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CSF protein dynamic driver network: At the crossroads of brain tumorigenesis

机译:CSF蛋白动态驱动程序网络:在脑肿瘤发生的十字路口

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To get a better understanding of the ongoing in situ environmental changes preceding the brain tumorigenesis, we assessed cerebrospinal fluid (CSF) proteome profile changes in a glioma rat model in which brain tumor invariably develop after a single in utero exposure to the neurocarcinogen ethylnitrosourea (ENU). Computationally, the CSF proteome profile dynamics during the tumorigenesis can be modeled as non-smooth or even abrupt state changes. Such brain tumor environment transition analysis, correlating the CSF composition changes with the development of early cellular hyperplasia, can reveal the pathogenesis process at network level during a time before the image detection of the tumors. In this controlled rat model study, matched ENU and salineexposed rats' CSF proteomics changes were quantified at approximately 30, 60, 90, 120, 150 days of age (P30, P60, P90, P120, P150). We applied our transition-based network entropy (TNE) method to compute the CSF proteome changes in the ENU rat model and test the hypothesis of the critical transition state prior to impending hyperplasia. Our analysis identified a dynamic driver network (DDN) of CSF proteins related with the emerging tumorigenesis progressing from the non-hyperplasia state. The DDN associated leading network CSF proteins can allow the early detection of such dynamics before the catastrophic shift to the clear clinical landmarks in gliomas. An improved understanding of the critical transition state (P60) during the brain tumor progression can provide the scientific groundwork to device novel therapeutics preventing tumor formation.
机译:为了更好地了解脑肿瘤发生之前正在进行的原位环境变化,我们评估了胶质瘤大鼠模型中的脑脊液(CSF)蛋白质组谱变化,在该模型中,在子宫内一次暴露于神经致癌物乙基亚硝基脲(ENU)后,脑瘤总是发育)。通过计算,可以将肿瘤发生过程中CSF蛋白质组图谱动力学建模为非平滑甚至突变的状态变化。这种脑肿瘤环境转变分析将CSF组成变化与早期细胞增生的发展相关联,可以揭示肿瘤图像检测之前一段时间内网络水平的发病过程。在这项对照大鼠模型研究中,在大约30、60、90、120、150日龄(P30,P60,P90,P120,P150)对匹配的ENU和盐暴露大鼠的CSF蛋白质组学变化进行了定量。我们应用了基于过渡的网络熵(TNE)方法来计算ENU大鼠模型中CSF蛋白质组的变化,并在即将发生增生之前测试了关键过渡状态的假设。我们的分析确定了CSF蛋白的动态驱动程序网络(DDN),与从非增生状态发展而来的新兴肿瘤发生有关。与DDN相关的领先网络CSF蛋白可以在胶质瘤发生灾难性转变为清晰的临床标志之前,就可以早期检测这种动态变化。对脑肿瘤进展过程中关键转变状态(P60)的更好理解可以为装置新的预防肿瘤形成的疗法提供科学依据。

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