A Lung Tumor-on-a-Chip Model Recapitulates the Effect of Hypoxia on Radiotherapy Response and FDG-PET Imaging

Abstract

Most solid tumors contain regions of hypoxia that pose a significant challenge to the efficacy of radiation therapy. This study introduces a novel 3D lung tumor-on-a-chip (ToC) model designed to replicate the hypoxic tumor microenvironment in vitro while also providing a platform for clinically relevant interventions such as radiotherapy and positron emission tomography (PET) imaging. To simulate the heterogeneous oxygen distribution found in tumors, the ToC model incorporates an oxygen gradient achieved through a straightforward chemical oxygen scavenging system. A unique innovation of this device is the integration of a thin scintillator plate, which enables high-resolution imaging of tumor metabolism under hypoxia and normoxia conditions through radioluminescence microscopy using clinically approved PET tracers such as fluorodeoxyglucose (FDG). The response of this hypoxic model to radiation therapy (10 Gy X-ray) demonstrated a ∼4-fold increase in radioresistance compared to the normoxic ToC model, as assessed by colony formation potential. Additionally, DNA damage observed in the normoxic ToC model was ∼5-fold higher than that in the hypoxic model. platforming addition, the metabolic consumption of glucose was found to mirror the localization of hypoxia, validating the use of this biomarker for planning radiation therapy. The integration of high-resolution radionuclide imaging within ToC models enables on-chip PET imaging and facilitates oncology research and discovery, offering innovative capabilities for the preclinical testing of novel cancer therapies in a clinically relevant environment.

Supplementary files

Article information

Article type
Paper
Submitted
18 Apr 2025
Accepted
28 Jul 2025
First published
30 Jul 2025

Lab Chip, 2025, Accepted Manuscript

A Lung Tumor-on-a-Chip Model Recapitulates the Effect of Hypoxia on Radiotherapy Response and FDG-PET Imaging

R. Nasiri, M. Kurosu Jalil, V. I. Gaspar, A. S. Flores Perez, H. T. M. Nguyen, S. Khan, S. K. Y. Tang, Y. P. Yang and G. Pratx, Lab Chip, 2025, Accepted Manuscript , DOI: 10.1039/D5LC00373C

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