7196 research outputs found
Sort by
ADAMTSL2 protein and a soluble biomarker signature identify significant and advanced fibrosis in adults with NAFLD
No full textAbstract
Aims and background: Identifying fibrosis in non-alcoholic fatty liver disease (NAFLD) is essential to predict liver-related outcomes and inform treatment decisions. A protein-based signature of fibrosis could serve as a valuable, non-invasive diagnostic tool. This study sought to identify circulating proteins associated with fibrosis in NAFLD.
Methods: We used aptamer-based proteomics to measure 4783 proteins in two cohorts (Cohort A and B). Targeted, quantitative assays coupling aptamer-based protein pull down and mass spectrometry (SPMS) validated the profiling results in a bariatric and NAFLD cohort (Cohort C and D, respectively). Generalized linear modelling-logistic regression assessed the candidate proteins to classify fibrosis.
Results: From the multiplex profiling, 16 proteins differed significantly by fibrosis in cohorts A (n=62) and B (n=98). Quantitative and robust SPMS assays were developed for 8 proteins and validated in Cohorts C (n=71) and D (n=84). The protein A disintegrin and metalloproteinase with thrombospondin motifs like 2 (ADAMTSL2) accurately distinguished NAFL/NASH with fibrosis stage 0-1 (F0-1) from at-risk NASH with fibrosis stage 2-4 with an AUROC of 0.83 and 0.86 in Cohorts C and D, respectively, and from NASH with significant fibrosis (F2-3) with an AUROC of 0.80 and 0.83 in Cohorts C and D, respectively. An 8-protein panel distinguished NAFL/NASH F0-1 from at-risk NASH (AUROC 0.90 and 0.87 in Cohort C and D, respectively) and NASH F2-3 (AUROC 0.89 and 0.83 in Cohorts C and D, respectively). The 8-protein panel and ADAMTSL2 protein had superior performance to the NAFLD fibrosis score and Fibrosis-4 score.
Conclusion: The ADAMTSL2 protein and an 8-protein soluble biomarker panel are highly associated with at-risk NASH and significant fibrosis with superior performance to standard of care fibrosis scores.
Lay summary: Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of liver disease worldwide. Diagnosing NAFLD and identifying fibrosis (scarring of the liver) currently requires a liver biopsy. Our study identified novel proteins found in blood which may identify fibrosis without the need for a liver biopsy
Technology transfer of a monitoring system to predict product concentration and purity of biopharmaceuticals in real‐time during chromatographic separation
No full textTechnological developments require the transfer to their location of application to make use of them. We describe the transfer of a real-time monitoring system for lab-scale preparative chromatography to two new sites where it will be used and developed further. Equivalent equipment was used. The capture of a biopharmaceutical model protein, human fibroblast growth factor 2 (FGF-2) was used to evaluate the system transfer. Predictive models for five quality attributes based on partial least squares regression were transferred. Six out of seven online sensors (UV/VIS, pH, conductivity, IR, RI, and MALS) showed comparable signals between the sites while one sensor (fluorescence) showed different signal profiles. A direct transfer of the models for real-time monitoring was not possible, mainly due to differences in sensor signals. Adaptation of the models was necessary. Then, among five prediction models, the prediction errors of the test run at the new sites were on average twice as high as at the training site (model-wise 0.9–5.7 times). Additionally, new prediction models for different products were trained at each new site. These allowed monitoring the critical quality attributes of two new biopharmaceutical products during their purification processes with mean relative deviations between 1% and 33%
Focal adhesion kinase inhibitor TAE226 combined with Sorafenib slows down hepatocellular carcinoma by multiple epigenetic effects
No full textBackground & Aims
Hepatocellular carcinoma (HCC) is one of the most common and lethal malignant tumours worldwide. Sorafenib (SOR), the first-line systemic treatment against advanced HCC, causes resistance as unresolved question. Recent studies highlighted the ability of focal adhesion kinase (FAK) inhibitors (FAKi) in reducing HCC growth. Therefore, we investigated the antitumor effects of three different FAKi, alone or in combination with SOR, using in vitro and in vivo models of HCC.
