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Steltzer, S.

Publications and source records attributed to Steltzer, S..

2 recordsLinked to original sources

Gene Therapy Mediates Therapeutic Improvement in Cardiac Hypertrophy and Survival in a Murine Model of MYBPC3-Associated Cardiomyopathy

BackgroundHypertrophic cardiomyopathy (HCM) affects an estimated 600,000 people in the U.S. and is the leading cause of sudden cardiac arrest in those under 18. Loss-of-function mutations in Myosin Binding Protein C3, MYBPC3, are the most common genetic cause of HCM. The majority of MYBPC3 mutations causative for HCM result in truncations. The sarcomeric pathophysiology of the majority of HCM patients with MYBPC3 mutations appears to be due to haploinsufficiency, as the total amount of MYBPC3 protein incorporated into sarcomeres falls significantly below normal. MethodsA clear path for the treatment of haploinsufficiency is the restoration of the insufficient gene product; in this case wild-type MYBPC3. To achieve this, we engineered an AAV vector (TN-201) with superior properties for mediating cardiomyocyte-selective expression of MYBPC3 after systemic delivery. ResultsWe have demonstrated for the first time with AAV gene therapy the ability of both a mouse surrogate and TN-201, which encodes human MYBPC3 to reverse cardiac hypertrophy and systolic dysfunction and to improve diastolic dysfunction and survival in a symptomatic MYBPC3-deficient murine model of disease. Dose-ranging efficacy studies exhibited restoration of wild-type MYBPC3 protein levels and saturation of cardiac improvement at the clinically relevant dose of 3E13 vg/kg, outperforming a previously published construct. Further, we have established stable cardiac benefit for greater than one year post-injection, as well as reversal of cardiac dysfunction even in late-stage models of disease. ConclusionsOur data suggest that by restoring MYBPC3 to the sarcomere, TN-201 has the potential to slow and even reverse the course of the disease in patients with MYBPC3-associated HCM.

genetics↗

Deep Learning Predicts Patterns of Cardiotoxicity in a High-Content Screen Using Induced Pluripotent Stem Cell-Derived Cardiomyocytes

Drug-induced cardiotoxicity and hepatotoxicity are major causes of drug attrition. To decrease late-stage drug attrition, pharmaceutical and biotechnology industries need to establish biologically relevant models that use phenotypic screening to predict drug-induced toxicity. In this study, we sought to rapidly detect patterns of cardiotoxicity using high-content image analysis with deep learning and induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). We screened a library of 1280 bioactive compounds and identified those predicted to have cardiotoxic liabilities using a single-parameter score based on deep learning. Compounds with major predicted cardiotoxicity included DNA intercalators, ion channel blockers, epidermal growth factor receptor, cyclin-dependent kinase, and multi-kinase inhibitors. We also screened a diverse library of molecules with unknown targets and identified chemical frameworks with predicted cardiotoxic liabilities. By using this screening approach during target discovery and lead optimization, we can de-risk early-stage drug discovery. We show that the broad applicability of combining deep learning with iPSC technology is an effective way to interrogate cellular phenotypes and identify drugs that protect against diseased phenotypes and deleterious mutations. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=161 HEIGHT=200 SRC="FIGDIR/small/436666v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@695707org.highwire.dtl.DTLVardef@1d0980forg.highwire.dtl.DTLVardef@1af30e7org.highwire.dtl.DTLVardef@b3a312_HPS_FORMAT_FIGEXP M_FIG C_FIG CONTRIBUTION TO THE FIELDIn this article, Grafton and colleagues use induced pluripotent stem cell technology and deep learning to train a neural network capable of detecting patterns of cardiotoxicity. To identify bioactive and chemical classes that lead to cardiotoxicity, they combine the neural network with high-content screening of 2560 compounds. The methods described in this study can be used to de-risk early-stage drug development, triage hits, and identify drugs that protect against disease. This screening paradigm will serve as a useful resource for drug discovery and phenotypic interrogation of stem cells and stem cell-derived cell types.

cell biology↗