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Simultaneous Imaging and Flow-Cytometry-based Detection of Multiple Fluorescent Senescence Markers in Therapy-Induced Senescent Cancer Cells
Published on: July 12, 2022
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Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry
Marco Malavolta1, Robertina Giacconi1, Francesco Piacenza1
1Advanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy.
Cells
|August 26, 2022
Summary
We developed a new imaging flow cytometry method using AI to detect cellular senescence, outperforming traditional markers. This simple assay can identify senescence in patient cells and evaluate senolytic treatments.
Area of Science:
- Biotechnology
- Cell Biology
- Gerontology
Background:
- Cellular senescence is a key aging factor and therapeutic target.
- Current methods for identifying senescent cells are complex and variable.
Purpose of the Study:
- To develop a simple, broadly applicable imaging flow cytometry (IFC) method for detecting cellular senescence.
- To utilize artificial intelligence (AI) and machine learning (ML) for senescence detection.
Main Methods:
- Developed an IFC method measuring autofluorescence and morphological parameters.
- Applied AI and ML tools to analyze IFC data.
- Compared the novel method with senescence-associated beta-galactosidase (SA-β-Gal) staining.
Main Results:
- The IFC method demonstrated superior performance compared to SA-β-Gal.
- Successfully detected senescence in cardiac pericytes from heart failure patients.
- Quantified senescence in vivo and evaluated senolytic compound efficacy.
Conclusions:
- The proposed IFC method offers a simple, fast, and versatile assay for cellular senescence detection.
- This method has potential for diagnostic and prognostic applications in aging-related diseases.
- It is applicable across different cell types and senescence induction methods.
