A spheroid whole mount drug testing pipeline with machine-learning based image analysis identifies cell-type specific
Mario Vitacolonna1,2, Roman Bruch3, Richard Schneider4
1CeMOS, Mannheim University of Applied Sciences, 68163, Mannheim, Germany. m.vitacolonna@hs-mannheim.de.
Background:
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.
Methods:
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.
Results:
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.
Conclusion:
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.
Insights
Tumor-stroma co-cultures show complex drug responses. New single-cell analysis reveals fibroblasts enhance cancer cell drug susceptibility, contrary to initial observations of increased tumor cell counts.
Area of Science:
- Oncology
- Cell Biology
- Biotechnology
Background:
- Tumor growth and drug response are influenced by stromal composition in vivo and in 3D models.
- Cellular interactions within tumors can affect drug susceptibility.
- Limited single-cell analysis methods hinder understanding of 3D co-culture effects.
Purpose of the Study:
- To develop a high-content pipeline for automated, cell-type-specific analysis in 3D tumor-fibroblast co-cultures.
- To investigate the impact of stromal fibroblasts on cancer cell drug susceptibility.
Main Methods:
- Established novel tumor-fibroblast spheroid co-cultures.
- Employed optical tissue clearing, whole mount staining, and 3D confocal microscopy.
- Utilized 3D-deep learning for automated analysis of cell proliferation, apoptosis, necrosis, and drug susceptibility.
Main Results:
- Co-cultures showed higher cell counts post-treatment than mono-cultures, initially suggesting a growth advantage.
- Single-cell analysis revealed fibroblasts had higher drug resilience, not cancer cells.
- Cancer cells exhibited increased susceptibility to drugs when co-cultured with fibroblasts.
Conclusions:
- A novel cell-type-specific single-cell analysis method provides critical insights into drug mechanisms in 3D models.
- Stromal interactions significantly modulate cancer cell drug response.
- Automated analysis of 3D co-cultures is crucial for understanding tumor biology and drug action.
