3D imaging analysis on an organoid-based platform guides personalized treatment in pancreatic ductal adenocarcinoma

Characteristics of chemically induced liver progenitors derived from a pig model of metabolic dysfunction-associated steatotic liver disease

We previously reported the efficacy of chemically induced liver progenitors (CLiP) as a source of cells for transplantation in patients with liver disease. This study aimed to characterize CLiP derived from steatotic livers using a pig model for future clinical applications. Livers were removed from miniature pigs with diet-induced steatosis and normal livers by laparoscopic hepatectomy. Mature hepatocytes (MH) isolated from the livers of each group were cultured in differentiation medium composed of Y-27632, A-83-01, and CHIR99021 (YAC medium). The characteristics of CLiP, including liver-specific function, proliferative capacity in vivo, and extracellular vesicles (EVs) production, were evaluated. Although CLiP in both groups expressed hepatic progenitor cell markers (Epithelial cell adhesion molecule and Trophoblast cell surface antigen 2), the proliferative potential was higher for the disease group than the healthy group. In contrast, markers of functional MH after re-differentiation were only detected in the healthy group. Both groups showed high cell viability and the ability to differentiate into albumin-positive cells in vivo. EVs counts were lower in disease-derived CLiP than in the normal group; however, there were no differences in microRNA expression within EVs. Using a pig model, CLiP was successfully produced from a liver that reproduced steatotic liver disease. Although there were slightly fewer EVs from CLiP in the disease group than in the normal liver group, the in vivo proliferative capacity of CLiP was high. Therefore, CLiP induced in the steatotic liver are a promising source for cell therapy in patients with liver disease.

Harnessing the power of artificial intelligence for human living organoid research

As a powerful paradigm, artificial intelligence (AI) is rapidly impacting every aspect of our day-to-day life and scientific research through interdisciplinary transformations. Living human organoids (LOs) have a great potential for in vitro reshaping many aspects of in vivo true human organs, including organ development, disease occurrence, and drug responses. To date, AI has driven the revolutionary advances of human organoids in life science, precision medicine and pharmaceutical science in an unprecedented way. Herein, we provide a forward-looking review, the frontiers of LOs, covering the engineered construction strategies and multidisciplinary technologies for developing LOs, highlighting the cutting-edge achievements and the prospective applications of AI in LOs, particularly in biological study, disease occurrence, disease diagnosis and prediction and drug screening in preclinical assay. Moreover, we shed light on the new research trends harnessing the power of AI for LO research in the context of multidisciplinary technologies. The aim of this paper is to motivate researchers to explore organ function throughout the human life cycle, narrow the gap between in vitro microphysiological models and the real human body, accurately predict human-related responses to external stimuli (cues and drugs), accelerate the preclinical-to-clinical transformation, and ultimately enhance the health and well-being of patients.

Identification and culture of functional salivary gland ductal epithelial cells

Sialadenitis is a prevalent salivary gland disease resulting in decreased salivary flow rate. To date, little is known about the exact changes and mechanism of ductal cells in sialadenitis. This study aims to establish an efficient method to identify and isolate ductal cells, thereby facilitating further research on this specific cell type. Immunofluorescence for cytokeratin 13 and cytokeratin 19 was conducted in salivary glands to confirm their specificity as ductal cell markers. The dissected ducts were assessed through PCR and Western blot of cytokeratin 19 and digested by dispase and collagenase. The functionality of the isolated ductal cells was determined by measuring intracellular calcium. Cytokeratin 19 and cytokeratin 13 were expressed in all segments of human ducts. Cytokeratin 19 was limited to ducts excluding granular convoluted tubules in rat and mouse. The purities of the obtained ductal cells were approximately 98% in humans and 93% in rats. Furthermore, intracellular free calcium increased with time and concentration of carbachol treatment. Cytokeratin 19 serves as a dependable marker for identifying ductal cells in salivary glands, except for granular convoluted tubules. Moreover, we have successfully developed an efficient method for isolating ductal cells from salivary glands.

