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Cellular senescence is a state of terminal growth arrest associated with the upregulation of different cell cycle inhibitors, mainly p16 and p21, structural and metabolic alterations, chronic DNA damage responses, and a hypersecretory state known as the senescence-associated secretory phenotype (SASP). The SASP is the major mediator of the paracrine effects of senescent cells in their tissue microenvironment and of various local and systemic biological functions. In this Review, we discuss the composition, dynamics and heterogeneity of the SASP as well as the mechanisms underlying its induction and regulation. We describe the various biological properties of the SASP, its beneficial and detrimental effects in different physiological and pathological settings, and its impact on overall health span. Finally, we discuss the use of the SASP as a biomarker and of SASP inhibitors as senomorphic interventions to treat cancer and other age-related conditions.The senescence-associated secretory phenotype (SASP) mediates the tissue effects of senescent cells. This Review discusses the composition, regulation and various biological implications of the SASP and its uses as a biomarker and a target of senomorphic drugs to treat cancer and other age-related conditions.

The senescence‐associated secretory phenotype (SASP), where senescent cells produce a variety of secreted proteins including inflammatory cytokines, chemokines, matrix remodelling factors, growth factors and so on, plays pivotal but varying roles in the tumour microenvironment. The effects of SASP on the surrounding microenvironment depend on the cell type and process of cellular senescence induction, which is often associated with innate immunity. Via SASP‐mediated paracrine effects, senescent cells can remodel the surrounding tissues by modulating the character of adjacent cells, such as stromal, immune cells, as well as cancer cells. The SASP is associated with both tumour‐suppressive and tumour‐promoting effects, as observed in senescence surveillance effects (tumour‐suppressive) and suppression of anti‐tumour immunity in most senescent cancer‐associated fibroblasts and senescent T cells (tumour‐promoting). In this review, we discuss the features and roles of senescent cells in tumour microenvironment with emphasis on their context‐dependency that determines whether they promote or suppress cancer development. Potential usage of recently developed drugs that suppress the SASP (senomorphics) or selectively kill senescence cells (senolytics) in cancer therapy are also discussed. The senescence‐associated secretory phenotype (SASP), where senescent cells produce a variety of secreted proteins, plays pivotal roles in the tumour microenvironment. SASP remodels the surrounding tissues by modulating the character of adjacent cells and can promote or suppress tumorigenesis. In this review, we discuss the features and roles of senescent cells in tumour microenvironment with focus on their context‐dependency.

Along with the increasing availability of electronic medical record (EMR) data, phenome-wide association studies (PheWAS) and phenome-disease association studies (PheDAS) have become a prominent, first-line method of analysis for uncovering the secrets of EMR .  Despite this recent growth, there is a lack of approachable software tools for conducting these analyses on large-scale EMR cohorts. In this article, we introduce pyPheWAS , an open-source python package for conducting PheDAS and related analyses. This toolkit includes 1) data preparation, such as cohort censoring and age-matching; 2) traditional PheDAS analysis of ICD-9 and ICD-10 billing codes; 3) PheDAS analysis applied to a novel EMR phenotype mapping: current procedural terminology (CPT) codes; and 4) novelty analysis of significant disease-phenotype associations found through PheDAS. The pyPheWAS toolkit is approachable and comprehensive, encapsulating data prep through result visualization all within a simple command-line interface. The toolkit is designed for the ever-growing scale of available EMR data, with the ability to analyze cohorts of 100,000 + patients in less than 2 h. Through a case study of Down Syndrome and other intellectual developmental disabilities, we demonstrate the ability of pyPheWAS to discover both known and potentially novel disease-phenotype associations across different experiment designs and disease groups. The software and user documentation are available in open source at https://github.com/MASILab/pyPheWAS .

The complex interaction between a genotype and its environment controls the biophysical properties of a plant, manifested in observable traits, i.e., plant's phenome, which influences resources acquisition, performance, and yield. High-throughput automated image-based plant phenotyping refers to the sensing and quantifying plant traits non-destructively by analyzing images captured at regular intervals and with precision. While phenomic research has drawn significant attention in the last decade, extracting meaningful and reliable numerical phenotypes from plant images especially by considering its individual components, e.g., leaves, stem, fruit, and flower, remains a critical bottleneck to the translation of advances of phenotyping technology into genetic insights due to various challenges including lighting variations, plant rotations, and self-occlusions. The paper provides (1) a framework for plant phenotyping in a multimodal, multi-view, time-lapsed, high-throughput imaging system; (2) a taxonomy of phenotypes that may be derived by image analysis for better understanding of morphological structure and functional processes in plants; (3) a brief discussion on publicly available datasets to encourage algorithm development and uniform comparison with the state-of-the-art methods; (4) an overview of the state-of-the-art image-based high-throughput plant phenotyping methods; and (5) open problems for the advancement of this research field.

