Quantitative Proteomic Analysis of the Senescence-Associated Secretory Phenotype by Data-Independent Acquisition.
Open accessAbstract
Cellular senescence is a complex stress response that induces an essentially permanent cell cycle arrest and a complex secretory phenotype termed the senescence‐associated secretory phenotype (SASP), which drives numerous aging pathologies. Characterization of the SASP can provide insights into aging and disease mechanisms, aging biomarker candidates, and targets for counteracting the deleterious effects of senescent cells. Here we describe a mass spectrometry (MS)‐compatible protocol to (1) generate senescent cells using different stimuli, (2) collect conditioned medium containing proteins secreted by senescent cells (i.e., SASP), and (3) prepare the SASP for quantitative proteomic analysis using data‐independent acquisition (DIA) MS. © 2021 The Authors. This article was corrected on 19 July 2022. See the end of the full text for details. Basic Protocol 1: Generating ionizing radiation‐induced senescent and control cells Alternate Protocol 1: Generating doxorubicin‐induced senescent and control cells Alternate Protocol 2: Generating oncogenic RAS‐induced senescent and control cells Alternate Protocol 3: Generating mitochondrial dysfunction‐induced senescent and control cells Alternate Protocol 4: Generating atazanavir/ritonavir‐induced senescent and control cells Support Protocol: A multiple‐assay approach to confirm the phenotype of senescent cells Basic Protocol 2: Generating conditioned medium from senescent cells cultured in low serum and quiescent control cells Alternate Protocol 5: Generating conditioned medium from senescent cells cultured in complete medium and quiescent control cells Basic Protocol 3: Quantitative proteomic analysis of the SASP
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The model of senescence induction using ionizing radiation has been well established and proven to yield highly robust senescence induction.
“In general, this model of senescence induction using ionizing radiation (IR), has been well established and has proven to yield highly robust senescence induction as demonstrated in the Campisi lab [10, 20, 21] and many other labs.”
From Senescent cell heterogeneity and responses to senolytic treatment are related to cell cycle status during senescence induction (2025) · cites this paper as [20]
Basic Protocol 1, under “Generation of senescent cells” (page unavailable), says that 15 Gy of ionizing radiation should produce a full senescent phenotype in approximately 10 days, with almost all fibroblasts showing senescent morphology. This supports robust induction under the described conditions, but Strategic Planning says the protocol is optimized for IMR-90 fibroblasts and requires adjustment for other cell types; the source does not establish equally robust induction generally. (LLM, conf=0.82)
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Cites
The senescence-associated secretory phenotype: the dark side of tumor suppression
Coppé, J.-P., Desprez, P.-Y., Krtolica, A., & Campisi, J. (2010) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathol-121808-102144 · Cited by 5,206 · see citing works
Self-citationCellular senescence: when bad things happen to good cells
Campisi, J., & d'Adda di Fagagna, F. (2007) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2233 · Cited by 4,441 · see citing works
Self-citationCellular 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
Self-citationAging, Cellular Senescence, and Cancer
Campisi, J. (2013) · Annual Review of Physiology · doi:10.1146/annurev-physiol-030212-183653 · Cited by 2,954 · cited 2× · see citing works
“Mouse models and human cell and tissue experiments show that senescent cells can contribute to frailty and many age-related conditions, including type II diabetes, pulmonary fibrosis, and cancer, making cellular senescence a key driver of aging (Campisi, 2013; Munoz-Espin & Serrano, 2014).”
BackgroundSelf-citationGillet, L. C., Navarro, P., Tate, S., Röst, H., Selevsek, N., Reiter, L., Bonner, R., & Aebersold, R. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o111.016717 · Cited by 2,877 · see citing works
Cellular senescence: from physiology to pathology
Muñoz-Espín, D., & Serrano, M. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3823 · Cited by 2,818 · 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
Self-citationReversal of human cellular senescence: roles of the p53 and p16 pathways
Beauséjour, C. M., Krtolica, A., Galimi, F., Narita, M., Lowe, S. W., Yaswen, P., & Campisi, J. (2003) · The EMBO Journal · doi:10.1093/emboj/cdg417 · Cited by 1,457 · see citing works
Self-citationA 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
Self-citationUnmasking 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 · cited 3× · see citing works
“The SASP is extremely heterogeneous and dynamic, varying with the cell type and senescence-inducing stimulus, as well as how much time has passed since senescence was induced (Hernandez-Segura et al., 2017).”
