Normal and tumor-derived organoids as a drug screening platform for tumor-specific drug vulnerabilities

A systematic review on the culture methods and applications of 3D tumoroids for cancer research and personalized medicine

Cancer is a highly heterogeneous disease, and thus treatment responses vary greatly between patients. To improve therapy efficacy and outcome for cancer patients, more representative and patient-specific preclinical models are needed. Organoids and tumoroids are 3D cell culture models that typically retain the genetic and epigenetic characteristics, as well as the morphology, of their tissue of origin. Thus, they can be used to understand the underlying mechanisms of cancer initiation, progression, and metastasis in a more physiological setting. Additionally, co-culture methods of tumoroids and cancer-associated cells can help to understand the interplay between a tumor and its tumor microenvironment. In recent years, tumoroids have already helped to refine treatments and to identify new targets for cancer therapy. Advanced culturing systems such as chip-based fluidic devices and bioprinting methods in combination with tumoroids have been used for high-throughput applications for personalized medicine. Even though organoid and tumoroid models are complex in vitro systems, validation of results in vivo is still the common practice. Here, we describe how both animal- and human-derived tumoroids have helped to identify novel vulnerabilities for cancer treatment in recent years, and how they are currently used for precision medicine.

In vitro models for neuropathic pain phenotypic screening in brain therapeutics

The discovery of brain therapeutics faces a significant challenge due to the low translatability of preclinical results into clinical success. To address this gap, several efforts have been made to obtain more translatable neuronal models for phenotypic screening. These models allow the selection of active compounds without predetermined knowledge of drug targets. In this review, we present an overview of various existing models within the field, examining their strengths and limitations, particularly in the context of neuropathic pain research. We illustrate the usefulness of these models through a comparative review in three crucial areas: i) the development of novel phenotypic screening strategies specifically for neuropathic pain, ii) the validation of the models for both primary and secondary screening assays, and iii) the use of the models in target deconvolution processes.

Patient-derived organoids for precision oncology: a platform to facilitate clinical decision making

BACKGROUND

Despite recent advances in research, there are still critical lacunae in our basic understanding of the cause, pathogenesis, and natural history of many cancers, especially heterogeneity in patient response to drugs and mediators in the transition from malignant to invasive phenotypes. The explication of the pathogenesis of cancer has been constrained by limited access to patient samples, tumor heterogeneity and lack of reliable biological models. Amelioration in cancer treatment depends on further understanding of the etiologic, genetic, biological, and clinical heterogeneity of tumor microenvironment. Patient-derived organoids recapitulate the basic features of primary tumors, including histological complexity and genetic heterogeneity, which is instrumental in predicting patient response to drugs.

METHODS

Human iPSCs from healthy donors, breast and ovarian cancer patients were successfully differentiated towards isogenic hepatic, cardiac, neural and endothelial lineages. Multicellular organoids were established using Primary cells isolated from tumor tissues, histologically normal tissues adjacent to the tumors (NATs) and adipose tissues (source of Mesenchymal Stem Cells) from ovarian and breast cancer patients. Further these organoids were propagated and used for drug resistance/sensitivity studies.

RESULTS

Ovarian and breast cancer patients' organoids showed heterogeneity in drug resistance and sensitivity. iPSCs-derived cardiomyocytes, hepatocytes and neurons showed donor-to-donor variability of chemotherapeutic drug sensitivity in ovarian cancer patients, breast cancer patients and healthy donors.

CONCLUSION

We report development of a novel integrated platform to facilitate clinical decision-making using the patient's primary cells, iPSCs and derivatives, to clinically relevant models for oncology research.

Small molecule-mediated targeting of microRNAs for drug discovery: Experiments, computational techniques, and disease implications

Small molecules have been providing medical breakthroughs for human diseases for more than a century. Recently, identifying small molecule inhibitors that target microRNAs (miRNAs) has gained importance, despite the challenges posed by labour-intensive screening experiments and the significant efforts required for medicinal chemistry optimization. Numerous experimentally-verified cases have demonstrated the potential of miRNA-targeted small molecule inhibitors for disease treatment. This new approach is grounded in their posttranscriptional regulation of the expression of disease-associated genes. Reversing dysregulated gene expression using this mechanism may help control dysfunctional pathways. Furthermore, the ongoing improvement of algorithms has allowed for the integration of computational strategies built on top of laboratory-based data, facilitating a more precise and rational design and discovery of lead compounds. To complement the use of extensive pharmacogenomics data in prioritising potential drugs, our previous work introduced a computational approach based on only molecular sequences. Moreover, various computational tools for predicting molecular interactions in biological networks using similarity-based inference techniques have been accumulated in established studies. However, there are a limited number of comprehensive reviews covering both computational and experimental drug discovery processes. In this review, we outline a cohesive overview of both biological and computational applications in miRNA-targeted drug discovery, along with their disease implications and clinical significance. Finally, utilizing drug-target interaction (DTIs) data from DrugBank, we showcase the effectiveness of deep learning for obtaining the physicochemical characterization of DTIs.

Longitudinal quantification of mouse gastric tumor organoid viability and growth using luminescence and microscopy

Tumor-derived organoids are valuable for testing anti-cancer drugs in vitro, but existing lysis-based protocols for viability measurement are laborious and restricted at a single time point. Here, we provide a lysis-free protocol for longitudinal and rapid assessment of mouse gastric tumor organoid viability and growth. We describe organoid plating, viability assessment via luminescence measurement, quantification of organoid growth by microscopy imaging, and treatment of organoids with test compounds to evaluate the effects on viability and growth at various time points.

