scholarly journals Transcriptomic profiling of human cardiac cells predicts protein kinase inhibitor-associated cardiotoxicity

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
J. G. Coen van Hasselt ◽  
Rayees Rahman ◽  
Jens Hansen ◽  
Alan Stern ◽  
Jaehee V. Shim ◽  
...  
Keyword(s):  
Adverse Event ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Adverse Event Reporting System ◽  
Gene Signature ◽  
Adverse Event Reporting ◽  
Cardiac Cells ◽  
Risk Scores ◽  
Patient Reports ◽  
Future Drug

Abstract 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.

scholarly journals Clinically-weighted transcriptomic signatures for protein kinase inhibitor associated cardiotoxicity

2016 ◽  
Author(s):  
JGC van Hasselt ◽  
J Hansen ◽  
Y Xiong ◽  
J Shim ◽  
A Pickard ◽  
...  
Keyword(s):  
Adverse Event ◽  
Protein Kinase ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Adverse Event Reporting System ◽  
Cardiac Contractility ◽  
Digital Gene Expression ◽  
Adverse Event Reporting ◽  
Protein Kinase Inhibitors ◽  
Risk Scores

ABSTRACTCardiotoxicity (CT) involving diminished cardiac contractility and heart failure is a major adverse event associated with otherwise efficacious protein kinase inhibitors (KIs). Here, we sought to develop clinically-weighted transcriptomic signatures to predict risk of CT and to better understand the biological processes associated with CT risk. We obtained transcriptome-wide response profiles in four human primary cardiomyocyte cell lines that were treated with 22 different KIs using mRNA sequencing with 3’ digital gene expression. The FDA Adverse Event Reporting System was used to derive relative risk scores for four types of CT for different KIs. We used elastic net regression to associate these transcriptomic profiles with KI-associated risk scores for CT subtypes to obtain clinically-weighted transcriptomic signatures, which showed good predictive properties (cross-validation R2>0.87). Our clinically-weighted transcriptomic signatures for KI-associated CT may be of relevance in early drug development for the prediction of KI-associated CT.

Comparison of Adverse Drug Reactions for Patients Treated with Tyrosine Kinase Inhibitors: Data Mining of the Public Version of the FDA Adverse Event Reporting System (AERS)

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 1698-1698
Author(s):  
Tetsuya Tanimoto ◽  
Yasuo Oshima ◽  
Koichiro Yuji ◽  
Masahiro Kami
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Odds Ratio ◽  
Kinase Inhibitors ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Drug Reactions ◽  
Suspected Drug ◽  
Event Reporting

Abstract Abstract 1698 Backgrounds: The consecutive approvals of tyrosine kinase inhibitors (TKIs) have been changing the landscape of treatment strategy for patients with chronic myeloid leukemia (CML). Currently, three TKIs are available worldwide, including imatinib (Glivec/Gleevec; Novartis Pharmaceuticals, East hanover, NJ), nilotinib (Tasigna; Novartis Pharmaceuticals) and dasatinib (Sprycel; Bristol-Myers Squibb, Princeton, NJ). Although second generation TKIs (nilotinib and dasatinib) have shown their efficacy and safety in recent clinical trials, additional data are needed for better understanding and differences in their safety profiles may be helpful when choosing a TKI. We compared the adverse drug reactions (ADRs) for patients treated with three TKIs using spontaneous adverse event reporting after approval to investigate the characteristics of safety profiles. Method: To compare adverse events characteristics among three TKIs, the case/noncase adverse events reports associated with TKIs use were retrieved from the U.S. Food and Drug Administration Adverse Event Reporting System (AERS) between 2004 and 2010. We calculated the reporting odds ratio (ROR), which is known as one of data mining algorithms for signal detection techniques of ADRs, characterized by providing a fast and cost-efficient way of detecting possible ADR signals. All events in the AERS have been coded for data entry in accordance with the standardized terminology, known as Preferred Terms, in the Medical Dictionary for Regulatory Activities. The ROR is similar to the idea of odds ratio, calculating the odds of exposure of the suspected drug in patients who had events divided by the odds of exposure of the suspected drug in those without events. The ROR -1.96 standard error greater than 1 with at least 4 ADR reports was used as a signal criterion in this study. Results: We identified 18,979 ADRs for imatinib, 5,388 ADRs for nilotinib, and 2,482 ADRs for dasatinib. The number of ADRs flagged by our signal criterion was 91 for imatinib, 82 for nilotinib, and 109 for dasatinib. Top 10 lists of ADRs with higher ROR are shown in Table for each TKI. The safety profiles were almost different among TKIs. ADRs related to skin and hepatic function were noted for imatinib, whereas ADRs related to cardiac events were prominent for nilotinib, and ADRs related to lymphocytosis, edema and effusion were noticeable for dasatinib. The different dosing requirements of dasatinib and nilotinib may be an additional factor of ADRs. Conclusions: ADRs reported in the AERS for each TKI were relatively consistent with known characteristics of ADRs reported in previous clinical trials. Our information would be supportive data for choosing a TKI for CML patients based on comorbidities and drug safety profiles. The choice of therapy in a given patient with CML may depend on age, past history and comorbidities as well as disease risk score and mutational analysis. Disclosures: Oshima: Sanofi Aventis: Employment.

