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

ABSTRACT: Monitoring tumor growth dynamics is crucial for understanding cancer. To establish an in vitro method for the continuous assessment of patient-specific tumor growth, tumor organoids were generated from patients with intrahepatic CCA (iCCA). Organoid growth was monitored for 48 h by label-free live brightfield imaging. Growth kinetics were calculated and validated by MTS assay as well as immunohistochemistry of Ki67 to determine proliferation rates. We exposed iCCA organoids (iCCAOs) and non-tumor intrahepatic cholangiocyte organoids (ICOs) to sub-therapeutic concentrations of sorafenib. Monitoring the expansion rate of iCCAOs and ICOs revealed that iCCAO growth was inhibited by sorafenib in a time- and dose-dependent fashion, while ICOs were unaffected. Quantification of the proliferation marker Ki67 confirmed inhibition of iCCAO growth by roughly 50% after 48 h of treatment with 4 µM sorafenib. We established a robust analysis pipeline combining brightfield microscopy and a straightforward image processing approach for the label-free growth monitoring of patient-derived iCCAOs. Combined with bioanalytical validation, this approach is suitable for a fast and efficient high-throughput drug screening in tumor organoids to develop patient-specific systemic treatment options.

SUBMITTER: Koch M

PROVIDER: S-EPMC9688926 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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

Koch Michael M Nickel Sandra S Lieshout Ruby R Lissek Susanna M SM Leskova Martina M van der Laan Luc J W LJW Verstegen Monique M A MMA Christ Bruno B Pampaloni Francesco F

Cells 20221115 22

Monitoring tumor growth dynamics is crucial for understanding cancer. To establish an in vitro method for the continuous assessment of patient-specific tumor growth, tumor organoids were generated from patients with intrahepatic CCA (iCCA). Organoid growth was monitored for 48 h by label-free live brightfield imaging. Growth kinetics were calculated and validated by MTS assay as well as immunohistochemistry of Ki67 to determine proliferation rates. We exposed iCCA organoids (iCCAOs) and non-tumo ...[more]

PMID: 36429040

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Project description:BackgroundPatient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications.MethodsHere, we developed a high-throughput compatible and automated live-cell image analysis software that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS), by combining computer vision with a convolutional network machine learning approach. The OrBITS deep learning analysis approach was validated against current standard assays for kinetic imaging and automated analysis of organoids. A drug screen of standard-of-care lung and pancreatic cancer treatments was also performed with the OrBITS platform and compared to the gold standard, CellTiter-Glo 3D assay. Finally, the optimal parameters and drug response metrics were identified to improve patient stratification.ResultsOrBITS allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D®-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. The obtained organoid Count, Mean Area, and Total Area had a strong correlation with the nuclear staining, Hoechst, following pairwise comparison over a broad range of sizes. By incorporating a fluorescent cell death marker, intra-well normalization for organoid death could be achieved, which was tested with a 10-point titration of cisplatin and validated against the current gold standard ATP-assay, CellTiter-Glo 3D. Using this approach with OrBITS, screening of chemotherapeutics and targeted therapies revealed further insight into the mechanistic action of the drugs, a feature not achievable with the CellTiter-Glo 3D assay. Finally, we advise the use of the growth rate-based normalised drug response metric to improve accuracy and consistency of organoid drug response quantification.ConclusionOur findings validate that OrBITS, as a scalable, automated live-cell image analysis software, would facilitate the use of patient-derived organoids for drug development and therapy screening. The developed wet-lab workflow and software also has broad application potential, from providing a launching point for further brightfield-based assay development to be used for fundamental research, to guiding clinical decisions for personalized medicine.

Project description:BackgroundBreast cancer Patient Derived Organoids (PDO) have been demonstrated to be a reliable model to study cancer that promised to replace and reduce the use of animals in pre-clinical research. They displayed concordance with the tissue of origin, resuming its heterogenicity and representing a good platform to develop approaches of personalized medicines. Although obtain PDOs from mammary tumour, was a very challenging process, several ongoing studies evaluated them as a platform to study efficacy, sensitivity and specificity of new drugs and exploited them in personalized medicine. Despite tissue organization represented a crucial point to evaluate in a 3-dimensional model, since it could influence drug penetration, morphology of breast cancer PDOs has not been analysed yet. Here, we proposed a complete ultrastructural analysis of breast PDOs obtained from tumour and healthy tissues to evaluate how typical structures observed in mammary gland were resumed in this model.Methods81 samples of mammary tissue (healthy or tumour) resulting from surgical resections have been processed to obtain PDO. The resulting PDOs embedded in matrigel drop have been processed for transmission electron microscopy and analysed. A comparison between ones from healthy and ones from cancerous tissue has been performed and PDOs derived from tumour tissue have been stratified according to their histological and molecular subtype.ResultThe morphological analysis performed on 81 PDO revealed an organized structure rich in Golgi, secretion granules and mitochondria, which was typical of cells with a strong secretory activity and active metabolism. The presence of desmosomes, inter and intracellular lumens and of microvilli and interdigitations signified a precise tissue-organization. Each PDO has been classified based on whether or not it possessed (i) peripheral ridges in mitochondria, (ii) intracellular lumens, (iii) intercellular lumens, (iv) micro-vesicles, (v) open desmosomes, (vi) cell debris, (vii) polylobed nuclei, (viii) lysosomes and (ix) secretion granules, in order to identify features coupled with the cancerous state or with a specific histological or molecular subtype.ConclusionHere we have demonstrated the suitability of breast cancer PDO as 3-dimensional model of mammary tissue. Besides, some structural features characterizing cancerous PDO have been observed, identifying the presence of distinctive traits.

Project description:BackgroundFragmentomics, the investigation of fragmentation patterns of cell-free DNA (cfDNA), has emerged as a promising strategy for the early detection of multiple cancers in the field of liquid biopsy. However, the clinical application of this approach has been hindered by a limited understanding of cfDNA biology. Furthermore, the prevalence of hematopoietic cell-derived cfDNA in plasma complicates the in vivo investigation of tissue-specific cfDNA other than that of hematopoietic origin. While conventional two-dimensional cell lines have contributed to research on cfDNA biology, their limited representation of in vivo tissue contexts underscores the need for more robust models. In this study, we propose three-dimensional organoids as a novel in vitro model for studying cfDNA biology, focusing on multifaceted fragmentomic analyses.ResultsWe established nine patient-derived organoid lines from normal lung airway, normal gastric, and gastric cancer tissues. We then extracted cfDNA from the culture medium of these organoids in both proliferative and apoptotic states. Using whole-genome sequencing data from cfDNA, we analyzed various fragmentomic features, including fragment size, footprints, end motifs, and repeat types at the end. The distribution of cfDNA fragment sizes in organoids, especially in apoptosis samples, was similar to that found in plasma, implying occupancy by mononucleosomes. The footprints determined by sequencing depth exhibited distinct patterns depending on fragment sizes, reflecting occupancy by a variety of DNA-binding proteins. Notably, we discovered that short fragments (< 118 bp) were exclusively enriched in the proliferative state and exhibited distinct fragmentomic profiles, characterized by 3 bp palindromic end motifs and specific repeats.ConclusionsIn conclusion, our results highlight the utility of in vitro organoid models as a valuable tool for studying cfDNA biology and its associated fragmentation patterns. This, in turn, will pave the way for further enhancements in noninvasive cancer detection methodologies based on fragmentomics.

Dataset Information

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

Publications

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

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