Computational discovery of transcription factors associated with drug response.
Computational discovery of transcription factors associated with drug response.
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DOI：
10.1038/tpj.2015.74
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发表时间：
2016-11
期刊：
影响因子：
--
通讯作者：
Sinha S
中科院分区：
文献类型：
--
作者：
Hanson C;Cairns J;Wang L;Sinha S
本研究将淋巴母细胞系中的基因表达、基因型和药物反应数据与ENCODE（基因组元件百科全书）中的转录因子（TF）结合位点整合在一种新的方法中，阐明了与细胞毒性相关的调控背景。该方法GENMi（中间基因表达）假设TF结合位点内的单核苷酸多态性可调节其调节活性，并且由此产生的基因表达变化导致药物反应的变化。对161个TF和24种治疗的分析显示了334个显著相关的TF-治疗对。对20对选定的研究产生了文献支持，这些协会中的13个，往往从研究中的TF表达的扰动改变药物反应。在两种三阴性乳腺癌细胞系中，紫杉烷类和蒽环类药物的显著GENMi相关性的实验验证证实了我们的发现。该方法被证明是更敏感的替代，全基因组关联研究为基础的方法，不使用基因表达。这些结果证明了GENMi在鉴定影响药物反应的TF中的效用，并为进一步测试提供了许多候选物。
This study integrates gene expression, genotype and drug response data in lymphoblastoid cell lines with transcription factor (TF)-binding sites from ENCODE (Encyclopedia of Genomic Elements) in a novel methodology that elucidates regulatory contexts associated with cytotoxicity. The method, GENMi (Gene Expression iN the Middle), postulates that single-nucleotide polymorphisms within TF-binding sites putatively modulate its regulatory activity, and the resulting variation in gene expression leads to variation in drug response. Analysis of 161 TFs and 24 treatments revealed 334 significantly associated TF–treatment pairs. Investigation of 20 selected pairs yielded literature support for 13 of these associations, often from studies where perturbation of the TF expression changes drug response. Experimental validation of significant GENMi associations in taxanes and anthracyclines across two triple-negative breast cancer cell lines corroborates our findings. The method is shown to be more sensitive than an alternative, genome-wide association study-based approach that does not use gene expression. These results demonstrate the utility of GENMi in identifying TFs that influence drug response and provide a number of candidates for further testing.