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首页> 外文期刊>Breast Cancer Research >Combined the SMAC mimetic and BCL2 inhibitor sensitizes neoadjuvant chemotherapy by targeting necrosome complexes in tyrosine aminoacyl-tRNA synthase-positive breast cancer
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Combined the SMAC mimetic and BCL2 inhibitor sensitizes neoadjuvant chemotherapy by targeting necrosome complexes in tyrosine aminoacyl-tRNA synthase-positive breast cancer

机译:结合SMAC模拟物和BCL2抑制剂通过靶向酪氨酸氨基酰基-TRNA合酶阳性乳腺癌的肮脏综合体来敏感Neoadjuvant化疗

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摘要

Chemotherapy is the standard treatment for breast cancer; however, the response to chemotherapy is disappointingly low. Here, we investigated the alternative therapeutic efficacy of novel combination treatment with necroptosis-inducing small molecules to overcome chemotherapeutic resistance in tyrosine aminoacyl-tRNA synthetase (YARS)-positive breast cancer. Pre-chemotherapeutic needle biopsy of 143 invasive ductal carcinomas undergoing the same chemotherapeutic regimen was subjected to proteomic analysis. Four different machine learning algorithms were employed to determine signature protein combinations. Immunoreactive markers were selected using three common candidate proteins from the machine-learning algorithms and verified by immunohistochemistry using 123 cases of independent needle biopsy FFPE samples. The regulation of chemotherapeutic response and necroptotic cell death was assessed using lentiviral YARS overexpression and depletion 3D spheroid formation assay, viability assays, LDH release assay, flow cytometry analysis, and transmission electron microscopy. The ROS-induced metabolic dysregulation and phosphorylation of necrosome complex by YARS were assessed using oxygen consumption rate analysis, flow cytometry analysis, and 3D cell viability assay. The therapeutic roles of SMAC mimetics (LCL161) and a pan-BCL2 inhibitor (ABT-263) were determined by 3D cell viability assay and flow cytometry analysis. Additional biologic process and protein-protein interaction pathway analysis were performed using Gene Ontology annotation and Cytoscape databases. YARS was selected as a potential biomarker by proteomics-based machine-learning algorithms and was exclusively associated with good response to chemotherapy by subsequent immunohistochemical validation. In 3D spheroid models of breast cancer cell lines, YARS overexpression significantly improved chemotherapy response via phosphorylation of the necrosome complex. YARS-induced necroptosis sequentially mediated mitochondrial dysfunction through the overproduction of ROS in breast cancer cell lines. Combination treatment with necroptosis-inducing small molecules, including a SMAC mimetic (LCL161) and a pan-BCL2 inhibitor (ABT-263), showed therapeutic efficacy in YARS-overexpressing breast cancer cells. Our results indicate that, before chemotherapy, an initial screening of YARS protein expression should be performed, and YARS-positive breast cancer patients might consider the combined treatment with LCL161 and ABT-263; this could be a novel stepwise clinical approach to apply new targeted therapy in breast cancer patients in the future.
机译:化疗是乳腺癌的标准治疗;然而,对化疗的反应是令人失望的。在这里,我们研究了新的组合治疗与诱导小分子的替代治疗疗效,以克服酪氨酸氨基酰基-TRNA合成酶(YARS)阳性乳腺癌的化疗抗性。对经受相同化学治疗方案的143个侵入性导管癌的化学治疗针活检进行蛋白质组学分析。使用四种不同的机器学习算法来确定特征蛋白质组合。使用来自机器学习算法的三种常见候选蛋白选择免疫反应性标记,并使用123例独立针活检FFPE样品进行免疫组化验证。使用慢病毒YARS过表达和耗尽3D球状形成测定,生存能测定,LDH释放测定,流式细胞术分析和透射电子显微镜评估化学治疗反应和死亡细胞死亡的调节。使用氧气消耗率分析,流式细胞术分析和3D细胞活力测定评估ROS诱导的代谢致多余测定和Necrosome复合物的磷酸化合物。 SMAC模拟物(LCL161)和PAN-BCL2抑制剂(ABT-263)的治疗作用由3D细胞活力测定和流式细胞术分析测定。使用基因本体注释和Cytoscape数据库进行额外的生物过程和蛋白质 - 蛋白质相互作用途径分析。由基于蛋白质组学的机器学习算法选择亚斯作为潜在的生物标志物,并且通过随后的免疫组化验证术后与对化疗的良好反应相关。在乳腺癌细胞系的3D球体模型中,雅雅过度表达通过肮脏络合物的磷酸化显着改善化疗反应。 YARs诱导的粪便逐渐介导通过乳腺癌细胞系ROS过量生产的线粒体功能障碍。用Necroptosis诱导小分子的组合处理,包括SMAC模拟物(LCL161)和PAN-BCL2抑制剂(ABT-263),在yars过表达乳腺癌细胞中显示出治疗效果。我们的结果表明,在化疗之前,应进行母蛋白表达的初始筛选,雅氏阳性乳腺癌患者可能会考虑使用LCL161和ABT-263的合并治疗;这可能是一种新的逐步临床方法,在未来应用乳腺癌患者的新靶向治疗。

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