given the broad range of senescent cells targeted by cardiac glycosides, their use against age-related diseases warrants further exploration.

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Fig. 1: Drug screens identify ouabain as a broad-spectrum senolytic.
Fig. 2: CGs induce apoptosis of senescent cells.
Fig. 3: Mechanism explaining the senolytic properties of CGs.
Fig. 4: Ouabain selectively eliminates cells undergoing oncogene-induced senescence.
Fig. 5: Dual benefits of treatment with ouabain on therapy-induced senescence.
Fig. 6: Ouabain resets immune infiltration in old mice.

Data availability

The data that support the findings of this study are available from the corresponding author upon request. The RNA-seq data generated in the present study have been deposited in the Gene Expression Omnibus database under accession number GSE122081. Source data for Figs. 16, Extended Data Figs. 19 and Supplementary Figs. 1, 2 and 47 are available online.

References

  1. 1.

    Kuilman, T., Michaloglou, C., Mooi, W. J. & Peeper, D. S. The essence of senescence. Genes Dev. 24, 2463–2479 (2010).

  2. 2.

    Herranz, N. & Gil, J. Mechanisms and functions of cellular senescence. J. Clin. Invest. 128, 1238–1246 (2018).

  3. 3.

    Salama, R., Sadaie, M., Hoare, M. & Narita, M. Cellular senescence and its effector programs. Genes Dev. 28, 99–114 (2014).

  4. 4.

    Coppe, J. P., Desprez, P. Y., Krtolica, A. & Campisi, J. The senescence-associated secretory phenotype: the dark side of tumor suppression. Annu. Rev. Pathol. 5, 99–118 (2010).

  5. 5.

    Kang, T. W. et al. Senescence surveillance of pre-malignant hepatocytes limits liver cancer development. Nature 479, 547–551 (2011).

  6. 6.

    Acosta, J. C. et al. A complex secretory program orchestrated by the inflammasome controls paracrine senescence. Nat. Cell Biol. 15, 978–990 (2013).

  7. 7.

    Tchkonia, T., Zhu, Y., van Deursen, J., Campisi, J. & Kirkland, J. L. Cellular senescence and the senescent secretory phenotype: therapeutic opportunities. J. Clin. Invest. 123, 966–972 (2013).

  8. 8.

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

  9. 9.

    Munoz-Espin, D. & Serrano, M. Cellular senescence: from physiology to pathology. Nat. Rev. Mol. Cell Biol. 15, 482–496 (2014).

  10. 10.

    Baker, D. J. et al. Clearance of p16Ink4a-positive senescent cells delays ageing-associated disorders. Nature 479, 232–236 (2011).

  11. 11.

    Demaria, M. et al. An essential role for senescent cells in optimal wound healing through secretion of PDGF-AA. Dev. Cell 31, 722–733 (2014).

  12. 12.

    Baker, D. J. et al. Naturally occurringp16(Ink4a)-positive cells shorten healthy lifespan. Nature 530, 184–189 (2016).

  13. 13.

    Childs, B. G. et al. Senescent intimal foam cells are deleterious at all stages of atherosclerosis. Science 354, 472–477 (2016).

  14. 14.

    Jeon, O. H. 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).

  15. 15.

    Chinta, S. J. et al. Cellular senescence is induced by the environmental neurotoxin paraquat and contributes to neuropathology linked to Parkinson’s disease. Cell Rep. 22, 930–940 (2018).

  16. 16.

    Bussian, T. J. et al. Clearance of senescent glial cells prevents tau-dependent pathology and cognitive decline. Nature 562, 578–582 (2018).

  17. 17.

    Zhu, Y. et al. The Achilles’ heel of senescent cells: from transcriptome to senolytic drugs. Aging Cell 14, 644–658 (2015).

  18. 18.

    Wang, Y. et al. Discovery of piperlongumine as a potential novel lead for the development of senolytic agents. Aging (Albany NY) 8, 2915–2926 (2016).

