Meta-analysis of senescent cell secretomes to identify common and specific features of the different senescent phenotypes: a tool for developing new senotherapeutics

Abstract

DNA damage resulting from genotoxic injury can initiate cellular senescence, a state characterized by alterations in cellular metabolism, lysosomal activity, and the secretion of factors collectively known as the senescence-associated secretory phenotype (SASP). Senescence can have beneficial effects on our bodies, such as anti-cancer properties, wound healing, and tissue development, which are attributed to the SASP produced by senescent cells in their intermediate stages. However, senescence can also promote cancer and aging, primarily due to the pro-inflammatory activity of SASP.

Studying senescence is complex due to various factors involved. Genotoxic stimuli cause random damage to cellular macromolecules, leading to variations in the senescent phenotype from cell to cell, despite a shared program. Furthermore, senescence is a dynamic process that cannot be analyzed as a static endpoint, adding further complexity.

Investigating SASP is particularly intriguing as it reveals how a senescence process triggered in a few cells can spread to many others, resulting in either positive or negative consequences for health. In our study, we conducted a meta-analysis of the protein content of SASP obtained from different research groups, including our own. We categorized the collected omic data based on: i) cell type, ii) harmful agent, and iii) senescence stage (early and late senescence).

By employing Gene Ontology and Network analysis on the omic data, we identified common and specific features of different senescent phenotypes. This research has the potential to pave the way for the development of new senotherapeutic drugs aimed at combating the negative consequences associated with the senescence process.

Video Abstract