Identification of a Proteomic Signature of Senescence in Primary Human Mammary Epithelial Cells
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Abstract
Abstract Senescence is a permanent cell cycle arrest that occurs in response to cellular stress. Because senescent cells promote age-related disease, there has been considerable interest in defining the proteomic alterations in senescent cells. 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, using mass spectrometry-based proteomics. By integrating data from replicative senescence, immortalization by telomerase reactivation, and drug-induced senescence, we identified a robust proteomic signature of HMEC senescence consisting of 77 upregulated and 36 downregulated proteins. This approach identified known biomarkers, such as downregulation of the nuclear lamina protein lamin-B1 (LMNB1), and novel upregulated proteins including the β-galactoside-binding protein galectin-7 (LGALS7). Gene ontology enrichment analysis demonstrated that senescent HMECs upregulated lysosomal proteins and downregulated RNA metabolic processes. We additionally integrated our proteomic signature of senescence with transcriptomic data from senescent HMECs to demonstrate that our proteomic signature can discriminate proliferating and senescent HMECs even at the transcriptional level. Taken together, our results demonstrate the power of proteomics to identify cell type-specific signatures of senescence and advance the understanding of senescence in primary HMECs.
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Cites
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works
Clearance of p16Ink4a-positive senescent cells delays ageing-associated disorders
Baker, D. J., Wijshake, T., Tchkonia, T., LeBrasseur, N. K., Childs, B. G., van de Sluis, B., Kirkland, J. L., & van Deursen, J. M. (2011) · Nature · doi:10.1038/nature10600 · Cited by 3,670 · see citing works
Cellular Senescence: Defining a Path Forward
Gorgoulis, V., Adams, P. D., Alimonti, A., Bennett, D. C., Bischof, O., Bishop, C., Campisi, J., Collado, M., Evangelou, K., Ferbeyre, G., et al. (2019) · Cell · doi:10.1016/j.cell.2019.10.005 · Cited by 3,225 · see citing works
Aging, Cellular Senescence, and Cancer
Campisi, J. (2013) · Annual Review of Physiology · doi:10.1146/annurev-physiol-030212-183653 · Cited by 2,954 · see citing works
Naturally occurring p16Ink4a-positive cells shorten healthy lifespan
Baker, D. J., Childs, B. G., Durik, M., Wijers, M. E., Sieben, C. J., Zhong, J., A. Saltness, R., Jeganathan, K. B., Verzosa, G. C., Pezeshki, A., et al. (2016) · Nature · doi:10.1038/nature16932 · Cited by 2,891 · see citing works
Cellular senescence in ageing: from mechanisms to therapeutic opportunities
Di Micco, R., Krizhanovsky, V., Baker, D., & d’Adda di Fagagna, F. (2021) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-020-00314-w · Cited by 2,277 · see citing works
An Essential Role for Senescent Cells in Optimal Wound Healing through Secretion of PDGF-AA
Demaria, M., Ohtani, N., Youssef, S. A., Rodier, F., Toussaint, W., Mitchell, J. R., Laberge, R.-M., Vijg, J., Van Steeg, H., Dollé, M. E. T., et al. (2014) · Developmental Cell · doi:10.1016/j.devcel.2014.11.012 · Cited by 2,045 · see citing works
Baar, M. P., Brandt, R. M. C., Putavet, D. A., Klein, J. D. D., Derks, K. W. J., Bourgeois, B. R. M., Stryeck, S., Rijksen, Y., van Willigenburg, H., Feijtel, D. A., et al. (2017) · Cell · doi:10.1016/j.cell.2017.02.031 · Cited by 1,454 · see citing works
Programmed cell senescence during mammalian embryonic development
Muñoz-Espín, D., Cañamero, M., Maraver, A., Gómez-López, G., Contreras, J., Murillo-Cuesta, S., Rodríguez-Baeza, A., Varela-Nieto, I., Ruberte, J., Collado, M., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.019 · Cited by 1,428 · see citing works
Hickson, L. J., Langhi Prata, L. G. P., Bobart, S. A., Evans, T. K., Giorgadze, N., Hashmi, S. K., Herrmann, S. M., Jensen, M. D., Jia, Q., Jordan, K. L., et al. (2019) · EBioMedicine · doi:10.1016/j.ebiom.2019.08.069 · Cited by 1,383 · see citing works
A proteomic atlas of senescence-associated secretomes for aging biomarker development
Basisty, N., Kale, A., Jeon, O. H., Kuehnemann, C., Payne, T., Rao, C., Holtz, A., Shah, S., Sharma, V., Ferrucci, L., et al. (2020) · PLOS Biology · doi:10.1371/journal.pbio.3000599 · Cited by 1,348 · see citing works
