Novel Screening Method Identifies PI3Kα, mTOR, and IGF1R as Key Kinases Regulating Cardiomyocyte Survival

Manar Elmadani1, Suleiman Khan2, Olli Tenhunen3

  • 1Research Unit of Biomedicine Department of Pharmacology and Toxicology University of Oulu Finland.

Insights

Predicting cancer drug cardiotoxicity is crucial. This study identifies key protein kinases affecting heart cell survival, offering a new computational method to forecast potential harm from kinase inhibitors.

Area of Science:

  • Biochemistry
  • Pharmacology
  • Computational Biology

Background:

  • Small molecule kinase inhibitors (KIs) are vital cancer therapeutics.
  • Some KIs cause cardiotoxicity, necessitating predictive methods.
  • Identifying kinases impacting cardiomyocyte viability is a key challenge.

Purpose of the Study:

  • To develop a novel computational method for identifying protein kinases critical to cardiomyocyte survival.
  • To predict the cardiotoxicity of kinase inhibitors.

Main Methods:

  • Screening 140 KIs for toxicity in cultured neonatal cardiomyocytes.
  • Determining KI kinase targets using integrated binding assay data.
  • Applying a machine learning model for target deconvolution, combining toxicity and kinase profiling data.

Main Results:

  • The computational model identified key kinases mediating KI cardiotoxicity.
  • Top identified kinases include phosphoinositide 3-kinase catalytic subunit alpha, mammalian target of rapamycin, and insulin-like growth factor 1 receptor.
  • Experimental knockdown of these kinases confirmed their role in cardiomyocyte viability.

Conclusions:

  • A novel computational approach integrating KI toxicity and target profiling can predict cardiotoxicity.
  • This method aids in identifying potentially cardiotoxic kinase inhibitors early in development.