scholarly journals Biobanked Glioblastoma Patient-Derived Organoids as a Precision Medicine Model to Study Inhibition of Invasion

2021 ◽  
Vol 22 (19) ◽  
pp. 10720
Author(s):  
Emilie Darrigues ◽  
Edward H. Zhao ◽  
Annick De Loose ◽  
Madison P. Lee ◽  
Michael J. Borrelli ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Ex Vivo ◽  
Model Systems ◽  
Established Cell Line ◽  
Matrigel Invasion Assay ◽  
Tubulin Inhibitor ◽  
Matrigel Invasion ◽  
Established Cell ◽  
Inhibitor Compounds ◽  
Invasion Inhibition

Glioblastoma (GBM) is highly resistant to treatment and invasion into the surrounding brain is a cancer hallmark that leads to recurrence despite surgical resection. With the emergence of precision medicine, patient-derived 3D systems are considered potentially robust GBM preclinical models. In this study, we screened a library of 22 anti-invasive compounds (i.e., NF-kB, GSK-3-B, COX-2, and tubulin inhibitors) using glioblastoma U-251 MG cell spheroids. We evaluated toxicity and invasion inhibition using a 3D Matrigel invasion assay. We next selected three compounds that inhibited invasion and screened them in patient-derived glioblastoma organoids (GBOs). We developed a platform using available macros for FIJI/ImageJ to quantify invasion from the outer margin of organoids. Our data demonstrated that a high-throughput invasion screening can be done using both an established cell line and patient-derived 3D model systems. Tubulin inhibitor compounds had the best efficacy with U-251 MG cells, however, in ex vivo patient organoids the results were highly variable. Our results indicate that the efficacy of compounds is highly related to patient intra and inter-tumor heterogeneity. These results indicate that such models can be used to evaluate personal oncology therapeutic strategies.

Activity of ARRY-614, an Inhibitor of p38 Map Kinase and Angiogenic Targets, in Hematologic Malignancies.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 4798-4798
Author(s):  
Shannon L. Winski ◽  
Stefan D. Gross ◽  
Suzy A. Brown ◽  
Deborah Anderson ◽  
Augusta Garrison ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Bone Marrow ◽  
Ex Vivo ◽  
Single Agent ◽  
Hematologic Malignancies ◽  
P38 Map Kinase ◽  
Matrigel Invasion Assay ◽  
In Vivo Models ◽  
Matrigel Invasion

Abstract Multiple Myeloma (MM) is a malignancy characterized by the clonal expansion of plasma cells within the bone marrow microenvironment. Within this compartment, the proliferative capacity of MM cells is enhanced by pro-inflammatory cytokines, and there is growing recognition that bone marrow stromal cells play an important role in the support of MM growth and chemo-resistance. We have identified a series of compounds, of which ARRY-614 is representative, that are potent inhibitors (EC50<10 nM) of cytokine synthesis through the inhibition of p38 MAPK. This compound is also a potent inhibitor of Abl tyrosine kinases and Tie2/Tek receptor tyrosine kinase. ARRY-614 is active against all of these targets on both the isolated enzymes and in cells. To confirm these activities, ARRY-614 was evaluated in relevant in vitro and in vivo models. ARRY-614 inhibited p38α in ex vivo stimulated human whole blood (EC50=2 nM) and the release of IL-6 and TNFα from SEA- or LPS-challenged mice (ED50<10 mg/kg). Further, ARRY-614 administered as a single agent was efficacious at inhibiting bFGF-driven angiogenesis in an in vivo matrigel invasion assay as well as inhibiting tumor growth in subcutaneous K562 (BCR-Abl dependent) and RPMI 8226 (multiple myeloma) tumor xenografts in mice, at doses ranging from 30 to 100 mg/kg qd, PO. In regulated safety studies, this compound was well-tolerated at doses up to 100 mg/kg qd and 30 mg/kg qd in rats and cynomolgus, respectively. Together, these data support the advancement of this agent into clinical trials for hematologic malignancies.

scholarly journals Metabolomics as a Truly Translational Tool for Precision Medicine

2021 ◽  
Vol 40 (5) ◽  
pp. 413-426
Author(s):  
Julian C. Schmidt ◽  
Bonnie V. Dougherty ◽  
Richard D. Beger ◽  
Dean P. Jones ◽  
Michael A. Schmidt ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Metabolic Networks ◽  
Cultured Cells ◽  
Ex Vivo ◽  
Metabolite Identification ◽  
Model Systems ◽  
Model Organisms ◽  
Data Repositories ◽  
Metabolomics Data ◽  
Toxicity Studies

