Mechanistic Systems Modeling to Improve Understanding and Prediction of Cardiotoxicity Caused by Targeted Cancer...

Area of Science:

• Oncology
• Cardiology
• Pharmacology
• Systems Biology

Background:

• Tyrosine kinase inhibitors (TKIs) are vital cancer drugs but can cause severe cardiotoxicity, including heart failure and QT prolongation.
• The precise mechanisms of TKI-induced cardiotoxicity are not fully understood due to complex signaling pathways and broad TKI targets.
• Understanding these mechanisms is crucial for patient safety and optimizing cancer therapy.

Purpose of the Study:

• To review TKI use in cancer and associated cardiotoxicities.
• To discuss potential mechanisms underlying TKI-induced cardiotoxicity.
• To highlight the potential of mechanistic models, specifically Quantitative Systems Pharmacology (QSP), for a systematic understanding of cardiotoxicity.

Main Methods:

• Review of existing literature on TKIs, cardiotoxicity, and proposed mechanisms.
• Discussion of the application of mechanistic modeling, particularly QSP, to study drug-induced toxicities.
• Proposal for integrating large-scale experimental measurements (e.g., genome-wide expression) with QSP models.

Main Results:

• TKIs are associated with significant cardiotoxic effects impacting cardiac function.
• Current mechanistic understanding of TKI cardiotoxicity is limited.
• QSP modeling, integrated with experimental data, shows promise for elucidating TKI cardiotoxicity mechanisms.

Conclusions:

• Quantitative Systems Pharmacology (QSP) modeling offers a powerful framework for systematically understanding and predicting TKI-induced cardiotoxicity.
• Integrating genome-wide expression data with QSP models is a key future strategy.
• Overcoming current challenges is essential for developing a comprehensive mechanistic understanding of TKI cardiotoxicity.