Risk prediction and modeling of cancer therapy related cardiotoxicity

The emergence of an ever-growing number of cancer therapies had a significant impact on cancer survival rates and converted a terminal illness into a chronic disease. Unfortunately, cancer treatment success has been offset by increased morbidity and mortality due to treatment related comorbidities. Cardiovascular complications are among the most serious side effects, sometimes not becoming manifest until many years after completion of therapy.

All cardiovascular diseases can be a manifestation of a cancer treatment side effect, yet cardiotoxicity or impairment of Left Ventricular (LV) pumping (or systolic) function is the greatest concern. In this project we specifically focus on three types of oncological treatments: radiation therapy, anthracycline-based chemotherapy and the new kid on the block, immune checkpoint inhibitors.

In an ideal, patient tailored approach, the treating oncologist knows in advance which anticancer agents provoke cardiotoxicity in a given patient and uses this knowledge to select the appropriate, least cardiotoxic, chemotherapeutic regimen. As such, dose reductions and dose delays of life‑saving anti-cancer drugs due to cardiotoxicity would be unnecessary. Recent advances in genomics and molecular medicine and more specifically the advent of induced pluripotent stem cells (iPSCs)-derived cardiac myocytes offer the prospect of precision medicine and the ability to predict, prevent, and treat cardiovascular diseases on an individual level. This precision medicine approach is based on the ability to better diagnose and stratify patients into different treatment groups by correlating a patient's genotype with their cellular phenotype. Here, we hypothesize that the same technique could be exploited as a disease model to assess the mechanisms and patient’s individual susceptibility to cancer therapy related cardiotoxicity.

Furthermore, there is an unmet need for mouse models to investigate mechanisms of cardiotoxicity in vivo. Inflammation plays an important role in the development, persistence and treatment of cancer. The contribution of chronic inflammation on the development of cardiotoxicity is currently unknown. We therefore want to create a model of chronic inflammation to study its effect on anthracycline-induced cardiotoxicity (AIC).

Lastly, we aim to create a model to investigate immune checkpoint inhibitors (ICI) induced myocarditis. ICI are a revolution in the treatment of cancer and are now approved both in mono- as combination therapy for more than 20 cancer types. ICI release the brakes on the immune system, thus inducing an immunity versus cancer effect. However, auto-immune events, whereby the activated immune system attacks healthy tissue, are a concern during ICI treatment. Although other cardiac events have been described by our own group, myocarditis remains the prototypical cardiac auto-immune event. How ICI-related myocarditis develops is still unclear, although multiple mechanisms have been proposed: HLA make up, cardiomyocyte death and (subclinical) myocardial infarction, exposure of specific cardiac antigens and/or pre-existing inflammation. This model might help to unravel the mechanism of ICI-induced myocarditis.