Development of Optical Metabolic Imaging for Pancreatic and Breast Cancer Precision Medicine

Abstract

There are no reliable methods to determine how an individual breast or pancreatic cancer patient will respond to a particular treatment option. Patient-derived tumor organoids offer the ability to screen drugs directly on a patient’s cells in vitro to determine drug effectiveness, however we currently lack the tools to evaluate distinct cellular subpopulations of response within these organoids. This cellular heterogeneity is a major cause of cancer treatment failure, as drug-resistant cell subpopulations continue to proliferate even when a majority of the tumor appears to be drug-responsive. Therefore, technology to assess heterogeneous responses to cancer treatments in patient organoids is needed. In this dissertation, optical metabolic imaging (OMI) was developed for measuring drug-induced changes in metabolic heterogeneity in pancreatic and breast cancer organoids. OMI leverages the intrinsic autofluorescence intensities and lifetimes of the metabolic coenzymes NAD(P)H and FAD to quantify the metabolic state of individual cells. First, a novel biochemical interpretation for changes in the fluorescence lifetime of NAD(P)H was established, connecting OMI measurements with shifts in flux through specific metabolic pathways which may contribute to anti-cancer drug resistance. Next, OMI was performed in vivo in an immunocompetent mouse model of breast cancer, and also in organoids derived from the same tumor model, to demonstrate that metabolic heterogeneity in tumor-derived organoids accurately recapitulates that of the original tumor. Finally, OMI of cellular heterogeneity in organoids was evaluated as a predictor of clinical treatment response for pancreatic cancer. Organoids were generated from fresh patient tissue samples acquired during surgery and treated with the same drugs as the patient’s prescribed adjuvant treatment. Early changes in metabolic heterogeneity in organoids agreed with long-term patient therapeutic response. OMI could serve as a sensitive, high-throughput tool to identify optimal therapies for individual pancreatic cancer patients, and to develop new effective therapies that address cellular heterogeneity in breast and pancreatic cancer.