  19. 19.

    Fuhrmann-Stroissnigg, H. et al. Identification of HSP90 inhibitors as a novel class of senolytics. Nat. Commun. 8, 422 (2017).

  20. 20.

    Chen, Q. et al. ABT-263 induces apoptosis and synergizes with chemotherapy by targeting stemness pathways in esophageal cancer. Oncotarget 6, 25883–25896 (2015).

  21. 21.

    Zhu, Y. et al. Identification of a novel senolytic agent, navitoclax, targeting the Bcl-2 family of anti-apoptotic factors. Aging Cell 15, 428–435 (2016).

  22. 22.

    Yosef, R. et al. Directed elimination of senescent cells by inhibition of BCL-W and BCL-XL. Nat. Commun. 7, 11190 (2016).

  23. 23.

    Ovadya, Y. & Krizhanovsky, V. Strategies targeting cellular senescence. J. Clin. Invest. 128, 1247–1254 (2018).

  24. 24.

    Georgilis, A. et al. PTBP1-mediated alternative splicing regulates the inflammatory secretome and the pro-tumorigenic effects of senescent cells. Cancer Cell 34, 85–102 e109 (2018).

  25. 25.

    Therien, A. G. & Blostein, R. Mechanisms of sodium pump regulation. Am. J. Physiol. Cell Physiol. 279, C541–C566 (2000).

  26. 26.

    Prassas, I. & Diamandis, E. P. Novel therapeutic applications of cardiac glycosides. Nat. Rev. Drug Discov. 7, 926–935 (2008).

  27. 27.

    Cheng, J. W. & Rybak, I. Use of digoxin for heart failure and atrial fibrillation in elderly patients. Am. J. Geriatr. Pharmacother. 8, 419–427 (2010).

  28. 28.

    Lopez-Lazaro, M. Digitoxin as an anticancer agent with selectivity for cancer cells: possible mechanisms involved. Expert Opin. Ther. Targets 11, 1043–1053 (2007).

  29. 29.

    Kurz, D. J., Decary, S., Hong, Y. & Erusalimsky, J. D. Senescence-associated (beta)-galactosidase reflects an increase in lysosomal mass during replicative ageing of human endothelial cells. J. Cell Sci. 113, 3613–3622 (2000).

  30. 30.

    Hildebrand, D. G. et al. alpha-Fucosidase as a novel convenient biomarker for cellular senescence. Cell Cycle 12, 1922–1927 (2013).

  31. 31.

    Dao, T. T. et al. Demethoxycurcumin is A potent inhibitor of P-Type ATPases from diverse kingdoms of life. PLoS ONE 11, e0163260 (2016).

  32. 32.

    Price, E. M. & Lingrel, J. B. Structure-function relationships in the Na,K-ATPase alpha subunit: site-directed mutagenesis of glutamine-111 to arginine and asparagine-122 to aspartic acid generates a ouabain-resistant enzyme. Biochemistry 27, 8400–8408 (1988).

  33. 33.

    Sieben, C. J., Sturmlechner, I., van de Sluis, B. & van Deursen, J. M. Two-step senescence-focused cancer therapies. Trends Cell Biol. 28, 723–737 (2018).

  34. 34.

    Collado, M. et al. Tumour biology: senescence in premalignant tumours. Nature 436, 642 (2005).

  35. 35.

    Michaloglou, C. et al. BRAFE600-associated senescence-like cell cycle arrest of human naevi. Nature 436, 720–724 (2005).

  36. 36.

    Braig, M. et al. Oncogene-induced senescence as an initial barrier in lymphoma development. Nature 436, 660–665 (2005).

  37. 37.

    Chen, Z. et al. Crucial role of p53-dependent cellular senescence in suppression of Pten-deficient tumorigenesis. Nature 436, 725–730 (2005).

  38. 38.

