Identification of a Proteomic Signature of Senescence in Primary Human Mammary Epithelial Cells

Senescence is a permanent cell cycle arrest that occurs in response to cellular stress and promotes age-related disease. Because senescence differs greatly depending on cell type and senescence inducer, continued progress in the characterization of senescent cells is needed. Here, we analyzed primary human mammary epithelial cells (HMECs), a model system for aging and cancer, using mass spectrometry-based proteomics. By integrating data from replicative senescence, immortalization by telomerase reactivation, and quiescence, we identified a robust proteomic signature of HMEC senescence consisting of 34 upregulated and 10 downregulated proteins. This approach identified known senescence biomarkers including beta-galactosidase (GLB1) as well as novel senescence biomarkers including catechol O-methyltransferase (COMT), synaptic vesicle membrane protein VAT-1 homolog (VAT1), and plastin-1/3 (PLS1/PLS3). Gene ontology enrichment analysis demonstrated that senescent HMECs upregulated lysosomal proteins and downregulated RNA metabolic processes. In addition, a classification model based on our proteomic signature successfully discriminated proliferating and senescent HMECs at the transcriptional level. Finally, we found that the HMEC senescence signature was positively and negatively correlated with proteomic alterations in HMEC aging and breast cancer, respectively. Taken together, our results demonstrate the power of proteomics to identify cell type-specific signatures of senescence and advance the understanding of senescence in HMECs.

Automated summary

Senescence is a permanent cell cycle arrest in response to cellular stress, with diverse effects depending on cell type and inducer. Analyzing primary human mammary epithelial cells using mass spectrometry-based proteomics revealed a robust proteomic signature of senescence. The study identified known and novel senescence biomarkers, and demonstrated upregulation of lysosomal proteins and downregulation of RNA metabolic processes in senescent cells. The results highlight the power of proteomics in identifying cell type-specific senescence signatures and enhancing understanding of senescence in HMECs.