Similar Datasets
Project description:Kinase inhibitors (KIs) represent an important class of anti-cancer drugs. Although cardiotoxicity is a serious adverse event associated with several KIs, the reasons remain poorly understood, and its prediction remains challenging. We obtain transcriptional profiles of human heart-derived primary cardiomyocyte like cell lines treated with a panel of 26 FDA-approved KIs and classify their effects on subcellular pathways and processes. Individual cardiotoxicity patient reports for these KIs, obtained from the FDA Adverse Event Reporting System, are used to compute relative risk scores. These are then combined with the cell line-derived transcriptomic datasets through elastic net regression analysis to identify a gene signature that can predict risk of cardiotoxicity. We also identify relationships between cardiotoxicity risk and structural/binding profiles of individual KIs. We conclude that acute transcriptomic changes in cell-based assays combined with drug substructures are predictive of KI-induced cardiotoxicity risk, and that they can be informative for future drug discovery.
| S-EPMC7511315 | biostudies-literature
Project description:Kinase inhibitors (KIs) represent an important class of anti-cancer drugs. Although cardiotoxicity is a serious adverse event associated with several KIs, the reasons remain poorly understood and its prediction remains challenging. Here, we perform transcriptomic profiling of human heart-derived primary cardiomyocyte cell lines treated with a panel of 26 FDA-approved KIs and classify their effects on subcellular pathways and processes. Individual cardiotoxicity patient reports for these KIs, obtained from the FDA Adverse Event Reporting System, are used to compute relative risk scores. These are then combined with cell line-derived transcriptomic datasets through elastic net regression analysis to identify a gene signature that can predict risk of cardiotoxicity. We also identify relationships between cardiotoxicity risk and structural/binding profiles of individual KIs. We conclude that acute transcriptomic changes in cell-based assays combined with drug substructures are predictive of KI-induced cardiotoxicity risk, and that they can be informative for future drug discovery.
2020-05-13 | GSE146096 | GEO
Project description:Kinase inhibitors (KIs) represent an important class of anti-cancer drugs. Although cardiotoxicity is a serious adverse event associated with several KIs, the reasons remain poorly understood and its prediction remains challenging. Here, we perform transcriptomic profiling of human heart-derived primary cardiomyocyte cell lines treated with a panel of 26 FDA-approved KIs and classify their effects on subcellular pathways and processes. Individual cardiotoxicity patient reports for these KIs, obtained from the FDA Adverse Event Reporting System, are used to compute relative risk scores. These are then combined with cell line-derived transcriptomic datasets through elastic net regression analysis to identify a gene signature that can predict risk of cardiotoxicity. We also identify relationships between cardiotoxicity risk and structural/binding profiles of individual KIs. We conclude that acute transcriptomic changes in cell-based assays combined with drug substructures are predictive of KI-induced cardiotoxicity risk, and that they can be informative for future drug discovery.
2020-05-13 | GSE146095 | GEO
Project description:Transcriptomic profiling of human cardiac cells predicts protein kinase inhibitor-associated cardiotoxicity
| PRJNA609277 | ENA
Project description:Transcriptomic profiling of human cardiac cells predicts protein kinase inhibitor-associated cardiotoxicity [Conv]
| PRJNA609282 | ENA
Project description:Transcriptomic profiling of human cardiac cells predicts protein kinase inhibitor-associated cardiotoxicity [DGE]
| PRJNA609281 | ENA
Project description:This SuperSeries is composed of the SubSeries listed below.
2016-11-02 | GSE89411 | GEO
Project description:BackgroundSunitinib, a multitargeted tyrosine-kinase inhibitor, which is approved by both US and European Commission regulatory agencies for clinical use, extends survival of patients with metastatic renal-cell carcinoma and gastrointestinal stromal tumours, but concerns have arisen about its cardiac safety. We therefore assessed the cardiovascular risk associated with sunitinib in patients with metastatic gastrointestinal stromal tumours.MethodsWe retrospectively reviewed all cardiovascular events in 75 patients with imatinib-resistant, metastatic, gastrointestinal stromal tumours who had been enrolled in a phase I/II trial investigating the efficacy of sunitinib. The composite cardiovascular endpoint was cardiac death, myocardial infarction, and congestive heart failure. We also examined sunitinib's effects on left ventricular ejection fraction (LVEF) and blood pressure. We investigated potential mechanisms of sunitinib-associated cardiac effects by studies in isolated rat cardiomyocytes and in mice.FindingsEight of 75 (11%) patients given repeating cycles of sunitinib in the phase I/II trial had a cardiovascular event, with congestive heart failure recorded in six of 75 (8%). Ten of 36 (28%) patients treated at the approved sunitinib dose had absolute LVEF reductions in ejection fraction (EF) of at least 10%, and seven of 36 (19%) had LVEF reductions of 15 EF% or more. Sunitinib induced increases in mean systolic and diastolic blood pressure, and 35 of 75 (47%) individuals developed hypertension (>150/100 mm Hg). Congestive heart failure and left ventricular dysfunction generally responded to sunitinib being withheld and institution of medical management. Sunitinib caused mitochondrial injury and cardiomyocyte apoptosis in mice and in cultured rat cardiomyocytes.InterpretationLeft ventricular dysfunction might be due, in part, to direct cardiomyocyte toxicity, exacerbated by hypertension. Patients treated with sunitinib should be closely monitored for hypertension and LVEF reduction, especially those with a history of coronary artery disease or cardiac risk factors.
| S-EPMC2643085 | biostudies-literature
Project description:Tyrosine Kinase Inhibitor Cardiotoxicity
| PRJNA352077 | ENA
Project description:Many drugs designed to inhibit kinases have their clinical utility limited by cardiotoxicity-related label warnings or prescribing restrictions. While this liability is widely recognized, designing safer kinase inhibitors (KI) requires knowledge of the causative kinase(s). Efforts to unravel the kinases have encountered pharmacology with nearly prohibitive complexity. At therapeutically relevant concentrations, KIs show promiscuity distributed across the kinome. Here, to overcome this complexity, 65 KIs with known kinome-scale polypharmacology profiles were assessed for effects on cardiomyocyte (CM) beating. Changes in human iPSC-CM beat rate and amplitude were measured using label-free cellular impedance. Correlations between beat effects and kinase inhibition profiles were mined by computation analysis (Matthews Correlation Coefficient) to identify associated kinases. Thirty kinases met criteria of having (1) pharmacological inhibition correlated with CM beat changes, (2) expression in both human-induced pluripotent stem cell-derived cardiomyocytes and adult heart tissue, and (3) effects on CM beating following single gene knockdown. A subset of these 30 kinases were selected for mechanistic follow up. Examples of kinases regulating processes spanning the excitation-contraction cascade were identified, including calcium flux (RPS6KA3, IKBKE) and action potential duration (MAP4K2). Finally, a simple model was created to predict functional cardiotoxicity whereby inactivity at three sentinel kinases (RPS6KB1, FAK, STK35) showed exceptional accuracy in vitro and translated to clinical KI safety data. For drug discovery, identifying causative kinases and introducing a predictive model should transform the ability to design safer KI medicines. For cardiovascular biology, discovering kinases previously unrecognized as influencing cardiovascular biology should stimulate investigation of underappreciated signaling pathways.
| S-EPMC5837613 | biostudies-literature