    Gonzalez-Meljem, J. M. et al. Stem cell senescence drives age-attenuated induction of pituitary tumours in mouse models of paediatric craniopharyngioma. Nat. Commun. 8, 1819 (2017).

  39. 39.

    Gaston-Massuet, C. et al. Increased Wingless (Wnt) signaling in pituitary progenitor/stem cells gives rise to pituitary tumors in mice and humans. Proc. Natl Acad. Sci. USA 108, 11482–11487 (2011).

  40. 40.

    Schmitt, C. A. et al. A senescence program controlled by p53 and p16INK4a contributes to the outcome of cancer therapy. Cell 109, 335–346 (2002).

  41. 41.

    Demaria, M. et al. Cellular senescence promotes adverse effects of chemotherapy and cancer relapse. Cancer Discov. 7, 165–176 (2016).

  42. 42.

    Wang, L. et al. High-throughput functional genetic and compound screens identify targets for senescence induction in cancer. Cell Rep. 21, 773–783 (2017).

  43. 43.

    Wang, L. & Bernards, R. Taking advantage of drug resistance, a new approach in the war on cancer. Front. Med. 12, 490–495 (2018).

  44. 44.

    Rudalska, R. et al. In vivo RNAi screening identifies a mechanism of sorafenib resistance in liver cancer. Nat. Med. 20, 1138–1146 (2014).

  45. 45.

    Chang, J. et al. Clearance of senescent cells by ABT263 rejuvenates aged hematopoietic stem cells in mice. Nat. Med. 22, 78–83 (2016).

  46. 46.

    Childs, B. G., Durik, M., Baker, D. J. & van Deursen, J. M. Cellular senescence in aging and age-related disease: from mechanisms to therapy. Nat. Med. 21, 1424–1435 (2015).

  47. 47.

    Selden, R. & Smith, T. W. Ouabain pharmacokinetics in dog and man. Determination by radioimmunoassay. Circulation 45, 1176–1182 (1972).

  48. 48.

    Salive, M. E. et al. Serum albumin in older persons: relationship with age and health status. J. Clin. Epidemiol. 45, 213–221 (1992).

  49. 49.

    Aran, D., Hu, Z. & Butte, A. J. xCell: digitally portraying the tissue cellular heterogeneity landscape. Genome Biol. 18, 220 (2017).

  50. 50.

    Wilson, W. H. et al. Navitoclax, a targeted high-affinity inhibitor of BCL-2, in lymphoid malignancies: a phase 1 dose-escalation study of safety, pharmacokinetics, pharmacodynamics, and antitumour activity. Lancet Oncol. 11, 1149–1159 (2010).

  51. 51.

    Childs, B. G. et al. Senescent cells: an emerging target for diseases of ageing. Nat. Rev. Drug Discov. 16, 718–735 (2017).

  52. 52.

    Triana-Martínez, F. et al. Identification and characterization of cardiac glycosides as senolytic compounds. Nat. Commun. https://doi.org/10.1038/s41467-019-12888-x (2019).

  53. 53.

    Mijatovic, T. et al. Cardiotonic steroids on the road to anti-cancer therapy. Biochim. Biophys. Acta 1776, 32–57 (2007).

  54. 54.

    Menger, L. et al. Cardiac glycosides exert anticancer effects by inducing immunogenic cell death. Sci. Transl. Med. 4, 143ra199 (2012).

  55. 55.

    Shi, H. et al. Digoxin reduces atherosclerosis in apolipoprotein E-deficient mice. Br. J. Pharm. 173, 1517–1528 (2016).

  56. 56.

    Li, B. et al. Ouabain ameliorates bleomycin induced pulmonary fibrosis by inhibiting proliferation and promoting apoptosis of lung fibroblasts. Am. J. Transl. Res. 10, 2967–2974 (2018).

  57. 57.

    Whayne, T. F. Jr. Clinical use of digitalis: a state of the art review. Am. J. Cardiovasc. Drugs 18, 427–440 (2018).

