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Novel Screening Method Identifies PI3Kα, mTOR, and IGF1R as Key Kinases Regulating Cardiomyocyte Survival
BACKGROUND: Small molecule kinase inhibitors (KIs) are a class of agents currently used for treatment of various cancers. Unfortunately, treatment of cancer patients with some of the KIs is associated with cardiotoxicity, and there is an unmet need for methods to predict their cardiotoxicity. Here,...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6898841/ https://www.ncbi.nlm.nih.gov/pubmed/31617439 http://dx.doi.org/10.1161/JAHA.119.013018 |
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author | Elmadani, Manar Khan, Suleiman Tenhunen, Olli Magga, Johanna Aittokallio, Tero Wennerberg, Krister Kerkelä, Risto |
author_facet | Elmadani, Manar Khan, Suleiman Tenhunen, Olli Magga, Johanna Aittokallio, Tero Wennerberg, Krister Kerkelä, Risto |
author_sort | Elmadani, Manar |
collection | PubMed |
description | BACKGROUND: Small molecule kinase inhibitors (KIs) are a class of agents currently used for treatment of various cancers. Unfortunately, treatment of cancer patients with some of the KIs is associated with cardiotoxicity, and there is an unmet need for methods to predict their cardiotoxicity. Here, we utilized a novel computational method to identify protein kinases crucial for cardiomyocyte viability. METHODS AND RESULTS: One hundred forty KIs were screened for their toxicity in cultured neonatal cardiomyocytes. The kinase targets of KIs were determined based on integrated data from binding assays. The key kinases mediating the toxicity of KIs to cardiomyocytes were identified by using a novel machine learning method for target deconvolution that combines the information from the toxicity screen and from the kinase profiling assays. The top kinases identified by the model were phosphoinositide 3‐kinase catalytic subunit alpha, mammalian target of rapamycin, and insulin‐like growth factor 1 receptor. Knockdown of the individual kinases in cardiomyocytes confirmed their role in regulating cardiomyocyte viability. CONCLUSIONS: Combining the data from analysis of KI toxicity on cardiomyocytes and KI target profiling provides a novel method to predict cardiomyocyte toxicity of KIs. |
format | Online Article Text |
id | pubmed-6898841 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68988412019-12-16 Novel Screening Method Identifies PI3Kα, mTOR, and IGF1R as Key Kinases Regulating Cardiomyocyte Survival Elmadani, Manar Khan, Suleiman Tenhunen, Olli Magga, Johanna Aittokallio, Tero Wennerberg, Krister Kerkelä, Risto J Am Heart Assoc Original Research BACKGROUND: Small molecule kinase inhibitors (KIs) are a class of agents currently used for treatment of various cancers. Unfortunately, treatment of cancer patients with some of the KIs is associated with cardiotoxicity, and there is an unmet need for methods to predict their cardiotoxicity. Here, we utilized a novel computational method to identify protein kinases crucial for cardiomyocyte viability. METHODS AND RESULTS: One hundred forty KIs were screened for their toxicity in cultured neonatal cardiomyocytes. The kinase targets of KIs were determined based on integrated data from binding assays. The key kinases mediating the toxicity of KIs to cardiomyocytes were identified by using a novel machine learning method for target deconvolution that combines the information from the toxicity screen and from the kinase profiling assays. The top kinases identified by the model were phosphoinositide 3‐kinase catalytic subunit alpha, mammalian target of rapamycin, and insulin‐like growth factor 1 receptor. Knockdown of the individual kinases in cardiomyocytes confirmed their role in regulating cardiomyocyte viability. CONCLUSIONS: Combining the data from analysis of KI toxicity on cardiomyocytes and KI target profiling provides a novel method to predict cardiomyocyte toxicity of KIs. John Wiley and Sons Inc. 2019-10-16 /pmc/articles/PMC6898841/ /pubmed/31617439 http://dx.doi.org/10.1161/JAHA.119.013018 Text en © 2019 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Research Elmadani, Manar Khan, Suleiman Tenhunen, Olli Magga, Johanna Aittokallio, Tero Wennerberg, Krister Kerkelä, Risto Novel Screening Method Identifies PI3Kα, mTOR, and IGF1R as Key Kinases Regulating Cardiomyocyte Survival |
title | Novel Screening Method Identifies PI3Kα, mTOR, and IGF1R as Key Kinases Regulating Cardiomyocyte Survival |
title_full | Novel Screening Method Identifies PI3Kα, mTOR, and IGF1R as Key Kinases Regulating Cardiomyocyte Survival |
title_fullStr | Novel Screening Method Identifies PI3Kα, mTOR, and IGF1R as Key Kinases Regulating Cardiomyocyte Survival |
title_full_unstemmed | Novel Screening Method Identifies PI3Kα, mTOR, and IGF1R as Key Kinases Regulating Cardiomyocyte Survival |
title_short | Novel Screening Method Identifies PI3Kα, mTOR, and IGF1R as Key Kinases Regulating Cardiomyocyte Survival |
title_sort | novel screening method identifies pi3kα, mtor, and igf1r as key kinases regulating cardiomyocyte survival |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6898841/ https://www.ncbi.nlm.nih.gov/pubmed/31617439 http://dx.doi.org/10.1161/JAHA.119.013018 |
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