Genome-wide expression patterns in physiological cardiac hypertrophy

Placental DNA methylation changes in detection of tetralogy of Fallot

OBJECTIVES

To determine whether the methylation level of cytosine nucleotides in placental DNA can be used to predict tetralogy of Fallot (TOF) and provide insights into the developmental mechanism of this condition.

METHODS

Tissue sections were obtained from formalin-fixed paraffin-embedded specimens of placental tissue obtained at birth from eight cases with non-chromosomal, non-syndromic TOF and 10 unaffected newborns. The Illumina Infinium HumanMethylation450 BeadChip assay was used to measure cytosine ('CpG' or 'cg') methylation levels at loci throughout the placental genome. Differential methylation was assessed by comparing the β-values (a measure of the extent of cytosine methylation) for individual CpG loci in fetuses with TOF vs in controls. The most discriminating CpG sites were determined based on a preset cut-off of ≥ 2.0-fold change in the methylation level. The predictive accuracy of CpG loci with significant methylation changes for TOF was determined by the area under the receiver-operating-characteristics curve (AUC). A false-discovery-rate (FDR) P-value < 0.05 was used to define a statistically significant difference in the methylation level. Ingenuity Pathway Analysis (IPA) (Qiagen) was used to identify gene pathways that were significantly overexpressed, and thus altered, in TOF cases compared with controls.

RESULTS

We found a total of 165 significantly differentially methylated CpG loci in TOF cases compared with controls, in 165 separate genes. These biomarkers demonstrated from fair to excellent individual predictive accuracy for TOF detection, with AUCs ≥ 0.75 (FDR P-value < 0.001 for all). The following CpG loci (gene) had the highest predictive accuracy: cg05273049 (ARHGAP22; AUC = 1.00; 95% CI, 1.00-1.00), cg02540011 (CDK5; AUC = 0.96; 95% CI, 0.87-1.00), cg08404201 (TRIM27; AUC = 0.95; 95% CI, 0.84-1.00) and cg00687252 (IER3; AUC = 0.95; 95% CI, 0.84-1.00). IPA revealed over-representation (dysregulation) of 14 gene pathways involved in normal cardiac development, including cardiomyocyte differentiation via bone morphogenetic protein receptors, cardiac hypertrophy signaling and role of nuclear factor of activated T cells in cardiac hypertrophy. Cardiac hypertrophy is an important feature of TOF.

CONCLUSIONS

Analysis of placental DNA cytosine methylation changes yielded accurate markers for TOF detection and provided mechanistic information on TOF development. Our work appears to confirm the central role of epigenetic changes and of the placenta in the development of TOF. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Understanding Key Mechanisms of Exercise-Induced Cardiac Protection to Mitigate Disease: Current Knowledge and Emerging Concepts

The benefits of exercise on the heart are well recognized, and clinical studies have demonstrated that exercise is an intervention that can improve cardiac function in heart failure patients. This has led to significant research into understanding the key mechanisms responsible for exercise-induced cardiac protection. Here, we summarize molecular mechanisms that regulate exercise-induced cardiac myocyte growth and proliferation. We discuss in detail the effects of exercise on other cardiac cells, organelles, and systems that have received less or little attention and require further investigation. This includes cardiac excitation and contraction, mitochondrial adaptations, cellular stress responses to promote survival (heat shock response, ubiquitin-proteasome system, autophagy-lysosomal system, endoplasmic reticulum unfolded protein response, DNA damage response), extracellular matrix, inflammatory response, and organ-to-organ crosstalk. We summarize therapeutic strategies targeting known regulators of exercise-induced protection and the challenges translating findings from bench to bedside. We conclude that technological advancements that allow for in-depth profiling of the genome, transcriptome, proteome and metabolome, combined with animal and human studies, provide new opportunities for comprehensively defining the signaling and regulatory aspects of cell/organelle functions that underpin the protective properties of exercise. This is likely to lead to the identification of novel biomarkers and therapeutic targets for heart disease.

