Senolytics

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    Senolytics are compounds designed to target and eliminate senescent cells. Senescent cells are cells that have stopped dividing and have entered a state of permanent growth arrest without undergoing cell death, known as apoptosis. Despite their arrested growth, these cells can affect surrounding tissues through their secretion of inflammatory cytokines, growth factors, and proteases, a phenomenon known as the senescence-associated secretory phenotype (SASP).

    Senescent cells accumulate with age and are thought to contribute to various age-related diseases, such as cardiovascular diseases, neurodegenerative disorders, and various types of cancer, by promoting inflammation and tissue dysfunction. By selectively inducing death in senescent cells, senolytics aim to reduce this burden and alleviate age-related ailments, potentially extending healthy lifespan.

    Researchers are investigating various compounds as potential senolytics, including naturally occurring compounds like quercetin, fisetin, and more targeted synthetic drugs. The field is relatively new but rapidly growing, with increasing interest in how clearing senescent cells can improve health and combat diseases associated with aging. However, while promising in preclinical studies, the safety and efficacy of senolytic drugs are still being evaluated in clinical trials.

    See Also

    Todo

    • 2019: Scientists at the Mayo Clinic report the first successful use of senolytics, a new class of drug with potential anti-aging benefits, to remove senescent cells from human patients with a kidney disease.

    [1][2]

    • 2021: Scientists report alternative approach to senolytics for removing senescent cells: invariant NKT (iNKT) cells.[3][4]
    • 2022: Biomedical gerontologists demonstrate a mechanism of anti-aging senolytics, in particular of Dasatinib plus Quercetin (D+Q) – an increase of α-Klotho as shown in mice, human cells and in a human trial.[5][6]
    • 2022: Scientists report that some apparently senescent cells – which are targeted by anti-aging senolytics – are required for regeneration, and suggest tailoring senolytics to precisely target harmful senescent cells while leaving the ones involved in regeneration intact.[7][8]
    • 2023: First senolytics discovered using artificial intelligence:[9][10] Teams from the University of Edinburgh and the Massachusetts Institute of Technology independently report the discovery of senolytics using artificial intelligence for screening large chemical libraries. The works reported compounds of comparable efficacy and increased potency than other known senolytics.[11][12]

