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Updated: May 16, 2025

Monitoring Cancer Cell Invasion and T-Cell Cytotoxicity in 3D Culture
Published on: June 23, 2020
3D Tumor Model to Study Immune Cell Infiltration
Jakob Dittmer1, Catarina Pinto1, Claudia Reichel-Voda1
1Boehringer Ingelheim RCV GmbH & Co KG, Vienna, Austria.
Abstract:
Drug discovery in oncology is characterized by high attrition rates in clinical trials. The main reasons are lack of efficacy or unacceptable toxicity. Thus, more predictive preclinical models for drug discovery and development are urgently needed. In the field of immune-oncology, preclinical models are particularly demanding since they have to reflect the complex interplay between tumor cells and immune cells in the human body.The recent years were characterized by vast advancement in 3D in vitro models and organoid techniques. These models mimic the tumor microenvironment more realistically than traditional 2D cell cultures. They can include the main components of the tumor microenvironment, like (primary) tumor cells, immune cells and other stromal cells and allow growth and interaction of the diverse cell types in 3D. Thus, these 3D models provide a physiologically relevant platform for studying the mode of action of (immuno-) oncologic therapeutic drugs. SMAC (second mitochondrial-derived activator of caspases) mimetics, like many other anticancer drugs, can exert their effects on different cell populations within the tumor microenvironment, which can be analyzed by using 3D co-cultures as preclinical models.Fluorescence microscopy is a powerful tool to study biological processes. In live cell imaging, entire cells or subcellular structures can be monitored over time with the help of fluorescent labels.In this chapter, we describe a human 3D co-culture infiltration assay combining tumor cells embedded in a hydrogel and immune cells added on top of the hydrogel. This 3D co-culture is stable for more than 1 week and gives insights into cellular drug responses over time. We used live cell imaging/fluorescence microscopy as the main readout to quantify immune cell infiltration in 3D in response to SMAC mimetic treatment.
Insights
Developing advanced 3D co-culture models improves preclinical cancer drug testing. This study uses live imaging to track immune cell infiltration in response to SMAC mimetic treatments within these models.
Area of Science:
- Oncology
- Immunology
- Biotechnology
Background:
- High attrition rates in oncology drug discovery due to lack of efficacy or toxicity necessitate improved preclinical models.
- Immuno-oncology requires models that accurately reflect the complex tumor-immune cell interactions within the human body.
- Recent advancements in 3D in vitro and organoid techniques offer more realistic tumor microenvironment simulations compared to traditional 2D cultures.
Purpose of the Study:
- To describe a human 3D co-culture infiltration assay for evaluating drug responses in cancer research.
- To assess the efficacy of SMAC (second mitochondrial-derived activator of caspases) mimetics using a novel 3D model.
- To quantify immune cell infiltration in a 3D tumor microenvironment using live cell imaging.
Main Methods:
- Development of a human 3D co-culture model with tumor cells in hydrogel and immune cells on top.
- Utilizing live cell imaging and fluorescence microscopy as the primary readout method.
- Monitoring cellular drug responses and immune cell infiltration over a one-week period.
Main Results:
- The described 3D co-culture model remained stable for over a week, providing sustained observation of cellular dynamics.
- Live cell imaging successfully quantified immune cell infiltration in response to SMAC mimetic treatment within the 3D model.
- The model demonstrated its utility in studying the effects of anticancer drugs on various cell populations in the tumor microenvironment.
Conclusions:
- 3D co-culture models offer a physiologically relevant platform for preclinical evaluation of immuno-oncology drugs.
- This assay provides valuable insights into cellular drug responses and immune cell infiltration dynamics.
- The developed model and imaging approach can enhance the predictive power of preclinical cancer drug discovery.