Comparative proteomic analysis of mouse models of pathological and physiological cardiac hypertrophy, with selection of biomarkers of pathological hypertrophy by integrative Proteogenomics

To determine fundamental characteristics of pathological cardiac hypertrophy, protein expression profiles in two widely accepted models of cardiac hypertrophy (swimming-trained mouse for physiological hypertrophy and pressure-overload-induced mouse for pathological hypertrophy) were compared using a label-free quantitative proteomics approach. Among 3955 proteins (19,235 peptides, false-discovery rate < 0.01) identified in these models, 486 were differentially expressed with a log2 fold difference ≥ 0.58, or were detected in only one hypertrophy model (each protein from 4 technical replicates, p < .05). Analysis of gene ontology biological processes and KEGG pathways identified cellular processes enriched in one or both hypertrophy models. Processes unique to pathological hypertrophy were compared with processes previously identified in cardiac-hypertrophy models. Individual proteins with differential expression in processes unique to pathological hypertrophy were further confirmed using the results of previous targeted functional analysis studies. Using a proteogenomic approach combining transcriptomic and proteomic analyses, similar patterns of differential expression were observed for 23 proteins and corresponding genes associated with pathological hypertrophy. A total of 11 proteins were selected as early-stage pathological-hypertrophy biomarker candidates, and the results of western blotting for five of these proteins in independent samples confirmed the patterns of differential expression in mouse models of pathological and physiological cardiac hypertrophy.

An 'Omics' Perspective on Cardiomyopathies and Heart Failure

Pathological enlargement of the heart, represented by hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM), occurs in response to many genetic and non-genetic factors. The clinical course of cardiac hypertrophy is remarkably variable, ranging from lifelong absence of symptoms to rapidly declining heart function and sudden cardiac death (SCD). Unbiased omics studies have begun to provide a glimpse into the molecular framework underpinning altered mechanotransduction, mitochondrial energetics, oxidative stress, and extracellular matrix in the heart undergoing physiological and pathological hypertrophy. Omics analyses indicate that post-transcriptional regulation of gene expression plays an overriding role in the normal and diseased heart. Studies to date highlight a need for more effective bioinformatics to better integrate patient omics data with their comprehensive clinical histories.

Investigating core genetic-and-epigenetic cell cycle networks for stemness and carcinogenic mechanisms, and cancer drug design using big database mining and genome-wide next-generation sequencing data

Recent studies have demonstrated that cell cycle plays a central role in development and carcinogenesis. Thus, the use of big databases and genome-wide high-throughput data to unravel the genetic and epigenetic mechanisms underlying cell cycle progression in stem cells and cancer cells is a matter of considerable interest.

Real genetic-and-epigenetic cell cycle networks (GECNs) of embryonic stem cells (ESCs) and HeLa cancer cells were constructed by applying system modeling, system identification, and big database mining to genome-wide next-generation sequencing data. Real GECNs were then reduced to core GECNs of HeLa cells and ESCs by applying principal genome-wide network projection. In this study, we investigated potential carcinogenic and stemness mechanisms for systems cancer drug design by identifying common core and specific GECNs between HeLa cells and ESCs. Integrating drug database information with the specific GECNs of HeLa cells could lead to identification of multiple drugs for cervical cancer treatment with minimal side-effects on the genes in the common core. We found that dysregulation of miR-29C, miR-34A, miR-98, and miR-215; and methylation of ANKRD1, ARID5B, CDCA2, PIF1, STAMBPL1, TROAP, ZNF165, and HIST1H2AJ in HeLa cells could result in cell proliferation and anti-apoptosis through NFκB, TGF-β, and PI3K pathways. We also identified 3 drugs, methotrexate, quercetin, and mimosine, which repressed the activated cell cycle genes, ARID5B, STK17B, and CCL2, in HeLa cells with minimal side-effects.

Gene network-based analysis identifies two potential subtypes of small intestinal neuroendocrine tumors

BACKGROUND

Tumor transcriptomes contain information of critical value to understanding the different capacities of a cell at both a physiological and pathological level. In terms of clinical relevance, they provide information regarding the cellular "toolbox" e.g., pathways associated with malignancy and metastasis or drug dependency. Exploration of this resource can therefore be leveraged as a translational tool to better manage and assess neoplastic behavior. The availability of public genome-wide expression datasets, provide an opportunity to reassess neuroendocrine tumors at a more fundamental level. We hypothesized that stringent analysis of expression profiles as well as regulatory networks of the neoplastic cell would provide novel information that facilitates further delineation of the genomic basis of small intestinal neuroendocrine tumors.

