Abstract

Abstract Patient-derived tumor organoids are a more physiologically relevant 3D cell culture model system amenable to drug screening. However, several challenges exist with this model system, including the ability to maintain the heterocellular complexity of the original tumor microenvironment (TME) as well as the ability to interrogate this complexity in a quantitative and dynamic manner. To overcome these challenges, we employ fluorescence lifetime imaging microscopy (FLIM) to measure the metabolic activity of unlabeled patient-derived colorectal cancer (CRC) organoids in response to drug perturbations. FLIM relies on the exponential decay rates of fluorescent molecules. By measuring autofluorescent signals from coenzyme NADH, we determined the metabolic state of individual organoids by representing the ratio of free and protein-bound NADH on a 2D phasor plot. Using a confocal microscope, we acquired z-stack images of patient-derived organoids at multiple time points in the presence and absence of clinically relevant chemotherapy and targeted agents (i.e., 5-fluorouracil, SN-38 [active metabolite of irinotecan], and cetuximab). Unlike traditional viability assays that measure the metabolic activity of a population of organoids and provide a single readout at a fixed time point, we can use FLIM to dynamically measure the metabolic activity of individual organoids and capture intra- and interpatient heterogeneity. We were able to detect drug responses in a dose-dependent manner by measuring a shift towards oxidative phosphorylation prior to an increase in fluorescent signal from a vital dye detecting cell death. Thus, FLIM can capture early drug-mediated changes in organoids on the order of hours compared to vital dyes, which are on the order of days. Additionally, cancer cells are in physical and biochemical contact with many different stromal cell types native to the host environment. Cancer-associated fibroblasts (CAFs) are the dominant stromal cell type within the TME and have been linked with increased tumor cell survival and protection against drug-induced apoptosis. When we cocultured organoids with CAFs, we were able to distinguish the metabolic signatures of each cell type without the need for fluorescent labels. Moreover, we quantified the drug-induced metabolic shifts at the IC50 value when CAFs were present. In conclusion, our imaging-based approach has advantages over traditional drug screening methods (e.g., ATP measurements, phototoxic dyes) by capturing the dynamics and heterogeneity of patient-specific drug responses. We are implementing this workflow to better understand the interactions between cancer cells and their microenvironment in the context of drug response. Citation Format: Emma J. Fong, Seungil Kim, Shannon M. Mumenthaler. Metabolic imaging of patient-derived tumor organoids provides a fast and dynamic readout of drug response [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr B15.

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