Methods
The effect of PND1186, PF431396, TAE226 on cell viability was compared to SOR. TAE226, emerging as the most effective FAKi, was then tested alone or in combination with SOR using 2D/3D human HCC cell line cultures and HCC xenograft murine models. The mechanisms of action were assessed by gene/protein expression and imaging approaches, combined with high-throughput methods.
Results
TAE226 emerged as the more effective FAKi to be combined with SOR against HCC. Combined TAE226 plus SOR treatment reduced HCC growth both in vitro and in vivo by affecting tumour-promoting gene expression and inducing epigenetic changes via dysregulation of the nuclear interactome of FAK. In particular, we characterize a novel nuclear functional interaction between FAK and the NuRD complex. TAE226-mediated FAK depletion and SOR-promoted MAPK down-modulation caused a decrease of the nuclear amount of HDAC1/2 with consequent increase of histone H3 lysine 27 acetylation, counteracting its trimethylation.
Conclusions
Altogether, our findings provide the first evidence that TAE226 combined with SOR efficiently reduce HCC growth in vitro and in vivo. Our data also highlight that deep analysis of FAK nuclear interactome may lead to the identification of new promising therapeutic approaches for HCC
Matrigel 3D bioprinting of contractile human skeletal muscle models recapitulating exercise and pharmacological responses
No full textA key to enhance the low translatability of preclinical drug discovery are in vitro human three-dimensional (3D) microphysiological systems (MPS). Here, we show a new method for automated engineering of 3D human skeletal muscle models in microplates and functional compound screening to address the lack of muscle wasting disease medication. To this end, we adapted our recently described 24-well plate 3D bioprinting platform with a printhead cooling system to allow microvalve-based drop-on-demand printing of cell-laden Matrigel containing primary human muscle precursor cells. Mini skeletal muscle models develop within a week exhibiting contractile, striated myofibers aligned between two attachment posts. As an in vitro exercise model, repeated high impact stimulation of contractions for 3 h by a custom-made electrical pulse stimulation (EPS) system for 24-well plates induced interleukin-6 myokine expression and Akt hypertrophy pathway activation. Furthermore, the known muscle stimulators caffeine and Tirasemtiv acutely increase EPS-induced contractile force of the models. This validated new human muscle MPS will benefit development of drugs against muscle wasting diseases. Moreover, our Matrigel 3D bioprinting platform will allow engineering of non-self-organizing complex human 3D MPS
ZNRF3 and RNF43 cooperate to safeguard metabolic liver zonation and hepatocyte proliferation.
No full textAXIN2 and LGR5 mark intestinal stem cells (ISCs) that require WNT/β-Catenin signaling for constant homeostatic proliferation. In contrast, AXIN2/LGR5+ pericentral hepatocytes show low proliferation rates despite a WNT/β-Catenin activity gradient required for metabolic liver zonation. The mechanisms restricting proliferation in AXIN2+ hepatocytes and metabolic gene expression in AXIN2+ ISCs remained elusive. We now show that restricted chromatin accessibility in ISCs prevents the expression of β-Catenin-regulated metabolic enzymes, whereas fine-tuning of WNT/β-Catenin activity by ZNRF3 and RNF43 restricts proliferation in chromatin-permissive AXIN2+ hepatocytes, while preserving metabolic function. ZNRF3 deletion promotes hepatocyte proliferation, which in turn becomes limited by RNF43 upregulation. Concomitant deletion of RNF43 in ZNRF3 mutant mice results in metabolic reprogramming of periportal hepatocytes and induces clonal expansion in a subset of hepatocytes, ultimately promoting liver tumors. Together, ZNRF3 and RNF43 cooperate to safeguard liver homeostasis by spatially and temporally restricting WNT/β-Catenin activity, balancing metabolic function and hepatocyte proliferation
Solving Complex Biologics Truncation Problems by Top-Down Mass Spectrometry
No full textSimilar to OAK 39509 (conference slides): this is the manuscript for research journal submission. It is about an analytical method developed for general biologics production. It will not disclose any info about the project, target, molecule, format, etc. It just described the studied protein is a therapeutic protein. The related projects are ATI9ATP(CD39 project) and NID9MOS(MOSAIC project). The studied candidates are TEC999, and CXH289 respectively. For some background info, Thomas Lehmeier and other project attorneys approved the content on OAK 39509 in March. There is no new content other than it's in article format
Pharmacokinetics, Metabolism, and Excretion of Licogliflozin, a Dual Inhibitor of SGLT1/2, in Rats, Dogs, and Humans
No full text1. The absorption, metabolism, and excretion (AME) of licogliflozin, a sodium-glucose co-transporters (SGLTs) 1 and 2 inhibitor, were studied in male rats, dogs, and healthy male volunteers and reported.
