使用因果推理评估体内心脏毒性机制到体外模型的可翻译性。

IF 2.9 3区 医学 Q2 Medicine
Ahmed E Enayetallah, Dinesh Puppala, Daniel Ziemek, James E Fischer, Sheila Kantesaria, Mathew T Pletcher
{"title":"使用因果推理评估体内心脏毒性机制到体外模型的可翻译性。","authors":"Ahmed E Enayetallah,&nbsp;Dinesh Puppala,&nbsp;Daniel Ziemek,&nbsp;James E Fischer,&nbsp;Sheila Kantesaria,&nbsp;Mathew T Pletcher","doi":"10.1186/2050-6511-14-46","DOIUrl":null,"url":null,"abstract":"<p><p>Drug-induced cardiac toxicity has been implicated in 31% of drug withdrawals in the USA. The fact that the risk for cardiac-related adverse events goes undetected in preclinical studies for so many drugs underscores the need for better, more predictive in vitro safety screens to be deployed early in the drug discovery process. Unfortunately, many questions remain about the ability to accurately translate findings from simple cellular systems to the mechanisms that drive toxicity in the complex in vivo environment. In this study, we analyzed translatability of cardiotoxic effects for a diverse set of drugs from rodents to two different cell systems (rat heart tissue-derived cells (H9C2) and primary rat cardiomyocytes (RCM)) based on their transcriptional response. To unravel the altered pathway, we applied a novel computational systems biology approach, the Causal Reasoning Engine (CRE), to infer upstream molecular events causing the observed gene expression changes. By cross-referencing the cardiotoxicity annotations with the pathway analysis, we found evidence of mechanistic convergence towards common molecular mechanisms regardless of the cardiotoxic phenotype. We also experimentally verified two specific molecular hypotheses that translated well from in vivo to in vitro (Kruppel-like factor 4, KLF4 and Transforming growth factor beta 1, TGFB1) supporting the validity of the predictions of the computational pathway analysis. In conclusion, this work demonstrates the use of a novel systems biology approach to predict mechanisms of toxicity such as KLF4 and TGFB1 that translate from in vivo to in vitro. We also show that more complex in vitro models such as primary rat cardiomyocytes may not offer any advantage over simpler models such as immortalized H9C2 cells in terms of translatability to in vivo effects if we consider the right endpoints for the model. Further assessment and validation of the generated molecular hypotheses would greatly enhance our ability to design predictive in vitro cardiotoxicity assays. </p>","PeriodicalId":48846,"journal":{"name":"BMC Pharmacology & Toxicology","volume":"14 ","pages":"46"},"PeriodicalIF":2.9000,"publicationDate":"2013-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/2050-6511-14-46","citationCount":"2","resultStr":"{\"title\":\"Assessing the translatability of in vivo cardiotoxicity mechanisms to in vitro models using causal reasoning.\",\"authors\":\"Ahmed E Enayetallah,&nbsp;Dinesh Puppala,&nbsp;Daniel Ziemek,&nbsp;James E Fischer,&nbsp;Sheila Kantesaria,&nbsp;Mathew T Pletcher\",\"doi\":\"10.1186/2050-6511-14-46\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Drug-induced cardiac toxicity has been implicated in 31% of drug withdrawals in the USA. The fact that the risk for cardiac-related adverse events goes undetected in preclinical studies for so many drugs underscores the need for better, more predictive in vitro safety screens to be deployed early in the drug discovery process. Unfortunately, many questions remain about the ability to accurately translate findings from simple cellular systems to the mechanisms that drive toxicity in the complex in vivo environment. In this study, we analyzed translatability of cardiotoxic effects for a diverse set of drugs from rodents to two different cell systems (rat heart tissue-derived cells (H9C2) and primary rat cardiomyocytes (RCM)) based on their transcriptional response. To unravel the altered pathway, we applied a novel computational systems biology approach, the Causal Reasoning Engine (CRE), to infer upstream molecular events causing the observed gene expression changes. By cross-referencing the cardiotoxicity annotations with the pathway analysis, we found evidence of mechanistic convergence towards common molecular mechanisms regardless of the cardiotoxic phenotype. We also experimentally verified two specific molecular hypotheses that translated well from in vivo to in vitro (Kruppel-like factor 4, KLF4 and Transforming growth factor beta 1, TGFB1) supporting the validity of the predictions of the computational pathway analysis. In conclusion, this work demonstrates the use of a novel systems biology approach to predict mechanisms of toxicity such as KLF4 and TGFB1 that translate from in vivo to in vitro. We also show that more complex in vitro models such as primary rat cardiomyocytes may not offer any advantage over simpler models such as immortalized H9C2 cells in terms of translatability to in vivo effects if we consider the right endpoints for the model. Further assessment and validation of the generated molecular hypotheses would greatly enhance our ability to design predictive in vitro cardiotoxicity assays. </p>\",\"PeriodicalId\":48846,\"journal\":{\"name\":\"BMC Pharmacology & Toxicology\",\"volume\":\"14 \",\"pages\":\"46\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2013-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1186/2050-6511-14-46\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Pharmacology & Toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/2050-6511-14-46\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Pharmacology & Toxicology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/2050-6511-14-46","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 2