RESULTS

We re-analyzed two publically available small intestinal tumor transcriptomes using stringent quality control parameters and network-based approaches and validated expression of core secretory regulatory elements e.g., CPE, PCSK1, secretogranins, including genes involved in depolarization e.g., SCN3A, as well as transcription factors associated with neurodevelopment (NKX2-2, NeuroD1, INSM1) and glucose homeostasis (APLP1). The candidate metastasis-associated transcription factor, ST18, was highly expressed (>14-fold, p < 0.004). Genes previously associated with neoplasia, CEBPA and SDHD, were decreased in expression (-1.5 - -2, p < 0.02). Genomic interrogation indicated that intestinal tumors may consist of two different subtypes, serotonin-producing neoplasms and serotonin/substance P/tachykinin lesions. QPCR validation in an independent dataset (n = 13 neuroendocrine tumors), confirmed up-regulated expression of 87% of genes (13/15).

CONCLUSIONS

An integrated cellular transcriptomic analysis of small intestinal neuroendocrine tumors identified that they are regulated at a developmental level, have key activation of hypoxic pathways (a known regulator of malignant stem cell phenotypes) as well as activation of genes involved in apoptosis and proliferation. Further refinement of these analyses by RNAseq studies of large-scale databases will enable definition of individual master regulators and facilitate the development of novel tissue and blood-based tools to better understand diagnose and treat tumors.

Gene Network and Proteomic Analyses of Cardiac Responses to Pathological and Physiological Stress

Background—

The molecular mechanisms underlying similarities and differences between physiological and pathological left ventricular hypertrophy (LVH) are of intense interest. Most previous work involved targeted analysis of individual signaling pathways or screening of transcriptomic profiles. We developed a network biology approach using genomic and proteomic data to study the molecular patterns that distinguish pathological and physiological LVH.

Methods and Results—

A network-based analysis using graph theory methods was undertaken on 127 genome-wide expression arrays of in vivo murine LVH. This revealed phenotype-specific pathological and physiological gene coexpression networks. Despite >1650 common genes in the 2 networks, network structure is significantly different. This is largely because of rewiring of genes that are differentially coexpressed in the 2 networks; this novel concept of differential wiring was further validated experimentally. Functional analysis of the rewired network revealed several distinct cellular pathways and gene sets. Deeper exploration was undertaken by targeted proteomic analysis of mitochondrial, myofilament, and extracellular subproteomes in pathological LVH. A notable finding was that mRNA–protein correlation was greater at the cellular pathway level than for individual loci.

Conclusions—

This first combined gene network and proteomic analysis of LVH reveals novel insights into the integrated pathomechanisms that distinguish pathological versus physiological phenotypes. In particular, we identify differential gene wiring as a major distinguishing feature of these phenotypes. This approach provides a platform for the investigation of potentially novel pathways in LVH and offers a freely accessible protocol ( http://sites.google.com/site/cardionetworks ) for similar analyses in other cardiovascular diseases.

Nrf2 deficiency prevents reductive stress-induced hypertrophic cardiomyopathy

AIMS

Mutant protein aggregation (PA) cardiomyopathy (MPAC) is characterized by reductive stress (RS), PA (of chaperones and cytoskeletal components), and ventricular dysfunction in transgenic mice expressing human mutant CryAB (hmCryAB). Sustained activation of nuclear erythroid-2 like factor-2 (Nrf2) causes RS, which contributes to proteotoxic cardiac disease. The goals of this pre-clinical study were to (i) investigate whether disrupting Nrf2-antioxidant signalling prevents RS and rescues redox homeostasis in hearts expressing the mutant chaperone and (ii) elucidate mechanisms that could delay proteotoxic cardiac disease.

