Ageing is the biggest risk factor for cardiovascular disease. Cellular senescence, a process driven in part by telomere shortening, has been implicated in age‐related tissue dysfunction. Here, we address the question of how senescence is induced in rarely dividing/post‐mitotic cardiomyocytes and investigate whether clearance of senescent cells attenuates age‐related cardiac dysfunction. During ageing, human and murine cardiomyocytes acquire a senescent‐like phenotype characterised by persistent DNA damage at telomere regions that can be driven by mitochondrial dysfunction and crucially can occur independently of cell division and telomere length. Length‐independent telomere damage in cardiomyocytes activates the classical senescence‐inducing pathways, p21CIP and p16INK4a, and results in a non‐canonical senescence‐associated secretory phenotype, which is pro‐fibrotic and pro‐hypertrophic. Pharmacological or genetic clearance of senescent cells in mice alleviates detrimental features of cardiac ageing, including myocardial hypertrophy and fibrosis. Our data describe a mechanism by which senescence can occur and contribute to age‐related myocardial dysfunction and in the wider setting to ageing in post‐mitotic tissues.

Cardiovascular disease is the leading cause of death in individuals over 60 years old. Aging is associated with an increased prevalence of coronary artery disease and a poorer prognosis following acute myocardial infarction (MI). With age, senescent cells accumulate in tissues, including the heart, and contribute to age‐related pathologies. However, the role of senescence in recovery following MI has not been investigated. In this study, we demonstrate that treatment of aged mice with the senolytic drug, navitoclax, eliminates senescent cardiomyocytes and attenuates profibrotic protein expression in aged mice. Importantly, clearance of senescent cells improved myocardial remodelling and diastolic function as well as overall survival following MI. These data provide proof‐of‐concept evidence that senescent cells are major contributors to impaired function and increased mortality following MI and that senolytics are a potential new therapeutic avenue for MI.

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Highlights Studies have demonstrated that senescence contributes to the pathophysiology of several age-related cardiovascular diseases. Senolytics eliminate senescent cells in cardiovascular tissues and prevent or reverse disease progression. While this data is encouraging, questions remain regarding the potential short and long-term detrimental effects of senolytic mediated apoptosis.

BackgroundMass spectrometric analysis of the blood proteome is an emerging method of clinical proteomics. The approach exploiting multi-protein/peptide sets (fingerprints) detected by mass spectrometry that reflect overall features of a specimen's proteome, termed proteome pattern analysis, have been already shown in several studies to have applicability in cancer diagnostics. We aimed to identify serum proteome patterns specific for early stage breast cancer patients using MALDI-ToF mass spectrometry.MethodsBlood samples were collected before the start of therapy in a group of 92 patients diagnosed at stages I and II of the disease, and in a group of age-matched healthy controls (104 women). Serum specimens were purified and the low-molecular-weight proteome fraction was examined using MALDI-ToF mass spectrometry after removal of albumin and other high-molecular-weight serum proteins. Protein ions registered in a mass range between 2,000 and 10,000 Da were analyzed using a new bioinformatic tool created in our group, which included modeling spectra as a sum of Gaussian bell-shaped curves.ResultsWe have identified features of serum proteome patterns that were significantly different between blood samples of healthy individuals and early stage breast cancer patients. The classifier built of three spectral components that differentiated controls and cancer patients had 83% sensitivity and 85% specificity. Spectral components (i.e., protein ions) that were the most frequent in such classifiers had approximate m/z values of 2303, 2866 and 3579 Da (a biomarker built from these three components showed 88% sensitivity and 78% specificity). Of note, we did not find a significant correlation between features of serum proteome patterns and established prognostic or predictive factors like tumor size, nodal involvement, histopathological grade, estrogen and progesterone receptor expression. In addition, we observed a significantly (p = 0.0003) increased level of osteopontin in blood of the group of cancer patients studied (however, the plasma level of osteopontin classified cancer samples with 88% sensitivity but only 28% specificity).ConclusionMALDI-ToF spectrometry of serum has an obvious potential to differentiate samples between early breast cancer patients and healthy controls. Importantly, a classifier built on MS-based serum proteome patterns outperforms available protein biomarkers analyzed in blood by immunoassays.