摘要

在美国,31%的药物停药与药物引起的心脏毒性有关。在许多药物的临床前研究中,心脏相关不良事件的风险未被发现,这一事实强调了在药物发现过程的早期部署更好、更具预测性的体外安全性筛查的必要性。不幸的是,关于将简单细胞系统的发现准确地转化为复杂体内环境中驱动毒性的机制的能力,仍然存在许多问题。在这项研究中,我们分析了多种药物对两种不同细胞系统(大鼠心脏组织来源细胞(H9C2)和原代大鼠心肌细胞(RCM))的心脏毒性作用的可翻译性,基于它们的转录反应。为了揭示改变的途径,我们应用了一种新的计算系统生物学方法,因果推理引擎(CRE),来推断导致观察到的基因表达变化的上游分子事件。通过交叉引用心脏毒性注释和通路分析,我们发现了与心脏毒性表型无关的共同分子机制趋同的机制证据。我们还通过实验验证了两个特定的分子假设(Kruppel-like factor 4, KLF4和转化生长因子β 1, TGFB1),这些假设从体内到体外都翻译得很好,支持了计算途径分析预测的有效性。总之,这项工作证明了使用一种新的系统生物学方法来预测毒性机制,如KLF4和TGFB1,从体内到体外转化。我们还表明,如果我们考虑模型的正确终点,更复杂的体外模型(如原代大鼠心肌细胞)在体内效应的可转译性方面可能不会比更简单的模型(如永生化H9C2细胞)提供任何优势。进一步评估和验证所产生的分子假设将大大提高我们设计体外预测心脏毒性试验的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Assessing the translatability of in vivo cardiotoxicity mechanisms to in vitro models using causal reasoning.

Assessing the translatability of in vivo cardiotoxicity mechanisms to in vitro models using causal reasoning.

Assessing the translatability of in vivo cardiotoxicity mechanisms to in vitro models using causal reasoning.

Assessing the translatability of in vivo cardiotoxicity mechanisms to in vitro models using causal reasoning.

Drug-induced cardiac toxicity has been implicated in 31% of drug withdrawals in the USA. The fact that the risk for cardiac-related adverse events goes undetected in preclinical studies for so many drugs underscores the need for better, more predictive in vitro safety screens to be deployed early in the drug discovery process. Unfortunately, many questions remain about the ability to accurately translate findings from simple cellular systems to the mechanisms that drive toxicity in the complex in vivo environment. In this study, we analyzed translatability of cardiotoxic effects for a diverse set of drugs from rodents to two different cell systems (rat heart tissue-derived cells (H9C2) and primary rat cardiomyocytes (RCM)) based on their transcriptional response. To unravel the altered pathway, we applied a novel computational systems biology approach, the Causal Reasoning Engine (CRE), to infer upstream molecular events causing the observed gene expression changes. By cross-referencing the cardiotoxicity annotations with the pathway analysis, we found evidence of mechanistic convergence towards common molecular mechanisms regardless of the cardiotoxic phenotype. We also experimentally verified two specific molecular hypotheses that translated well from in vivo to in vitro (Kruppel-like factor 4, KLF4 and Transforming growth factor beta 1, TGFB1) supporting the validity of the predictions of the computational pathway analysis. In conclusion, this work demonstrates the use of a novel systems biology approach to predict mechanisms of toxicity such as KLF4 and TGFB1 that translate from in vivo to in vitro. We also show that more complex in vitro models such as primary rat cardiomyocytes may not offer any advantage over simpler models such as immortalized H9C2 cells in terms of translatability to in vivo effects if we consider the right endpoints for the model. Further assessment and validation of the generated molecular hypotheses would greatly enhance our ability to design predictive in vitro cardiotoxicity assays.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
BMC Pharmacology & Toxicology
BMC Pharmacology & Toxicology PHARMACOLOGY & PHARMACY-TOXICOLOGY
CiteScore
4.40
自引率
0.00%
发文量
0
审稿时长
12 weeks
期刊介绍: BMC Pharmacology and Toxicology is an open access, peer-reviewed journal that considers articles on all aspects of chemically defined therapeutic and toxic agents. The journal welcomes submissions from all fields of experimental and clinical pharmacology including clinical trials and toxicology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信