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Published on: June 28, 2019
Algorithmic assessment of cellular senescence in experimental and clinical specimens
J Kohli1, B Wang1, S M Brandenburg1
1European Research Institute for the Biology of Ageing (ERIBA), University Medical Center Groningen (UMCG), University of Groningen (RUG), Groningen, the Netherlands.
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.
Insights
A new two-phase algorithm aids in identifying senescent cells and their subtypes. This method overcomes limitations of single markers, improving senescence research and senotherapy validation.
Area of Science:
- Biogerontology
- Cell Biology
- Molecular Biology
Background:
- Senescent cells play roles in aging and disease, leading to the development of senotherapies.
- Current challenges in senescence research stem from the lack of universal and specific markers for cell identification.
- Senotherapies are advancing to clinical trials, necessitating robust methods for evaluating senescent cell burden.
Purpose of the Study:
- To develop a comprehensive algorithmic approach for quantifying senescent cells and their subtypes.
- To overcome the limitations of relying on single markers for senescence identification.
- To provide a tool for improved characterization of senescence-associated phenotypes and validation of senotherapies.
Main Methods:
- A two-phase algorithmic assessment was designed to quantify senescence-associated parameters.
- Phase one combines lysosomal and proliferative features with general senescence-associated gene expression.
- Phase two measures pro-inflammatory markers to specify senescence subtypes.
Main Results:
- The protocol enables the quantification of multiple senescence markers within a single specimen.
- It facilitates the validation of senescent cell presence using combined cellular and molecular features.
- The method allows for the classification of different senescence subtypes based on inflammatory profiles.
Conclusions:
- This algorithmic protocol offers a robust method for characterizing senescent cells and their subtypes.
- It addresses the critical need for improved senescence identification in basic research.
- The protocol can significantly aid in the clinical validation of senotherapies and the role of senescent cells.
