Browse
Submit Data
Databases
API
Help

Dataset Information

13 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A Quantitative Pharmacology Model of Exosome-Mediated Drug Efflux and Perturbation-Induced Synergy.

ABSTRACT: Exosomes, naturally occurring vesicles secreted by cells, are undergoing development as drug carriers. We used experimental and computational studies to investigate the kinetics of intracellular exosome processing and exosome-mediated drug efflux and the effects of exosome inhibition. The experiments used four human-breast or ovarian cancer cells, a cytotoxic drug paclitaxel (PTX), two exosome inhibitors (omeprazole (OME), which inhibits exosome release, and GW4869 (GW), which inhibits synthesis of sphingolipid ceramide required for exosome formation), LC-MS/MS analysis of PTX levels in exosomes, and confocal microscopic study of endocytic transport (monitored using fluorescent nanoparticles and endocytic organelle markers). In all four cells, exosome production was enhanced by PTX but diminished by OME or GW (p < 0.05); the PTX enhancement was completely reversed by OME or GW. Co-treatment with OME or GW simultaneously reduced PTX amount in exosomes and increased PTX amount and cytotoxicity in exosome-donor cells (corresponding to >2-fold synergy as indicated by curve shift and uncertainty envelope analyses). This synergy is consistent with the previous reports that OME co-administration significantly enhances the taxane activity in tumor-bearing mice and in patients with triple negative metastatic breast cancer. The experimental results were used to develop a quantitative pharmacology model; model simulations revealed the different effects of the two exosome inhibitors on intracellular PTX processing and subcellular distribution.

SUBMITTER: Wang J

PROVIDER: S-EPMC8308960 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Confinement-Induced Drug-Tolerance in Mycobacteria Mediated by an Efflux Mechanism.

Project description:Tuberculosis (TB) is the world's deadliest curable disease, responsible for an estimated 1.5 million deaths annually. A considerable challenge in controlling this disease is the prolonged multidrug chemotherapy (6 to 9 months) required to overcome drug-tolerant mycobacteria that persist in human tissues, although the same drugs can sterilize genetically identical mycobacteria growing in axenic culture within days. An essential component of TB infection involves intracellular Mycobacterium tuberculosis bacteria that multiply within macrophages and are significantly more tolerant to antibiotics compared to extracellular mycobacteria. To investigate this aspect of human TB, we created a physical cell culture system that mimics confinement of replicating mycobacteria, such as in a macrophage during infection. Using this system, we uncovered an epigenetic drug-tolerance phenotype that appears when mycobacteria are cultured in space-confined bioreactors and disappears in larger volume growth contexts. Efflux mechanisms that are induced in space-confined growth environments contribute to this drug-tolerance phenotype. Therefore, macrophage-induced drug tolerance by mycobacteria may be an effect of confined growth among other macrophage-specific mechanisms.

| S-EPMC4546595 | biostudies-literature

Systems-pharmacology dissection of a drug synergy in imatinib-resistant CML.

Project description:Occurrence of the BCR-ABL(T315I) gatekeeper mutation is among the most pressing challenges in the therapy of chronic myeloid leukemia (CML). Several BCR-ABL inhibitors have multiple targets and pleiotropic effects that could be exploited for their synergistic potential. Testing combinations of such kinase inhibitors identified a strong synergy between danusertib and bosutinib that exclusively affected CML cells harboring BCR-ABL(T315I). To elucidate the underlying mechanisms, we applied a systems-level approach comprising phosphoproteomics, transcriptomics and chemical proteomics. Data integration revealed that both compounds targeted Mapk pathways downstream of BCR-ABL, resulting in impaired activity of c-Myc. Using pharmacological validation, we assessed that the relative contributions of danusertib and bosutinib could be mimicked individually by Mapk inhibitors and collectively by downregulation of c-Myc through Brd4 inhibition. Thus, integration of genome- and proteome-wide technologies enabled the elucidation of the mechanism by which a new drug synergy targets the dependency of BCR-ABL(T315I) CML cells on c-Myc through nonobvious off targets.

| S-EPMC4038039 | biostudies-literature

A quantitative systems pharmacology approach, incorporating a novel liver model, for predicting pharmacokinetic drug-drug interactions.

Project description:All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs) of new chemical entities (NCEs) and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit), located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level). A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK) model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s) including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies.

| S-EPMC5598964 | biostudies-literature

Drug tolerance in replicating mycobacteria mediated by a macrophage-induced efflux mechanism.

