van der Vegt Solveig A, Wang Ying-Jie, Polonchuk Liudmila, Wang Ken, Waters Sarah L, Baker Ruth E
Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, United Kingdom.
Department of Cardiovascular Medicine, Radcliffe Department of Medicine, Wellcome Centre of Human Genetics, University of Oxford, Oxford, United Kingdom.
Front Pharmacol. 2022 Sep 26;13:966180. doi: 10.3389/fphar.2022.966180. eCollection 2022.
Immune checkpoint inhibitors (ICIs), as a novel immunotherapy, are designed to modulate the immune system to attack malignancies. Despite their promising benefits, immune-related adverse events (IRAEs) may occur, and incidences are bound to increase with surging demand of this class of drugs in treating cancer. Myocarditis, although rare compared to other IRAEs, has a significantly higher fatal frequency. Due to the overwhelming complexity of the immune system, this condition is not well understood, despite the significant research efforts devoted to it. To better understand the development and progression of autoimmune myocarditis and the roles of ICIs therein, we suggest a new approach: mathematical modelling. Mathematical modelling of myocarditis has enormous potential to determine which parts of the immune system are critical to the development and progression of the disease, and therefore warrant further investigation. We provide the immunological background needed to develop a mathematical model of this disease and review relevant existing models of immunology that serve as the mathematical inspiration needed to develop this field.
免疫检查点抑制剂（ICIs）作为一种新型免疫疗法，旨在调节免疫系统以攻击恶性肿瘤。尽管它们具有显著的益处，但免疫相关不良事件（IRAEs）仍可能发生，并且随着这类药物在治疗癌症方面的需求激增，其发生率必然会增加。心肌炎虽然与其他IRAEs相比较为罕见，但其致死率明显更高。由于免疫系统极其复杂，尽管对此投入了大量研究工作，但这种情况仍未得到充分了解。为了更好地理解自身免疫性心肌炎的发生发展以及ICIs在其中的作用，我们提出一种新方法：数学建模。心肌炎的数学建模在确定免疫系统的哪些部分对疾病的发生发展至关重要方面具有巨大潜力，因此值得进一步研究。我们提供了建立该疾病数学模型所需的免疫学背景，并回顾了相关的现有免疫学模型，这些模型为该领域的发展提供了数学灵感。
