Determining the genetic basis of anthracycline-cardiotoxicity by molecular response QTL mapping in induced cardiomyocytes.
Determining the genetic basis of anthracycline-cardiotoxicity by molecular response QTL mapping in induced cardiomyocytes.
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DOI：
10.7554/elife.33480
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发表时间：
2018-05-08
期刊：
影响因子：
7.7
通讯作者：
Gilad Y
中科院分区：
文献类型：
--
作者：
Knowles DA;Burrows CK;Blischak JD;Patterson KM;Serie DJ;Norton N;Ober C;Pritchard JK;Gilad Y
蒽环类药物诱导的心脏毒性（ACT）是设定最佳化疗方案的关键限制因素，预计几乎一半的患者在高剂量下会发生充血性心力衰竭。然而，对蒽环类药物敏感的遗传基础仍不清楚。我们从45个个体中创建了一组iPSC衍生的心肌细胞，并在暴露于不同的阿霉素剂量24小时后进行RNA-seq。转录组学反应是实质性的：大多数基因差异表达，超过6000个基因显示差异剪接的证据，后者由多柔比星存在下剪接保真度降低驱动。我们表明，个体间的转录反应的变化是预测体外细胞损伤，这反过来又与体内ACT风险。我们检测到447个反应表达数量性状位点（QTL）和42个反应剪接QTL，这些QTL在较低的ACT GWAS值中富集，支持我们的细胞对蒽环类抗生素反应的遗传调控图谱的体内相关性。许多癌症，包括白血病、淋巴瘤和乳腺癌，都是用蒽环类等强效化疗药物治疗的。然而，蒽环类药物具有强烈的副作用，称为蒽环类药物心脏毒性，影响心脏健康。几乎一半的患者给予高剂量的蒽环类药物发展为慢性心力衰竭。虽然蒽环类药物的心脏毒性很常见，但人们的基因可能会影响他们对这些药物的敏感程度，但目前还不清楚哪些基因会导致这种影响。以前的研究只使用了少量的参与者，无法确定遗传因素，这些遗传因素使一些患者对蒽环类药物反应良好，而另一些患者在服用这些药物时容易发生心力衰竭。为了找出哪些基因影响蒽环类药物的心脏毒性，Knowles，Burrows等人将45个个体的血细胞转化为干细胞，然后将其发育成心肌细胞。然后，通过测量这些基因产生的RNA（用于制造蛋白质的模板分子）的量来分析基因的活性。在细胞暴露于蒽环类药物阿霉素24小时后，可以在个体之间的心肌细胞中发现数百个基因活性差异。其中一些差异与药物治疗后细胞的健康状况较差有关。结果，发现了许多可能使患者易患阿霉素副作用的遗传变异。实验还揭示了阿霉素如何破坏一个重要的过程，该过程将RNA的“垃圾”部分与用作蛋白质模板的部分分开。能够预测谁可能对阿霉素等药物敏感，可以帮助医生更有效地定制化疗治疗，最大限度地降低心力衰竭的风险。在未来，更大规模的研究可能会导致准确预测患者对特定化疗药物的反应，以个性化他们的癌症治疗。
Anthracycline-induced cardiotoxicity (ACT) is a key limiting factor in setting optimal chemotherapy regimes, with almost half of patients expected to develop congestive heart failure given high doses. However, the genetic basis of sensitivity to anthracyclines remains unclear. We created a panel of iPSC-derived cardiomyocytes from 45 individuals and performed RNA-seq after 24 hr exposure to varying doxorubicin dosages. The transcriptomic response is substantial: the majority of genes are differentially expressed and over 6000 genes show evidence of differential splicing, the later driven by reduced splicing fidelity in the presence of doxorubicin. We show that inter-individual variation in transcriptional response is predictive of in vitro cell damage, which in turn is associated with in vivo ACT risk. We detect 447 response-expression quantitative trait loci (QTLs) and 42 response-splicing QTLs, which are enriched in lower ACT GWAS -values, supporting the in vivo relevance of our map of genetic regulation of cellular response to anthracyclines. Many cancers, including leukaemia, lymphoma and breast cancer, are treated with potent chemotherapy drugs such as anthracyclines. However, anthracyclines have strong side effects known as anthracycline cardiotoxicity, which affect the health of the heart. Almost half of the patients given high doses of anthracyclines develop chronic heart failure. While anthracycline cardiotoxicity is very common, people’s genes may contribute to how sensitive they are to these drugs but it is not understood which genes can cause this effect. Previous studies using only a small number of participants have not been able to pin down the genetic factors that make some patients respond well to anthracyclines, and others prone to developing heart failure when taking these drugs. To find out which genes affect anthracycline cardiotoxicity, Knowles, Burrows et al. transformed blood cells from 45 individuals into stem cells, which were then developed into heart muscle cells. Then, the activity of genes was analyzed by measuring the amount of RNA (the template molecules used to make proteins) produced by those genes. After the cells had been exposed for 24 hours to the anthracycline drug doxorubicin, hundreds of gene activity differences could be found in the heart muscle cells between individuals. Some of these differences were linked to poorer health of the cells after treatment with the drug. As a result, a number of genetic variants that could predispose patients to the side effects of doxorubicin were discovered. The experiments also revealed how doxorubicin disrupts an important process that separates ‘junk’ parts of the RNA from the parts that are used as a template for proteins. Being able to predict who is likely to be sensitive to drugs such as doxorubicin could help doctors to tailor chemotherapy treatments more effectively, minimising the risk of heart failure. In future, larger studies could lead to accurate predictions of a patient’s response to a particular chemotherapy drug to personalize their cancer treatment.