  58. 58.

    Banito, A. et al. Senescence impairs successful reprogramming to pluripotent stem cells. Genes Dev. 23, 2134–2139 (2009).

  59. 59.

    Barradas, M. et al. Histone demethylase JMJD3 contributes to epigenetic control of INK4a/ARF by oncogenic RAS. Genes Dev. 23, 1177–1182 (2009).

  60. 60.

    Agostini, S. et al. Inhibition of non canonical HIV-1 Tat secretion through the cellular Na+,K+-ATPase blocks HIV-1 infection. EBioMedicine 21, 170–181 (2017).

  61. 61.

    Fellmann, C. et al. An optimized microRNA backbone for effective single-copy RNAi. Cell Rep. 5, 1704–1713 (2013).

  62. 62.

    Tordella, L. et al. SWI/SNF regulates a transcriptional program that induces senescence to prevent liver cancer. Genes Dev. 30, 2187–2198 (2016).

  63. 63.

    Herranz, N. et al. mTOR regulates MAPKAPK2 translation to control the senescence-associated secretory phenotype. Nat. Cell Biol. 17, 1205–1217 (2015).

  64. 64.

    Andoniadou, C. L. et al. Lack of the murine homeobox gene Hesx1 leads to a posterior transformation of the anterior forebrain. Development 134, 1499–1508 (2007).

  65. 65.

    Harada, N. et al. Intestinal polyposis in mice with a dominant stable mutation of the beta-catenin gene. EMBO J. 18, 5931–5942 (1999).

  66. 66.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

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Acknowledgements

We are grateful to members of J. Gil’s laboratory for reagents, comments and other contributions to this project. We thank R. Laberge and A. Bhushan for feedback and members of the Genomics LMS facility (L. Game, K. Rekopoulou and A. Ivan) for help with RNA-seq. Core support from Medical Research Council (MRC; MC_U120085810) and grants from Worlwide Cancer Research (WCR; 18-0215), LifeArc and Unity Biotechnology funded this research in J. Gil’s laboratory. D.J.W. was funded by a Wellcome Trust Strategic Award (no. 098565) and core support from the MRC (MC-A654-5QB40). L.Z. is supported by the German Research Foundation: DFG EXC 2180–390900677 (‘Image Guided and Functionally Instructed Tumour Therapies’); FOR2314, SFB-TR209, Gottfried Wilhelm Leibniz Program; the German Ministry for Education and Research: eMed/Multiscale HCC; the European Research Council: Concolidartor grant ‘CholangioConcept’; and the German Centre for Translational Cancer Research. J.P.M.-B. was funded by the Brain Tumour Charity (SIGNAL and EVEREST), Great Ormond Street Hospital (GOSH) Children’s Charity and the National Institute of Health Research Biomedical Research Centre at GOSH for Children NHS Foundation Trust and University College London. J.P.M.-B. is a GOSH for Children’s Charity Principal Investigator. S.M. is a PhD fellow funded by Boehringer Ingelheim Fonds.

Author information

A.G. and N.H. performed, designed and analysed the experiments, and wrote the manuscript. B.S., V.W., A.J.I., J. Birch, J.H., A.O., S.G., R.G., K.W., J.P., E.E.I., D.H., J. Glegola and S.M. performed, designed and analysed the experiments. G.D. carried out the bioinformatics analysis. J. Behmoaras, D.D., A.G.U., L.Z., S.V., J.P.M.-B. and D.J.W. designed the experiments and secured funding. J. Gil conceived and designed the project, secured funding and wrote the manuscript, with all authors providing feedback.

Correspondence to Jesús Gil.

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Competing interests

J. Gil owns equity and has acted as a consultant for Unity Biotechnology and Geras Bio. Unity Biotechnology funded research on senolytics in J. Gil’s laboratory. J. Gil, A.G. and N.H. are named inventors in an MRC patent related to senolytic therapies (PCT/GB2018/051437).

