Does rapamycin slow down time?

Cellular senescence: when growth stimulation meets cell cycle arrest

At the very moment of cell-cycle arrest, the cell is not senescent yet. For several days in cell culture, the arrested cell is acquiring a senescent phenotype. What is happening during this geroconversion? Cellular enlargement (hypertrophy) and hyperfunctions (lysosomal and hyper-secretory) are hallmarks of geroconversion.

Discovery of small molecule mechanistic target of rapamycin inhibitors as anti-aging and anti-cancer therapeutics

To date, the most studied drug in anti-aging research is the mTOR inhibitor - rapamycin. Despite its almost perfect anti-aging profile, rapamycin exerts one significant limitation - inappropriate physicochemical properties. Therefore, we have decided to utilize virtual high-throughput screening and fragment-based design in search of novel mTOR inhibiting scaffolds with suitable physicochemical parameters. Seven lead compounds were selected from the list of obtained hits that were commercially available (4, 5, and 7) or their synthesis was feasible (1, 2, 3, and 6) and evaluated in vitro and subsequently in vivo. Of all these substances, only compound 3 demonstrated a significant cytotoxic, senolytic, and senomorphic effect on normal and cancerous cells. Further, it has been confirmed that compound 3 is a direct mTORC1 inhibitor. Last but not least, compound 3 was found to exhibit anti-SASP activity concurrently being relatively safe within the test of in vivo tolerability. All these outstanding results highlight compound 3 as a scaffold worthy of further investigation.

The hyperfunction theory: An emerging paradigm for the biology of aging

The process of senescence (aging) is predominantly determined by the action of wild-type genes. For most organisms, this does not reflect any adaptive function that senescence serves, but rather evolutionary effects of declining selection against genes with deleterious effects later in life. To understand aging requires an account of how evolutionary mechanisms give rise to pathogenic gene action and late-life disease, that integrates evolutionary (ultimate) and mechanistic (proximate) causes into a single explanation. A well-supported evolutionary explanation by G.C. Williams argues that senescence can evolve due to pleiotropic effects of alleles with antagonistic effects on fitness and late-life health (antagonistic pleiotropy, AP). What has remained unclear is how gene action gives rise to late-life disease pathophysiology. One ultimate-proximate account is T.B.L. Kirkwood's disposable soma theory. Based on the hypothesis that stochastic molecular damage causes senescence, this reasons that aging is coupled to reproductive fitness due to preferential investment of resources into reproduction, rather than somatic maintenance. An alternative and more recent ultimate-proximate theory argues that aging is largely caused by programmatic, developmental-type mechanisms. Here ideas about AP and programmatic aging are reviewed, particularly those of M.V. Blagosklonny (the hyperfunction theory) and J.P. de Magalhães (the developmental theory), and their capacity to make sense of diverse experimental findings is assessed.

The hoverfly and the wasp: A critique of the hallmarks of aging as a paradigm

With the goal of representing common denominators of aging in different organisms López-Otín et al. in 2013 described nine hallmarks of aging. Since then, this representation has become a major reference point for the biogerontology field. The template for the hallmarks of aging account originated from landmark papers by Hanahan and Weinberg (2000, 2011) defining first six and later ten hallmarks of cancer. Here we assess the strengths and weaknesses of the hallmarks of aging account. As a checklist of diverse major foci of current aging research, it has provided a useful shared overview for biogerontology during a time of transition in the field. It also seems useful in applied biogerontology, to identify interventions (e.g. drugs) that impact multiple symptomatic features of aging. However, while the hallmarks of cancer provide a paradigmatic account of the causes of cancer with profound explanatory power, the hallmarks of aging do not. A worry is that as a non-paradigm the hallmarks of aging have obscured the urgent need to define a genuine paradigm, one that can provide a useful basis for understanding the mechanistic causes of the diverse aging pathologies. We argue that biogerontology must look and move beyond the hallmarks to understand the process of aging.

Rapamycin Inhibits Glioma Cells Growth and Promotes Autophagy by miR-26a-5p/DAPK1 Axis

Background

Glioma is a common intracranial malignant tumor with high rates of invasiveness and mortality. This study aimed to investigate the mechanism of rapamycin in glioma.

