The power of proteomics to monitor senescence-associated secretory phenotypes and beyond: toward clinical applications

Figures & data

Table 1. Proteomic Studies of Senescent Cells.

Method	Cell type	Cellular compartment	Senescence inducer	Reference
Label-free MS	Human bladder cancer cells	PM	p21-induced, p16-induced	[54]
	Human bone marrow and adipose mesenchymal stromal cells	SASP	GSIS, RS	[69]
	Human breast cancer cells	EVs	GSIS	[109]
	Human retinal pigment epithelial cells	EVs	GSIS	[111]
	Human fetal lung fibroblasts	PM	GSIS	[55]
Label-free quantitative MS	Human fetal lung fibroblasts, proximal tubule epithelial cells	SASP and EVs	GSIS, OIS, atazanavir treatment	[3]
	Human foreskin fibroblasts	EVs	OIS and GSIS	[67]
SILAC	Human fibroblasts	SASP	GSIS	[68]
	Human fetal lung fibroblasts	PM	OIS	[56]
	Human fetal lung fibroblasts	SASP	OIS	[15]
Antibody-array- based proteomics	Human fibroblasts, renal epithelial cells, epithelial tumor cells	SASP	GSIS, RS	[20]
	MEF and primary adult mammary gland fibroblasts	SASP	GSIS	[52]
	Human fetal lung fibroblasts	SASP	OIS	[19]
	Mouse embryonic fibroblasts	SASP	GSIS	[22]

Figure 1. Pipeline for the development of senescence-based biomarkers of aging and disease. In phase 1, discovery, the secretomes (SASP) of senescent cells are characterized in cell-culture systems to generate biomarker candidates that can be tailored to specific biological contexts, based on the disease and cell type. Multiple cell types and senescence-inducing stimuli (e.g., genotoxic/oncogenic/metabolic stress) can be interrogated, and the most robust biomarkers of all conditions used for later stages of biomarker development. In step 2, verification, biomarker candidates are filtered, based on whether they can be detected in plasma (or other biofluids), and biomarker assays are developed based on the most reproducible and quantitative peptide(s) from each protein biomarker candidate. Finally, these biomarkers are interrogated in human cohorts in step 3, validation. Cohorts for step 3 should be chosen so that they contain subjects with high and low senescent cell burdens, and ideally, an intervention that either increases or reduces senescent cell burden. Examples of cohorts with variable senescence burden are old and young individuals, and doxorubicin-treated patients and untreated patients (or before and after doxorubicin treatment).

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