Evidence map›Paper›PMID 33524224›Full record

ArticleCurrent protocols2021

Quantitative Proteomic Analysis of the Senescence-Associated Secretory Phenotype by Data-Independent Acquisition.

Francesco Neri, Nathan Basisty, Pierre-Yves Desprez, Judith Campisi, Birgit Schilling

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Current protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
4.7field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 50 citations in OpenAlex.

  1. AcutebioRxiv : the preprint server for biology · 2026
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  6. Review
  7. Article
  8. A multi-omics analysis of human fibroblasts overexpressing anbioRxiv : the preprint server for biology · 2025
    Article
  9. Article
  10. Review
  11. Article
  12. Article
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  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Francesco NeriThe Buck Institute for Research on Aging, Novato, California.
Nathan BasistyThe Buck Institute for Research on Aging, Novato, California.
Pierre-Yves DesprezThe Buck Institute for Research on Aging, Novato, California.
Judith CampisiThe Buck Institute for Research on Aging, Novato, California.
Birgit SchillingThe Buck Institute for Research on Aging, Novato, California.
Buck Institute for Research on Aging · USCalifornia Pacific Medical Center · USUniversity of California, Berkeley · US

Funding

THE IMPACT OF CELLULAR DEFENSE ON THE ROLE OF Ku80 IN GENOME MAINTENANCE AND LONGP01AG017242 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR SAN ANT · PI VIJG, JAN · 1999 to 2023
$46.1M
USC-Buck Institute Nathan Shock Admin CoreP30AG068345 · NIA · BUCK INSTITUTE FOR RESEARCH ON AGING · PI LITHGOW, GORDON J · 2020 to 2024
$5.0M
Quantitative Proteomics to Develop Robust Senescence-Related Biomarkers for AgingU01AG060906 · NIA · BUCK INSTITUTE FOR RESEARCH ON AGING · PI SCHILLING, BIRGIT · 2018 to 2022
$4.0M
Cellular Senescence, astrocytes and Alzheimer's diseaseR01AG051729 · NIA · BUCK INSTITUTE FOR RESEARCH ON AGING · PI CAMPISI, JUDITH · 2016 to 2020
$2.7M
Orbitrap Fusion Lumos ETD with FAIMS ProS10OD028654 · OD · BUCK INSTITUTE FOR RESEARCH ON AGING · PI SCHILLING, BIRGIT · 2020 to 2020
$1.1M
TripleTOF 5600 High Resolution Mass SpectrometerS10OD016281 · OD · BUCK INSTITUTE FOR RESEARCH ON AGING · PI GIBSON, BRADFORD WAYNE · 2013 to 2013
$597k
Quantitating, Targeting, and Phenotyping In Vivo Cellular Senescence in HumansK99AG065484 · NIA · BUCK INSTITUTE FOR RESEARCH ON AGING · PI BASISTY, NATAN BOHDONIVICH · 2020 to 2021
$158k
NIA NIH HHS K99 AG065484NIA NIH HHS P01 AG017242NIA NIH HHS P30 AG068345NIA NIH HHS R01 AG051729NIA NIH HHS U01 AG060906NIH HHS 1S10 OD016281NIH HHS K99 AG065484NIH HHS P01 AG017242NIH HHS R01 AG051729NIH HHS S10 OD016281NIH HHS S10 OD028654NIH HHS U01 AG060906-02NIH HHS U01 AG060906-02S1
6 · The paper itself

Abstract

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. 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.

Indexed as

Cellular SenescenceProteomicsCells, CulturedCulture Media, ConditionedPhenotypeCulture Media, Conditionedagingdata-independent acquisitionmass spectrometryquantitative proteomic analysissecretomesenescence

Identifiers

PMID33524224
PMCPMC7898702
OpenAlexW3127124851

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.