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Updated: Mar 6, 2026
Generation of High-Throughput Three-Dimensional Tumor Spheroids for Drug Screening
Published on: September 5, 2018
RNAi High-Throughput Screening of Single- and Multi-Cell-Type Tumor Spheroids: A Comprehensive Analysis in Two and
Jiaqi Fu1, Daniel Fernandez1, Marc Ferrer1
11 Division of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, USA.
Abstract:
The widespread use of two-dimensional (2D) monolayer cultures for high-throughput screening (HTS) to identify targets in drug discovery has led to attrition in the number of drug targets being validated. Solid tumors are complex, aberrantly growing microenvironments that harness structural components from stroma, nutrients fed through vasculature, and immunosuppressive factors. Increasing evidence of stromally-derived signaling broadens the complexity of our understanding of the tumor microenvironment while stressing the importance of developing better models that reflect these interactions. Three-dimensional (3D) models may be more sensitive to certain gene-silencing events than 2D models because of their components of hypoxia, nutrient gradients, and increased dependence on cell-cell interactions and therefore are more representative of in vivo interactions. Colorectal cancer (CRC) and breast cancer (BC) models composed of epithelial cells only, deemed single-cell-type tumor spheroids (SCTS) and multi-cell-type tumor spheroids (MCTS), containing fibroblasts were developed for RNAi HTS in 384-well microplates with flat-bottom wells for 2D screening and round-bottom, ultra-low-attachment wells for 3D screening. We describe the development of a high-throughput assay platform that can assess physiologically relevant phenotypic differences between screening 2D versus 3D SCTS, 3D SCTS, and MCTS in the context of different cancer subtypes. This assay platform represents a paradigm shift in how we approach drug discovery that can reduce the attrition rate of drugs that enter the clinic.
Insights
Developing advanced three-dimensional (3D) cancer models improves drug discovery by better reflecting in vivo conditions than traditional 2D cultures, reducing drug target attrition.
Area of Science:
- Oncology
- Drug Discovery
- Biotechnology
Background:
- Two-dimensional (2D) monolayer cultures are widely used in high-throughput screening (HTS) for drug discovery but show limitations in validating drug targets.
- Solid tumors are complex microenvironments involving stromal components, vasculature, and immunosuppressive factors, necessitating more physiologically relevant models.
- Three-dimensional (3D) models, incorporating hypoxia and nutrient gradients, offer a more accurate representation of in vivo tumor biology compared to 2D cultures.
Purpose of the Study:
- To develop a high-throughput assay platform for assessing phenotypic differences between 2D and 3D cancer models.
- To compare the efficacy of single-cell-type tumor spheroids (SCTS) and multi-cell-type tumor spheroids (MCTS) in 3D screening.
- To establish a more predictive model for drug discovery, aiming to reduce clinical trial attrition.
Main Methods:
- Development of 3D colorectal cancer (CRC) and breast cancer (BC) models, including SCTS and MCTS with fibroblasts.
- Utilized 384-well microplates with flat-bottom wells for 2D screening and round-bottom, ultra-low-attachment wells for 3D screening.
- Established a high-throughput assay to evaluate phenotypic differences in various cancer models.
Main Results:
- The developed platform can differentiate physiologically relevant phenotypic variations between 2D and 3D SCTS, and between 3D SCTS and MCTS.
- 3D models demonstrated increased sensitivity to gene-silencing events due to inherent hypoxia and nutrient gradients.
- The assay platform facilitates the assessment of cancer models reflecting in vivo interactions more accurately.
Conclusions:
- The high-throughput assay platform represents a significant advancement in drug discovery modeling.
- This approach can reduce the attrition rate of drug candidates entering clinical trials.
- The study highlights the importance of 3D cancer models for more effective target identification and validation.
