scholarly journals Co-expression of calcium and hERG potassium channels reduces the incidence of proarrhythmic events

2020 ◽  
Author(s):  
Sara Ballouz ◽  
Melissa M Mangala ◽  
Matthew D Perry ◽  
Stewart Heitmann ◽  
Jesse A Gillis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Electrical Activity ◽  
Ion Channel ◽  
In Silico ◽  
Large Scale ◽  
Heart Function ◽  
Surrogate Marker ◽  
Heart Tissue ◽  
Delayed Rectifier ◽  
Cardiac Electrical Activity

Abstract Aims Cardiac electrical activity is extraordinarily robust. However, when it goes wrong it can have fatal consequences. Electrical activity in the heart is controlled by the carefully orchestrated activity of more than a dozen different ion conductances. While there is considerable variability in cardiac ion channel expression levels between individuals, studies in rodents have indicated that there are modules of ion channels whose expression co-vary. The aim of this study was to investigate whether meta-analytic co-expression analysis of large-scale gene expression datasets could identify modules of co-expressed cardiac ion channel genes in human hearts that are of functional importance. Methods and results Meta-analysis of 3653 public human RNA-seq datasets identified a strong correlation between expression of CACNA1C (L-type calcium current, ICaL) and KCNH2 (rapid delayed rectifier K+ current, IKr), which was also observed in human adult heart tissue samples. In silico modelling suggested that co-expression of CACNA1C and KCNH2 would limit the variability in action potential duration seen with variations in expression of ion channel genes and reduce susceptibility to early afterdepolarizations, a surrogate marker for proarrhythmia. We also found that levels of KCNH2 and CACNA1C expression are correlated in human-induced pluripotent stem cell-derived cardiac myocytes and the levels of CACNA1C and KCNH2 expression were inversely correlated with the magnitude of changes in repolarization duration following inhibition of IKr. Conclusion Meta-analytic approaches of multiple independent human gene expression datasets can be used to identify gene modules that are important for regulating heart function. Specifically, we have verified that there is co-expression of CACNA1C and KCNH2 ion channel genes in human heart tissue, and in silico analyses suggest that CACNA1C–KCNH2 co-expression increases the robustness of cardiac electrical activity.

scholarly journals Co-expression of calcium channels and delayed rectifier potassium channels protects the heart from proarrhythmic events

2019 ◽  
Author(s):  
Sara Ballouz ◽  
Melissa M Mangala ◽  
Matthew D Perry ◽  
Stewart Heitmann ◽  
Jesse A Gillis ◽  
...  
Keyword(s):  
Ion Channel ◽  
Cardiac Electrophysiology ◽  
Meta Analysis ◽  
Surrogate Marker ◽  
Induced Pluripotent Stem Cell ◽  
Delayed Rectifier ◽  
Cardiac Electrical Activity ◽  
Channel Expression ◽  
Induced Pluripotent ◽  
Electrical Signaling

AbstractCardiac electrical activity is controlled by the carefully orchestrated activity of more than a dozen different ion conductances. Yet, there is considerable variability in cardiac ion channel expression levels both within and between subjects. In this study we tested the hypothesis that variations in ion channel expression between individuals are not random but rather there are modules of co-expressed genes and that these modules make electrical signaling in the heart more robust.Meta-analysis of 3653 public RNA-Seq datasets identified a strong correlation between expression of CACNA1C (L-type calcium current, ICaL) and KCNH2 (rapid delayed rectifier K+ current, IKr), which was verified in mRNA extracted from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM). In silico modeling, validated with functional measurements in hiPSC-CM, indicates that the co-expression of CACNA1C and KCNH2 limits the variability in action potential duration and reduces susceptibility to early afterdepolarizations, a surrogate marker for pro-arrhythmia.Impact StatementCoexpressed levels of potassium and calcium ion channel genes in the heart encode more robust cardiac electrophysiology and provide insights into genetic basis of arrhythmic risk

scholarly journals Effect of Carvacrol, TRP Channels Modulator, on Cardiac Electrical Activity

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Mantė Almanaitytė ◽  
Jonas Jurevičius ◽  
Regina Mačianskienė
Keyword(s):  
Electrical Activity ◽  
Trp Channels ◽  
Heart Function ◽  
Atrioventricular Node ◽  
Rabbit Heart ◽  
Inhibitory Effect ◽  
Resting Membrane Potential ◽  
Cardiac Electrical Activity ◽  
Epicardial Pacing ◽  
High Concentrations

