Algorithmic assessment of cellular senescence in experimental and clinical samples

Unequivocal identification and examination of cellular senescence remains highly difficult because of the lack of universal and specific markers. 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.

 

Kohli J, Wang B, Brandenburg SM, Basisty N, Evangelou K, Varela-Eirin M, Campisi J, Schilling B, Gorgoulis V, Demaria M. Algorithmic assessment of cellular senescence in experimental and clinical specimens. Nature Protocols 2021. 2021 May;16(5):2471-2498.

 

 

VG New

Prof. Vassilis G. Gorgoulis

Laboratory of Histology-Embryology
Molecular Carcinogenesis Group
Medical School
National and Kapodistrian University of Athens

 

 

Chair of Clinical Molecular Pathology,

Ninewells Hospital and School of Medicine

 

University of Dundee, Dundee, UK

 

Biomedical Research Foundation of the Academy of Athens

 

Faculty Institute for Cancer Sciences, University of Manchester,
Manchester Academic Health Science Centre, Manchester, UK

Manchester Centre for Cellular Metabolism,
University of Manchester, Manchester Academic Health Science Centre, Manchester

 

EMBO member

 

European Academy
of Cancer Sciences member

 

Academia Europaea member

 

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