Label-Free Imaging Analysis of Patient-Derived Cholangiocarcinoma Organoids after Sorafenib Treatment

Liver and bile duct organoids and tumoroids

Organoids refer to 3D cultures established to recapitulate histology, pathology, architecture, and genetic traits of various organs and tissues in the body, thereby replacing 2D cell cultures, xenograft, and animal models. Organoids form a 3D in vitro mimic of original tissues like the liver and are derived from embryonic or adult tissue stem cells. Liver and bile duct tumor organoids, also called, tumoroids capture genetic diversity, cellular, and pathophysiological properties of original tumors. Moreover, co-culture techniques along with genetic modulation of organoids allow for using tumoroids in liver and bile duct cancer research and drug screening/testing. Therefore, tumoroids are promising platforms for studying liver and bile duct cancer, which paves the way for the new era of personalized therapies. In the current review, we aimed to discuss liver and bile duct organoids with special emphasis on tumoroids and their applications, advantages, and shortcomings.

Building consensus on the application of organoid-based drug sensitivity testing in cancer precision medicine and drug development

Patient-derived organoids (PDOs) have emerged as a promising platform for clinical and translational studies. A strong correlation exists between clinical outcomes and the use of PDOs to predict the efficacy of chemotherapy and/or radiotherapy. To standardize interpretation and enhance scientific communication in the field of cancer precision medicine, we revisit the concept of PDO-based drug sensitivity testing (DST). We present an expert consensus-driven approach for medication selection aimed at predicting patient responses. To further standardize PDO-based DST, we propose guidelines for clarification and characterization. Additionally, we identify several major challenges in clinical prediction when utilizing PDOs.

Viability Analysis and High-Content Live-Cell Imaging for Drug Testing in Prostate Cancer Xenograft-Derived Organoids

Tumor organoids have been pushed forward as advanced model systems for in vitro oncology drug testing, with the eventual goal to direct personalized cancer treatments. However, drug testing efforts suffer from a large variation in experimental conditions for organoid culturing and organoid treatment. Moreover, most drug tests are restricted to whole-well viability as the sole read-out, thereby losing important information about key biological aspects that might be impacted due to the use of administered drugs. These bulk read-outs also discard potential inter-organoid heterogeneity in drug responses. To tackle these issues, we developed a systematic approach for processing organoids from prostate cancer (PCa) patient-derived xenografts (PDXs) for viability-based drug testing and identified essential conditions and quality checks for consistent results. In addition, we generated an imaging-based drug testing procedure using high-content fluorescence microscopy in living PCa organoids to detect various modalities of cell death. Individual organoids and cell nuclei in organoids were segmented and quantified using a dye combination of Hoechst 33342, propidium iodide and Caspase 3/7 Green, allowing the identification of cytostatic and cytotoxic treatment effects. Our procedures provide important insights into the mechanistic actions of tested drugs. Moreover, these methods can be adapted for tumor organoids originating from other cancer types to increase organoid-based drug test validity, and ultimately, accelerate clinical implementation.

Quantifying the drug response of patient-derived organoid clusters by aggregated morphological indicators with multi-parameters based on optical coherence tomography

Patient-derived organoids (PDOs) serve as excellent tools for personalized drug screening to predict clinical outcomes of cancer treatment. However, current methods for efficient quantification of drug response are limited. Herein, we develop a method for label-free, continuous tracking imaging and quantitative analysis of drug efficacy using PDOs. A self-developed optical coherence tomography (OCT) system was used to monitor the morphological changes of PDOs within 6 days of drug administration. OCT image acquisition was performed every 24 h. An analytical method for organoid segmentation and morphological quantification was developed based on a deep learning network (EGO-Net) to simultaneously analyze multiple morphological organoid parameters under the drug's effect. Adenosine triphosphate (ATP) testing was conducted on the last day of drug treatment. Finally, a corresponding aggregated morphological indicator (AMI) was established using principal component analysis (PCA) based on the correlation analysis between OCT morphological quantification and ATP testing. Determining the AMI of organoids allowed quantitative evaluation of the PDOs responses to gradient concentrations and combinations of drugs. Results showed that there was a strong correlation (correlation coefficient >90%) between the results using the AMI of organoids and those from ATP testing, which is the standard test used for bioactivity measurement. Compared with single-time-point morphological parameters, the introduction of time-dependent morphological parameters can reflect drug efficacy with improved accuracy. Additionally, the AMI of organoids was found to improve the efficiency of 5-fluorouracil(5FU) against tumor cells by allowing the determination of the optimum concentration, and the discrepancies in response among different PDOs using the same drug combinations could also be measured. Collectively, the AMI established by OCT system combined with PCA could quantify the multidimensional morphological changes of organoids under the drug's effect, providing a simple and efficient tool for drug screening in PDOs.

Human liver cancer organoids: Biological applications, current challenges, and prospects in hepatoma therapy

Liver cancer and disease are among the most socially challenging global health concerns. Although organ transplantation, surgical resection and anticancer drugs are the main methods for the treatment of liver cancer, there are still no proven cures owing to the lack of donor livers and tumor heterogeneity. Recently, advances in tumor organoid technology have attracted considerable attention as they can simulate the spatial constructs and pathophysiological characteristics of tumorigenesis and metastasis in a more realistic manner. Organoids may further contribute to the development of tailored therapies. Combining organoids with other emerging techniques, such as CRISPR-HOT, organ-on-a-chip, and 3D bioprinting, may further develop organoids and address their bottlenecks to create more practical models that generalize different tissue or organ interactions in tumor progression. In this review, we summarize the various methods in which liver organoids may be generated and describe their biological and clinical applications, present challenges, and prospects for their integration with emerging technologies. These rapidly developing liver organoids may become the focus of in vitro clinical model development and therapeutic research for liver diseases in the near future.