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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Vitacolonna, Mario (VerfasserIn) , Bruch, Roman (VerfasserIn) , Schneider, Richard (VerfasserIn) , Jabs, Julia (VerfasserIn) , Hafner, Mathias (VerfasserIn) , Reischl, Markus (VerfasserIn) , Rudolf, Rüdiger (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 18 December 2024
In: BMC cancer
Year: 2024, Jahrgang: 24, Heft: 1, Pages: 1-23
ISSN:1471-2407
DOI:10.1186/s12885-024-13329-9
Online-Zugang: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
Volltext
Verfasserangaben:Mario Vitacolonna, Roman Bruch, Richard Schneider, Julia Jabs, Mathias Hafner, Markus Reischl and Rüdiger Rudolf
Beschreibung
Zusammenfassung: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.
Beschreibung:Gesehen am 24.04.2025
Beschreibung:Online Resource
ISSN:1471-2407
DOI:10.1186/s12885-024-13329-9