METHODS AND RESULTS

Non-transgenic (NTG), transgenic (TG) with MPAC and MPAC-TG:Nrf2-deficient (Nrf2-def) mice were used in this study. The effects of Nrf2 diminution (Nrf2±) on RS mediated MPAC in TG mice were assessed at 6-7 and 10 months of age. The diminution of Nrf2 prevented RS and prolonged the survival of TG mice (∼50 weeks) by an additional 20-25 weeks. The TG:Nrf2-def mice did not exhibit cardiac hypertrophy at even 60 weeks, while the MPAC-TG mice developed pathological hypertrophy and heart failure starting at 24-28 weeks of age. Aggregation of cardiac proteins was significantly reduced in TG:Nrf2-def when compared with TG mice at 7 months. Preventing RS and maintaining redox homeostasis in the TG:Nrf2-def mice ameliorated PA, leading to decreased ubiquitination of proteins.

CONCLUSION

Nrf2 deficiency rescues redox homeostasis, which reduces aggregation of mutant proteins, thereby delaying the proteotoxic pathological cardiac remodelling caused by RS and toxic protein aggregates.

EGFR/TGFα and TGFβ/CTGF Signaling in Neuroendocrine Neoplasia: Theoretical Therapeutic Targets

Neuroendocrine neoplasms (NENs) are a heterogeneous family of malignancies whose proliferation is partially dependent on growth factors secreted by the microenvironment and the tumor itself. Growth factors which were demonstrated to be important in experimental models of NENs include EGF (epidermal growth factor), TGF (transforming growth factor) α, TGFβ and CTGF (connective tissue growth factor). EGF and TGFα bind to the EGF receptor to stimulate an intact RAS/RAF/MAPK pathway, leading to the transcription of genes associated with cell proliferation, invasion and metastasis. Theoretically, TGFα stimulation can be inhibited at several points of the MAPK pathway, but success is limited to NEN models and is not evident in the clinical setting. TGFβ1 stimulates TGFβ receptors (TGFβRI and TGFβRII) resulting in inhibition of neuroendocrine cell growth through SMAD-mediated activation of the growth inhibitor P21(WAF1/CIP1). Although some NENs are inhibited by TGFβ1, paradoxical growth is seen in experimental models of gastric and small intestinal (SI) NENs. Therapeutic targeting of TGFβ1 in NENs is therefore complicated by uncertainty of the effect of TGFβ1 secretion on the direction of proliferative regulation. CTGF expression is associated with more malignant clinical phenotypes in a variety of cancers, including NENs. CTGF promotes growth in gastric and SI-NEN models, and is implicated as a mediator of local and distant fibrosis caused by NENs of enterochromaffin cell origin. CTGF inhibitors are available, but their anti-proliferative effect has not been tested in NENs. In summary, growth factors are essential for NEN proliferation, and although interventions targeting these proteins are effective in experimental models, only limited clinical efficacy has been identified.

Proteomics: from single molecules to biological pathways

The conventional reductionist approach to cardiovascular research investigates individual candidate factors or linear signalling pathways but ignores more complex interactions in biological systems. The advent of molecular profiling technologies that focus on a global characterization of whole complements allows an exploration of the interconnectivity of pathways during pathophysiologically relevant processes, but has brought about the issue of statistical analysis and data integration. Proteins identified by differential expression as well as those in protein–protein interaction networks identified through experiments and through computational modelling techniques can be used as an initial starting point for functional analyses. In combination with other ‘-omics’ technologies, such as transcriptomics and metabolomics, proteomics explores different aspects of disease, and the different pillars of observations facilitate the data integration in disease-specific networks. Ultimately, a systems biology approach may advance our understanding of cardiovascular disease processes at a ‘biological pathway’ instead of a ‘single molecule’ level and accelerate progress towards disease-modifying interventions.