Manifestations of cardiovascular toxicity associated with the approved tyrosine kinase inhibitors

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 14152-14152
Author(s):  
S. L. Verbois ◽  
H. Saber ◽  
K. A. Benson ◽  
D. E. Morse ◽  
R. Justice
Keyword(s):  
Cardiac Function ◽  
Tyrosine Kinase ◽  
Tyrosine Kinase Inhibitors ◽  
Kinase Inhibitors ◽  
Vascular Inflammation ◽  
Adverse Event Reporting System ◽  
Clinical Signs ◽  
Adverse Event Reporting ◽  
Specific Pattern ◽  
Patient Reports

14152 Background: Since 2001, 5 tyrosine kinase inhibitors (TKi’s; imatinib, erlotinib, sorafenib, sunitinib and dasatinib) have been approved for hematologic and solid tumor indications including, CML, ALL, GIST, RCC, pancreatic and NSCLC. While individual agents are designed to inhibit the TK activity of specific targets, “cross-talk” with non-target TKs (e.g., ABL, EGFR, VEGFRs, KIT, KDR, CSF1R, PDGFRs, RET, the SRC family, EPHA2, RAF, and FLT3) is extensive. The relationship between inhibition of individual kinases and the toxicity profile of each drug is unclear. Methods: Following from the observation of cardiovascular (CV) toxicity in clinical settings (pre- and post- marketing) and from the original non-clinical toxicologic evaluations, a new “class-related” review of non-clinical toxicological findings was conducted. To compare the non-clinical and clinical CV findings, the Adverse Event Reporting System (AERS) was searched for all events, excluding those of non-CV nature and those unlikely to be drug-related (e.g. hemorrhagic events were excluded from the initial analyses). Individual patient reports were not reviewed in full, therefore definitive attribution of disease related events can not be made. Results: While variable in expression, the non-clinical signs of toxicity included cardiac and vascular inflammation, cardiac degeneration and hypertrophy, decreased cardiac function (e.g. LVEF decreases), alterations in blood pressure, and QT prolongation. Clinical reports for the TKi’s have included hypo- and hypertension, conduction abnormalities and arrhythmias, cardiac hypertrophy and changes in cardiac function (LVEF and CHF). Conclusions: It is not possible at this time to relate the CV toxicities associated with the TKi’s to a specific pattern of TK inhibition. CV toxicity has been observed both clinically and non-clinically and warrants further investigation. No significant financial relationships to disclose.

Novel Adverse Events of Iloperidone: A Disproportionality Analysis in US Food and Drug Administration Adverse Event Reporting System (FAERS) Database

2019 ◽  
Vol 14 (1) ◽  
pp. 21-26 ◽  
Author(s):  
Viswam Subeesh ◽  
Eswaran Maheswari ◽  
Hemendra Singh ◽  
Thomas Elsa Beulah ◽  
Ann Mary Swaroop
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Adverse Events ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Disproportionality Analysis ◽  
Positive Signal ◽  
Data Mining Algorithms ◽  
Mining Algorithms

Background: The signal is defined as “reported information on a possible causal relationship between an adverse event and a drug, of which the relationship is unknown or incompletely documented previously”. Objective: To detect novel adverse events of iloperidone by disproportionality analysis in FDA database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs). Methodology: The US FAERS database consists of 1028 iloperidone associated Drug Event Combinations (DECs) which were reported from 2010 Q1 to 2016 Q3. We consider DECs for disproportionality analysis only if a minimum of ten reports are present in database for the given adverse event and which were not detected earlier (in clinical trials). Two data mining algorithms, namely, Reporting Odds Ratio (ROR) and Information Component (IC) were applied retrospectively in the aforementioned time period. A value of ROR-1.96SE>1 and IC- 2SD>0 were considered as the threshold for positive signal. Results: The mean age of the patients of iloperidone associated events was found to be 44years [95% CI: 36-51], nevertheless age was not mentioned in twenty-one reports. The data mining algorithms exhibited positive signal for akathisia (ROR-1.96SE=43.15, IC-2SD=2.99), dyskinesia (21.24, 3.06), peripheral oedema (6.67,1.08), priapism (425.7,9.09) and sexual dysfunction (26.6-1.5) upon analysis as those were well above the pre-set threshold. Conclusion: Iloperidone associated five potential signals were generated by data mining in the FDA AERS database. The result requires an integration of further clinical surveillance for the quantification and validation of possible risks for the adverse events reported of iloperidone.

scholarly journals Systematic analysis of safety profile for darunavir and its boosted agents using data mining in the FDA Adverse Event Reporting System database

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaojiang Tian ◽  
Yao Yao ◽  
Guanglin He ◽  
Yuntao Jia ◽  
Kejing Wang ◽  
...  
Keyword(s):  
Data Mining ◽  
Adverse Event ◽  
Reporting System ◽  
Proportional Reporting Ratio ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Reporting Odds Ratio ◽  
Systematic Analysis ◽  
Event Reporting ◽  
Exfoliative Dermatitis

AbstractThis current investigation was aimed to generate signals for adverse events (AEs) of darunavir-containing agents by data mining using the US Food and Drug Administration Adverse Event Reporting System (FAERS). All AE reports for darunavir, darunavir/ritonavir, or darunavir/cobicistat between July 2006 and December 2019 were identified. The reporting Odds Ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN) were used to detect the risk signals. A suspicious signal was generated only if the results of the three algorithms were all positive. A total of 10,756 reports were identified commonly observed in hepatobiliary, endocrine, cardiovascular, musculoskeletal, gastrointestinal, metabolic, and nutrition system. 40 suspicious signals were generated, and therein 20 signals were not included in the label. Severe high signals (i.e. progressive extraocular muscle paralysis, acute pancreatitis, exfoliative dermatitis, acquired lipodystrophy and mitochondrial toxicity) were identified. In pregnant women, umbilical cord abnormality, fetal growth restriction, low birth weight, stillbirth, premature rupture of membranes, premature birth and spontaneous abortion showed positive signals. Darunavir and its boosted agents induced AEs in various organs/tissues, and were shown to be possibly associated with multiple adverse pregnant conditions. This study highlighted some novel and severe AEs of darunavir which need to be monitored prospectively.

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