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Automated Contraction Analysis of Human Engineered Heart Tissue for Cardiac Drug Safety Screening
Published on: April 15, 2017
Virtual drug screen reveals context-dependent inhibition of cardiomyocyte hypertrophy
Taylor G Eggertsen1,2, Jeffrey J Saucerman1,2
1Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.
Insights
This study used a network model to identify FDA-approved drugs that suppress pathological cardiomyocyte hypertrophy, a key factor in heart failure. Midostaurin was identified as a potential antihypertrophic drug, with its efficacy context-dependent.
Area of Science:
- Cardiovascular Biology
- Pharmacology
- Computational Biology
Background:
- Pathological cardiomyocyte hypertrophy is a significant contributor to heart failure, yet therapeutic options are limited.
- Targeting cardiomyocyte hypertrophy is crucial for managing cardiac remodeling and preventing heart failure progression.
Purpose of the Study:
- To virtually screen FDA-approved drugs for their ability to modulate cardiomyocyte hypertrophy using a network model.
- To identify novel therapeutic agents for pathological cardiac hypertrophy and heart failure.
Main Methods:
- A logic-based differential equation model of cardiomyocyte signaling was employed for drug screening.
- Model predictions were validated against existing literature data and new experimental results.
- Network analysis was used to investigate drug mechanisms and polypharmacology.
Main Results:
- The model successfully predicted drug effects in 60 out of 70 independent experiments, identifying 38 hypertrophy inhibitors.
- Midostaurin was identified as a potential antihypertrophic drug, with context-dependent efficacy (inhibiting TGFβ-induced but not NE-induced hypertrophy).
- Network analysis revealed roles for PI3K and RAS pathways, and predicted synergistic effects of brigatinib and irbesartan.
Conclusions:
- A validated computational platform for drug efficacy assessment in cardiomyocyte hypertrophy was established.
- Midostaurin is highlighted as a promising candidate for further investigation as an antihypertrophic therapy.
- The study underscores the context-dependent nature of drug efficacy in treating cardiac hypertrophy.
Background And Purpose:
Pathological cardiomyocyte hypertrophy is a response to cardiac stress that typically leads to heart failure. Despite being a primary contributor to pathological cardiac remodelling, the therapeutic space that targets hypertrophy is limited. Here, we apply a network model to virtually screen for FDA-approved drugs that induce or suppress cardiomyocyte hypertrophy.
Experimental Approach:
A logic-based differential equation model of cardiomyocyte signalling was used to predict drugs that modulate hypertrophy. These predictions were validated against curated experiments from the prior literature. The actions of midostaurin were validated in new experiments using TGFβ- and noradrenaline (NE)-induced hypertrophy in neonatal rat cardiomyocytes.
Key Results:
Model predictions were validated in 60 out of 70 independent experiments from the literature and identify 38 inhibitors of hypertrophy. We additionally predict that the efficacy of drugs that inhibit cardiomyocyte hypertrophy is often context dependent. We predicted that midostaurin inhibits cardiomyocyte hypertrophy induced by TGFβ, but not noradrenaline, exhibiting context dependence. We further validated this prediction by cellular experiments. Network analysis predicted critical roles for the PI3K and RAS pathways in the activity of celecoxib and midostaurin, respectively. We further investigated the polypharmacology and combinatorial pharmacology of drugs. Brigatinib and irbesartan in combination were predicted to synergistically inhibit cardiomyocyte hypertrophy.
Conclusion And Implications:
This study provides a well-validated platform for investigating the efficacy of drugs on cardiomyocyte hypertrophy and identifies midostaurin for consideration as an antihypertrophic drug.
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