BEST IN PHYSICS (MULTI-DISCIPLINARY): A Lung Tumor-on-a-Chip Model for Studying Hypoxia Driven Radiation Resistance and FDG-PET Based Metabolic Response
Abstract
Purpose
Tumor hypoxia is a major driver of radiation resistance in solid tumors, yet its contribution to treatment response and metabolic reprogramming remains challenging to study using conventional models. This work proposes and validates a lung tumor-on-a-chip platform for preclinical radiotherapy research, with a focus on investigating hypoxia impact on radiation response and tumor metabolism.
Methods
A lung tumor-on-a-chip platform was developed using A549 lung cancer cells embedded in a fibrin-based hydrogel, enabling tumor growth under controlled perfusion conditions. Hypoxic regions were generated within the tumor compartment using oxygen scavenging chemistry, and spatial oxygen gradients were experimentally validated. Tumor chips were exposed to 10Gy X-ray irradiation. Radiation response was assessed using clonogenic assay, lactate dehydrogenase (LDH) release, and markers of DNA damage. To evaluate metabolic adaptation associated with hypoxia, uptake of 18F-fluorodeoxyglucose (FDG) was measured using an integrated CdWO4 scintillator that enabled on-chip radioluminescence microscopy (RLM) with cellular scale resolution.
Results
The tumor-on-a-chip model reproducibly established hypoxic gradients within the 3D tumor tissue. Hypoxic conditions significantly reduced colony formation by approximately four-fold and decreased LDH release by three-fold compared with normoxic conditions. DNA damage exhibited a clear oxygen dependent response, with a spatial gradient of reduced damage observed across the hypoxic gradient chip. FDG imaging revealed increased glucose uptake in hypoxic tumor regions, indicating enhanced glycolytic metabolism. RLM further resolved spatial metabolic heterogeneity within the tumor microenvironment that could not be captured using conventional PET imaging.
Conclusion
This work demonstrates the potential of a lung tumor-on-a-chip platform as a preclinical model for radiotherapy research that captures hypoxia mediated modulation of radiation response and tumor metabolism. Integration of FDG-based RLM enables high resolution metabolic imaging of treatment response and intratumoral heterogeneity. This platform provides a promising approach for studying mechanisms of radiation resistance and improving preclinical evaluation of radiotherapy strategies.