npj Systems Biology and Applications ( IF 4 ) Pub Date : 2018-11-05 , DOI: 10.1038/s41540-018-0075-y Greta Del Mistro 1, 2 , Philippe Lucarelli 3 , Ines Müller 1, 2 , Sébastien De Landtsheer 3 , Anna Zinoveva 1, 2 , Meike Hutt 4 , Martin Siegemund 4 , Roland E Kontermann 4, 5 , Stefan Beissert 1 , Thomas Sauter 3 , Dagmar Kulms 1, 2
Metastatic melanoma remains a life-threatening disease because most tumors develop resistance to targeted kinase inhibitors thereby regaining tumorigenic capacity. We show the 2nd generation hexavalent TRAIL receptor-targeted agonist IZI1551 to induce pronounced apoptotic cell death in mutBRAF melanoma cells. Aiming to identify molecular changes that may confer IZI1551 resistance we combined Dynamic Bayesian Network modelling with a sophisticated regularization strategy resulting in sparse and context-sensitive networks and show the performance of this strategy in the detection of cell line-specific deregulations of a signalling network. Comparing IZI1551-sensitive to IZI1551-resistant melanoma cells the model accurately and correctly predicted activation of NFκB in concert with upregulation of the anti-apoptotic protein XIAP as the key mediator of IZI1551 resistance. Thus, the incorporation of multiple regularization functions in logical network optimization may provide a promising avenue to assess the effects of drug combinations and to identify responders to selected combination therapies.
中文翻译:
系统网络分析确定 XIAP 和 IκBα 是 TRAIL 耐药 BRAF 突变黑色素瘤的潜在药物靶点
转移性黑色素瘤仍然是一种危及生命的疾病,因为大多数肿瘤对靶向激酶抑制剂产生耐药性,从而恢复致瘤能力。我们展示了第二代六价 TRAIL 受体靶向激动剂 IZI1551 在mut BRAF 黑色素瘤细胞中诱导明显的细胞凋亡。为了识别可能赋予 IZI1551 耐药性的分子变化,我们将动态贝叶斯网络建模与复杂的正则化策略相结合,产生稀疏和上下文敏感的网络,并展示了该策略在检测信号网络的细胞系特异性失调方面的性能。通过比较 IZI1551 敏感细胞和 IZI1551 耐药黑色素瘤细胞,该模型准确、正确地预测了 NFκB 的激活以及作为 IZI1551 耐药性关键介质的抗凋亡蛋白 XIAP 的上调。因此,在逻辑网络优化中结合多个正则化函数可能为评估药物组合的效果和识别对所选组合疗法的反应者提供有希望的途径。