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首页> 外文期刊>PLoS Computational Biology >Model-Based Analysis of HER Activation in Cells Co-Expressing EGFR, HER2 and HER3
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Model-Based Analysis of HER Activation in Cells Co-Expressing EGFR, HER2 and HER3

机译：基于模型分析她在COLCOMET，HER2和HER3中的细胞激活分析

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The HER/ErbB family of receptor tyrosine kinases drives critical responses in normal physiology and cancer, and the expression levels of the various HER receptors are critical determinants of clinical outcomes. HER activation is driven by the formation of various dimer complexes between members of this receptor family. The HER dimer types can have differential effects on downstream signaling and phenotypic outcomes. We constructed an integrated mathematical model of HER activation, and trafficking to quantitatively link receptor expression levels to dimerization and activation. We parameterized the model with a comprehensive set of HER phosphorylation and abundance data collected in a panel of human mammary epithelial cells expressing varying levels of EGFR/HER1, HER2 and HER3. Although parameter estimation yielded multiple solutions, predictions for dimer phosphorylation were in agreement with each other. We validated the model using experiments where pertuzumab was used to block HER2 dimerization. We used the model to predict HER dimerization and activation patterns in a panel of human mammary epithelial cells lines with known HER expression levels in response to stimulations with ligands EGF and HRG. Simulations over the range of expression levels seen in various cell lines indicate that: i) EGFR phosphorylation is driven by HER1-HER1 and HER1-HER2 dimers, and not HER1-HER3 dimers, ii) HER1-HER2 and HER2-HER3 dimers both contribute significantly to HER2 activation with the EGFR expression level determining the relative importance of these species, and iii) the HER2-HER3 dimer is largely responsible for HER3 activation. The model can be used to predict phosphorylated dimer levels for any given HER expression profile. This information in turn can be used to quantify the potencies of the various HER dimers, and can potentially inform personalized therapeutic approaches.
机译：HER / ERBB受体酪氨酸激酶系列在正常生理和癌症中驱动关键反应，各种受体的表达水平是临床结果的关键决定因素。通过在该受体家族成员之间形成各种二聚体复合物的激活。她的二聚体类型可以对下游信号传导和表型结果具有差异影响。我们构建了一种综合数学模型的激活，并将定量链接受体表达水平的贩运分二聚化和活化。我们将模型参数化，具有一套综合的磷酸化和丰富的数据，并在表达不同水平的EGFR / HER1，HER2和HER3的人乳腺上皮细胞面板中收集的丰富数据。尽管参数估计产生多种溶液，但是对二聚体磷酸化的预测彼此一致。我们使用实验验证了模型，其中使用Pertuzumab阻断HER2二聚体。我们利用该模型预测人乳腺上皮细胞系的小组中的二聚化和激活模式，响应于用配体EGF和HRG的刺激而已知她的表达水平。在各种细胞系中看到的表达水平范围的模拟表明：i）EGFR磷酸化由Her1-Her1和Her1-Her2二聚体驱动，而不是Her1-Her3二聚体，II）Her1-Her2和Her2-Her3二聚体贡献显着达到HER2激活与EGFR表达水平确定这些物种的相对重要性，并且III）HER2-HER3二聚体在很大程度上对HER3活化负责。该模型可用于预测任何给定她的表达谱的磷酸化二聚体水平。该信息依次可用于量化各种二聚体的恒期性，并且可能会通知个性化的治疗方法。

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