    References

    1. ↑ Mayo researchers demonstrate senescent cell burden is reduced in humans by senolytic drugs, https://newsnetwork.mayoclinic.org/discussion/mayo-researchers-demonstrate-senescent-cell-burden-is-reduced-in-humans-by-senolytic-drugs/
    2. ↑ Senolytics decrease senescent cells in humans: Preliminary report from a clinical trial of Dasatinib plus Quercetin in individuals with diabetic kidney disease, https://www.ebiomedicine.com/article/S2352-3964(19)30591-2/pdf
    3. ↑ Template:cite news
    4. ↑ Arora S, Thompson PJ, Wang Y, Bhattacharyya A, Apostolopoulou H, Hatano R, Naikawadi RP, Shah A, Wolters PJ, Koliwad S, Bhattacharya M, Bhushan A; "Invariant Natural Killer T cells coordinate removal of senescent cells" , https://doi.org/10.1016/j.medj.2021.04.014
    5. ↑ Template:cite news
    6. ↑ Zhu Y et al.: Orally-active, clinically-translatable senolytics restore α-Klotho in mice and humans. EBioMedicine 2022. (PMID 35292270) [PubMed] [DOI] [Full text] BACKGROUND: α-Klotho is a geroprotective protein that can attenuate or alleviate deleterious changes with ageing and disease. Declines in α-Klotho play a role in the pathophysiology of multiple diseases and age-related phenotypes. Pre-clinical evidence suggests that boosting α-Klotho holds therapeutic potential. However, readily clinically-translatable, practical strategies for increasing α-Klotho are not at hand. Here, we report that orally-active, clinically-translatable senolytics can increase α-Klotho in mice and humans. METHODS: We examined α-Klotho expression in three different human primary cell types co-cultured with conditioned medium (CM) from senescent or non-senescent cells with or without neutralizing antibodies. We assessed α-Klotho expression in aged, obese, and senescent cell-transplanted mice treated with vehicle or senolytics. We assayed urinary α-Klotho in patients with idiopathic pulmonary fibrosis (IPF) who were treated with the senolytic drug combination, Dasatinib plus Quercetin (D+Q). FINDINGS: We found exposure to the senescent cell secretome reduces α-Klotho in multiple nonsenescent human cell types. This was partially prevented by neutralizing antibodies against the senescence-associated secretory phenotype (SASP) factors, activin A and Interleukin 1α (IL-1α). Consistent with senescent cells' being a cause of decreased α-Klotho, transplanting senescent cells into younger mice reduced brain and urine α-Klotho. Selectively removing senescent cells genetically or pharmacologically increased α-Klotho in urine, kidney, and brain of mice with increased senescent cell burden, including naturally-aged, diet-induced obese (DIO), or senescent cell-transplanted mice. D+Q increased α-Klotho in urine of patients with IPF, a disease linked to cellular senescence. INTERPRETATION: Senescent cells cause reduced α-Klotho, partially due to their production of activin A and IL-1α. Targeting senescent cells boosts α-Klotho in mice and humans. Thus, clearing senescent cells restores α-Klotho, potentially opening a novel, translationally-feasible avenue for developing orally-active small molecule, α-Klotho-enhancing clinical interventions. Furthermore, urinary α-Klotho may prove to be a useful test for following treatments in senolytic clinical trials. FUNDING: This work was supported by National Institute of Health grants AG013925 (J.L.K.), AG062413 (J.L.K., S.K.), AG044271 (N.M.), AG013319 (N.M.), and the Translational Geroscience Network (AG061456: J.L.K., T.T., N.M., S.B.K., S.K.), Robert and Arlene Kogod (J.L.K.), the Connor Group (J.L.K.), Robert J. and Theresa W. Ryan (J.L.K.), and the Noaber Foundation (J.L.K.). The previous IPF clinical trial was supported by the Claude D. Pepper Older Americans Independence Centers at WFSM (AG021332: J.N.J., S.B.K.), UTHSCA (AG044271: A.M.N.), and the Translational Geroscience Network.
    7. ↑ Template:cite news
    8. ↑ Reyes NS et al.: Sentinel p16INK4a+ cells in the basement membrane form a reparative niche in the lung. Science 2022. (PMID 36227993) [PubMed] [DOI] [Full text] We engineered an ultrasensitive reporter of p16INK4a, a biomarker of cellular senescence. Our reporter detected p16INK4a-expressing fibroblasts with certain senescent characteristics that appeared shortly after birth in the basement membrane adjacent to epithelial stem cells in the lung. Furthermore, these p16INK4a+ fibroblasts had enhanced capacity to sense tissue inflammation and respond through their increased secretory capacity to promote epithelial regeneration. In addition, p16INK4a expression was required in fibroblasts to enhance epithelial regeneration. This study highlights a role for p16INK4a+ fibroblasts as tissue-resident sentinels in the stem cell niche that monitor barrier integrity and rapidly respond to inflammation to promote tissue regeneration.
    9. ↑ AI helps discover three drugs which could fight effects of ageing, https://news.sky.com/story/ai-helps-discover-three-drugs-which-could-fight-effects-of-ageing-12902182
    10. ↑ AI finds drugs that could kill 'zombie cells' behind ageing, https://www.thetimes.co.uk/article/ai-finds-drugs-that-could-kill-zombie-cells-behind-ageing-g6929hstl#:~:text=The%20AI%20selected%2021%20compounds,senescent%20drug%20of%20its%20kind
    11. ↑ Smer-Barreto V et al.: Discovery of senolytics using machine learning. Nat Commun 2023. (PMID 37301862) [PubMed] [DOI] [Full text] Cellular senescence is a stress response involved in ageing and diverse disease processes including cancer, type-2 diabetes, osteoarthritis and viral infection. Despite growing interest in targeted elimination of senescent cells, only few senolytics are known due to the lack of well-characterised molecular targets. Here, we report the discovery of three senolytics using cost-effective machine learning algorithms trained solely on published data. We computationally screened various chemical libraries and validated the senolytic action of ginkgetin, periplocin and oleandrin in human cell lines under various modalities of senescence. The compounds have potency comparable to known senolytics, and we show that oleandrin has improved potency over its target as compared to best-in-class alternatives. Our approach led to several hundred-fold reduction in drug screening costs and demonstrates that artificial intelligence can take maximum advantage of small and heterogeneous drug screening data, paving the way for new open science approaches to early-stage drug discovery.
    12. ↑ Wong F et al.: Discovering small-molecule senolytics with deep neural networks. Nat Aging 2023. (PMID 37142829) [PubMed] [DOI] [Full text] The accumulation of senescent cells is associated with aging, inflammation and cellular dysfunction. Senolytic drugs can alleviate age-related comorbidities by selectively killing senescent cells. Here we screened 2,352 compounds for senolytic activity in a model of etoposide-induced senescence and trained graph neural networks to predict the senolytic activities of >800,000 molecules. Our approach enriched for structurally diverse compounds with senolytic activity; of these, three drug-like compounds selectively target senescent cells across different senescence models, with more favorable medicinal chemistry properties than, and selectivity comparable to, those of a known senolytic, ABT-737. Molecular docking simulations of compound binding to several senolytic protein targets, combined with time-resolved fluorescence energy transfer experiments, indicate that these compounds act in part by inhibiting Bcl-2, a regulator of cellular apoptosis. We tested one compound, BRD-K56819078, in aged mice and found that it significantly decreased senescent cell burden and mRNA expression of senescence-associated genes in the kidneys. Our findings underscore the promise of leveraging deep learning to discover senotherapeutics.
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