Patient-Derived Organoids on a Microarray for Drug Resistance Study in Breast Cancer

Drug resistance is always a challenge in cancer treatment, whether for chemotherapy, targeting, or immunotherapy. Although tumor cell lines are derived from cancer patients, they gradually lost the original characteristics, including heterogeneity and tumor microenvironment (TME), during the long period of in vitro culturing. Therefore, it is urgent to use patient-derived tumor models instead of cancer cell lines to study tumor drug resistance. Herein, we developed a microarray device that serves as a platform for high-throughput and three-dimensional culture of breast cancer patient-derived organoids (BCOs) and investigated their resistance to adriamycin (ADM). Coupled with fluorescence microscopy, this system enabled on-chip drug response monitoring and cell viability assessment without the consumption of a large number of tumor cells. The organoids were divided into a resistant BCO group (RBCO) and a sensitive BCO group (SBCO) according to their half-inhibitory concentration (IC50). Different from cancer cell lines, BCOs demonstrated obvious heterogeneity in drug treatment. Ivermectin (IVM), a broad-spectrum antiparasitic agent approved by the Food and Drug Administration (FDA), was observed to synergistically augment ADM-induced cytotoxicity in organoids. The BCO chip provides a promising platform for investigation of drug resistance and preclinical drug screening based on clinical samples.

Organoid-based precision medicine in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) ranks among the leading causes of cancer-related deaths worldwide. Despite advances in precision oncology in other malignancies, treatment of PDAC still largely relies on conventional chemotherapy. Given the dismal prognosis and heterogeneity in PDAC, there is an urgent need for personalized therapeutic strategies to improve treatment response. Organoids, generated from patients' tumor tissue, have emerged as a powerful tool in cancer research. These three-dimensional models faithfully recapitulate the morphological and genetic features of the parental tumor and retain patient-specific heterogeneity. This review summarizes existing precision oncology approaches in PDAC, explores current applications and limitations of organoid cultures in personalized medicine, details preclinical studies correlating in vitro organoid prediction and patient treatment response, and provides an overview of ongoing organoid-based clinical trials.

Unravelling the complexities of resistance mechanism in pancreatic cancer: Insights from in vitro and ex-vivo model systems

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with poor prognosis and rising global deaths. Late diagnosis, due to absent early symptoms and biomarkers, limits treatment mainly to chemotherapy, which soon encounters resistance. PDAC treatment innovation is hampered by its complex and heterogeneous resistant nature, including mutations in key genes and a stromal-rich, immunosuppressive tumour microenvironment. Recent studies on PDAC resistance stress the need for suitable in vitro and ex vivo models to replicate its complex molecular and microenvironmental landscape. This review summarises advances in these models, which can aid in combating chemoresistance and serve as platforms for discovering new therapeutics. Immortalised cell lines offer homogeneity, unlimited proliferation, and reproducibility, but while many gemcitabine-resistant PDAC cell lines exist, fewer models are available for resistance to other drugs. Organoids from PDAC patients show promise in mimicking tumour heterogeneity and chemosensitivity. Bioreactors, co-culture systems and organotypic slices, incorporating stromal and immune cells, are being developed to understand tumour-stroma interactions and the tumour microenvironment's role in drug resistance. Lastly, another innovative approach is three-dimensional bioprinting, which creates tissue-like structures resembling PDAC architecture, allowing for drug screening. These advanced models can guide researchers in selecting optimal in vitro tests, potentially improving therapeutic strategies and patient outcomes.

Auranofin as a Novel Anticancer Drug for Anaplastic Thyroid Cancer

Background/Objectives: Anaplastic thyroid cancer (ATC) is an aggressive and rare cancer with a poor prognosis, and traditional therapies have limited efficacy. This study investigates drug repositioning, focusing on auranofin, a gold-based drug originally used for rheumatoid arthritis, as a potential treatment for ATC. Methods: Auranofin was identified from an FDA-approved drug library and tested on two thyroid cancer cell lines, 8505C and FRO. Antitumor efficacy was evaluated through gene and protein expression analysis using Western blot, FACS, and mRNA sequencing. In vivo experiments were conducted using subcutaneous injections in nude mice to confirm the anticancer effects of auranofin. Results: Auranofin induced reactive oxygen species (ROS) production and apoptosis, leading to a dose-dependent reduction in cell viability, G1/S phase cell cycle arrest, and altered expression of regulatory proteins. It also inhibited cancer stem cell activity and suppressed epithelial-mesenchymal transition. mRNA sequencing revealed significant changes in the extracellular matrix-receptor interaction pathway, supported by Western blot results. In vivo xenograft models demonstrated strong antitumor activity. Conclusions: Auranofin shows promise as a repurposed therapeutic agent for ATC, effectively inhibiting cell proliferation, reducing metastasis, and promoting apoptosis. These findings suggest that auranofin could play a key role in future ATC treatment strategies.