Despite the wide application of carvacrol (CAR) in medicines, dietary supplements, and foods, there is still insufficient electrophysiological data on the mechanisms of action of CAR, particularly with regard to heart function. Therefore, in this study, we attempted to elucidate whether CAR, whose inhibitory effect on both cardiac and vascular TRPM7 and L-type Ca2+ currents has been demonstrated previously, could modify cardiac electrical activity. We used a combination of optical mapping and microelectrode techniques to track the action potentials (APs) and the spread of electrical activity in a Langendorff-perfused rabbit heart model during atrial/endo/epicardial pacing. Simultaneously, ECG recordings were acquired. Because human trials on CAR are still lacking, we tested the action of CAR on human ventricular preparations obtained from explanted hearts. Activation time (AT), AP duration (APD), and conduction velocity maps were constructed. We demonstrated that at a low concentration (10 μM) of CAR, only marginal changes in the AP parameters were observed. At higher concentrations (≥100 μM), a decrease in AP upstroke velocity (dV/dtmax), suggesting inhibition of Na+ current, and APD (at 50 and 90% repolarization) was detected; also slowing in the spread of electrical signals via the atrioventricular node was observed, suggesting impaired functioning of Ca2+ channels. In addition, a decrease in the T-wave amplitude was seen on the ECG, suggesting an impaired repolarization process. Nevertheless, those changes occurred without a significant impact on the resting membrane potential and were reversible. We suggest that CAR might play a role in modulating cardiac electrical activity at high concentrations.

scholarly journals Computational drug repositioning of bortezomib to reverse metastatic effect ofGALNT14in lung cancer

2018 ◽  
Author(s):  
Ok-Seon Kwon ◽  
Haeseung Lee ◽  
Hyeon-Joon Kong ◽  
Ji Eun Park ◽  
Wooin Lee ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
In Silico ◽  
Large Scale ◽  
Cancer Metastasis ◽  
Drug Repositioning ◽  
Expression Patterns ◽  
Lung Cancer Metastasis

AbstractAlthough many molecular targets for cancer therapy have been discovered, they often show poor druggability, which is a major obstacle to develop targeted drugs. As an alternative route to drug discovery, we adopted anin silicodrug repositioning (in silicoDR) approach based on large-scale gene expression signatures, with the goal of identifying inhibitors of lung cancer metastasis. Our analysis of clinicogenomic data identified GALNT14, an enzyme involved in O-linked N-acetyl galactosamine glycosylation, as a putative driver of lung cancer metastasis leading to poor survival. To overcome the poor druggability of GALNT14, we leveraged Connectivity Map approach, anin silicoscreening for drugs that are likely to revert the metastatic expression patterns. It leads to identification of bortezomib (BTZ) as a potent metastatic inhibitor, bypassing direct inhibition of poorly druggable target, GALNT14. The anti-metastatic effect of BTZ was verifiedin vitroandin vivo. Notably, both BTZ treatment andGALNT14knockdown attenuated TGFβ-mediated gene expression and suppressed TGFβ-dependent metastatic genes, suggesting that BTZ acts by modulating TGFβ signalingTaken together, these results demonstrate that ourin silicoDR approach is a viable strategy to identify a candidate drug for undruggable targets, and to uncover its underlying mechanisms.

scholarly journals In silico analysis suggests disruption of interactions between HAMP from hepatocytes and SLC40A1 from macrophages in hepatocellular carcinoma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Liang Hu ◽  
Chao Wu
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
In Silico ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
In Silico Analysis ◽  
Hepatocyte Proliferation ◽  
Upregulated Genes ◽  
Silico Analysis

Abstract Background Identification of factors associated with proliferation in the hepatocellular carcinoma (HCC) microenvironment aids in understanding the mechanisms of disease progression and provides druggable targets. Gene expression profiles of individual cells in HCC and para-carcinoma tissues can be effectively obtained using the single-cell RNA sequencing (scRNA-Seq) technique. Here, we aimed to identify proliferative hepatocytes from HCC and para-carcinoma tissues, detect differentially expressed genes between the two types of proliferative hepatocytes, and investigate their potential roles in aberrant proliferation. Results Two respective gene signatures for proliferative cells and hepatocytes were established and used to identify proliferative hepatocytes from HCC and para-carcinoma tissues based on scRNA-Seq data. Gene expression profiles between the two types of proliferative hepatocytes were compared. Overall, 40 genes were upregulated in proliferative hepatocytes from para-carcinoma tissue, whereas no upregulated genes were detected in those from HCC tissue. Twelve of the genes, including HAMP, were specifically expressed in the liver tissue. Based on previous reports, we found that HAMP modulates cell proliferation through interaction with its receptor SLC40A1. Comprehensive analysis of cells in HCC and para-carcinoma tissues revealed that: (1) HAMP is specifically expressed in hepatocytes and significantly downregulated in malignant hepatocytes; (2) a subset of macrophages expressing SLC40A1 and genes reacting to various infections is present in para-carcinoma but not in HCC tissue. We independently validated the findings with scRNA-Seq and large-scale tissue bulk RNA-Seq/microarray analyses. Conclusion HAMP was significantly downregulated in malignant hepatocytes. In addition, a subset of macrophages expressing SLC40A1 and genes reacting to various infections was absent in HCC tissue. These findings support the involvement of HAMP-SLC40A1 signaling in aberrant hepatocyte proliferation in the HCC microenvironment. The collective data from our in silico analysis provide novel insights into the mechanisms underlying HCC progression and require further validation with wet laboratory experiments.