2. Oral absorption of licogliflozin was rapid (tmax < 1 hr) with absorption estimated at 87%, 100% and 77% in rats, dogs and humans, respectively.
3. The excretion of licogliflozin-related radioactivity was rapid and nearly complete following oral administration with total radioactivity recovery ranging from 73% in dogs, 92.5% in humans, to 100% in rats. Dose-related radioactivity was excreted in both urine and faeces with urinary excretion playing a slightly more important role in humans (~56%) than in animal species (~19-41%).
4. The elimination of licogliflozin was predominantly via metabolism with majority of the radioactivity dose (~54-74%) excreted as metabolites across species.
5. The principal biotransformation pathways involved direct glucuronidation and oxidation across all species. In humans, direct glucuronidation to M17 and M27 was the major pathway observed, accounting for ~38% of the dose in excreta while oxidative metabolism also contributed to >29% of the dose in excreta. Oxidative pathways were predominant in animal species
MAIP: A prediction platform for predicting blood-stage malaria inhibitors
No full textMalaria is a disease affecting hundreds of millions of people across the world, mainly in developing countries and especially in Sub-Saharan Africa. It is the cause of hundreds of thousands of deaths each year and there is an ever-present need to identify and develop effective new therapies to tackle the disease and overcome increasing drug resistance. Here, we extend a previous study in which a number of partners collaborated to develop a consensus in silico model that can be used to identify novel molecules that may have antimalarial properties. The performance of machine learning methods generally improves with the number of data points available for training. One practical challenge in building large training sets is that the data is often proprietary and cannot be straightforwardly integrated. Here, this was addressed by sharing QSAR models, each built on a private data set. We describe the development of an open-source software platform for creating such models, a comprehensive evaluation of methods to create a single consensus model and a web platform called MAIP available at https://www.ebi.ac.uk/chembl/maip/. MAIP is freely available for the wider community to make large-scale predictions. This project also highlights some of the practical challenges in reproducing published computational methods and the opportunities that open source software can offer to the community
Matched Targeted Therapy for Pediatric Patients with Relapsed, Refractory or High-risk Leukemias: A Report from the LEAP Consortium.
No full textDespite a remarkable increase in the genomic profiling of cancer, integration of genomic discoveries into clinical care has lagged behind. We report the feasibility of rapid identification of targetable mutations in 153 pediatric patients with relapsed/refractory or high-risk leukemias enrolled on a prospective clinical trial conducted by the LEAP Consortium. Eighteen percent of patients had a high confidence, Tier 1 or 2, recommendation. We describe clinical responses in the 14% of patients with relapsed/refractory leukemia who received the matched targeted therapy. Further, in order to inform future targeted therapy for patients, we validated variants of uncertain significance (VUS), performed ex vivo drug sensitivity testing in patient leukemia samples, and identified new combinations of targeted therapies in cell lines and patient-derived xenograft models. These data and our collaborative approach should inform the design of future precision medicine trials
Chemical Reactivity Prediction: Current Methods and Different Application Areas.
No full textThe ability to predict chemical reactivity of a molecule is highly desirable in drug discovery, both ex vivo (synthetic route planning, formulation, stability) and in vivo: metabolic reactions determine pharmacodynamics, pharmacokinetics and potential toxic effects, and early assessment of liabilities is vital to reduce attrition rates in later stages of development. Quantum mechanics offer a precise description of the interactions between electrons and orbitals in the breaking and forming of new bonds. Modern algorithms and faster computers have allowed the study of more complex systems in a punctual and accurate fashion, and answers for chemical questions around stability and reactivity can now be provided. Through machine learning, predictive models can be built out of descriptors derived from quantum mechanics and cheminformatics, even in the absence of experimental data to train on. In this article, current progress on computational reactivity prediction is reviewed: applications to problems in drug design, such as modelling of metabolism and covalent inhibition, are highlighted and unmet challenges are posed