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Peer review information Primary Handling Editor: Christoph Schmitt.

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Extended data

Extended Data Fig. 1 IMR90 ER:RAS cells as a model of OIS.

a, Quantification of immunofluorescence staining for BrdU, p16INK4a, and SA-β-Galactosidase of IMR90 ER:RAS cells 6 or 8 days after treatment with 4-OHT or vehicle (DMSO) (n = 3). b, Representative immunofluorescence images. BrdU incorporation, which indicates proliferation, is stained green; p16INK4a is stained red. Scale bar, 50 μm. SA-β-Galactosidase is stained red. Scale bar, 100 μm. c, Expression levels for IL8 and IL1A of senescent and control IMR90 ER:RAS cells 6 days after 4-OHT or vehicle (DMSO) (n = 4). d, DAPI staining of senescent and control IMR90 ER:RAS cells after 1 μM ABT-263 treatment for 3 days showing reduced numbers of senescent cells after ABT-263 treatment. Scale bar, 100 μm. e, Senolytic activity of the indicated drugs in the context of oncogene-induced senescence in IMR90 ER:RAS cells (n = 4). f, Quantification of immunofluorescence staining for BrdU in IMR90 ER:RAS cells expressing E6 and E7 proteins of HPV16 (n = 3). g, Senolytic activity of the indicated drugs in IMR90 ER:RAS cells expressing E6 and E7 proteins of HPV16. All error bars represent mean ± s.d; n represents independent experiments. All statistical significances were calculated using unpaired two-tailed Student’s t-tests. Source data

Extended Data Fig. 2 Senolytic drug screen in therapy-induced senescence.

a, Quantification of immunofluorescence staining for BrdU, SA-β-Galactosidase activity, p21CIP1 and 53BP1 in IMR90 cells treated with 50 μM etoposide (n = 3). bc, Senolytic activity of the indicated drugs in the context of therapy-induced senescence in IMR90 (n = 4, b) and oncogene-induced senescence in IMR90 ER:RAS cells (n = 4, c). All error bars represent mean ± s.d; n represents independent experiments. All statistical significances were calculated using unpaired two-tailed Student’s t-tests. Source data

Extended Data Fig. 3 The glycoside chain in CGs is dispensable for their senolytic activity.

a, Dose response analysis of senolytic activity of ouabain in IMR90, control IMR90 ER:RAS cells (DMSO), senescent IMR90 ER:RAS cells (4-OHT) and IMR90 ER:RAS cells expressing E6 and E7 proteins of HPV16 (n = 3). b, Dose response analysis of senolytic activity of digitoxin in the context of oncogene-induced senescence in IMR90 ER:RAS cells (n = 3). c, Chemical structure of ouabain and its aglycone version, ouabagenin. d, Quantification of cell survival in senescent and control IMR90 ER:RAS cells after treatment with ouabagenin, the aglycone version of ouabain (n = 6). ef, Quantification of cell survival of IMR90 ER:RAS cells undergoing OIS and the corresponding controls after treatment with the CG K-Strophanthin (e) (n = 4) or its aglycone version Strophanthidin (f) (n = 5). g, Quantification of cell survival in senescent and control IMR90 ER:RAS 3 days after 1 μM ABT-263 or treatment with CGs (50 nM ouabain, 100 nM digoxin). Senolytic drugs were added 8 days after 4-OHT or vehicle (DMSO) (n = 4). All error bars represent mean ± s.d; n represents independent experiments. All statistical significances were calculated using unpaired two-tailed Student’s t-tests. Source data

Extended Data Fig. 4 Senescent cells are more sensitive to CGs due to their altered osmotic balance.

