Single-cell metabolism predicts drug response in patient-derived pancreatic cancer organoids (Conference Presentation)

Abstract

Pancreatic cancer has the worst prognosis of all cancers (5-year survival rate of 7%). Patients that are eligible for surgery often receive adjuvant chemotherapy to improve survival. There is a critical need for a tool to match individual patients with optimal drugs for their cancer. The goal of this work is to validate Optical Metabolic Imaging (OMI) of patient-derived pancreatic tumor organoids as a high-throughput predictive drug screen for patients. Three-dimensional organoids were successfully generated from surgically resected pancreatic tumors. These organoids were treated with the patient’s prescribed adjuvant therapy, and early metabolic changes were measured using multiphoton fluorescence lifetime imaging microscopy (FLIM) of the metabolic co-enzymes NAD(P)H and FAD. Changes at the single-cell level were quantified using the OMI Index, a linear combination of the optical redox ratio (ratio of the fluorescence intensities of NAD(P)H to FAD), and the mean NAD(P)H and FAD fluorescence lifetimes. Population density modeling on the OMI Index was used to evaluate cell-level heterogeneities in drug responses. Additionally, mass spectrometry imaging (MSI) was used to map metabolites in organoids. Combining multiphoton OMI images and MSI images provides a detailed map of the complex metabolic changes that occur in response to treatment, which may be used to identify additional drug targets. Patient survival data after surgery was used as validation of drug response in organoids. This platform shows promise for predicting long-term response to therapy in pancreatic cancer patients.