Scholarlink

<p>Senescent cells accumulate in most tissues with organismal aging, exposure to stressors, or disease progression. It is challenging to identify senescent cells because cellular senescence signatures and phenotypes vary widely across distinct cell types and tissues. Here we developed an analytical algorithm that defines cell-type-specific and universal signatures of cellular senescence across a wide range of cell types and tissues. We utilize 72 mouse and 64 human weighted single-cell transcriptomic signatures of cellular senescence to create the <i>SenePy</i> scoring platform. <i>SenePy</i> signatures better recapitulate in vivo cellular senescence than signatures derived from in vitro senescence studies. We use <i>SenePy</i> to map the kinetics of senescent cell accumulation in healthy aging as well as multiple disease contexts, including tumorigenesis, inflammation, and myocardial infarction. <i>SenePy</i> characterizes cell-type-specific in vivo cellular senescence and could lead to the identification of genes that serve as mediators of cellular senescence and disease progression.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Unveiling the cell-type-specific landscape of cellular senescence through single-cell transcriptomics using SenePy

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月22日

查看全文
  • Mark A. Sanborn,
  • Xinge Wang,
  • Shang Gao,
  • Yang Dai,
  • Jalees Rehman

摘要

Senescent cells accumulate in most tissues with organismal aging, exposure to stressors, or disease progression. It is challenging to identify senescent cells because cellular senescence signatures and phenotypes vary widely across distinct cell types and tissues. Here we developed an analytical algorithm that defines cell-type-specific and universal signatures of cellular senescence across a wide range of cell types and tissues. We utilize 72 mouse and 64 human weighted single-cell transcriptomic signatures of cellular senescence to create the SenePy scoring platform. SenePy signatures better recapitulate in vivo cellular senescence than signatures derived from in vitro senescence studies. We use SenePy to map the kinetics of senescent cell accumulation in healthy aging as well as multiple disease contexts, including tumorigenesis, inflammation, and myocardial infarction. SenePy characterizes cell-type-specific in vivo cellular senescence and could lead to the identification of genes that serve as mediators of cellular senescence and disease progression.