Reverse Engineering of Cell Senescence

细胞衰老的逆向工程

基本信息

批准号：
10573323
负责人：
MARC Wallace KIRSCHNER
金额：
$ 69.39万
依托单位：
HARVARD MEDICAL SCHOOL
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-02-15 至 2026-11-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10573323
关键词：
Address Affect Age Aging Animals Biochemical Biological Assay Cell Aging Cell Culture Techniques Cell Cycle Cell Cycle Arrest Cell Line Cell Senescence Induction Cell Size Cell Survival Cells Cellular biology Cessation of life Clustered Regularly Interspaced Short Palindromic Repeats Critical Pathways Cultured Cells DNA Damage Dasatinib Dependence Development Disease Dryness Event Exposure to FRAP1 gene Genes Goals Growth Growth Factor Hepatocyte Heterogeneity Hormones Human Hydrogen Peroxide Hypertrophy Inflammatory Insulin Ionizing radiation Kinetics Laboratories Learning Life Lipids Liver Logic Machine Learning Mass Spectrum Analysis Measures Methods Microscopic Microscopy Molecular Mus Mutagenesis Normal Cell Normal tissue morphology Oncogene Activation Pathology Pathway interactions Pattern Pharmaceutical Preparations Pharmacologic Substance Pharmacology Phenotype Phosphoproteins Phosphorylated Peptide Phosphorylation Phosphorylation Site Phosphotransferases Physiological Process Proteins Proteomics Radiation Reactive Oxygen Species Research Personnel Reverse engineering Role Signal Transduction Sirolimus Site Small Interfering RNA Stress Swelling Symptoms Testing Time Tissues cell growth cell type chemokine experimental study healthspan insight interest kinase inhibitor knock-down mTOR inhibition new technology novel therapeutics pharmacologic phosphoproteomics prevent programs proteostasis response senescence stressor tool

项目摘要

Abstract Cellular senescence is not just a symptom of aging, but a contributor to aging pathologies. Recent experiments in the mouse show that elimination of senescent cells (a.k.a. senolysis) can reverse several features of the aging process and extend life- and health-span. This has stimulated interest in cell senescence and in finding ways to suppress it that can be easily ported from mouse to human and made even more effective. This implies looking for such drugs as an early senolytic candidate – a kinase inhibitor dasatinib, whose mode of action is unclear. Taking senolytic therapies into human will also require a better understanding of the cell type specific progression towards senescence and diverse sub-types of senescence. In addition to aging per se cells respond to insults such as DNA damage, cell cycle arrest or oncogene activation by expressing aging phenotypes, such as hypertrophy, cell cycle arrest markers, and by secreting growth factors and chemokines, which are thought to produce degenerative responses in nearby cells. Hypertrophy may be one of the most pervasive senescent cell responses but has been hard to study, as until recently we have not had accurate enough means to measure cell mass and cell size, protein and lipid content. Yet, hypertrophy is of special interest because it is deeply connected to cell growth, which is normally under strict control in normal cells. We propose to study how cells, prompted by stressors like radiation or drugs or simply by age, become hypertrophic and how they come to express senescence markers. We have three goals: 1) to trace the progression of cell senescence in molecular terms by quantitative mass spectrometry and phospho-mass spectrometry, and in physiological terms by Raman microscopy, 2) to identify protein circuits responsible for cell senescence, and 3) to find drugs that will prevent, reverse, or eliminate senescent cells. As our tools of perturbation, we have chosen kinase inhibitors. Employing a machine learning approach, we will probe senescent cell development and senescent cell viability via a small set of well-characterized poly-specific kinase inhibitors; then regress a phenotype, such as senescence- specific signaling and senescent cell formation or death, to the activity of key kinases and their downstream circuits. Kinases implicated that way will be independently validated using siRNA knock downs and CRISPR. Additionally, extensive phospho-proteomic profiling will identify the phosphorylation sites on key proteins that most contribute to the phenotypes of senescence and which could be druggable by other means. Taken together, these methods will produce insight into the mode of action of already identified senolytic drugs and suggest new targets and new drugs for seno-therapies. This combination of pharmacology, machine learning, quantitative proteomics and new forms of microscopy can provide fresh insights into aging and suggest potential therapies for aging-related disease.

抽象的细胞衰老不仅是衰老的症状，而且是导致衰老病理的一个因素。小鼠实验表明，消除衰老细胞（又名衰老作用）可以逆转多种衰老细胞。衰老过程的特征并延长寿命和健康寿命这激发了人们对细胞衰老的兴趣。并找到抑制它的方法，这些方法可以很容易地从小鼠移植到人类身上，并产生更多的效果这意味着寻找这样的药物作为早期的senolytic候选药物——激酶抑制剂达沙替尼，将 senolytics 疗法应用于人体还需要更好的方法。了解细胞类型特定的衰老进展和衰老的不同亚型。除了衰老本身之外，细胞还会对 DNA 损伤、细胞周期停滞或癌基因等损伤做出反应通过表达衰老表型（例如肥大、细胞周期停滞标记物）以及通过分泌生长因子和趋化因子，被认为会在附近细胞中产生退行性反应。肥大可能是最普遍的衰老细胞反应之一，但一直很难研究，直到最近我们还没有足够准确的手段来测量细胞质量和细胞大小、蛋白质和脂质然而，肥大特别令人感兴趣，因为它与细胞生长密切相关。通常在正常细胞中受到严格控制，我们建议研究细胞如何受到压力等因素的促进。辐射或药物或简单地通过年龄，变得肥大以及它们如何表达衰老标记。我们有三个目标：1）通过定量质量从分子角度追踪细胞衰老的进展光谱测定法和磷质谱测定法，以及生理学术语中的拉曼显微镜，2) 识别导致细胞衰老的蛋白质回路，以及 3) 寻找能够预防、逆转或作为我们的干扰工具，我们选择了激酶抑制剂。机器学习方法，我们将通过一个小模型来探究衰老细胞的发育和衰老细胞的活力一组特征明确的多特异性激酶抑制剂；然后使表型回归，例如衰老- 特定信号传导和衰老细胞形成或死亡，影响关键激酶及其下游的活性涉及这种方式的激酶将使用 siRNA 敲低和 CRISPR 进行独立验证。此外，广泛的磷酸化蛋白质组分析将识别关键蛋白质上的磷酸化位点对衰老表型影响最大，并且可以通过其他方式进行药物治疗。总之，这些方法将深入了解已识别的抗衰老药物的作用模式并提出了声疗法的新靶点和新药物这种药理学、机器的结合。学习、定量蛋白质组学和新型显微镜可以为衰老和衰老提供新的见解。提出了治疗衰老相关疾病的潜在疗法。