Human Cardiac Ventricular-Like Organoid Chambers and Tissue Strips From Pluripotent Stem Cells as a Two-Tiered Assay for Inotropic Responses.

Traditional drug discovery is an inefficient process. Human pluripotent stem cell-derived cardiomyocytes can potentially fill the gap between animal and clinical studies, but conventional two-dimensional cultures inadequately recapitulate the human cardiac phenotype. Here, we systematically examined the pharmacological responses of engineered human ventricular-like cardiac tissue strips (hvCTS) and organoid chambers (hvCOC) to 25 cardioactive compounds covering various drug classes. While hvCTS effectively detected negative and null inotropic effects, the sensitivity to positive inotropes was modest. We further quantified the predictive capacity of hvCTS in a blinded screening, with accuracies for negative, positive, and null inotropic effects at 100%, 86%, and 80%, respectively. Interestingly, hvCOC, with a pro-maturation milieu that yields physiologically complex parameters, displayed enhanced positive inotropy. Based on these results, we propose a two-tiered screening system for avoiding false positives and negatives. Such an approach would facilitate drug discovery by leading to better overall success.

Probing flecainide block of INa using human pluripotent stem cell-derived ventricular cardiomyocytes adapted to automated patch-clamping and 2D monolayers.

Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) are emerging tools for applications such as drug discovery and screening for pro-arrhythmogenicity and cardiotoxicity as leading causes for drug attrition. Understanding the electrophysiology (EP) of hPSC-CMs is essential but conventional manual patch-clamping is highly laborious and low-throughput. Here we adapted hPSC-CMs derived from two human embryonic stem cell (hESC) lines, HES2 and H7, for a 16-channel automated planar-recording approach for single-cell EP characterization. Automated current- and voltage-clamping, with an overall success rate of 55.0 ±â€¯11.3%, indicated that 90% of hPSC-CMs displayed ventricular-like action potential (AP) and the ventricular cardiomyocytes (VCMs) derived from the two hESC lines expressed similar levels of INa, ICaL, Ikr and If and similarly lacked Ito and IK1. These well-characterized hPSC-VCMs could also be readily adapted for automated assays of pro-arrhythmic drug screening. As an example, we showed that flecainide (FLE) induced INa blockade, leftward steady-state inactivation shift, slowed recovery from inactivation in our hPSC-VCMs. Since single-cell EP assay is insufficient to predict drug-induced reentrant arrhythmias, hPSC-VCMs were further reassembled into 2D human ventricular cardiac monolayers (hvCMLs) for multi-cellular electrophysiological assessments. Indeed, FLE significantly slowed the conduction velocity while causing AP prolongation. Our RNA-seq data suggested that cell-cell interaction enhanced the maturity of hPSC-VCMs. Taken collectively, a combinatorial approach using single-cell EP and hvCMLs is needed to comprehensively assess drug-induced arrhythmogenicity.

Machine Learning of Human Pluripotent Stem Cell-Derived Engineered Cardiac Tissue Contractility for Automated Drug Classification.

Accurately predicting cardioactive effects of new molecular entities for therapeutics remains a daunting challenge. Immense research effort has been focused toward creating new screening platforms that utilize human pluripotent stem cell (hPSC)-derived cardiomyocytes and three-dimensional engineered cardiac tissue constructs to better recapitulate human heart function and drug responses. As these new platforms become increasingly sophisticated and high throughput, the drug screens result in larger multidimensional datasets. Improved automated analysis methods must therefore be developed in parallel to fully comprehend the cellular response across a multidimensional parameter space. Here, we describe the use of machine learning to comprehensively analyze 17 functional parameters derived from force readouts of hPSC-derived ventricular cardiac tissue strips (hvCTS) electrically paced at a range of frequencies and exposed to a library of compounds. A generated metric is effective for then determining the cardioactivity of a given drug. Furthermore, we demonstrate a classification model that can automatically predict the mechanistic action of an unknown cardioactive drug.

Proarrhythmic risk of embryonic stem cell-derived cardiomyocyte transplantation in infarcted myocardium.

BACKGROUND: Cellular replacement strategies using embryonic stem cells (ESCs) and their cardiac derivatives are emerging as novel experimental therapeutic paradigms for the treatment of post-myocardial infarction (MI) left ventricular (LV) dysfunction; however, their potential proarrhythmic risk remains unclear. OBJECTIVE: The purpose of this study was to investigate the functional effect and proarrhythmic risk of ESC transplantation in a mouse model of MI. METHODS: We compared the functional effects and proarrhythmic risk of direct intramyocardial transplantation of 3 × 10(5) undifferentiated mouse ESCs (MI+ESC group, n = 33) and mouse ESC-derived cardiomyocytes (MI+ESC-CM group, n = 40) versus culture medium (MI group, n = 33) at the infarct border zone in a mouse model of acute MI. LV performance was assessed with serial cardiac magnetic resonance imaging (MRI) at 1 and 3 week(s) post-MI, and invasive LV pressure measurement was assessed (dP/dt) at 4 weeks before sacrifice for histological examination. Furthermore, electrophysiological study was also performed in another set of animals in each group (n = 24) to assess for proarrhythmias after transplantation. RESULTS: In vitro cellular electrophysiological study demonstrated that ESC-CMs exhibit arrhythmogenesis including automaticity, lengthened action potential duration, and depolarized resting membrane potential. At 4 weeks, the MI+ESC-CM group (21/40, 53%) had a higher mortality rate compared with those in the MI group (10/33, 30%, P = .08) and in the MI+ESC group (7/33, 21%, P = .012). Electrophysiological study showed a significantly higher incidence of inducible ventricular tachyarrhythmias in the MI+ESC-CM group (13/24, 54%) compared with in the MI group (6/24, 21%, P = .039) and in the MI+ESC group (5/24, 21%, P = .017). Cardiac MRI showed similar improvement in LV ejection fraction in the MI+ESC and MI+ESC-CM groups compared with in the MI group at 1 week (27.5% ± 3.8%; 30.3% ± 5.2% vs. 12.4% ± 1.4%; P < .05) and 3 weeks (29.8% ± 3.9%; 27.0% ± 4.8% vs. 10.6% ± 2.8%; P < .05) post-MI, respectively. Furthermore, invasive hemodynamic assessment at 4 weeks showed significant similar improvement in LV +dP/dt in the MI+ESC (2,644 ± 391 mmHg/s, P < .05) and MI+ESC-CM groups (2,539 ± 389 mmHg/s; P < .05) compared with in the MI group (2,042 ± 406 mmHg/s). CONCLUSIONS: Our results demonstrate that transplantation of undifferentiated ESCs and ESC-CMs provides similar improvement in cardiac function post-MI. However, transplantation of ESC-CMs is associated with a significantly higher prevalence of inducible ventricular tachyarrhythmias and early mortality than transplantations with ESCs.