ArticleJournal of pharmacokinetics and pharmacodynamics2018
Systems pharmacological analysis of mitochondrial cardiotoxicity induced by selected tyrosine kinase inhibitors.
Article in Journal of pharmacokinetics and pharmacodynamics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- Mitochondrial Dysfunction in Cardiotoxicity Induced by BCR-ABL1 Tyrosine Kinase Inhibitors -Underlying Mechanisms, Detection, Potential Therapies.Cardiovascular toxicology · 2023Review
- Cardiotoxicity of Selected Vascular Endothelial Growth Factor Receptor Tyrosine Kinase Inhibitors in Patients with Renal Cell Carcinoma.Biomedicines · 2023Review
- Precision Cardio-Oncology: Use of Mechanistic Pharmacokinetic and Pharmacodynamic Modeling to Predict Cardiotoxicities of Anti-Cancer Drugs.Frontiers in oncology · 2021Review
- Induction of autophagy has protective roles in imatinib-induced cardiotoxicity.Toxicology reports · 2021Article
- Chronic Treatment with Multi-Kinase Inhibitors Causes Differential Toxicities on Skeletal and Cardiac Muscles.Cancers · 2019Article
- Cancer Therapy-Related Cardiac Dysfunction: An Overview for the Clinician.Clinical Medicine Insights. Cardiology · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tyrosine kinase inhibitors (TKIs) are targeted therapies rapidly becoming favored over conventional cytotoxic chemotherapeutics. Our study investigates two FDA approved TKIs, DASATINIB; indicated for IMATINIB-refractory chronic myeloid leukemia, and SORAFENIB; indicated for hepatocellular carcinoma and advanced renal cell carcinoma. Limited but crucial evidence suggests that these agents can have cardiotoxic side effects ranging from hypertension to heart failure. A greater understanding of the underlying mechanisms of this cardiotoxicity are needed as concerns grow and the capacity to anticipate them is lacking. The objective of this study was to explore the mitochondrial-mediated cardiotoxic mechanisms of the two selected TKIs. This was achieved experimentally using immortalized human cardiomyocytes, AC16 cells, to investigate dose- and time-dependent cell killing, along with measurements of temporal changes in key signaling proteins involved in the intrinsic apoptotic and autophagy pathways upon exposure to these agents. Quantitative systems pharmacology (QSP) models were developed to capture the toxicological response in AC16 cells using protein dynamic data. The developed QSP models captured well all the various trends in protein signaling and cellular responses with good precision on the parameter estimates, and were successfully qualified using external data sets. An interplay between the apoptotic and autophagic pathways was identified to play a major role in determining toxicity associated with the investigated TKIs. The established modeling platform showed utility in elucidating the mechanisms of cardiotoxicity of SORAFENIB and DASATINIB. It may be useful for other small molecule targeted therapies demonstrating cardiac toxicities, and may aid in informing alternate dosing strategies to alleviate cardiotoxicity associated with these therapies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.