Middle-out methods for spatiotemporal tissue engineering of organoids

Organoids recapitulate many aspects of the complex three-dimensional (3D) organization found within native tissues and even display tissue and organ-level functionality. Traditional approaches to organoid culture have largely employed a top-down tissue engineering strategy, whereby cells are encapsulated in a 3D matrix, such as Matrigel, alongside well-defined biochemical cues that direct morphogenesis. However, the lack of spatiotemporal control over niche properties renders cellular processes largely stochastic. Therefore, bottom-up tissue engineering approaches have evolved to address some of these limitations and focus on strategies to assemble tissue building blocks with defined multi-scale spatial organization. However, bottom-up design reduces the capacity for self-organization that underpins organoid morphogenesis. Here, we introduce an emerging framework, which we term middle-out strategies, that relies on existing design principles and combines top-down design of defined synthetic matrices that support proliferation and self-organization with bottom-up modular engineered intervention to limit the degrees of freedom in the dynamic process of organoid morphogenesis. We posit that this strategy will provide key advances to guide the growth of organoids with precise geometries, structures and function, thereby facilitating an unprecedented level of biomimicry to accelerate the utility of organoids to more translationally relevant applications.

Single Plane Illumination Microscopy for Microfluidic Device Imaging

Three-dimensional imaging of live processes at a cellular level is a challenging task. It requires high-speed acquisition capabilities, low phototoxicity, and low mechanical disturbances. Three-dimensional imaging in microfluidic devices poses additional challenges as a deep penetration of the light source is required, along with a stationary setting, so the flows are not perturbed. Different types of fluorescence microscopy techniques have been used to address these limitations; particularly, confocal microscopy and light sheet fluorescence microscopy (LSFM). This manuscript proposes a novel architecture of a type of LSFM, single-plane illumination microscopy (SPIM). This custom-made microscope includes two mirror galvanometers to scan the sample vertically and reduce shadowing artifacts while avoiding unnecessary movement. In addition, two electro-tunable lenses fine-tune the focus position and reduce the scattering caused by the microfluidic devices. The microscope has been fully set up and characterized, achieving a resolution of 1.50 μm in the x-y plane and 7.93 μm in the z-direction. The proposed architecture has risen to the challenges posed when imaging microfluidic devices and live processes, as it can successfully acquire 3D volumetric images together with time-lapse recordings, and it is thus a suitable microscopic technique for live tracking miniaturized tissue and disease models.

Organoids in gastrointestinal diseases: from experimental models to clinical translation

We are entering an era of medicine where increasingly sophisticated data will be obtained from patients to determine proper diagnosis, predict outcomes and direct therapies. We predict that the most valuable data will be produced by systems that are highly dynamic in both time and space. Three-dimensional (3D) organoids are poised to be such a highly valuable system for a variety of gastrointestinal (GI) diseases. In the lab, organoids have emerged as powerful systems to model molecular and cellular processes orchestrating natural and pathophysiological human tissue formation in remarkable detail. Preclinical studies have impressively demonstrated that these organs-in-a-dish can be used to model immunological, neoplastic, metabolic or infectious GI disorders by taking advantage of patient-derived material. Technological breakthroughs now allow to study cellular communication and molecular mechanisms of interorgan cross-talk in health and disease including communication along for example, the gut-brain axis or gut-liver axis. Despite considerable success in culturing classical 3D organoids from various parts of the GI tract, some challenges remain to develop these systems to best help patients. Novel platforms such as organ-on-a-chip, engineered biomimetic systems including engineered organoids, micromanufacturing, bioprinting and enhanced rigour and reproducibility will open improved avenues for tissue engineering, as well as regenerative and personalised medicine. This review will highlight some of the established methods and also some exciting novel perspectives on organoids in the fields of gastroenterology. At present, this field is poised to move forward and impact many currently intractable GI diseases in the form of novel diagnostics and therapeutics.

Patient-derived organoids as a model for tumor research

Cancer represents a leading cause of death, despite the rapid progress of cancer research, leading to urgent need for accurate preclinical model to further study of tumor mechanism and accelerate translational applications. Cancer cell lines cannot fully recapitulate tumors of different patients due to the lack of tumor complexity and specification, while the high technical difficulty, long time, and substantial cost of patient-derived xenograft model makes it unable to be used extensively for all types of tumors and large-scale drug screening. Patient-derived organoids can be established rapidly with a high success rate from many tumors, and precisely replicate the key histopathological, genetic, and phenotypic features, as well as therapeutic response of patient tumor. Therefore, they are extensively used in cancer basic research, biobanking, disease modeling and precision medicine. The combinations of cancer organoids with other advanced technologies, such as 3D bio-printing, organ-on-a-chip, and CRISPR-Cas9, contributes to the more complete replication of complex tumor microenvironment and tumorigenesis. In this review, we discuss the various methods of the establishment and the application of patient-derived organoids in diverse tumors as well as the limitations and future prospects of these models. Further advances of tumor organoids are expected to bridge the huge gap between bench and bedside and provide the unprecedented opportunities to advance cancer research.