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Secreted Protein Combination GAPDH/S100A8/S100A9 from Human Expanded Potential Stem Cells Counteracts Mesenchymal Stem Cell Senescence

GSE326160 Homo sapiens Expression profiling by high throughput sequencing 3 samples Submitted 2026/04/01 Platform GPL20795
Summary
Human mesenchymal stem cells (hMSCs) remain the most clinically advanced adult stem cell source; however, their therapeutic potential is limited by rapid replicative senescence during ex vivo expansion. Replicative senescence in hMSCs is characterized by cell cycle arrest, acquisition of senescence-associated β-galactosidase (SA-β-Gal) activity, and secretion of the senescence-associated secretory phenotype (SASP) factors. We investigated whether conditioned medium derived from human extended pluripotent stem cells (hEPSCs), which possess both embryonic and extra-embryonic developmental potential beyond that of conventional hESCs, could attenuate replicative senescence in hMSCs. Using sequential ultrafiltration (10 kDa and 3 kDa) followed by LC-MS/MS, we identified several proteins from hEPSC-conditioned medium. We then tested the combination of S100A9/GAPDH/S100A8 proteins for their effects on doxorubicin-induced and replicative senescence.hEPSC-conditioned medium markedly attenuated replicative senescence in hMSCs. Notably, the combination of S100A9/GAPDH/S100A8 proteins not only mitigated doxorubicin-induced senescence but also counteracted replicative senescence, as evidenced by a significant reduction in SA-β-Gal-positive cells and downregulated mRNA expression of senescence-associated genes, including p16, p21, and the SASP factor IL-6. Furthermore, EdU incorporation assays revealed significantly enhanced proliferative capacity following treatment. Collectively, our findings establish a defined protein combination (S100A9/GAPDH/S100A8) that counteracts both replicative and stress-induced senescence, offering a novel, cell-free strategy to enhance the clinical utility of hMSCs.
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Also filed as BioProject PRJNA1444037 and SRA study SRP687166. Searching any of these in the dataset finder brings you back here.

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