Comparison of in vitro migration assays evaluating nintedanib’s migration inhibitory effects on melanoma cells

Cell migration plays a central role in tumor progression and metastasis, making it a critical parameter in both cancer biology and therapeutic evaluation. A range of in vitro migration assays are commonly used to assess treatment-induced effects on motility, each with distinct advantages and limitations that must be considered when interpreting results. In this study, we systematically compared four migration assay formats-scratch, zone-exclusion (Z-E), transwell, and single-cell tracking-across five melanoma cell lines treated with the multi-kinase inhibitor nintedanib. Migration inhibition was quantified for each assay, alongside machine learning-based classification to evaluate the discriminative power of assay-derived features in detecting treatment effects. All assays detected inhibitory effects of nintedanib, although response magnitude varied across formats. The transwell assay demonstrated clear inhibition in most lines but was sensitive to morphological changes. Gap closure assay-based migration rankings were influenced by cell size, underscoring the importance of size normalization. Scratch assays exhibited greater variability and potential confounding due to cell damage, while Z-E assays generated more uniform gaps without mechanical disruption. Single-cell tracking enabled high-resolution phenotypic profiling, including cell-specific features such as size and shape, resulting in consistently high classification accuracy. These findings highlight the importance of selecting appropriate assay formats to accurately evaluate migration behavior and the therapeutic efficacy of anti-migratory compounds.

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Publication Details

Journal
Scientific Reports
Published
2025-11-28
DOI
https://doi.org/10.1038/s41598-025-26571-3
Primary Topic
Mathematical Biology Tumor Growth
Type
article
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article

Comparison of in vitro migration assays evaluating nintedanib’s migration inhibitory effects on melanoma cells

Csaba Márton Köllőd, Afrodíté Németh, Gréta L. Bányai, Nikolett Kitti Dobos et al.
Scientific Reports
Mathematical Biology Tumor Growth
article

Comparison of in vitro migration assays evaluating nintedanib’s migration inhibitory effects on melanoma cells

Csaba Márton Köllőd, Afrodíté Németh, Gréta L. Bányai, Nikolett Kitti Dobos, Tamás Garay, Mátyás Andrészek
article en

Abstract

Cell migration plays a central role in tumor progression and metastasis, making it a critical parameter in both cancer biology and therapeutic evaluation. A range of in vitro migration assays are commonly used to assess treatment-induced effects on motility, each with distinct advantages and limitations that must be considered when interpreting results. In this study, we systematically compared four migration assay formats-scratch, zone-exclusion (Z-E), transwell, and single-cell tracking-across five melanoma cell lines treated with the multi-kinase inhibitor nintedanib. Migration inhibition was quantified for each assay, alongside machine learning-based classification to evaluate the discriminative power of assay-derived features in detecting treatment effects. All assays detected inhibitory effects of nintedanib, although response magnitude varied across formats. The transwell assay demonstrated clear inhibition in most lines but was sensitive to morphological changes. Gap closure assay-based migration rankings were influenced by cell size, underscoring the importance of size normalization. Scratch assays exhibited greater variability and potential confounding due to cell damage, while Z-E assays generated more uniform gaps without mechanical disruption. Single-cell tracking enabled high-resolution phenotypic profiling, including cell-specific features such as size and shape, resulting in consistently high classification accuracy. These findings highlight the importance of selecting appropriate assay formats to accurately evaluate migration behavior and the therapeutic efficacy of anti-migratory compounds.

Scientific ReportsVol. 15(1)
Semmelweis University (HU), Pázmány Péter Catholic University (HU)
Openalex Percentile: Top 59%
Mathematical Biology Tumor Growth
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