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Date Available

4-29-2027

Year of Publication

2026

Document Type

Doctoral Dissertation

Degree Name

Doctor of Philosophy (PhD)

College

Engineering

Department/School/Program

Biomedical Engineering

Faculty

Caigang Zhu

Faculty

Sridhar Sunderam

Abstract

Radiation resistance poses a major challenge in the treatment management of head and neck squamous cell carcinoma (HNSCC) by reducing the effectiveness of radiation therapy. Traditionally, hypoxia has been considered a key driver of radiation resistance. However, growing evidence suggests that hypoxia alone cannot fully explain therapy resistance. Recent studies indicate that metabolic reprogramming also contributes to radiation resistance. Cancer cells frequently reprogram metabolic pathways to adapt to varying oxygen conditions, enabling survival under hostile conditions. Therefore, it is crucial to simultaneously assess both tumor metabolism and the associated vasculature to better understand the biological mechanisms underlying therapy resistance and to improve therapeutic outcomes. Moreover, because vascular oxygenation and metabolic activity can change rapidly and dynamically following therapy, there is a pressing need for tools that can frequently and rapidly assess both metabolic and vascular parameters. Existing tools, such as Seahorse XF Analyzer, metabolomics, immunohistochemistry, FDG-PET, and several optical techniques, can measure either metabolic or vascular parameters, but not both simultaneously and rapidly in vivo. In addition, many of these systems are expensive, bulky, and require specialized expertise, making frequent and rapid measurements impractical. To address this technical gap, a fiber probe-based PEERS (Point of care, Easy to use, Easy to access, Rapid, Systematic) spectroscopy system was developed (Chapter 2). The system can simultaneously measure metabolic endpoints, including glucose uptake and mitochondrial membrane potential, using the exogenous fluorophores 2-NBDG and TMRE, along with vascular parameters such as oxygen saturation (SO₂) and total hemoglobin concentration [THB] using diffuse reflectance in vivo. Moreover, a novel ratio-metric algorithm and a simple analytical model were developed for processing spectral data, enabling rapid measurement of these endpoints. Tissue-mimicking phantom studies with known optical properties were used to validate the accuracy of the algorithms and device. In vivo animal studies were conducted using flank tumor models of HNSCC, including radiation-sensitive (SCC-61) and radiation-resistant (rSCC-61) tumors, to further validate the method. The studies revealed distinct metabolic and vascular profiles between the two tumor types, which were consistent with previous research. The results were also compared with a gold-standard Monte Carlo spectral data processing algorithm and showed consistent findings. One limitation of fiber probe-based spectroscopy is measurement error caused by inconsistent probe-tissue contact. Specifically, accessing certain anatomical sites, such as the mouse tongue, is practically challenging with a fiber probe. To overcome these limitations, a non-contact version of PEERS spectroscopy was developed for orthotopic tongue tumor studies (chapters 3 & 4). The algorithms from the fiber-based system were adapted for the non-contact device and validated using tissue-mimicking phantoms. In vivo studies using SCC-61 and rSCC-61 tongue tumor models showed results consistent with previous studies and revealed distinct metabolic and vascular profiles across normal tissue and tumors. Together, these PEERS spectroscopy, both contact (fiber-based) and non-contact versions, demonstrate the capability of multiparametric measurements (SO₂, [THB], glucose uptake, and mitochondrial membrane potential) across multiple tumor models (flank and orthotopic). With their low cost, ease of use, portability, and rapid measurement capabilities, these technologies can significantly impact cancer research by providing researchers and biologists with a more complete understanding of cancer therapy resistance mechanisms.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2026.165

Archival?

Archival

Funding Information

This work was supported by the National Institute of Dental and Craniofacial Research (NIDCR) and the National Institute of General Medical Sciences (NIGMS) (U.S. National Institutes of Health, R01 DE031998, 2023-2028), and the University of Kentucky Startup (2019-2024).

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Available for download on Thursday, April 29, 2027

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