3D Cell Models Derived from Patient Tumors – A New Approach to Accelerate Identification of Drug Targets and Testing

Adding another dimension to cell models sharpens a predictive tool

2D monolayer cell cultures fail to imitate many aspects of tumor architecture and microenvironments. These limitations have driven the development of 3D models that more accurately recapitulate the cellular composition of tumors. 3D models have many advantages over 2D models ^[3], including:

• The natural cell morphology is preserved, and cells grow into multiple layers
• The 3D form mimics the access to nutrients in tumors, with core cells often inactive
• Cells are well differentiated
• Cell junctions are common
• 3D models are more resistant to drugs and with better metabolism to give a more accurate representation of drug effects
• Cell proliferation rates are realistic and can be modulated
• Gene and protein expression levels resemble those of cells in vivo
• Levels of resistance to drug-induced apoptosis are higher
• Cells respond more realistically to mechanical stimuli

Overall, 3D cell cultures increase the dimensionality of cell-cell interactions that are fundamental to generating a phenotype predictive of in vivo biology but performed in vitro ^[4]. As a result, 3D models are a better predictive tool for drug discovery compared to 2D models, and show great promise in guiding personalized medicine, including immunotherapy ^[5,6,7].

3D cell models can take many forms

Spheroids are relatively simple 3D cell models derived from cell lines, multicellular mixtures, primary cells, tumor cells and tissues.

Organoids are more complex than spheroids and have been defined in many ways ^[8]. One definition is a self-organized cell aggregate derived from primary tissue or mesenchymal stem cells (MSCs) capable of self-renewal, typically organized in 3D constructs that replicate the complex structure of an organ and mimic its in vivo physiology ^[7].

Tumoroids are essentially “tumor-like organoids” that are typically prepared using cells from primary tumors harvested from patients.

Tumoroids – highly translational tools that give new insights into cancer

Tumoroids can recapitulate the complex genetic and molecular compositions of solid cancers, making them extremely valuable in the study of disease progression, the identification of drug targets, and drug testing in general. At the level of the individual, a tumoroid based on a patient’s tumor cells can be used in personalized medicine to predict the response of specific tumors to therapy.

One series of proof-of-concept studies demonstrates the potential for high-resolution image-based analysis of 3D spheroid models for drug discovery applications that could soon be routine practice in drug discovery workflows ^[9]. The studies included studying real-time immune cell interactions in a multicellular 3D lung cancer model and using a 3D model of gastric carcinoma in a high throughput screening application to determine dose-dependent drug efficacy.

Another example examines factors affecting human glioblastoma angiogenesis and shows the power of tumoroids in mimicking complex tumor microenvironments ^[10]. The model is scalable, easy to control, cost-effective, and can be used as a preclinical model to study microenvironment cues of tumor angiogenesis.

The value of tumoroids in personalized medicine is illustrated by a study on lung cancer ^[11]. A cancer form that shows substantial genetic and phenotypic heterogeneity across individuals, making it particularly interesting as a target for personalized medicine. Tumoroids and normal bronchial organoids were quickly established from patient tissues and recapitulated the original tissue architecture and genomic alterations even after extensive in vitro expansion. The tumoroids also responded to drugs based on their genomic alterations, making them a powerful tool for predicting patient-specific drug responses.