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Updated: Oct 1, 2025

Longitudinal Measurement of Extracellular Matrix Rigidity in 3D Tumor Models Using Particle-tracking Microrheology
Published on: June 10, 2014
3D microgels to quantify tumor cell properties and therapy response dynamics
Nila C Wu1, Jose L Cadavid2, Xinzhu Tan3
1Institute of Biomedical Engineering, University of Toronto, Toronto, ON, M5S 3G9, Canada.
Abstract:
Tumors contain heterogeneous and dynamic populations of cells that do not all display the fast-proliferating properties that traditional chemotherapies target. There is a need therefore, to develop novel treatment strategies that target diverse tumor cell properties. Identifying therapy combinations is challenging however. Current approaches have relied on cell lines cultured in monolayers with treatment response being assessed using endpoint metabolic assays, which although enable large-scale throughput, do not capture tumor heterogeneity. Here, a 3D in vitro tumor model using micro-molded hydrogels (microgels), the Gels for Live Analysis of Compartmentalized Environments (GLAnCE) platform, is adapted into a 96-well plate format (96-GLAnCE) that integrates patient-derived organoids (PDOs) and is combined with longitudinal automated imaging to address these limitations. Using 96-GLAnCE, two measures of tumor aggressiveness are quantified, tumor cell growth and in situ regrowth after drug treatment, in both cell lines and PDOs. The use of longitudinal image-based readouts enables the identification of tumor cell phenotypes with cell population and subpopulation resolution that cannot be detected by standard bulk-soluble assays. 96-GLAnCE is a versatile and robust platform that combines 3D-ECM based models, PDOs, and real-time assay readouts, to provide an additional tool for pre-clinical anti-cancer drug discovery for the identification of novel targets with translatable clinical significance.
Insights
A new 96-well plate platform, 96-GLAnCE, uses 3D organoids and imaging to better assess anti-cancer drug effectiveness by capturing tumor cell diversity and regrowth dynamics.
Area of Science:
- Oncology
- Biotechnology
- Drug Discovery
Background:
- Tumors exhibit cellular heterogeneity, challenging traditional chemotherapy efficacy.
- Current drug screening methods using 2D cell cultures and endpoint assays fail to capture complex tumor biology.
- Novel therapeutic strategies are needed to target diverse tumor cell properties and improve pre-clinical drug discovery.
Purpose of the Study:
- To develop and validate a 3D in vitro tumor model for enhanced pre-clinical drug screening.
- To assess tumor cell growth and drug-induced regrowth dynamics in a heterogeneous cell environment.
- To identify novel therapeutic targets by analyzing longitudinal, image-based readouts of tumor phenotypes.
Main Methods:
- Adaptation of the Gels for Live Analysis of Compartmentalized Environments (GLAnCE) platform into a 96-well format (96-GLAnCE).
- Integration of patient-derived organoids (PDOs) within a 3D extracellular matrix (ECM) microgel environment.
- Longitudinal automated imaging for quantitative assessment of tumor cell growth and in situ regrowth post-treatment.
Main Results:
- The 96-GLAnCE platform successfully quantified tumor aggressiveness, including cell growth and post-drug regrowth, in both cell lines and PDOs.
- Longitudinal imaging revealed distinct tumor cell phenotypes and subpopulation dynamics not detectable by standard bulk assays.
- The platform demonstrated robustness in combining 3D ECM models, PDOs, and real-time imaging for drug response assessment.
Conclusions:
- The 96-GLAnCE platform offers a versatile tool for pre-clinical anti-cancer drug discovery.
- This model overcomes limitations of traditional methods by incorporating tumor heterogeneity and dynamic responses.
- It facilitates the identification of novel therapeutic targets with potential clinical significance.
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