A Head and Neck Cancer Patient-Specific Microphysiological System for Predicting Response to Chemoradiation

Avatar
Poster
Voice is AI-generated
Connected to paperThis paper is a preprint and has not been certified by peer review

A Head and Neck Cancer Patient-Specific Microphysiological System for Predicting Response to Chemoradiation

Authors

Ahmed, A.; Hendrikse, N.; Schwartz, R. W.; Li, Y.; Lares, M.; Felix, C. K.; Burr, A. R.; Ong, I. M.; Harari, P. M.; Beebe, D. J.; Kerr, S. C.

Abstract

Head and neck cancer (HNC) is the 6th most common malignancy worldwide. 60% of patients present with advanced disease and approximately 50% of patients recur following primary treatment. Chemoradiation remains a standard of care for most patients. However, clinicians lack functional tools to predict which patients will respond to chemoradiation prior to treatment and current models, including organoids and animal model systems, fail to capture either full complexity or patient-to-patient heterogeneity of the individual HNC tumor and microenvironment (TME). Here, we have developed, characterized, and tested a patient-specific microphysiological system (MPS) that reconstructs the HNC TME in a vascularized 3D environment. This MPS was constructed from malignant cells, fibroblasts, and immune cells from a surgically resected tumor, seeded within a 3D hydrogel with molded endothelial lumens. Single-cell RNA sequencing confirmed that the MPS preserved 12 transcriptionally distinct cell populations found in matched native tissue. The platform recapitulated tumor hypoxia, with a 12-fold increase in hypoxic marker expression that altered radiation response, consistent with clinical HNC biology. Compartment-resolved imaging revealed distinct treatment dynamics in tumor, stromal, and vascular regions, and individual patients exhibited divergent responses to chemoradiation in spheroid morphology, cell viability, and migration. We found the slope of spheroid area change with treatment tracked with tumor recurrence, suggesting this metric could serve as a functional predictor of therapeutic response.

Follow Us on

0 comments

Add comment