Point-of-care Optical Spectroscopy Platform and Novel Ratio-metric Algorithms for Rapid and Systematic Functional Characterization of Biological Models in Vivo

PROJECT SUMMARY Cellular metabolism is highly dynamic and strongly influenced by its local vascular microenvironment, gaining a systems-level view of tumor metabolism and vasculature in vivo is essential in understanding many critical cancer biology questions. However, there are surprisingly few techniques available that can quantify the key metabolic and vascular endpoints together in vivo in real-time with easy access. The goal here is to fill this gap by developing a point-of-care optical spectroscopy platform with a tumor-sensitive fiber probe and novel data processing techniques to quantify the major axes of tumor metabolism (glucose uptake, mitochondrial membrane potential, Bodipy) and the associated vasculature (oxygenation, hemoglobin) on biological models in vivo in near real-time. For scientific validation and translational research purposes, we will compare our optical platform against well-established metabolic assays. We will then demonstrate the technology through addressing a contemporary problem in cancer therapy for head and neck squamous cell cancer (HNSCC). Specifically, we will address the critical challenge of radio-resistance (RR) in HNSCC and test the hypothesis that radiotherapy (RT) induced HIF-1α and HIF-2α activation and the following metabolic changes are responsible for HNSCC RR and recurrence, the tumor-specific genetic editing platform targeting on HIF-1α and HIF-2α can improve RT efficacy. Our point-of-care optical spectroscopy provides new ways of studying cancer biology and diseases, and it will also impact the study of a wide array of other biomedical problems through the lens of tumor bioenergetics and vasculature. Our study on HNSCC RR mechanisms and the demonstration of tumor-specific genetic editing platform in orthotropic HNSCC models will offer new ways for targeted RT to improve HNSCC patient survival rates. The platforms and methodologies developed in this project will be applicable to the study of RR and recurrence in other types of human cancers.