Transcriptome signature of cellular senescence

Abstract

Cellular senescence, an integral component of aging and cancer, arises in response to diverse triggers, including telomere attrition, macromolecular damage and signaling from activated oncogenes. At present, senescent cells are identified by the combined presence of multiple traits, such as senescence-associated protein expression and secretion, DNA damage and β-galactosidase activity; unfortunately, these traits are neither exclusively nor universally present in senescent cells. To identify robust shared markers of senescence, we have performed RNA-sequencing analysis across eight diverse models of senescence triggered in human diploid fibroblasts (WI-38, IMR-90) and endothelial cells (HUVEC, HAEC) by replicative exhaustion, exposure to ionizing radiation or doxorubicin, and expression of the oncogene HRASG12V. The intersection of the altered transcriptomes revealed 50 RNAs consistently elevated and 18 RNAs consistently reduced across all senescence models, including many protein-coding mRNAs and some non-coding RNAs. We propose that these shared transcriptome profiles will enable the identification of senescent cells in vivo, the investigation of their roles in aging and malignancy and the development of strategies to target senescent cells therapeutically.

A proteomic atlas of senescence-associated secretomes for aging biomarker development

“…The meta-transcriptomic profiles, as described by Hernandez-Segura and colleagues [24], are based on whole transcriptome (at least three replicates each) profiles of several fibroblast strains: MRC-5 and HFF datasets were used for analysis of IR-induced senescence and IMR-90 were used for RAS-induced senescence. We combined these analyses with a more recent RNA-sequencing analysis of both IRinduced senescence in WI-38 and IMR-90 human fibroblasts and RAS-induced senescence in WI-38 fibroblasts [44] to generate lists of genes that are exclusively expressed in senescent fibroblasts following IR or RAS (S7 Table). The combined transcriptome profiles contained 33 gene expression changes exclusive to IR-induced senescence and 1,749 gene expression changes exclusive to RAS-induced senescence.…”

A Proteomic Atlas of Senescence-Associated Secretomes for Aging Biomarker Development

“…The meta-transcriptomic profiles, as described by Hernandez-Segura and colleagues [24], are based on whole transcriptome (at least three replicates each) profiles of several fibroblast strains: MRC-5 and HFF datasets were used for analysis of IR-induced senescence and IMR-90 were used for RAS-induced senescence. We combined these analyses with a more recent RNA-sequencing analysis of both IRinduced senescence in WI-38 and IMR-90 human fibroblasts and RAS-induced senescence in WI-38 fibroblasts [44] to generate lists of genes that are exclusively expressed in senescent fibroblasts following IR or RAS (S7 Table). The combined transcriptome profiles contained 33 gene expression changes exclusive to IR-induced senescence and 1,749 gene expression changes exclusive to RAS-induced senescence.…”

“…We compared the secretomes of radiation-induced senescent lung fibroblasts and similarly treated senescent renal epithelial cells to determine the cell-type specificity of the sSASP. For renal epithelial cells, the sSASP comprised a mixture of proteins with significantly lower or 44] and combined. Transcriptome data were filtered for changes that were inducer specific (genes changing exclusively in one inducer but not the other) and were consistent in both studies.…”

“…Inducer-specific transcriptomes were then compared with inducer-specific secretome changes in the sSASP (from the current study) to produce a combined inducer-specific RNA and protein signature. (D) Log2-fold changes of the top five RAS-specific genes in the sSASP secretome and in two published transcriptome datasets [24,44]. CTL, quiescent control; IR, X-irradiation; RAS, inducible RAS overexpression; SEN, senescent; sSASP, soluble senescence-associated secretory phenotype.…”

The lncRNA MIR31HG regulates the senescence associated secretory phenotype

“…During aging, excessive SASP secretion can induce chronic in ammation that can lead to aged-related pathologies (Baker, Wijshake et al, 2011, Jeyapalan, Ferreira et al, 2007. The composition of the SASP is very variable depending on different aspects such as the senescence stimuli and the cell type (Casella, Munk et al, 2019, Hernandez-Segura, de Jong et al, 2017. De ning the composition of the secretome and identifying new regulators in each biological context is crucial to identify molecular signatures of such a complex phenotype.…”