Parallel Characterization of Genetic Variants in Chemotherapy-Induced Cardiotoxicity Using iPSCs

项目摘要 癌症治疗的高毒性可导致癌症幸存者的严重心力衰竭或停止治疗。 癌症治疗目前，评估谁在使用前有发生心脏毒性的风险是具有挑战性的。 癌症治疗和预防不良副作用。全基因组关联研究（GWAS） 表明遗传倾向是化疗风险易感性的关键决定因素之一- 诱发心脏毒性。因此，对抗癌药物的敏感性可以由患者概括- 特异性诱导多能干细胞（iPSC）衍生的心肌细胞（iPSC-CM），其反映供体 病人的基因组成该项目的目标是确定影响人类健康的基因和遗传变异。 抗癌药物的敏感性，用于开发心脏保护疗法和风险评估系统。 虽然该建议集中于阿霉素，这是最常用的抗癌剂之一， 本文所述的方法可扩展到任何其他癌症治疗诱导的心脏毒性，例如通过 酪氨酸激酶抑制剂和放射治疗。首先，我计划识别那些抑制或激活可以 使用我们基于iPSC的CRISPR筛选平台保护iPSC-CM免受阿霉素的侵害。筛选出的基因将 是多柔比星诱导的心脏毒性（DIC）的原因，因此是有希望的治疗靶点。第二，我计划 利用生物工程技术和体内小鼠模型来评估候选疗法的效果 比简单的单层培养系统更准确。由于批准药物的再利用会加速 为了研究这些发现的临床应用，我计划在这些模型中测试现有的针对已验证基因的药物。 最后，为了开发一个系统来评估DIC的遗传易感性，我计划进行并行 在DIC中使用基于iPSC的碱基/引物编辑筛选来表征许多遗传变体，并产生 临床上涉及DIC的个体变体的“易感性评分”。结果将有助于降低风险 接受化疗的患者分层。

Project Summary Cardiotoxicity of cancer treatments can lead to severe heart failure in cancer survivors or discontinuation of cancer treatments. Currently, it is challenging to evaluate who is at the risk of developing cardiotoxicity prior to cancer treatments and prevent the adverse side effects. Genome-wide association studies (GWASs) have shown that genetic predispositions are one of the key determinants of risk susceptibility to chemotherapy- induced cardiotoxicity. Consistently, the susceptibility to anti-cancer agents can be recapitulated by patient- specific induced pluripotent stem cell (iPSC)-derived cardiomyocytes (iPSC-CMs), which reflect the donor patients’ genetic makeup. The goal of this project is to identify genes and genetic variants that affect the susceptibility to anti-cancer agents for developing cardio-protective therapies and risk assessment systems. Although this proposal focuses on doxorubicin, which is one of the most commonly-used anti-cancer agents, the approach described here is expandable to any other cancer treatment-induced cardiotoxicities such as those by tyrosine kinase inhibitors and radiation therapy. First, I plan to identify genes whose inhibition or activation can protect iPSC-CMs from doxorubicin using our iPSC-based CRISPR screening platform. The screened genes will be causative in doxorubicin-induced cardiotoxicity (DIC) and thus promising therapeutic targets. Second, I plan to utilize bioengineering technologies and in vivo mouse models to assess the effects of candidate therapies more accurately than simple monolayer culture systems. Since repurposing of approved drugs can accelerate the clinical application of the findings, I plan to test existing drugs that target the validated genes in these models. Finally, to develop a system to evaluate the genetic susceptibility to DIC, I plan to perform parallel characterization of many genetic variants using iPSC-based base/prime-editing screens in DIC and generate “susceptibility scores” of individual variants that are clinically implicated in DIC. The result will help with risk stratification of patients who receive chemotherapies.