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: | , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
18 December 2024
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| 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 |
MARC
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| 245 | 1 | 2 | |a 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 |b research |c Mario Vitacolonna, Roman Bruch, Richard Schneider, Julia Jabs, Mathias Hafner, Markus Reischl and Rüdiger Rudolf |
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| 520 | |a 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. | ||
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| 700 | 1 | |a Schneider, Richard |e VerfasserIn |4 aut | |
| 700 | 1 | |a Jabs, Julia |e VerfasserIn |4 aut | |
| 700 | 1 | |a Hafner, Mathias |d 1956- |e VerfasserIn |0 (DE-588)1027781187 |0 (DE-627)729718379 |0 (DE-576)375302956 |4 aut | |
| 700 | 1 | |a Reischl, Markus |e VerfasserIn |4 aut | |
| 700 | 1 | |a Rudolf, Rüdiger |e VerfasserIn |4 aut | |
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