The Third Affiliated Hospital, Jinzhou Medical University, Jinzhou, China.
Jinzhou Medical University, Jinzhou, China.
BMC Cardiovasc Disord. 2020 Feb 3;20(1):43. doi: 10.1186/s12872-020-01346-y.
The current diagnostic methods and treatments still fail to lower the incidence of anthracycline-induced cardiotoxicity effectively. In this study, we aimed to (1) analyze the cardiotoxicity-related genes after breast cancer chemotherapy in gene expression database and (2) carry out bioinformatic analysis to identify cardiotoxicity-related abnormal expressions, the biomarkers of such abnormal expressions, and the key regulatory pathways after breast cancer chemotherapy.
Cardiotoxicity-related gene expression data (GSE40447) after breast cancer chemotherapy was acquired from the Gene Expression Omnibus (GEO) database. The biomarker expression data of women with chemotherapy-induced cardiotoxicity (group A), chemotherapy history but no cardiotoxicity (group B), and confirmatory diagnosis of breast cancer but normal ejection fraction before chemotherapy (group C) were analyzed to obtain the mRNA with differential expressions and predict the micro RNAs (miRNAs) regulating the differential expressions. The miRanda formula and functional enrichment analysis were used to screen abnormal miRNAs. Then, the Gene Ontology (GO) analysis was adapted to further screen the miRNAs related to cardiotoxicity after breast cancer chemotherapy.
The data of differential analysis of biomarker expression of groups A, B, and C using the GSE40447-related gene expression profile database showed that there were 30 intersection genes. The differentially expressed mRNAs were predicted using the miRanda and Target Scan software, and a total of 2978 miRNAs were obtained by taking the intersections. Further, the GO analysis and targeted regulatory relationship between miRNA and target genes were used to establish miRNA-gene interaction network to screen and obtain seven cardiotoxicity-related miRNAs with relatively high centrality, including hsa-miR-4638-3p, hsa-miR-5096, hsa-miR-4763-5p, hsa-miR-1273 g-3p, hsa-miR6192, hsa-miR-4726-5p and hsa-miR-1273a. Among them, hsa-miR-4638-3p and hsa-miR-1273 g-3p had the highest centrality. The PCR verification results were consistent with those of the chip data. There are differentially expressed miRNAs in the peripheral blood of breast cancer patients with anthracycline cardiotoxicity. Among them, hsa-miR-4638-3p and hsa-miR-1273 g-3p are closely associated with the onset of anthracycline cardiotoxicity in patients with breast cancer. The signaling pathway is mainly concentrated in TGF-β signaling pathway and adhesion signaling pathway.
Changes in expression of hsa-miR-4638-3p and hsa-miR-1273 g-3p may contribute to the detection of anthracyclines induced cardiac toxicity, and their potential function may be related to TGF-β signaling pathway and adhesion signaling pathway.
目前的诊断方法和治疗手段仍未能有效降低蒽环类药物诱导的心脏毒性的发生率。本研究旨在:(1)在基因表达数据库中分析乳腺癌化疗后与心脏毒性相关的基因;(2)进行生物信息学分析,以确定乳腺癌化疗后与心脏毒性相关的异常表达、这些异常表达的生物标志物,以及关键调控途径。
从基因表达综合数据库(GEO)中获取乳腺癌化疗后与心脏毒性相关的基因表达数据(GSE40447)。分析有化疗诱导性心脏毒性(A 组)、化疗史但无心脏毒性(B 组)和经确认诊断患有乳腺癌但化疗前射血分数正常(C 组)的女性的生物标志物表达数据,以获得差异表达的 mRNA,并预测调节这些差异表达的 microRNA(miRNA)。采用 miRanda 公式和功能富集分析筛选异常 miRNA。然后,采用基因本体论(GO)分析进一步筛选乳腺癌化疗后与心脏毒性相关的 miRNA。
使用 GSE40447 相关基因表达谱数据库对 A、B 和 C 组的生物标志物表达差异进行分析,显示有 30 个交集基因。使用 miRanda 和 TargetScan 软件预测差异表达的 mRNAs,取交集共获得 2978 个 miRNA。进一步通过 GO 分析和 miRNA 与靶基因之间的靶向调控关系,建立 miRNA-基因相互作用网络,筛选出七个具有相对较高中心性的心脏毒性相关 miRNA,包括 hsa-miR-4638-3p、hsa-miR-5096、hsa-miR-4763-5p、hsa-miR-1273g-3p、hsa-miR6192、hsa-miR-4726-5p 和 hsa-miR-1273a。其中,hsa-miR-4638-3p 和 hsa-miR-1273g-3p 的中心性最高。PCR 验证结果与芯片数据一致。乳腺癌患者外周血中存在差异表达的 miRNA。其中,hsa-miR-4638-3p 和 hsa-miR-1273g-3p 与乳腺癌患者蒽环类药物心脏毒性的发生密切相关。信号通路主要集中在 TGF-β信号通路和黏附信号通路。
hsa-miR-4638-3p 和 hsa-miR-1273g-3p 的表达变化可能有助于检测蒽环类药物引起的心脏毒性,其潜在功能可能与 TGF-β信号通路和黏附信号通路有关。