A spheroid whole mount drug testing pipeline with machine-learning based image analysis identifies cell-type specific differences in drug efficacy on a single-cell level: research

The growth and drug response of tumors are influenced by their stromal composition, both in vivo and 3D-cell culture models. Cell-type inherent features as well as mutual relationships between the different cell types in a tumor might affect drug susceptibility of the tumor as a whole and/or of its...

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Main Authors: Vitacolonna, Mario (Author) , Bruch, Roman (Author) , Schneider, Richard (Author) , Jabs, Julia (Author) , Hafner, Mathias (Author) , Reischl, Markus (Author) , Rudolf, Rüdiger (Author)
Format: Article (Journal)
Language:English
Published: 18 December 2024
In: BMC cancer
Year: 2024, Volume: 24, Issue: 1, Pages: 1-23
ISSN:1471-2407
DOI:10.1186/s12885-024-13329-9
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1186/s12885-024-13329-9
Verlag, kostenfrei, Volltext: http://bmccancer.biomedcentral.com/articles/10.1186/s12885-024-13329-9
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Author Notes:Mario Vitacolonna, Roman Bruch, Richard Schneider, Julia Jabs, Mathias Hafner, Markus Reischl and Rüdiger Rudolf
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Summary:The growth and drug response of tumors are influenced by their stromal composition, both in vivo and 3D-cell culture models. Cell-type inherent features as well as mutual relationships between the different cell types in a tumor might affect drug susceptibility of the tumor as a whole and/or of its cell populations. However, a lack of single-cell procedures with sufficient detail has hampered the automated observation of cell-type-specific effects in three-dimensional stroma-tumor cell co-cultures. Here, we developed a high-content pipeline ranging from the setup of novel tumor-fibroblast spheroid co-cultures over optical tissue clearing, whole mount staining, and 3D confocal microscopy to optimized 3D-image segmentation and a 3D-deep-learning model to automate the analysis of a range of cell-type-specific processes, such as cell proliferation, apoptosis, necrosis, drug susceptibility, nuclear morphology, and cell density. This demonstrated that co-cultures of KP-4 tumor cells with CCD-1137Sk fibroblasts exhibited a growth advantage compared to tumor cell mono-cultures, resulting in higher cell counts following cytostatic treatments with paclitaxel and doxorubicin. However, cell-type-specific single-cell analysis revealed that this apparent benefit of co-cultures was due to a higher resilience of fibroblasts against the drugs and did not indicate a higher drug resistance of the KP-4 cancer cells during co-culture. Conversely, cancer cells were partially even more susceptible in the presence of fibroblasts than in mono-cultures. In summary, this underlines that a novel cell-type-specific single-cell analysis method can reveal critical insights regarding the mechanism of action of drug substances in three-dimensional cell culture models.
Item Description:Gesehen am 24.04.2025
Physical Description:Online Resource
ISSN:1471-2407
DOI:10.1186/s12885-024-13329-9