scholarly journals A simple in silico approach to generate gene-expression profiles from subsets of cancer genomics data

BioTechniques ◽  
2019 ◽  
Vol 67 (4) ◽  
pp. 172-176 ◽  
Author(s):  
Mohammed Khurshed ◽  
Remco J Molenaar ◽  
Cornelis JF van Noorden
Keyword(s):  
Gene Expression ◽  
In Silico ◽  
Large Scale ◽  
Cancer Genomics ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Large Datasets ◽  
Web Interface ◽  
Simple Method ◽  
Clinical Interest

In biomedical research, large-scale profiling of gene expression has become routine and offers a valuable means to evaluate changes in onset and progression of diseases, in particular cancer. An overwhelming amount of cancer genomics data has become publicly available, and the complexity of these data makes it a challenge to perform in silico data exploration, integration and analysis, in particular for scientists lacking a background in computational programming or informatics. Many web interface tools make these large datasets accessible but are limited to process large datasets. To accelerate the translation of genomic data into new insights, we provide a simple method to explore and select data from cancer genomic datasets to generate gene-expression profiles of subsets that are of specific genetic, biological or clinical interest.

The Role of Computer Modeling in Electrocardiography

1990 ◽  
Vol 29 (04) ◽  
pp. 282-288 ◽  
Author(s):  
A. van Oosterom
Keyword(s):  
Electrical Activity ◽  
Computer Modeling ◽  
Body Surface ◽  
Electrical Current ◽  
The Body ◽  
Volume Conductor ◽  
Current Generator ◽  
Cardiac Electrical Activity ◽  
Source Models

AbstractThis paper introduces some levels at which the computer has been incorporated in the research into the basis of electrocardiography. The emphasis lies on the modeling of the heart as an electrical current generator and of the properties of the body as a volume conductor, both playing a major role in the shaping of the electrocardiographic waveforms recorded at the body surface. It is claimed that the Forward-Problem of electrocardiography is no longer a problem. Several source models of cardiac electrical activity are considered, one of which can be directly interpreted in terms of the underlying electrophysiology (the depolarization sequence of the ventricles). The importance of using tailored rather than textbook geometry in inverse procedures is stressed.

Molecular Epidemiology and Biomarkers in Etiologic Cancer Research: The New in Light of the Old

2020 ◽  
Author(s):  
Lungwani Muungo
Keyword(s):  
Gene Expression ◽  
Cancer Research ◽  
Molecular Epidemiology ◽  
Exposure Assessment ◽  
Large Scale ◽  
First Generation ◽  
Cancer Epidemiology ◽  
Policy Changes ◽  
The Past ◽  
New Generation

The purpose of this review is to evaluate progress inmolecular epidemiology over the past 24 years in canceretiology and prevention to draw lessons for futureresearch incorporating the new generation of biomarkers.Molecular epidemiology was introduced inthe study of cancer in the early 1980s, with theexpectation that it would help overcome some majorlimitations of epidemiology and facilitate cancerprevention. The expectation was that biomarkerswould improve exposure assessment, document earlychanges preceding disease, and identify subgroupsin the population with greater susceptibility to cancer,thereby increasing the ability of epidemiologic studiesto identify causes and elucidate mechanisms incarcinogenesis. The first generation of biomarkers hasindeed contributed to our understanding of riskandsusceptibility related largely to genotoxic carcinogens.Consequently, interventions and policy changes havebeen mounted to reduce riskfrom several importantenvironmental carcinogens. Several new and promisingbiomarkers are now becoming available for epidemiologicstudies, thanks to the development of highthroughputtechnologies and theoretical advances inbiology. These include toxicogenomics, alterations ingene methylation and gene expression, proteomics, andmetabonomics, which allow large-scale studies, includingdiscovery-oriented as well as hypothesis-testinginvestigations. However, most of these newer biomarkershave not been adequately validated, and theirrole in the causal paradigm is not clear. There is a needfor their systematic validation using principles andcriteria established over the past several decades inmolecular cancer epidemiology.

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