Functional and topological properties in hepatocellular carcinoma transcriptome

Hepatocellular carcinoma (HCC) is a leading cause of global cancer mortality. However, little is known about the precise molecular mechanisms involved in tumor formation and pathogenesis. The primary goal of this study was to elucidate genome-wide molecular networks involved in development of HCC with multiple etiologies by exploring high quality microarray data. We undertook a comparative network analysis across 264 human microarray profiles monitoring transcript changes in healthy liver, liver cirrhosis, and HCC with viral and alcoholic etiologies. Gene co-expression profiling was used to derive a consensus gene relevance network of HCC progression that consisted of 798 genes and 2,012 links. The HCC interactome was further confirmed to be phenotype-specific and non-random. Additionally, we confirmed that co-expressed genes are more likely to share biological function, but not sub-cellular localization. Analysis of individual HCC genes revealed that they are topologically central in a human protein-protein interaction network. We used quantitative RT-PCR in a cohort of normal liver tissue (n = 8), hepatitis C virus (HCV)-induced chronic liver disease (n = 9), and HCC (n = 7) to validate co-expressions of several well-connected genes, namely ASPM, CDKN3, NEK2, RACGAP1, and TOP2A. We show that HCC is a heterogeneous disorder, underpinned by complex cross talk between immune response, cell cycle, and mRNA translation pathways. Our work provides a systems-wide resource for deeper understanding of molecular mechanisms in HCC progression and may be used further to define novel targets for efficient treatment or diagnosis of this disease.

Functional Genomics Assistant (FUGA): a toolbox for the analysis of complex biological networks

Background

Cellular constituents such as proteins, DNA, and RNA form a complex web of interactions that regulate biochemical homeostasis and determine the dynamic cellular response to external stimuli. It follows that detailed understanding of these patterns is critical for the assessment of fundamental processes in cell biology and pathology. Representation and analysis of cellular constituents through network principles is a promising and popular analytical avenue towards a deeper understanding of molecular mechanisms in a system-wide context.

Findings

We present Functional Genomics Assistant (FUGA) - an extensible and portable MATLAB toolbox for the inference of biological relationships, graph topology analysis, random network simulation, network clustering, and functional enrichment statistics. In contrast to conventional differential expression analysis of individual genes, FUGA offers a framework for the study of system-wide properties of biological networks and highlights putative molecular targets using concepts of systems biology.

Conclusion

FUGA offers a simple and customizable framework for network analysis in a variety of systems biology applications. It is freely available for individual or academic use at http://code.google.com/p/fuga.

In cardiac myoblasts, cellular redox regulates FosB and Fra-1 through multiple cis-regulatory modules

Depending on the dose, norepineprine (NE) can induce hypertrophy or apoptosis in cardiac myocytes. Reactive oxygen species (ROS) play a key role in mediating both responses, but the mechanisms are not understood as yet. Earlier we demonstrated that the two pathways are marked by the differential induction of FosB and Fra-1, two members of the AP-1 family of transcription factors. We now demonstrate that NE induces both fosB and fra-1 at the transcriptional level. Catalase and MnTMPyP (a superoxide dismutase mimetic) suppress their activation by NE. In contrast, in cells without NE treatment, MnTMPyP upregulates their expression, whereas catalase inhibits it. Thus, regulation of fosB and fra-1 by ROS is context specific. To delineate the mechanisms, the 1493- and 2689-bp upstream regions of the fosB and fra-1 genes were cloned into the luciferase vector and assayed for transient expression. Catalase and MnTMPyP regulated both promoters the same as their endogenous counterparts in NE-treated and untreated cells. Deletion, mutation, and ChIP analyses suggested that multiple cis-elements including SP-1, CEBP, and AP-1 in the fosB promoter make discrete contributions to mediating the redox response. A gel mobility-shift-based oxidation-reduction assay suggested that, whereas SP-1 is a direct sensor of cellular redox state, CEBP is not. This study suggests that multiple redox signals generate gene-specific modules affecting their expression.

The clinical implications and biologic relevance of neurofilament expression in gastroenteropancreatic neuroendocrine neoplasms

BACKGROUND

Although gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) exhibit widely divergent behavior, limited biologic information (apart from Ki-67) is available to characterize malignancy. Therefore, the identification of alternative biomarkers is a key unmet need. Given the role of internexin alpha (INA) in neuronal development, the authors assessed its function in neuroendocrine cell systems and the clinical implications of its expression as a GEP-NEN biomarker.