BackgroundInfluentialSelf-citationA guide to assessing cellular senescence <i>in vitro</i> and <i>in vivo</i>
González‐Gualda, E., Baker, A. G., Fruk, L., & Muñoz‐Espín, D. (2021) · The FEBS Journal · doi:10.1111/febs.15570 · Cited by 645 · see citing works
The dynamic nature of senescence in cancer
Lee, S., & Schmitt, C. A. (2019) · Nature Cell Biology · doi:10.1038/s41556-018-0249-2 · Cited by 588 · see citing works
Collins, B. C., Hunter, C. L., Liu, Y., Schilling, B., Rosenberger, G., Bader, S. L., Chan, D. W., Gibson, B. W., Gingras, A.-C., Held, J. M., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00249-5 · Cited by 576 · see citing works
Self-citationA repository of assays to quantify 10,000 human proteins by SWATH-MS
Rosenberger, G., Koh, C. C., Guo, T., Röst, H. L., Kouvonen, P., Collins, B. C., Heusel, M., Liu, Y., Caron, E., Vichalkovski, A., et al. (2014) · Scientific Data · doi:10.1038/sdata.2014.31 · Cited by 413 · see citing works
The senescence-associated secretome as an indicator of age and medical risk
Schafer, M. J., Zhang, X., Kumar, A., Atkinson, E. J., Zhu, Y., Jachim, S., Mazula, D. L., Brown, A. K., Berning, M., Aversa, Z., et al. (2020) · JCI Insight · doi:10.1172/jci.insight.133668 · Cited by 401 · see citing works
Senescent cells and osteoarthritis: a painful connection
Jeon, O. H., David, N. E., Campisi, J., & Elisseeff, J. H. (2018) · Journal of Clinical Investigation · doi:10.1172/jci95147 · Cited by 354 · see citing works
Self-citationBorghesan, M., Fafián-Labora, J., Eleftheriadou, O., Carpintero-Fernández, P., Paez-Ribes, M., Vizcay-Barrena, G., Swisa, A., Kolodkin-Gal, D., Ximénez-Embún, P., Lowe, R., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.05.095 · Cited by 315 · see citing works
Coppé, J.-P., Patil, C. K., Rodier, F., Sun, Y., Muñoz, D. P., Goldstein, J., Nelson, P. S., Desprez, P.-Y., & Campisi, J. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060301 · Cited by 302 · cited 3× · see citing works
“Many biological effects (both beneficial and detrimental) that senescent cells exert on organisms are triggered by their secretome, termed senescence-associated secretory phenotype (SASP; Coppe et al., 2008).”
BackgroundMethodInfluentialÖzcan, S., Alessio, N., Acar, M. B., Mert, E., Omerli, F., Peluso, G., & Galderisi, U. (2016) · Aging · doi:10.18632/aging.100971 · Cited by 295 · see citing works
Jeon, O. H., Wilson, D. R., Clement, C. C., Rathod, S., Cherry, C., Powell, B. H., Lee, Z., Khalil, A. M., Green, J. J., Campisi, J., et al. (2019) · JCI Insight · doi:10.1172/jci.insight.125019 · Cited by 186 · see citing works
Self-citationSILAC Analysis Reveals Increased Secretion of Hemostasis-Related Factors by Senescent Cells
Wiley, C. D., Liu, S., Limbad, C., Zawadzka, A. M., Beck, J., Demaria, M., Artwood, R., Alimirah, F., Lopez-Dominguez, J.-A., Kuehnemann, C., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.08.049 · Cited by 137 · see citing works
Self-citationSchilling, B., Gibson, B. W., & Hunter, C. L. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-6747-6_16 · Cited by 88 · see citing works
Self-citationBasisty, N., Kale, A., Patel, S., Campisi, J., & Schilling, B. (2020) · Expert Review of Proteomics · doi:10.1080/14789450.2020.1766976 · Cited by 69 · see citing works
Self-citationThe induction of the fibroblast extracellular senescence metabolome is a dynamic process
James, E. N., Bennett, M. H., & Parkinson, E. K. (2018) · Scientific Reports · doi:10.1038/s41598-018-29809-5 · Cited by 16 · see citing works
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Self-citation
- Authors
- Neri, F., Basisty, N., Desprez, P., Campisi, J., & Schilling, B.
- Affiliations
- Buck Institute for Research on Aging (US)
- Corresponding author
- Schilling, Birgit
- Venue
- Current Protocols
- Publisher
- Wiley
- Published
- 2021-02
- Volume
- 1
- Issue
- 2
- Pages
- e32-e32
- ISSN
- 2691-1299 (ISSN-L)
- PMC
- PMC7898702
- OpenAlex
- W3127124851
- Cited by
- 48
- References
- 24
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 11 · 2023: 12 · 2022: 10 · 2021: 1
- FWCI
- 5.33
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Current Protocols (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Science Foundation (U01 AG060906‐02, U01 AG060906‐02S1, P01 AG017242, R01 AG051729, K99 AG065484, 1S10 OD016281)
- Topics
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Keywords
- cellular senescence, senescence-associated secretory phenotype, conditioned medium, secreted proteins, data-independent acquisition, quantitative proteomics, doxorubicin-induced senescence, mitochondrial dysfunction, atazanavir/ritonavir, aging biomarkers, senolytics
- MeSH terms
- Cells, Cultured, Phenotype, Cellular Senescence, Culture Media, Conditioned, Proteomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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