Bioprinting of Cells, Organoids and Organs-on-a-Chip Together with Hydrogels Improves Structural and Mechanical Cues

The 3D bioprinting technique has made enormous progress in tissue engineering, regenerative medicine and research into diseases such as cancer. Apart from individual cells, a collection of cells, such as organoids, can be printed in combination with various hydrogels. It can be hypothesized that 3D bioprinting will even become a promising tool for mechanobiological analyses of cells, organoids and their matrix environments in highly defined and precisely structured 3D environments, in which the mechanical properties of the cell environment can be individually adjusted. Mechanical obstacles or bead markers can be integrated into bioprinted samples to analyze mechanical deformations and forces within these bioprinted constructs, such as 3D organoids, and to perform biophysical analysis in complex 3D systems, which are still not standard techniques. The review highlights the advances of 3D and 4D printing technologies in integrating mechanobiological cues so that the next step will be a detailed analysis of key future biophysical research directions in organoid generation for the development of disease model systems, tissue regeneration and drug testing from a biophysical perspective. Finally, the review highlights the combination of bioprinted hydrogels, such as pure natural or synthetic hydrogels and mixtures, with organoids, organoid-cell co-cultures, organ-on-a-chip systems and organoid-organ-on-a chip combinations and introduces the use of assembloids to determine the mutual interactions of different cell types and cell-matrix interferences in specific biological and mechanical environments.

Patient-Derived Organoids as Therapy Screening Platforms in Cancer Patients

Patient-derived organoids (PDOs) developed ex vivo and in vitro are increasingly used for therapeutic screening. They provide a more physiologically relevant model for drug discovery and development compared to traditional cell lines. However, several challenges remain to be addressed to fully realize the potential of PDOs in therapeutic screening. This paper summarizes recent advancements in PDO development and the enhancement of PDO culture models. This is achieved by leveraging materials engineering and microfabrication technologies, including organs-on-a-chip and droplet microfluidics. Additionally, this work discusses the application of PDOs in therapy screening to meet diverse requirements and overcome bottlenecks in cancer treatment. Furthermore, this work introduces tools for data processing and analysis of organoids, along with their microenvironment. These tools aim to achieve enhanced readouts. Finally, this work explores the challenges and future perspectives of using PDOs in drug development and personalized screening for cancer patients.

Three-dimensional structural and metric characterisation of cardioids

Exact three-dimensional (3D) structural information of developing organoids is key for optimising organoid generation and for studying experimental outcomes in organoid models. We set up a 3D imaging technique and studied complexly arranged native and experimentally challenged cardioids of two stages of remodelling. The imaging technique we employed is S-HREM (Scanning High Resolution Episcopic Microscopy), a variant of HREM, which captures multiple images of subsequently exposed surfaces of resin blocks and automatically combines them to large sized digital volume data of voxels sizes below 1 μm3. We provide precise volumetric information of the examined specimens and their single components and comparisons between stages in terms of volume and micro- and macroanatomic structure. We describe the 3D arrangement and lining of different types of cavities and their changes between day 10 and day 14 and map the various cell types to their precise spatial and structural environment. Exemplarily, we conducted semiautomatic counts of nuclei. In cryo-injured cardioids, we examined the extension and composition of the injured areas. Our results demonstrate the high quality and the great potential of digital volume data produced with S-HREM. It also provides sound metric and structural information, which assists production of native and experimentally challenged left ventricle cardioids and interpretation of their structural remodelling.

A Convexity-Preserving Level-Set Method for the Segmentation of Tumor Organoids

Tumor organoid cultures play a crucial role in clinical practice, particularly in guiding medication by accurately determining the morphology and size of the organoids. However, segmenting individual tumor organoids is challenging due to their inhomogeneous internal intensity and overlapping structures. This paper proposes a convexity-preserving level-set segmentation 4 model based on the characteristics of tumor organoid images to segment individual tumor organoids precisely. Considering the predominant spherical shape exhibited by organoid growth, we propose a level-set model that includes a data-driven term, a curvature term, and a regularization term. The data-driven term pulls the contour to the vicinity of the boundary; the curvature term ensures the maintenance of convexity in the targeted segmentation, and the regularization term controls the smoothness and propagation of the contour. The proposed model aids in overcoming interference from factors such as overlap and noise, enabling the evolving curve to converge to the actual boundary of the target accurately. Furthermore, we propose a selectable and targeted initialization method that guarantees precise segmentation of specific regions of interest. Experiments on 51 pancreatic ductal adenocarcinoma organoid images show that our model achieved excellent segmentation results. The average Dice value and computation time are 98.81±0.48% and 20.67 s. Compared with the C-V and CPLSE models, it is more accurate and takes less time.

