Algorithmic assessment of cellular senescence in experimental and clinical specimens

J Kohli, B Wang, S M Brandenburg, N Basisty, K Evangelou, M Varela-Eirin, J Campisi, B Schilling, V Gorgoulis*, M Demaria

*Corresponding author for this work

    Research output: Contribution to journalReview articlepeer-review

    126 Citations (Scopus)
    140 Downloads (Pure)

    Abstract

    The development of genetic tools allowed for the validation of the pro-aging and pro-disease functions of senescent cells in vivo. These discoveries prompted the development of senotherapies-pharmaceutical interventions aimed at interfering with the detrimental effect of senescent cells-that are now entering the clinical stage. However, unequivocal identification and examination of cellular senescence remains highly difficult because of the lack of universal and specific markers. Here, to overcome the limitation of measuring individual markers, we describe a detailed two-phase algorithmic assessment to quantify various senescence-associated parameters in the same specimen. In the first phase, we combine the measurement of lysosomal and proliferative features with the expression of general senescence-associated genes to validate the presence of senescent cells. In the second phase we measure the levels of pro-inflammatory markers for specification of the type of senescence. The protocol can help graduate-level basic scientists to improve the characterization of senescence-associated phenotypes and the identification of specific senescent subtypes. Moreover, it can serve as an important tool for the clinical validation of the role of senescent cells and the effectiveness of anti-senescence therapies.

    Original languageEnglish
    Pages (from-to)2471-1501
    Number of pages31
    JournalNature protocols
    Volume16
    Issue number5
    Early online date28-Apr-2021
    DOIs
    Publication statusPublished - May-2021

    Fingerprint

    Dive into the research topics of 'Algorithmic assessment of cellular senescence in experimental and clinical specimens'. Together they form a unique fingerprint.

    Cite this