Methods

U118-MG cells were treated with and without rapamycin in vivo and then collected for RNA sequencing. Differentially expressed miRNAs (DEMs) were screened and verified. MiR-26a-5p was selected for functional verification, and the target gene of miR-26a-5p was identified. The effects of miR-26a-5p on cell proliferation, cell cycle, apoptosis, and autophagy were also investigated.

Results

In total, 58 up-regulated and 41 down-regulated DEMs were identified between rapamycin-treated and untreated U118-MG cells. MiR-26-5p levels were up-regulated in U118-MG cells treated with 12.5 μM rapamycin, and death-associated protein kinase 1 (DAPK1) expression, a direct miR-26a-5p target gene, was down-regulated. Rapamycin substantially inhibited cell proliferation and cell percentage in the S phase and promoted cell apoptosis; miR-26a-5p inhibitor increased cell proliferation and cell cycle and decreased cell apoptosis; DAPK1 overexpression further induced cell proliferation, increased the cell number in the S phase, and inhibited apoptosis in glioma cells. Notably, rapamycin increased the autophagy-related Beclin1 protein expression levels and the LC3 II/I ratio.

Conclusion

Rapamycin exerts anti-tumor effects by promoting autophagy in glioma cells, which was dependent on the miR-26a-5p/DAPK1 pathway activation by rapamycin.

DNA- and telomere-damage does not limit lifespan: evidence from rapamycin

Failure of rapamycin to extend lifespan in DNA repair mutant and telomerase-knockout mice, while extending lifespan in normal mice, indicates that neither DNA damage nor telomere shortening limits normal lifespan or causes normal aging.

From causes of aging to death from COVID-19

COVID-19 is not deadly early in life, but mortality increases exponentially with age, which is the strongest predictor of mortality. Mortality is higher in men than in women, because men age faster, and it is especially high in patients with age-related diseases, such as diabetes and hypertension, because these diseases are manifestations of aging and a measure of biological age. At its deepest level, aging (a program-like continuation of developmental growth) is driven by inappropriately high cellular functioning. The hyperfunction theory of quasi-programmed aging explains why COVID-19 vulnerability (lethality) is an age-dependent syndrome, linking it to other age-related diseases. It also explains inflammaging and immunosenescence, hyperinflammation, hyperthrombosis, and cytokine storms, all of which are associated with COVID-19 vulnerability. Anti-aging interventions, such as rapamycin, may slow aging and age-related diseases, potentially decreasing COVID-19 vulnerability.

PhotoAgeClock: deep learning algorithms for development of non-invasive visual biomarkers of aging

Aging biomarkers are the qualitative and quantitative indicators of the aging processes of the human body. Estimation of biological age is important for assessing the physiological state of an organism. The advent of machine learning lead to the development of the many age predictors commonly referred to as the “aging clocks” varying in biological relevance, ease of use, cost, actionability, interpretability, and applications. Here we present and investigate a novel non-invasive class of visual photographic biomarkers of aging. We developed a simple and accurate predictor of chronological age using just the anonymized images of eye corners called the PhotoAgeClock. Deep neural networks were trained on 8414 anonymized high-resolution images of eye corners labeled with the correct chronological age. For people within the age range of 20 to 80 in a specific population, the model was able to achieve a mean absolute error of 2.3 years and 95% Pearson and Spearman correlation.

Rapamycin, proliferation and geroconversion to senescence

Rapamycin inhibits cell proliferation, yet preserves (re)-proliferative potential (RPP). RPP is a potential of quiescent cells that is lost in senescent cells. mTOR drives conversion from quiescence to senescence (geroconversion). By suppressing geroconversion, rapamycin preserves RPP. Geroconversion is characterized by proliferation-like levels of phospho-S6K/S6/4E-BP1 in nonproliferating cells arrested by p16 and/or p21. mTOR-driven geroconversion is associated with cellular hyperfunction, which in turn leads to organismal aging manifested by age-related diseases.