Abstract Pleiotropy, a phenomenon of multiple phenotypic effects of the same genetic alteration, is one of the most important features of genotype-to-phenotype networks. Over the last century, biologists have actively debated the prevalence, mechanisms, and consequences of pleiotropy. In this work, we employed data on genotype-to-phenotype associations from the Human Phenotype Ontology and Mouse Genome Database, as well as genome-wide associations from the UK Biobank and FinnGen cohorts to investigate the similarities and dissimilarities in the patterns of pleiotropy between species and different trait types (i.e. Mendelian traits and complex traits). We found that the pleiotropic effects of genes correlate well between species but have a much weaker correlation when comparing different types of traits for the same species. In all cases, however, highly pleiotropic genes possessed a common set of features, such as broad expression across tissues, involvement in many biological processes, or a high number of protein–protein interactions of the respective gene products. Furthermore, we observed a universal tendency of highly pleiotropic genes to be under greater negative selection pressure compared to other groups of genes, including genes essential for cell growth and development. Besides, highly pleiotropic genes also show a significant enrichment of recent positive selection signals. Taken together, our results pinpoint a common mechanism underlying pleiotropic effects in different trait domains and suggest that high degree of pleiotropy plays a role in adaptation, despite imposing additional constraint on genetic variation.

Senescence is a cellular state in which cells undergo persistent cell cycle arrest in response to nonlethal stress. In the treatment of cancer, senescence induction is a potent method of suppressing tumour cell proliferation. In spite of this, senescent cancer cells and adjacent nontransformed cells of the tumour microenvironment can remain metabolically active, resulting in paradoxical secretion of pro‐inflammatory factors, collectively termed the senescence‐associated secretory phenotype (SASP). The SASP plays a critical role in tumorigenesis, affecting numerous processes including invasion, metastasis, epithelial‐to‐mesenchymal transition (EMT) induction, therapy resistance and immunosuppression. With increasing evidence, it is becoming clear that cell type, tissue of origin and the primary cellular stressor are key determinants in how the SASP will influence tumour development and progression, including whether it will be pro‐ or antitumorigenic. In this review, we will focus on recent evidence regarding therapy‐induced senescence (TIS) from anticancer agents, including chemotherapy, radiation, immunotherapy, and targeted therapies, and how each therapy can trigger the SASP, which in turn influences treatment efficacy. We will also discuss novel pharmacological manipulation of senescent cancer cells and the SASP, which offers an exciting and contemporary approach to cancer therapeutics. With future research, these adjuvant options may help to mitigate many of the negative side effects and protumorigenic roles that are currently associated with TIS in cancer. In response to therapy or other stimuli, cancer cells can undergo cellular senescence, a stress response leading to cell cycle arrest. An unintended consequence of cellular senescence is a perturbed, pro‐inflammatory cancer cell secretome, the senescence‐associated secretory phenotype (SASP). Here, we explore the role of SASP in promoting tumorigenesis and treatment resistance, with particular focus on mechanisms of therapy‐induced senescence (TIS).

Mitochondrial dysfunction and cell senescence are hallmarks of aging and are closely interconnected. Mitochondrial dysfunction, operationally defined as a decreased respiratory capacity per mitochondrion together with a decreased mitochondrial membrane potential, typically accompanied by increased production of oxygen free radicals, is a cause and a consequence of cellular senescence and figures prominently in multiple feedback loops that induce and maintain the senescent phenotype. Here, we summarize pathways that cause mitochondrial dysfunction in senescence and aging and discuss the major consequences of mitochondrial dysfunction and how these consequences contribute to senescence and aging. We also highlight the potential of senescence-associated mitochondrial dysfunction as an antiaging and antisenescence intervention target, proposing the combination of multiple interventions converging onto mitochondrial dysfunction as novel, potent senolytics.

Aging leads to increased cellular senescence and is associated with decreased potency of tissue‐specific stem/progenitor cells. Here, we have done an extensive analysis of cardiac progenitor cells (CPCs) isolated from human subjects with cardiovascular disease, aged 32–86 years. In aged subjects (>70 years old), over half of CPCs are senescent (p16INK4A, SA‐β‐gal, DNA damage γH2AX, telomere length, senescence‐associated secretory phenotype [SASP]), unable to replicate, differentiate, regenerate or restore cardiac function following transplantation into the infarcted heart. SASP factors secreted by senescent CPCs renders otherwise healthy CPCs to senescence. Elimination of senescent CPCs using senolytics abrogates the SASP and its debilitative effect in vitro. Global elimination of senescent cells in aged mice (INK‐ATTAC or wild‐type mice treated with D + Q senolytics) in vivo activates resident CPCs and increased the number of small Ki67‐, EdU‐positive cardiomyocytes. Therapeutic approaches that eliminate senescent cells may alleviate cardiac deterioration with aging and restore the regenerative capacity of the heart.

Vascular smooth muscle cells (VSMCs) are the most abundant cell in vessels. Earlier experiments have found that VSMCs possess high plasticity. Vascular injury stimulates VSMCs to switch into a dedifferentiated type, also known as synthetic VSMCs, with a high migration and proliferation capacity for repairing vascular injury. In recent years, largely owing to rapid technological advances in single-cell sequencing and cell-lineage tracing techniques, multiple VSMCs phenotypes have been uncovered in vascular aging, atherosclerosis (AS), aortic aneurysm (AA), etc. These VSMCs all down-regulate contractile proteins such as α-SMA and calponin1, and obtain specific markers and similar cellular functions of osteoblast, fibroblast, macrophage, and mesenchymal cells. This highly plastic phenotype transformation is regulated by a complex network consisting of circulating plasma substances, transcription factors, growth factors, inflammatory factors, non-coding RNAs, integrin family, and Notch pathway. This review focuses on phenotypic characteristics, molecular profile and the functional role of VSMCs phenotype landscape; the molecular mechanism regulating VSMCs phenotype switching; and the contribution of VSMCs phenotype switching to vascular aging, AS, and AA. B-3bjxQLrZLMREQzgTDw7N Video Abstract