Metabolomics is unique among omics technologies in being applicable to metabolism and toxicity studies broadly across organisms (e.g., humans, other mammals, model organisms, and even bacteria) and across biological materials (e.g., blood, urine, saliva, biopsy, and stool), including cultured cells and subcellular fractions. Metabolomics can be used to characterize biologic response patterns in humans as well as to support mechanistic studies in model systems and ex vivo studies. A broad range of resources are available, including publicly accessible data repositories (e.g., Metabolomics Workbench), tools for biostatistics and bioinformatics (e.g., MetaboAnalyst), metabolite identification (e.g., Metlin), and pathway analysis (e.g., Kyoto Encyclopedia of Genes and Genomes). Thus, metabolomics is more than a promise of the future; metabolomics is already available as a translational approach to facilitate precision medicine. This ACT Symposium review will contain an introduction to metabolomics in toxicity studies followed by sections on translational metabolic networks, translational metabolite biomarkers of acetaminophen-induced acute liver injury, translational framework using high-resolution metabolomics for integrated pharmacokinetics and pharmacodynamics, and precision medicine applications: extracting actionable targets from untargeted metabolomics data following one year in space.

Learning from metabolic networks: current trends and future directions for precision medicine.

2020 ◽  
Vol 28 ◽  
Author(s):  
Ilaria Granata ◽  
Mario Manzo ◽  
Ari Kusumastuti ◽  
Mario R Guarracino
Keyword(s):  
Systems Biology ◽  
Precision Medicine ◽  
Metabolic Networks ◽  
Information Modeling ◽  
Model Systems ◽  
Specific Information ◽  
Important Indicator ◽  
Predictive Values ◽  
Metabolic Systems ◽  
Metabolic Models

Purpose: Systems biology and network modeling represent, nowadays, the hallmark approaches for the development of predictive and targeted-treatment based precision medicine. The study of health and disease as properties of the human body system allows the understanding of the genotype-phenotype relationship through the definition of molecular interactions and dependencies. In this scenario, metabolism plays a central role as its interactions are well characterized and it is considered an important indicator of the genotype-phenotype associations. In metabolic systems biology, the genome-scale metabolic models are the primary scaffolds to integrate multi-omics data as well as cell-, tissue-, condition-specific information. Modeling the metabolism has both investigative and predictive values. Several methods have been proposed to model systems, which involve steady-state or kinetic approaches, and to extract knowledge through machine and deep learning. Method: This review collects, analyzes, and compares the suitable data and computational approaches for the exploration of metabolic networks as tools for the development of precision medicine. To this extent, we organized it into three main sections: "Data and Databases", "Methods and Tools", and "Metabolic Networks for medicine". In the first one, we have collected the most used data and relative databases to build and annotate metabolic models. In the second section, we have reported the state-of-the-art methods and relative tools to reconstruct, simulate, and interpret metabolic systems. Finally, we have reported the most recent and innovative studies which exploited metabolic networks for the study of several pathological conditions, not only those directly related to the metabolism. Conclusion: We think that this review can be a guide to researchers of different disciplines, from computer science to biology and medicine, in exploring the power, challenges and future promises of the metabolism as predictor and target of the so-called P4 medicine (predictive, preventive, personalized and participatory).

scholarly journals SpheroidPicker for automated 3D cell culture manipulation using deep learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Istvan Grexa ◽  
Akos Diosdi ◽  
Maria Harmati ◽  
Andras Kriston ◽  
Nikita Moshkov ◽  
...  
Keyword(s):  
Cell Culture ◽  
Precision Medicine ◽  
High Throughput Screening ◽  
Standard Sample ◽  
Ex Vivo ◽  
Low Cost ◽  
3D Cell Culture ◽  
Syringe Pump ◽  
Experimental Conditions ◽  
The Past

AbstractRecent statistics report that more than 3.7 million new cases of cancer occur in Europe yearly, and the disease accounts for approximately 20% of all deaths. High-throughput screening of cancer cell cultures has dominated the search for novel, effective anticancer therapies in the past decades. Recently, functional assays with patient-derived ex vivo 3D cell culture have gained importance for drug discovery and precision medicine. We recently evaluated the major advancements and needs for the 3D cell culture screening, and concluded that strictly standardized and robust sample preparation is the most desired development. Here we propose an artificial intelligence-guided low-cost 3D cell culture delivery system. It consists of a light microscope, a micromanipulator, a syringe pump, and a controller computer. The system performs morphology-based feature analysis on spheroids and can select uniform sized or shaped spheroids to transfer them between various sample holders. It can select the samples from standard sample holders, including Petri dishes and microwell plates, and then transfer them to a variety of holders up to 384 well plates. The device performs reliable semi- and fully automated spheroid transfer. This results in highly controlled experimental conditions and eliminates non-trivial side effects of sample variability that is a key aspect towards next-generation precision medicine.

scholarly journals Gut-Ex-Vivo system as a model to study gluten response in celiac disease

