Why the study?
Autoimmune myocarditis is a rare, frequently fatal side effect of immune checkpoint inhibitors, but the importance of the different immunological pathways involved remains largely unknown.
This mathematical model provides a theoretical framework showing how immune checkpoint inhibitors lower the immune tolerance threshold, thereby increasing the risk of autoimmune myocarditis.
Mathematical model of ICI-myocarditis offers a framework for pathway exploration; leaves open empirical validation before clinical or trial use.
Autoimmune myocarditis is a rare, but frequently fatal, side effect of immune checkpoint inhibitors (ICIs), a class of cancer therapies. Despite extensive experimental work on the causes, development and progression of this disease, much still remains unknown about the importance of the different immunological pathways involved. We present a mathematical model of autoimmune myocarditis and the effects of ICIs on its development and progression to either resolution or chronic inflammation. From this, we gain a better understanding of the role of immune cells, cytokines and other components of the immune system in driving the cardiotoxicity of ICIs. We parameterise the model using existing data from the literature, and show that qualitative model behaviour is consistent with disease characteristics seen in patients in an ICI-free context. The bifurcation structures of the model show how the presence of ICIs increases the risk of developing autoimmune myocarditis. This predictive modelling approach is a first step towards determining treatment regimens that balance the benefits of treating cancer with the risk of developing autoimmune myocarditis.
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Vegt et al. (2021) studied this question.
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