The categorization of cell states into neat taxonomy is an attempt to conceptually simplify a much more complex, analog underlying reality. Any two cells in a given category may be different in ways that turn out to be meaningful in some contexts. So it should be taken as read that the senescent cells that grow in number with age and contribute to age-related disease differ from one another in many ways, and that what we call senescence is at present an oversimplified big tent. It may well turn out require separation into smaller categories to aid continued research and development into ways to reduce the impact of cellular senescence on later life health.
Better understanding the many differences that can exist between any two given senescent cells is of great interest to researchers who are attempting to produce novel senolytic therapies that can selectively destroy these cells. The existing better explored target mechanisms of first generation senolytic drugs produce variable efficacy in clearance of senescent cells depending on tissue type, duration of senescence, reasons for the onset of senescence, and no doubt many other aspects of senescent biochemistry. The best senolytics to date clear only a fraction of senescent cells, that fraction varying by tissue. In today's open access paper, researchers present a view of cellular senescence as an emergent phenomenon driven by a range of distinct stress response packages, a step on the road to better understanding how to produce better senolytic therapies.
Mosaic Regulation of Stress Pathways Underlies Senescent Cell Heterogeneity
Cellular senescence (CS) and quiescence (CQ) are stress responses characterised by persistent and reversible cell cycle arrest, respectively. These phenotypes are heterogeneous, dependent on the cell type arrested and the insult inciting arrest. Because a universal biomarker for CS has yet to be identified, combinations of senescence-associated biomarkers linked to various biological stress responses including lysosomal activity (β-galactosidase staining), inflammation (senescence-associated secretory phenotypes, SASPs), and apoptosis (senescent cell anti-apoptotic pathways) are used to identify senescent cells.
Using in vitro human bulk RNA-seq datasets, we find that senescent states enrich for various stress responses in a cell-type, temporal, and insult-dependent manner. We further demonstrate that various gene signatures used to identify senescent cells in the literature also enrich for stress responses, and are inadequate for universally and exclusively identifying senescent samples. Genes regulating stress responses - including transcription factors and genes controlling chromatin accessibility - are contextually differentially expressed, along with key enzymes involved in metabolism across arrest phenotypes. Additionally, significant numbers of SASP proteins can be predicted from senescent cell transcriptomes and also heterogeneously enrich for various stress responses in a context-dependent manner.
We propose that 'senescence' cannot be meaningfully defined due to the lack of underlying preserved biology across senescent states, and CS is instead a mosaic of stress-induced phenotypes regulated by various factors, including metabolism, transcription factors, and chromatin accessibility. We introduce the concept of Stress Response Modules, clusters of genes modulating stress responses, and present a new model of CS and CQ induction conceptualised as the differential activation of these clusters.
View the full article at FightAging
