Abstract B15: Metabolic imaging of patient-derived tumor organoids provides a fast and dynamic readout of drug response

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.

Anti-EGFR Therapy Induces EGF Secretion by Cancer-Associated Fibroblasts to Confer Colorectal Cancer Chemoresistance

Targeted agents have improved the efficacy of chemotherapy for cancer patients, however, there remains a lack of understanding of how these therapies affect the unsuspecting bystanders of the stromal microenvironment. Cetuximab, a monoclonal antibody therapy targeting the epidermal growth factor receptor (EGFR), is given in combination with chemotherapy as the standard of care for a subset of metastatic colorectal cancer patients. The overall response to this treatment is underwhelming and, while genetic mutations that confer resistance have been identified, it is still not known why this drug is ineffective for some patients. We discovered that cancer-associated fibroblasts (CAFs), a major cellular subset of the tumor stroma, can provide a source of cancer cell resistance. Specifically, we observed that upon treatment with cetuximab, CAFs increased their secretion of EGF, which was sufficient to render neighboring cancer cells resistant to cetuximab treatment through sustained mitogen-activated protein kinases (MAPK) signaling. Furthermore, we show the cetuximab-induced EGF secretion to be specific to CAFs and not to cancer cells or normal fibroblasts. Altogether, this work emphasizes the importance of the tumor microenvironment and considering the potential unintended consequences of therapeutically targeting cancer-driving proteins on non-tumorigenic cell types.

Comparison of Cell and Organoid-Level Analysis of Patient-Derived 3D Organoids to Evaluate Tumor Cell Growth Dynamics and Drug Response

3D cell culture models have been developed to better mimic the physiological environments that exist in human diseases. As such, these models are advantageous over traditional 2D cultures for screening drug compounds. However, the practicalities of transitioning from 2D to 3D drug treatment studies pose challenges with respect to analysis methods. Patient-derived tumor organoids (PDTOs) possess unique features given their heterogeneity in size, shape, and growth patterns. A detailed assessment of the length scale at which PDTOs should be evaluated (i.e., individual cell or organoid-level analysis) has not been done to our knowledge. Therefore, using dynamic confocal live cell imaging and data analysis methods we examined tumor cell growth rates and drug response behaviors in colorectal cancer (CRC) PDTOs. High-resolution imaging of H2B-GFP-labeled organoids with DRAQ7 vital dye permitted tracking of cellular changes, such as cell birth and death events, in individual organoids. From these same images, we measured morphological features of the 3D objects, including volume, sphericity, and ellipticity. Sphericity and ellipticity were used to evaluate intra- and interpatient tumor organoid heterogeneity. We found a strong correlation between organoid live cell number and volume. Linear growth rate calculations based on volume or live cell counts were used to determine differential responses to therapeutic interventions. We showed that this approach can detect different types of drug effects (cytotoxic vs cytostatic) in PDTO cultures. Overall, our imaging-based quantification workflow results in multiple parameters that can provide patient- and drug-specific information for screening applications.

A Perspective on Expanding Our Understanding of Cancer Treatments by Integrating Approaches from the Biological and Physical Sciences

Multicellular systems such as cancer suffer from immense complexity. It is imperative to capture the heterogeneity of these systems across scales to achieve a deeper understanding of the underlying biology and develop effective treatment strategies. In this perspective article, we will discuss how recent technologies and approaches from the biological and physical sciences have transformed traditional ways of measuring, interpreting, and treating cancer. During the SLAS 2019 Annual Meeting, SBI² hosted a Special Interest Group (SIG) on this topic. Academic and industry leaders engaged in discussions surrounding what biological model systems are appropriate to study cancer complexity, what assays are necessary to interrogate this complexity, and how physical sciences approaches may be useful to detangle this complexity. In particular, we examined the utility of mathematical models in predicting cancer progression and treatment response when tightly integrated with reproducible, quantitative, and dynamic biological measurements achieved using high-content imaging and analysis. The dialogue centered around the impetus for convergent biosciences, bringing new perspectives to cancer research to further understand this complex adaptive system and successfully intervene therapeutically.