A high-throughput workflow for assessing self-renewal using colony formation assays

The colony formation assay (CFA) is a widely used method to assess the self-renewal capacity of cancer cells and evaluate how this property is affected by drug treatment. This protocol presents a streamlined, high-throughput CFA workflow optimized for T-cell acute lymphoblastic leukemia (T-ALL), making it suitable for large-scale drug screening projects. Colonies are grown in a methylcellulose-based 3D matrix and quantified using an automated analysis pipeline, allowing robust estimation of colony number and size. This cost-effective approach provides a scalable platform for identifying compounds that impair self-renewal, facilitating prioritization of hits for validation in more complex in vivo models.

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Publication Details

Journal
Stem Cell Research
Published
2025-06-19
DOI
https://doi.org/10.1016/j.scr.2025.103757
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

A high-throughput workflow for assessing self-renewal using colony formation assays

Majd A. Al‐Hamaly, Jessica S. Blackburn
Stem Cell Research
Cell Image Analysis Techniques
article

A high-throughput workflow for assessing self-renewal using colony formation assays

Majd A. Al‐Hamaly, Jessica S. Blackburn
article en

Abstract

The colony formation assay (CFA) is a widely used method to assess the self-renewal capacity of cancer cells and evaluate how this property is affected by drug treatment. This protocol presents a streamlined, high-throughput CFA workflow optimized for T-cell acute lymphoblastic leukemia (T-ALL), making it suitable for large-scale drug screening projects. Colonies are grown in a methylcellulose-based 3D matrix and quantified using an automated analysis pipeline, allowing robust estimation of colony number and size. This cost-effective approach provides a scalable platform for identifying compounds that impair self-renewal, facilitating prioritization of hits for validation in more complex in vivo models.

Stem Cell ResearchVol. 87
University of Kentucky (US), Markey Cancer Center (US)
Pediatric Cancer Research Foundation, University of Kentucky, National Cancer Institute
Openalex Percentile: Top 89%
Cell Image Analysis Techniques
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