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.

Construction of tumor organoids and their application to cancer research and therapy

Cancer remains a severe public health burden worldwide. One of the challenges hampering effective cancer therapy is that the existing cancer models hardly recapitulate the tumor microenvironment of human patients. Over the past decade, tumor organoids have emerged as an in vitro 3D tumor model to mimic the pathophysiological characteristics of parental tumors. Various techniques have been developed to construct tumor organoids, such as matrix-based methods, hanging drop, spinner or rotating flask, nonadhesive surface, organ-on-a-chip, 3D bioprinting, and genetic engineering. This review elaborated on cell components and fabrication methods for establishing tumor organoid models. Furthermore, we discussed the application of tumor organoids to cancer modeling, basic cancer research, and anticancer therapy. Finally, we discussed current limitations and future directions in employing tumor organoids for more extensive applications.

Bioengineering Approaches for the Pancreatic Tumor Organoids Research and Application

Pancreatic cancer is a highly lethal form of digestive malignancy that poses significant health risks to individuals worldwide. Chemotherapy-based comprehensive treatment is the primary therapeutic approach for midlife and late-life patients. Nevertheless, the heterogeneity of the tumor and individual genetic backgrounds result in substantial variations in drug sensitivity among patients, rendering a single treatment regimen unsuitable for all patients. Conventional pancreatic cancer tumor organoid models are capable of emulating the biological traits of pancreatic cancer and are utilized in drug development and screening. However, these tumor organoids can still not mimic the tumor microenvironment (TME) in vivo, and the poor controllability in the preparation process hinders translation from essential drug screening to clinical pharmacological therapy. In recent years, many engineering methods with remarkable results have been used to develop pancreatic cancer organoid models, including bio-hydrogel, co-culture, microfluidic, and gene editing. Here, this work summarizes and analyzes the recent developments in engineering pancreatic tumor organoid models. In addition, the future direction of improving engineered pancreatic cancer organoids is discussed for their application prospects in clinical treatment.

Preclinical liver cancer models in the context of immunoprecision therapy: Application and perspectives

Hepatocellular carcinoma (HCC), ranking as the third leading cause of cancer-related mortality globally, continues to pose challenges in achieving optimal treatment outcomes. The complex nature of HCC, characterized by high spatiotemporal heterogeneity, invasive potential, and drug resistance, presents difficulties in its research. Consequently, an in-depth understanding and accurate simulation of the immune microenvironment of HCC are of paramount importance. This article comprehensively explores the application of preclinical models in HCC research, encompassing cell line models, patient-derived xenograft mouse models, genetically engineered mouse models, chemically induced models, humanized mouse models, organoid models, and microfluidic chip-based patient derived organotypic spheroids models. Each model possesses its distinct advantages and limitations in replicating the biological behavior and immune microenvironment of HCC. By scrutinizing the limitations of existing models, this paper aims to propel the development of next-generation cancer models, enabling more precise emulation of HCC characteristics. This will, in turn, facilitate the optimization of treatment strategies, drug efficacy prediction, and safety assessments, ultimately contributing to the realization of personalized and precision therapies. Additionally, this article also provides insights into future trends and challenges in the fields of tumor biology and preclinical research.

Top advances of the year: Pancreatic cancer

This commentary highlights the key recent advances made in the field of pancreatic cancer. Although there has yet to be a major breakthrough in clinical care for the majority of patients, significant strides have been made in understanding the complex biology of this malignancy and identifying new therapeutic targets.

A Phase I Expansion Cohort Study Evaluating the Safety and Efficacy of the CHK1 Inhibitor LY2880070 with Low-dose Gemcitabine in Patients with Metastatic Pancreatic Adenocarcinoma

PURPOSE

Combining gemcitabine with CHK1 inhibition has shown promise in preclinical models of pancreatic ductal adenocarcinoma (PDAC). Here, we report the findings from a phase I expansion cohort study (NCT02632448) investigating low-dose gemcitabine combined with the CHK1 inhibitor LY2880070 in patients with previously treated advanced PDAC.

PATIENTS AND METHODS

Patients with metastatic PDAC were treated with gemcitabine intravenously at 100 mg/m2 on days 1, 8, and 15, and LY2880070 50 mg orally twice daily on days 2-6, 9-13, and 16-20 of each 21-day cycle. Pretreatment tumor biopsies were obtained from each patient for correlative studies and generation of organoid cultures for drug sensitivity testing and biomarker analyses.

