Abstract
Cellular senescence is a cell fate driven by different types of stress, where damaged cells exit from the cell cycle and, in many cases, develop an inflammatory senescence-associated secretory phenotype (SASP). Senescence has often been linked to driving aging and the onset of multiple diseases conferred by the harmful SASP, which disrupts tissue homeostasis and impairs the regular function of many tissues. This phenomenon was first observed in vitro when fibroblasts halted replication after approximately 50 population doublings. In addition to replication-induced senescence, factors such as DNA damage and oncogene activation can induce cellular senescence both in culture and in vivo. Despite their contribution to aging and disease, identifying senescent cells in vivo has been challenging due to their heterogeneity. Although senescent cells can express the cell cycle inhibitors p16(Ink4a) and/or p21(Cip1) and exhibit SA-ß-gal activity and evidence of a DNA damage response, there is no universal biomarker for these cells, regardless of inducer or cell type. Recent studies have analyzed the transcriptomic characteristics of these cells, leading to the identification of signature gene sets like CellAge, SeneQuest, and SenMayo. Advancements in single-cell and spatial RNA sequencing now allow for analyzing senescent cell heterogeneity within the same tissue and the development of machine learning algorithms, e.g., SenPred, SenSig, and SenCID, to discover cellular senescence using RNA sequencing data. Such insights not only deepen our understanding of the genetic pathways driving cellular senescence, but also promote the development of its quantifiable biomarkers. This review summarizes the current knowledge of transcriptomic signatures of cellular senescence and their potential as in vivo biomarkers.