Hypertrophic cardiomyopathy (HCM) is a pathological disorder predominantly due to mutations in sarcomeric components. Germline mutations in BRAF cause a developmental syndrome called cardio-facio-cutaneous syndrome (CFCS), in which 40% of patients also develop HCM. Since the role of the RAS/MAPK pathway in HCM is still unclear, we generated a human induced pluripotent stem cell model for CFCS from three patients with activating BRAF T599R or Q257R mutations. In order to examine hiPSC-derived cell-type specific phenotypes and cellular interactions underpinning HCM, we generated a method to purify cardiomyocytes and non-cardiomyocytes simultaneously by cell sorting based on SIRPα and CD90 expression. Purified BRAF-mutant SIRPα+/CD90- cells were >95% cardiomyocytes, displayed cellular hypertrophy with pro-hypertrophic gene expression, and dysregulation of the RAS/MAPK pathway. BRAF-mutant cardiomyocytes also displayed intrinsic calcium handling defects, including increased calcium transient irregularity and increased stored calcium within the sarcoplasmic reticulum. In addition, purified BRAF-mutant SIRPα-/CD90+ cells, which were fibroblast-like, displayed activation of the RAS/MAPK pathway and exhibited a pro-fibrotic phenotype. Cross-culture studies revealed that BRAF-mutant fibroblast-like cells critically modulate cardiomyocyte hypertrophy through TGFβ paracrine signaling, as TGFβ inhibition prevented cardiomyocyte hypertrophy induced by BRAF-mutant fibroblast-like cells. Additionally, inhibition of RAS/MAPK signaling was capable of rescuing BRAF-mutant cardiomyocyte hypertrophy and cardiomyocyte-intrinsic calcium handling abnormalities. Thus, we show for the first time that cell autonomous and non-autonomous defects underlie RASopathy-associated HCM. As fibroblast activation has been documented previously in sarcomeric HCM, our findings suggest that cardiac fibroblasts may contribute to pathologic hypertrophy in addition to causing fibrosis in primary forms of HCM. TGFβ inhibition may be a useful therapeutic option for patients with HCM due to RASopathies or other etiologies.

Creating a cDNA library for deep mRNA sequencing (mRNAseq) is generally done by random priming, creating multiple sequencing fragments along each transcript. A 3'-end-focused library approach cannot detect differential splicing, but has potentially higher throughput at a lower cost, along with the ability to improve quantification by using transcript molecule counting with unique molecular identifiers (UMI) that correct PCR bias. Here, we compare an implementation of such a 3'-digital gene expression (3'-DGE) approach with "conventional" random primed mRNAseq. Given our particular datasets on cultured human cardiomyocyte cell lines, we find that, while conventional mRNAseq detects ~15% more genes and needs ~500,000 fewer reads per sample for equivalent statistical power, the resulting differentially expressed genes, biological conclusions, and gene signatures are highly concordant between two techniques. We also find good quantitative agreement at the level of individual genes between two techniques for both read counts and fold changes between given conditions. We conclude that, for high-throughput applications, the potential cost savings associated with 3'-DGE approach are likely a reasonable tradeoff for modest reduction in sensitivity and inability to observe alternative splicing, and should enable many larger scale studies focusing on not only differential expression analysis, but also quantitative transcriptome profiling.

This paper is the second of a series of three reviews published in this issue resulting from the University of California Davis Cardiovascular Symposium 2014: Systems approach to understanding cardiac excitation-contraction coupling and arrhythmias: Na(+) channel and Na(+) transport. The goal of the symposium was to bring together experts in the field to discuss points of consensus and controversy on the topic of sodium in the heart. The present review focuses on Na(+) channel function and regulation, Na(+) channel structure and function, and Na(+) channel trafficking, sequestration and complexing.

This white paper presents principles for validating proarrhythmia risk prediction models for regulatory use as discussed at the In Silico Breakout Session of a Cardiac Safety Research Consortium/Health and Environmental Sciences Institute/US Food and Drug Administration-sponsored Think Tank Meeting on May 22, 2018. The meeting was convened to evaluate the progress in the development of a new cardiac safety paradigm, the Comprehensive in Vitro Proarrhythmia Assay (CiPA). The opinions regarding these principles reflect the collective views of those who participated in the discussion of this topic both at and after the breakout session. Although primarily discussed in the context of in silico models, these principles describe the interface between experimental input and model-based interpretation and are intended to be general enough to be applied to other types of nonclinical models for proarrhythmia assessment. This document was developed with the intention of providing a foundation for more consistency and harmonization in developing and validating different models for proarrhythmia risk prediction using the example of the CiPA paradigm.

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.