RESULTS

Eleven patients with PDAC were enrolled in the expansion cohort between August 27, 2020 and July 30, 2021. Four patients (36%) experienced drug-related grade 3 adverse events. No objective radiologic responses were observed, and all patients discontinued the trial by 3.2 months. In contrast to the lack of efficacy observed in patients, organoid cultures derived from biopsies procured from two patients demonstrated strong sensitivity to the gemcitabine/LY2880070 combination and showed treatment-induced upregulation of replication stress and DNA damage biomarkers, including pKAP1, pRPA32, and γH2AX, as well as induction of replication fork instability.

CONCLUSIONS

No evidence of clinical activity was observed for combined low-dose gemcitabine and LY2880070 in this treatment-refractory PDAC cohort. However, the gemcitabine/LY2880070 combination showed in vitro efficacy, suggesting that drug sensitivity for this combination in organoid cultures may not predict clinical benefit in patients.

Opportunities and challenges of 5G network technology toward precision medicine

Moving away from traditional "one-size-fits-all" treatment to precision-based medicine has tremendously improved disease prognosis, accuracy of diagnosis, disease progression prediction, and targeted-treatment. The current cutting-edge of 5G network technology is enabling a growing trend in precision medicine to extend its utility and value to the smart healthcare system. The 5G network technology will bring together big data, artificial intelligence, and machine learning to provide essential levels of connectivity to enable a new health ecosystem toward precision medicine. In the 5G-enabled health ecosystem, its applications involve predictive and preventative measurements which enable advances in patient personalization. This review aims to discuss the opportunities, challenges, and prospects posed to 5G network technology in moving forward to deliver personalized treatments and patient-centric care via a precision medicine approach.

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.

The application of pancreatic cancer organoids for novel drug discovery

INTRODUCTION

Pancreatic ductal adenocarcinoma presents with a dismal prognosis. Personalized therapy is urgently warranted to overcome the treatment limitations of the "one-size-fits-all" scheme. Organoids have emerged as fundamental novel tools to study tumor biology and heterogeneity, hence overcoming limitations of other model systems by better-reflecting tissue heterogeneity and recapitulating in-vivo processes. Besides their crucial role in basic research, they have evolved as tools for translational drug discovery and patient stratification.

AREAS COVERED

This review highlights the achievements of an organoid-based drug investigation and discovery. The authors present an overview of studies using organoids for drug testing. Further, they pinpoint studies correlating the in vitro prediction of organoids to the actual patient`s response. Furthermore, the authors describe novel model systems and take a thorough overlook of microfluidic chips, synthetic matrices, multicellular systems, bioprinting, and stem cell-derived pancreatic organoid systems.

EXPERT OPINION

Organoid systems promise great potential for future clinical applications. Indeed, they may be implemented into informed decision-making for guiding therapies. However, validation by randomized trials is mandatory. Additionally, organoids in combination with other cellular compartments may be exploited for drug discovery by studying niche-tumor interaction. Yet, several precautions must be kept in mind, such as standardization and reproducibility.

Automated detection and growth tracking of 3D bio-printed organoid clusters using optical coherence tomography with deep convolutional neural networks

Organoids are advancing the development of accurate prediction of drug efficacy and toxicity in vitro. These advancements are attributed to the ability of organoids to recapitulate key structural and functional features of organs and parent tumor. Specifically, organoids are self-organized assembly with a multi-scale structure of 30-800 μm, which exacerbates the difficulty of non-destructive three-dimensional (3D) imaging, tracking and classification analysis for organoid clusters by traditional microscopy techniques. Here, we devise a 3D imaging, segmentation and analysis method based on Optical coherence tomography (OCT) technology and deep convolutional neural networks (CNNs) for printed organoid clusters (Organoid Printing and optical coherence tomography-based analysis, OPO). The results demonstrate that the organoid scale influences the segmentation effect of the neural network. The multi-scale information-guided optimized EGO-Net we designed achieves the best results, especially showing better recognition workout for the biologically significant organoid with diameter ≥50 μm than other neural networks. Moreover, OPO achieves to reconstruct the multiscale structure of organoid clusters within printed microbeads and calibrate the printing errors by segmenting the printed microbeads edges. Overall, the classification, tracking and quantitative analysis based on image reveal that the growth process of organoid undergoes morphological changes such as volume growth, cavity creation and fusion, and quantitative calculation of the volume demonstrates that the growth rate of organoid is associated with the initial scale. The new method we proposed enable the study of growth, structural evolution and heterogeneity for the organoid cluster, which is valuable for drug screening and tumor drug sensitivity detection based on organoids.