3D microgels to quantify tumor cell properties and therapy response 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.