Project description:Treatment of tuberculosis, a complex granulomatous disease, requires long-term multidrug therapy to overcome tolerance, an epigenetic drug resistance that is widely attributed to nonreplicating bacterial subpopulations. Here, we deploy Mycobacterium marinum-infected zebrafish larvae for in vivo characterization of antitubercular drug activity and tolerance. We describe the existence of multidrug-tolerant organisms that arise within days of infection, are enriched in the replicating intracellular population, and are amplified and disseminated by the tuberculous granuloma. Bacterial efflux pumps that are required for intracellular growth mediate this macrophage-induced tolerance. This tolerant population also develops when Mycobacterium tuberculosis infects cultured macrophages, suggesting that it contributes to the burden of drug tolerance in human tuberculosis. Efflux pump inhibitors like verapamil reduce this tolerance. Thus, the addition of this currently approved drug or more specific efflux pump inhibitors to standard antitubercular therapy should shorten the duration of curative treatment.

| S-EPMC3117281 | biostudies-literature

Quantitative systems pharmacology model of GITR-mediated T cell dynamics in tumor microenvironment.

Project description:T cell interaction in the tumor microenvironment is a key component of immuno-oncology therapy. Glucocorticoid-induced tumor necrosis factor receptor (TNFR)-related protein (GITR) is expressed on immune cells including regulatory T cells (Tregs) and effector T cells (Teffs). Preclinical data suggest that agonism of GITR in combination with Fc-γ receptor-mediated depletion of Tregs results in increased intratumoral Teff:Treg ratio and tumor shrinkage. A novel quantitative systems pharmacology (QSP) model was developed for the murine anti-GITR agonist antibody, DTA-1.mIgG2a, to describe the kinetics of intratumoral Tregs and Teffs in Colon26 and A20 syngeneic mouse tumor models. It adequately captured the time profiles of intratumoral Treg and Teff and serum DTA-1.mIgG2a and soluble GITR concentrations in both mouse models, and described the response differences between the two models. The QSP model provides a quantitative understanding of the trade-off between maximizing Treg depletion versus Teff agonism, and offers insights to optimize drug design and dose regimen.

| S-EPMC10014051 | biostudies-literature

Quantitative collision-induced unfolding differentiates model antibody-drug conjugates.

Project description:Antibody-drug conjugates (ADCs) are antibody-based therapeutics that have proven to be highly effective cancer treatment platforms. They are composed of monoclonal antibodies conjugated with highly potent drugs via chemical linkers. Compared to cysteine-targeted chemistries, conjugation at native lysine residues can lead to a higher degree of structural heterogeneity, and thus it is important to evaluate the impact of conjugation on antibody conformation. Here, we present a workflow involving native ion mobility (IM)-MS and gas-phase unfolding for the structural characterization of lysine-linked monoclonal antibody (mAb)-biotin conjugates. Following the determination of conjugation states via denaturing Liquid Chromatography-Mass Spectrometry (LC-MS) measurements, we performed both size exclusion chromatography (SEC) and native IM-MS measurements in order to compare the structures of biotinylated and unmodified IgG1 molecules. Hydrodynamic radii (Rh) and collision cross-sectional (CCS) values were insufficient to distinguish the conformational changes in these antibody-biotin conjugates owing to their flexible structures and limited instrument resolution. In contrast, collision induced unfolding (CIU) analyses were able to detect subtle structural and stability differences in the mAb upon biotin conjugation, exhibiting a sensitivity to mAb conjugation that exceeds native MS analysis alone. Destabilization of mAb-biotin conjugates was detected by both CIU and differential scanning calorimetry (DSC) data, suggesting a previously unknown correlation between the two measurement tools. We conclude by discussing the impact of IM-MS and CIU technologies on the future of ADC development pipelines.

| S-EPMC6371214 | biostudies-literature

An in vitro quantitative systems pharmacology approach for deconvolving mechanisms of drug-induced, multilineage cytopenias.

Project description:Myelosuppression is one of the most common and severe adverse events associated with anti-cancer therapies and can be a source of drug attrition. Current mathematical modeling methods for assessing cytopenia risk rely on indirect measurements of drug effects and primarily focus on single lineage responses to drugs. However, anti-cancer therapies have diverse mechanisms with varying degrees of effect across hematopoietic lineages. To improve predictive understanding of drug-induced myelosuppression, we developed a quantitative systems pharmacology (QSP) model of hematopoiesis in vitro for quantifying the effects of anti-cancer agents on multiple hematopoietic cell lineages. We calibrated the system parameters of the model to cell kinetics data without treatment and then validated the model by showing that the inferred mechanisms of anti-proliferation and/or cell-killing are consistent with the published mechanisms for three classes of drugs with different mechanisms of action. Using a set of compounds as a reference set, we then analyzed novel compounds to predict their mechanisms and magnitude of myelosuppression. Further, these quantitative mechanisms are valuable for the development of translational in vivo models to predict clinical cytopenia effects.

| S-EPMC7402526 | biostudies-literature

Quantifying Drug-Induced Bone Marrow Toxicity Using a Novel Haematopoiesis Systems Pharmacology Model.

