Network Reconstruction and Systems Analysis of Cardiac Myocyte Hypertrophy Signaling

Ryall, Karen A.; Holland, D. O.; Delaney, Kyle A.; Kraeutler, Matthew J.; Parker, Audrey J.; Saucerman, Jeffrey J.

doi:10.1074/jbc.m112.382937

Cited by 92 publications

(144 citation statements)

References 37 publications

(43 reference statements)

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“…This result is significant given the high level of cross talk in the hypertrophy signaling network and lack of differential regulation between pathways in commonly measured hypertrophy readouts such as fetal gene expression [107]. Follow-up experiments identified positive regulation of Bax mRNA abundance by CTGF, negative regulation of myocyte elongation by CITED4, and increased cell size with CITED4 overexpression.…”

Section: Discussionmentioning

confidence: 81%

“…Previous work has established a role for these 15 agonists in hypertrophy [13], [107], but the contributions of these pathways to distinct hypertrophic features and relative dominance among the agonists to specific phenotypic outputs was less characterized. We previously compared changes in shape and sarcomere organization between four of the hypertrophic agonists, PE, Iso, IGF1, and TNFα [37].…”

Section: Discussionmentioning

confidence: 99%

“…While many commonly measured markers of hypertrophy such as cell size and fetal gene expression are not substantially differentially regulated between hypertrophy pathways [107], measuring outputs related to shape, fibrosis, cell death, inflammation, and proliferation revealed distinct phenotypic signatures among the hypertrophy pathways. Correlation coefficients among the shape features further reveal differential regulation of cell area, elongation, and form factor.…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, the pathways governing hypertrophy are highly connected with much cross-talk between pathways [107]. It is unclear how all of the parts of such an interconnected network function together as a coordinated system that can induce distinct, context-dependent hypertrophy features.…”

Section: Introductionmentioning

confidence: 99%

“…It is unclear how all of the parts of such an interconnected network function together as a coordinated system that can induce distinct, context-dependent hypertrophy features. Commonly measured markers of hypertrophy such as cell size and fetal gene expression are not markedly differentially regulated between receptor pathways in the signaling network [107].…”

Section: Introductionmentioning

confidence: 99%

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Systems Analysis of the Cardiac Myocyte Hypertrophy Signaling Network

Ryall¹

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Section: Discussionmentioning

confidence: 81%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Systems Analysis of the Cardiac Myocyte Hypertrophy Signaling Network

Ryall¹

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Network model‐based screen for FDA‐approved drugs affecting cardiac fibrosis

Zeigler

Chandrabhatla

Christiansen

et al. 2021

CPT Pharmacom & Syst Pharma

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Cardiac fibrosis is a significant component of pathological heart remodeling, yet it is not directly targeted by existing drugs. Systems pharmacology approaches have the potential to provide mechanistic frameworks with which to predict and understand how drugs modulate biological systems. Here, we combine network modeling of the fibroblast signaling network with 36 unique drug-target interactions from DrugBank to predict drugs that modulate fibroblast phenotype and fibrosis. Galunisertib was predicted to decrease collagen and αsmooth muscle actin expression, which we validated in human cardiac fibroblasts. In vivo fibrosis data from the literature validated predictions for 10 drugs. Further, the model was used to identify network mechanisms by which these drugs work. Arsenic trioxide was predicted to induce fibrosis by AP1-driven TGFβ expression and MMP2-driven TGFβ activation. Entresto (valsartan/sacubitril) was predicted to suppress fibrosis by valsartan suppression of ERK signaling and sacubitril enhancement of PKG activity, both of which decreased Smad3 activity. Overall, this study provides a framework for integrating drugtarget mechanisms with logic-based network models, which can drive further studies both in cardiac fibrosis and other conditions.

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Systems medicine: evolution of systems biology from bench to bedside

Wang

Maron

Loscalzo

2015

WIREs Mechanisms of Disease

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High-throughput experimental techniques for generating genomes, transcriptomes, proteomes, metabolomes, and interactomes have provided unprecedented opportunities to interrogate biological systems and human diseases on a global level. Systems biology integrates the mass of heterogeneous high-throughput data and predictive computational modeling to understand biological functions as system-level properties. Most human diseases are biological states caused by multiple components of perturbed pathways and regulatory networks rather than individual failing components. Systems biology not only facilitates basic biological research, but also provides new avenues through which to understand human diseases, identify diagnostic biomarkers, and develop disease treatments. At the same time, systems biology seeks to assist in drug discovery, drug optimization, drug combinations, and drug repositioning by investigating the molecular mechanisms of action of drugs at a system’s level. Indeed, systems biology is evolving to systems medicine as a new discipline that aims to offer new approaches for addressing the diagnosis and treatment of major human diseases uniquely, effectively, and with personalized precision.

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Network Reconstruction and Systems Analysis of Cardiac Myocyte Hypertrophy Signaling

Cited by 92 publications

References 37 publications

Systems Analysis of the Cardiac Myocyte Hypertrophy Signaling Network

Systems Analysis of the Cardiac Myocyte Hypertrophy Signaling Network

Network model‐based screen for FDA‐approved drugs affecting cardiac fibrosis

Systems medicine: evolution of systems biology from bench to bedside

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