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Mara Gagliardi ◽  
Nausicaa Clemente ◽  
Romina Monzani ◽  
Luca Fusaro ◽  
Eleonora Ferrari ◽  
...  
Keyword(s):  
Celiac Disease ◽  
Intestinal Epithelium ◽  
Complex Disease ◽  
Ex Vivo ◽  
Dynamic Condition ◽  
Model Systems ◽  
In Vivo Models ◽  
Effective Manner ◽  
Junction Protein ◽  
The Impact

AbstractCeliac disease (CD) is a complex immune-mediated chronic disease characterized by a consistent inflammation of the gastrointestinal tract induced by gluten intake in genetically predisposed individuals. Although initiated by the interaction between digestion-derived gliadin, a gluten component, peptides, and the intestinal epithelium, the disorder is highly complex and involving other components of the intestine, such as the immune system. Therefore, conventional model systems, mainly based on two- or three-dimension cell cultures and co-cultures, cannot fully recapitulate such a complex disease. The development of mouse models has facilitated the study of different interacting cell types involved in the disorder, together with the impact of environmental factors. However, such in vivo models are often expensive and time consuming. Here we propose an organ ex vivo culture (gut-ex-vivo system) based on small intestines from gluten-sensitive mice cultivated in a dynamic condition, able to fully recapitulate the biochemical and morphological features of the mouse model exposed to gliadin (4 weeks), in 16 h. Indeed, upon gliadin exposure, we observed: i) a down-regulation of cystic fibrosis transmembrane regulator (CFTR) and an up-regulation of transglutaminase 2 (TG2) at both mRNA and protein levels; ii) increased intestinal permeability associated with deregulated tight junction protein expression; iii) induction and production of pro-inflammatory cytokines such as interleukin (IL)-15, IL-17 and interferon gamma (IFNγ); and iv) consistent alteration of intestinal epithelium/villi morphology. Altogether, these data indicate that the proposed model can be efficiently used to study the pathogenesis of CD, test new or repurposed molecules to accelerate the search for new treatments, and to study the impact of the microbiome and derived metabolites, in a time- and cost- effective manner.

scholarly journals Experimental Models to Study COVID-19 Effect in Stem Cells

Cells ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 91
Author(s):  
Rishi Man Chugh ◽  
Payel Bhanja ◽  
Andrew Norris ◽  
Subhrajit Saha
Keyword(s):  
Stem Cells ◽  
Ex Vivo ◽  
Drug Efficacy ◽  
Cell Loss ◽  
Experimental Models ◽  
Model Systems ◽  
Virus Infectivity ◽  
Ex Vivo Model ◽  
Global Pandemic ◽  
The Impact

The new strain of coronavirus (severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2)) emerged in 2019 and hence is often referred to as coronavirus disease 2019 (COVID-19). This disease causes hypoxic respiratory failure and acute respiratory distress syndrome (ARDS), and is considered as the cause of a global pandemic. Very limited reports in addition to ex vivo model systems are available to understand the mechanism of action of this virus, which can be used for testing of any drug efficacy against virus infectivity. COVID-19 induces tissue stem cell loss, resulting inhibition of epithelial repair followed by inflammatory fibrotic consequences. Development of clinically relevant models is important to examine the impact of the COVID-19 virus in tissue stem cells among different organs. In this review, we discuss ex vivo experimental models available to study the effect of COVID-19 on tissue stem cells.

scholarly journals Considerations to Model Heart Disease in Women with Preeclampsia and Cardiovascular Disease

Cells ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 899
Author(s):  
Clara Liu Chung Ming ◽  
Kimberly Sesperez ◽  
Eitan Ben-Sefer ◽  
David Arpon ◽  
Kristine McGrath ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Cardiovascular Disease ◽  
Ex Vivo ◽  
Myocardial Damage ◽  
Cardiovascular Disorder ◽  
Model Systems ◽  
Ex Vivo Model ◽  
Disease Manifestation

Preeclampsia is a multifactorial cardiovascular disorder diagnosed after 20 weeks of gestation, and is the leading cause of death for both mothers and babies in pregnancy. The pathophysiology remains poorly understood due to the variability and unpredictability of disease manifestation when studied in animal models. After preeclampsia, both mothers and offspring have a higher risk of cardiovascular disease (CVD), including myocardial infarction or heart attack and heart failure (HF). Myocardial infarction is an acute myocardial damage that can be treated through reperfusion; however, this therapeutic approach leads to ischemic/reperfusion injury (IRI), often leading to HF. In this review, we compared the current in vivo, in vitro and ex vivo model systems used to study preeclampsia, IRI and HF. Future studies aiming at evaluating CVD in preeclampsia patients could benefit from novel models that better mimic the complex scenario described in this article.

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