Project description:Haematological toxicity associated with cancer therapeutics is monitored by changes in blood cell count, and their primary effect is on proliferative progenitors in the bone marrow. Using observations in rat bone marrow and blood, we characterize a mathematical model that comprises cell proliferation and differentiation of the full haematopoietic phylogeny, with interacting feedback loops between lineages in homeostasis as well as following carboplatin exposure. We accurately predicted the temporal dynamics of several mature cell types related to carboplatin-induced bone marrow toxicity and identified novel insights into haematopoiesis. Our model confirms a significant degree of plasticity within bone marrow cells, with the number and type of both early progenitors and circulating cells affecting cell balance, via feedback mechanisms, through fate decisions of the multipotent progenitors. We also demonstrated cross-species translation of our predictions to patients, applying the same core model structure and considering differences in drug-dependent and physiology-dependent parameters.

| S-EPMC6875710 | biostudies-literature

Quantitative Assessment of Arsenite-Induced Perturbation of Ubiquitinated Proteome.

Project description:Arsenic contamination in food and groundwater constitutes a public health concern for more than 200 million people worldwide. Individuals chronically exposed to arsenic through drinking and ingestion exhibit a higher risk of developing cancers and cardiovascular diseases. Nevertheless, the underlying mechanisms of arsenic toxicity are not fully understood. Arsenite is known to bind to and deactivate RING finger E3 ubiquitin ligases; thus, we reason that a systematic interrogation about how arsenite exposure modulates global protein ubiquitination may reveal novel molecular targets for arsenic toxicity. By employing liquid chromatography-tandem mass spectrometry, in combination with stable isotope labeling by amino acids in cell culture (SILAC) and immunoprecipitation of di-glycine-conjugated lysine-containing tryptic peptides, we assessed the alterations in protein ubiquitination in GM00637 human skin fibroblast cells upon arsenite exposure at the entire proteome level. We observed that arsenite exposure led to altered ubiquitination of many proteins, where the alterations in a large majority of ubiquitination events are negatively correlated with changes in expression of the corresponding proteins, suggesting their modulation by the ubiquitin-proteasomal pathway. Moreover, we observed that arsenite exposure confers diminished ubiquitination of a rate-limiting enzyme in cholesterol biosynthesis, HMGCR, at Lys248. We also revealed that TRC8 is the major E3 ubiquitin ligase for HMGCR ubiquitination in HEK293T cells, and the arsenite-induced diminution of HMGCR ubiquitination is abrogated upon genetic depletion of TRC8. In summary, we systematically characterized arsenite-induced perturbations in a ubiquitinated proteome in human cells and found that the arsenite-elicited attenuation of HMGCR ubiquitination in HEK293T cells involves TRC8.

| S-EPMC9869663 | biostudies-literature

The promises of quantitative systems pharmacology modelling for drug development.

Project description:Recent growth in annual new therapeutic entity (NTE) approvals by the U.S. Food and Drug Administration (FDA) suggests a positive trend in current research and development (R&D) output. Prior to this, the cost of each NTE was considered to be rising exponentially, with compound failure occurring mainly in clinical phases. Quantitative systems pharmacology (QSP) modelling, as an additional tool in the drug discovery arsenal, aims to further reduce NTE costs and improve drug development success. Through in silico mathematical modelling, QSP can simulate drug activity as perturbations in biological systems and thus understand the fundamental interactions which drive disease pathology, compound pharmacology and patient response. Here we review QSP, pharmacometrics and systems biology models with respect to the diseases covered as well as their clinical relevance and applications. Overall, the majority of modelling focus was aligned with the priority of drug-discovery and clinical trials. However, a few clinically important disease categories, such as Immune System Diseases and Respiratory Tract Diseases, were poorly covered by computational models. This suggests a possible disconnect between clinical and modelling agendas. As a standard element of the drug discovery pipeline the uptake of QSP might help to increase the efficiency of drug development across all therapeutic indications.

| S-EPMC5064996 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data