METHODS

Functional assays were undertaken to investigate the mechanistic role of INA in the pancreatic BON cell line. Expression levels of INA were investigated in 50 pancreatic NENs (43 primaries, 7 metastases), 43 small intestinal NENs (25 primaries, 18 metastases), normal pancreas (n = 10), small intestinal mucosa (n = 16), normal enterochromaffin (EC) cells (n = 9), mouse xenografts (n = 4) and NEN cell lines (n = 6) using quantitative polymerase chain reaction, Western blot, and immunostaining analyses.

RESULTS

In BON cells, decreased levels of INA messenger RNA and protein were associated with the inhibition of both proliferation and mitogen-activated protein kinase (MAPK) signaling. INA was not expressed in normal neuroendocrine cells but was overexpressed (from 2-fold to 42-fold) in NEN cell lines and murine xenografts. In pancreatic NENs, INA was overexpressed compared with pancreatic adenocarcinomas and normal pancreas (27-fold [P = .0001], and 9-fold [P = .02], respectively). INA transcripts were correlated positively with Ki-67 (correlation coefficient [r] = 0.5; P < .0001) and chromogranin A (r = 0.59; P < .0001). INA distinguished between primary tumors and metastases (P = .02), and its expression was correlated with tumor size, infiltration, and grade (P < .05).

CONCLUSIONS

INA is a novel NEN biomarker, and its expression was associated with MAPK signaling and proliferation. In clinical samples, elevated INA was correlated with Ki-67 and identified malignancy. INA may provide additional biologic information relevant to delineation of both pancreatic NEN tumor phenotypes and clinical behavior.

Panhistone deacetylase inhibitors inhibit proinflammatory signaling pathways to ameliorate interleukin-18-induced cardiac hypertrophy

We investigated the genome-wide consequences of pan-histone deacetylase inhibitors (HDACIs) trichostatin A (TSA) and m-carboxycinnamic acid bis-hydroxamide (CBHA) in the hearts of BALB/c mice eliciting hypertrophy in response to interleukin-18 (IL-18). Both TSA and CBHA profoundly altered cardiac chromatin structure that occurred concomitantly with normalization of IL-18-induced gene expression and amelioration of cardiac hypertrophy. The hearts of mice exposed to IL-18+/-TSA or CBHA elicited distinct gene expression profiles. Of 184 genes that were differentially regulated by IL-18 and TSA, 33 were regulated in an opposite manner. The hearts of mice treated with IL-18 and/or CBHA elicited 147 differentially expressed genes (DEGs), a third of which were oppositely regulated by IL-18 and CBHA. Ingenuity Pathways and Kyoto Encyclopedia of Genes and Genomes analyses of DEGs showed that IL-18 impinged on TNF-α- and IFNγ-specific gene networks relegated to controlling immunity and inflammation, cardiac metabolism and energetics, and cell proliferation and apoptosis. These TNF-α- and IFNγ-specific gene networks, extensively connected with PI3K, MAPK, and NF-κB signaling pathways, were oppositely regulated by IL-18 and pan-HDACIs. Evidently, both TSA and CBHA caused a two- to fourfold induction of phosphatase and tensin homolog expression to counteract IL-18-induced proinflammatory signaling and cardiac hypertrophy.

In search of new therapeutic targets and strategies for heart failure: recent advances in basic science

Chronic heart failure continues to impose a substantial health-care burden, despite recent treatment advances. The key pathophysiological process that ultimately leads to chronic heart failure is cardiac remodelling in response to chronic disease stresses. Here, we review recent advances in our understanding of molecular and cellular mechanisms that play a part in the complex remodelling process, with a focus on key molecules and pathways that might be suitable targets for therapeutic manipulation. Such pathways include those that regulate cardiac myocyte hypertrophy, calcium homoeostasis, energetics, and cell survival, and processes that take place outside the cardiac myocyte--eg, in the myocardial vasculature and extracellular matrix. We also discuss major gaps in our current understanding, take a critical look at conventional approaches to target discovery that have been used to date, and consider new investigational avenues that might accelerate clinically relevant discovery.