首页> 外文期刊>Biochimica et biophysica acta: BBA: International journal of biochemistry, biophysics and molecular biololgy. Proteins and Proteomics >Evaluation of reverse phase protein array (RPPA)-based pathway-activation profiling in 84 non-small cell lung cancer (NSCLC) cell lines as platform for cancer proteomics and biomarker discovery
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Evaluation of reverse phase protein array (RPPA)-based pathway-activation profiling in 84 non-small cell lung cancer (NSCLC) cell lines as platform for cancer proteomics and biomarker discovery

机译:评价基于反相蛋白质阵列(RPPA)的84种非小细胞肺癌(NSCLC)细胞系中的通路激活谱,作为癌症蛋白质组学和生物标记物发现的平台

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The reverse phase protein array (RPPA) approach was employed for a quantitative analysis of 71 cancer-relevant proteins and phosphoproteins in 84 non-small cell lung cancer (NSCLC) cell lines and by monitoring the activation state of selected receptor tyrosine kinases, PI3K/AKT and MEK/ERK1/2 signaling, cell cycle control, apoptosis, and DNA damage. Additional information on NSCLC cell lines such as that of transcriptomic data, genomic aberrations, and drug sensitivity was analyzed in the context of proteomic data using supervised and non-supervised approaches for data analysis. First, the unsupervised analysis of proteomic data indicated that proteins clustering closely together reflect well-known signaling modules, e.g. PI3K/AKT- and RAS/RAF/ERK-signaling, cell cycle regulation, and apoptosis. However, mutations of EGFR, ERBB2, RAF, RAS, TP53, and PI3K were found dispersed across different signaling pathway clusters. Merely cell lines with an amplification of EGFR and/or ERBB2 clustered closely together on the proteomic, but not on the transcriptomic level. Secondly, supervised data analysis revealed that sensitivity towards anti-EGFR drugs generally correlated better with high level EGFR phosphorylation than with EGFR abundance itself. High level phosphorylation of RB and high abundance of AURKA were identified as candidates that can potentially predict sensitivity towards the aurora kinase inhibitor VX680. Examples shown demonstrate that the RPPA approach presents a useful platform for targeted proteomics with high potential for biomarker discovery. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.
机译:反相蛋白质阵列(RPPA)方法用于定量分析84种非小细胞肺癌(NSCLC)细胞系中71种与癌症相关的蛋白质和磷蛋白,并通过监测选定的受体酪氨酸激酶PI3K / AKT和MEK / ERK1 / 2信号传导,细胞周期控制,细胞凋亡和DNA损伤。在蛋白质组学数据的背景下,使用监督和非监督方法对NSCLC细胞系的其他信息(例如转录组数据,基因组畸变和药物敏感性)进行了分析。首先,蛋白质组学数据的无监督分析表明,紧密聚集在一起的蛋白质反映了众所周知的信号传导模块,例如蛋白质。 PI3K / AKT和RAS / RAF / ERK信号,细胞周期调节和凋亡。然而,发现EGFR,ERBB2,RAF,RAS,TP53和PI3K的突变分散在不同的信号通路簇中。仅具有EGFR和/或ERBB2扩增的细胞系在蛋白质组学上紧密聚集在一起,但在转录组学水平上却不紧密。其次,有监督的数据分析显示,对高浓度的EGFR磷酸化对抗EGFR药物的敏感性通常比与EGFR丰度本身更好地相关。 RB的高水平磷酸化和AURKA的高丰度被确定为可以潜在预测对极光激酶抑制剂VX680的敏感性的候选药物。显示的例子表明,RPPA方法为具有高生物标志物发现潜力的靶向蛋白质组学提供了有用的平台。本文是名为“生物标志物:蛋白质组学挑战”的特刊的一部分。

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