a, Quantification of cell survival of senescent and control IMR90 ER:RAS cells after treatment with curcumin (n = 6). Statistical significance was calculated using unpaired two-tailed, Student’s t-test. b, Experimental design for the transcriptional profiling of senescent and control IMR90 ER:RAS cells after treatment with cardiac glycosides (CGs). QVD indicates treatment with a general caspase inhibitor (Q-VD-OPh). c, IMR90 ER:RAS cells were transfected with 2 independent siRNAs targeting BCL-2 family genes at day 6 after senescence induction as indicated in the scheme. d, IMR90 ER:RAS were transfected with at least two independent siRNAs targeting BCL-2 family genes at day 6 after senescence induction (n = 3; scrambled siRNA versus three different siRNAs against NOXA, ***P < 0.001). The timeline of the experiment is shown in (c). Statistical significance was calculated using one-way ANOVA (Dunnett’s test). e, Expression levels of NOXA after knock down with three independent siRNAs (n = 3). Statistical significance was calculated using one-way ANOVA (Dunnett’s test). f, Expression levels of NOXA after knock down with four independent shRNAs (n = 3; vector versus different shRNAs against NOXA, ****P < 0.0001). Statistical significance was calculated using one-way ANOVA (Dunnett’s test). All error bars represent mean ± s.d; n represents independent experiments. Source data

Extended Data Fig. 5 Ouabain eliminates liver preneoplastic senescent cells.

a, Representative images of immunofluorescence staining of Nras. Mice were treated with vehicle (n = 9) or ouabain (n = 12) as explained in Fig 4a. Nras is stained in red. Scale bar, 70 μm. b, Immunofluorescence staining and quantification of p21Cip1 in Nras-positive senescent hepatocytes vs Nras-negative normal hepatocytes. Nras is stained in green, p21Cip1 is stained in red. White arrows indicate Nras-positive, p21Cip1-positive cells; green arrow indicates a Nras-positive, p21Cip1-negative cells (n = 10 per group). c, SCID/beige mice were treated with saline or Digoxin (1mg/kg) on two consecutive days, 5 days after hydrodynamic transduction of Nras-GFP. Mice were culled 6 hours after the second treatment. Representative images of immunofluorescence staining of GFP and cleaved caspase-3 and quantification of intensity levels in 1/2 independent experiments (n = 200 cells). Scale bar, 50 μm. Statistical significance was calculated using unpaired two-tailed Student’s t-test. Data represent mean ± s.d; n represents number of mice. Source data

Extended Data Fig. 6 Ouabain eliminates preneoplastic senescent cells.

a, Representative images of immunofluorescence staining of β-catenin (green) and synaptophysin (red) in tumoral pituitaries from 18.5 dpc Hesx1Cre/+;Ctnnb1lox(ex3)/+ mice that were cultured in the presence of either ABT-737 (2.5 μM), ouabain (250 nM and 500 nM) or vehicle (DMSO) (n = 10 per group). Scale bar, 50 μm. b, Quantitative analysis of the immunofluorescence in (a) demonstrates that ABT-737 and ouabain significantly reduce the number of β-catenin-positive cells. Statistical significance was calculated using Kruskal-Wallis and Dunn’s multiple comparisons test. c, Representative images of immunofluorescence staining of ACTH (adrenocorticotropic hormone; magenta). Scale bar: 50μm. d, qRT-PCR analysis revealing that the senescent marker Cdkn1a (encoding for p21Cip1) and the SASP components Il1b and Il6 are reduced in neoplastic pituitaries treated with 100 nM ouabain and 100 nM digoxin relative to vehicle controls (n = 3 per group). Statistical significance was calculated using unpaired two-tailed Student’s t-test; data represent mean ± s.d; n represents number of mice. Source data

Extended Data Fig. 7 Anti-cancer effect of cardiac glycosides across different human cancer cell lines.