Senolytic drugs: from discovery to translation
Kirkland, J. L., & Tchkonia, T. (2020) · Journal of Internal Medicine · doi:10.1111/joim.13141 · Cited by 1,227 · see citing works
Senescence in tumours: evidence from mice and humans
Collado, M., & Serrano, M. (2010) · Nature Reviews Cancer · doi:10.1038/nrc2772 · Cited by 1,124 · see citing works
Senolytic CAR T cells reverse senescence-associated pathologies
Amor, C., Feucht, J., Leibold, J., Ho, Y.-J., Zhu, C., Alonso-Curbelo, D., Mansilla-Soto, J., Boyer, J. A., Li, X., Giavridis, T., et al. (2020) · Nature · doi:10.1038/s41586-020-2403-9 · Cited by 1,098 · see citing works
Unmasking Transcriptional Heterogeneity in Senescent Cells
Hernandez-Segura, A., de Jong, T. V., Melov, S., Guryev, V., Campisi, J., & Demaria, M. (2017) · Current Biology · doi:10.1016/j.cub.2017.07.033 · Cited by 972 · see citing works
Synthetic lethal metabolic targeting of cellular senescence in cancer therapy
Dörr, J. R., Yu, Y., Milanovic, M., Beuster, G., Zasada, C., Däbritz, J. H. M., Lisec, J., Lenze, D., Gerhardt, A., Schleicher, K., et al. (2013) · Nature · doi:10.1038/nature12437 · Cited by 541 · see citing works
Cardiac glycosides are broad-spectrum senolytics
Guerrero, A., Herranz, N., Sun, B., Wagner, V., Gallage, S., Guiho, R., Wolter, K., Pombo, J., Irvine, E. E., Innes, A. J., et al. (2019) · Nature Metabolism · doi:10.1038/s42255-019-0122-z · Cited by 359 · see citing works
Transcriptome signature of cellular senescence
Casella, G., Munk, R., Kim, K. M., Piao, Y., De, S., Abdelmohsen, K., & Gorospe, M. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz555 · Cited by 359 · see citing works
A versatile drug delivery system targeting senescent cells
Muñoz‐Espín, D., Rovira, M., Galiana, I., Giménez, C., Lozano‐Torres, B., Paez‐Ribes, M., Llanos, S., Chaib, S., Muñoz‐Martín, M., Ucero, A. C., et al. (2018) · EMBO Molecular Medicine · doi:10.15252/emmm.201809355 · Cited by 339 · see citing works
Loss of linker histone H1 in cellular senescence
Funayama, R., Saito, M., Tanobe, H., & Ishikawa, F. (2006) · The Journal of Cell Biology · doi:10.1083/jcb.200604005 · Cited by 241 · see citing works
Cellular senescence in the aging and diseased kidney
Valentijn, F. A., Falke, L. L., Nguyen, T. Q., & Goldschmeding, R. (2018) · Journal of Cell Communication and Signaling · doi:10.1007/s12079-017-0434-2 · Cited by 173 · see citing works
High-Dimensional Phenotyping Identifies Age-Emergent Cells in Human Mammary Epithelia
Pelissier Vatter, F. A., Schapiro, D., Chang, H., Borowsky, A. D., Lee, J. K., Parvin, B., Stampfer, M. R., LaBarge, M. A., Bodenmiller, B., & Lorens, J. B. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.03.114 · Cited by 58 · see citing works
Senescence in aging and disorders of the central nervous system
Swenson, B. L., Meyer, C. F., Bussian, T. J., & Baker, D. J. (2019) · Translational Medicine of Aging · doi:10.1016/j.tma.2019.01.002 · Cited by 24 · see citing works
Flagged first, then by citations
- Authors
- Delfarah, A., Hartel, N. G., Zheng, D., Yang, J., & Graham, N. A.
- Affiliations
- University of Southern California (US)
- Corresponding author
- Graham, Nicholas A.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2021-10-12
- Volume
- 20
- Issue
- 11
- Pages
- 5169-5179
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W3105792631
- Cited by
- 8
- References
- 23
- Citations by year
- 2026: 1 · 2024: 3 · 2023: 2 · 2022: 2
- FWCI
- 1.10
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Journal of Proteome Research (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- Funders
- American Association for Cancer Research (20-80-44-GRAH)
- Rose Hills Foundation
- USC Provost's Office
- Viterbi School of Engineering
- Topics
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Keywords
- cellular senescence, proteomic signatures, human mammary epithelial cells, replicative senescence, telomerase reactivation, drug-induced senescence, lamin B1, galectin-7, lysosomal proteins, RNA metabolism, senescence biomarkers, transcriptome integration, aging
- MeSH terms
- Breast, Epithelial Cells, Humans, Cellular Senescence, Telomerase, Proteomics
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