Detection of treatment-induced changes in signaling pathways in gastrointestinal stromal tumors using transcriptomic data.
Detection of treatment-induced changes in signaling pathways in gastrointestinal stromal tumors using transcriptomic data.
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DOI：
10.1158/0008-5472.can-09-1709
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发表时间：
2009-12-01
期刊：
影响因子：
11.2
通讯作者：
Godwin AK
中科院分区：
文献类型：
--
作者：
Ochs MF;Rink L;Tarn C;Mburu S;Taguchi T;Eisenberg B;Godwin AK
细胞信号在癌症的病因学中起着核心作用。许多正在使用或正在开发的靶点信号蛋白治疗药物，然而，非靶点效应往往限制了对预期靶点的积极临床反应的分配。由于在治疗期间直接测量信号蛋白活性通常是不可行的，因此需要更强大的方法来确定治疗药物是否抑制了他们的靶点以及何时发生了靶外效应。我们使用贝叶斯分解算法和转录调控数据创建了一种新的方法，DESAD(信号确定的差异表达)，用于从微阵列测量中推断信号活性。我们应用DESID来推断靶向治疗甲磺酸伊马替尼(Gleevec)治疗的胃肠道间质瘤细胞系中的信号活性。我们检测到KIT途径中预期的活性降低，以及P53途径中的意外变化。追寻这些发现，我们已经确定伊马替尼诱导的DNA损伤是P53活性增加的原因，并确定了该药物的一种新的靶外活性。然后，我们使用来自切除的、伊马替尼治疗后的肿瘤样本的数据，在这些肿瘤中识别出与细胞系后期时间点相似的模式，并且这种模式与最初的临床反应相关。这种模式显示ELK1和STAT3转录因子的活性增加，这与侧群细胞的生长有关。Deside推断治疗期间信号网络的全球重新编程，允许利用正在进行的药物开发努力进行治疗修改，这对个性化药物至关重要。
Cell signaling plays a central role in the etiology of cancer. Numerous therapeutics in use or under development target signaling proteins, however off-target effects often limit assignment of positive clinical response to the intended target. As direct measurements of signaling protein activity are not generally feasible during treatment, there is a need for more powerful methods to determine if therapeutics inhibit their targets and when off-target effects occur. We have used the Bayesian Decomposition algorithm and data on transcriptional regulation to create a novel methodology, DESIDE (Differential Expression for SIgnaling DEtermination), for inferring signaling activity from microarray measurements. We applied DESIDE to deduce signaling activity in gastrointestinal stromal tumor cell lines treated with the targeted therapeutic imatinib mesylate (Gleevec). We detected the expected reduced activity in the KIT pathway, as well as unexpected changes in the P53 pathway. Pursuing these findings, we have determined that imatinib-induced DNA damage is responsible for the increased activity of P53, identifying a novel off-target activity for this drug. We then used DESIDE on data from resected, post-imatinib treatment tumor samples and identified a pattern in these tumors similar to that at late time points in the cell lines, and this pattern correlated with initial clinical response. The pattern showed increased activity of ELK1 and STAT3 transcription factors, which are associated with the growth of side population cells. DESIDE infers the global reprogramming of signaling networks during treatment, permitting treatment modification that leverages ongoing drug development efforts, which is crucial for personalized medicine.