ab, Quantification of cell survival by trypan blue staining of Huh7 cells (a) and HLF cells (b) after treatment with the indicated drug combinations (n = 3). Timeline of the experiment is shown in Supplementary Fig 4a. Statistical significance was calculated using unpaired two-tailed Student’s t-test. c, Quantification of cell survival of senescent (alisertib, palbociclib) and control (DMSO) SK-Mel-5 melanoma cells (n = 4). Statistical significance was calculated using two-way ANOVA (Dunnett’s test). d, Quantification of cell survival of senescent (doxorubicin, palbociclib) and control (DMSO) MCF7 or MCF7 breast cancer cells infected with a shRNA against TP53 (n = 4). Statistical significance was calculated using two-way ANOVA (Dunnett’s test). ef, mRNA expression levels of TP53 in MCF7 cells (e) and HCT116 cells (n = 3). Statistical significance was calculated using unpaired two-tailed, Student’s t-test. Data represent mean ± s.d; n represents independent experiments; ns, not significant. Source data

Extended Data Fig. 8 Ouabain treatment reverses age-associated changes in old mice.

a, Ouabain levels in plasma were assessed by ELISA 24 hours after finishing a 4-day course of daily 1mg/kg ouabain i.p. injections. (n = 6). b, Phosphate and amylase levels of young (n = 7) and old mice, either treated with vehicle (n = 6) or ouabain (n = 9), were determined in whole-blood samples at the endpoint of the experiment. Statistical significance was calculated using unpaired two-tailed Student’s t-test. c, Grip strength assessment in old mice treated with vehicle (n = 7) or ouabain (n = 9) 10 weeks after the start of the experiment, referred to the basal test. Statistical significance was calculated using unpaired two-tailed Student’s t-test. d, Expression levels of p16Ink4a in heart and kidney were determined by qRT-PCR following treatment with vehicle (n = 6) or ouabain (n = 7). mRNA expression levels in young mice (n = 7) were used as reference. Statistical significance was calculated using unpaired two-tailed Student’s t-test. ef, GSEA signature for chemokines, oncogene-induced senescence (e) and ageing (f). g, Quantitative analysis (left) and representative IHC pictures (right) of p21Cip1 positive hepatocytes in the liver of young (n = 6) and old mice treated with ouabain (n = 8) or vehicle (saline) (n = 6). Scale bar, 100 μm. Data represent mean ± s.e.m. Statistical significance was calculated using one-way ANOVA with Tukey’s post hoc comparison. h, Quantitative analysis (left) and representative IHC pictures (right) of LINE-1 ORF in the liver of young (n = 6) and old mice treated with ouabain (n = 8) or vehicle (saline) (n = 7). Statistical significance was calculated using one-way ANOVA with Tukey’s post hoc comparison. Scale bar, 50 μm. Data represent mean ± s.d; n represents number of mice. Source data

Extended Data Fig. 9 Ouabain treatment resets immune infiltration in old mice.

a, xCell analysis of the transcriptome data predicts changes in immune infiltration in the liver of old mice that could be reverted with ouabain. RNA-Seq data from the livers of young (n = 6) and old mice, either treated with vehicle (n = 6) or ouabain (n = 6) was used. Statistical significance was calculated using unpaired two-tailed Student’s t-test. b, Blood analysis at the end of the experiment show that ouabain treatment does not change immune composition. Blood from young (n = 8) and old mice, either treated with vehicle (n = 6) or ouabain (n = 8) was used. Statistical significance was calculated using unpaired two-tailed Student’s t-test. cd, Representative IHC images (c) and quantification (d) of the indicated immune cell markers in the liver of young (n = 6) and old mice, either treated with vehicle (n = 6) or ouabain (n = 8). Scale bar: 100µm. Statistical significance was calculated using one-way ANOVA with Tukey’s post hoc comparison. Data represent mean ± s.e.m.; n represents number of mice; ns, not significant. Source data

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Guerrero, A., Herranz, N., Sun, B. et al. Cardiac glycosides are broad-spectrum senolytics. Nat Metab (2019) doi:10.1038/s42255-019-0122-z

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