首页> 外文期刊>Nature reviews neuroscience >Molecular Network-Based Drug Prediction in Thyroid Cancer
【24h】

Molecular Network-Based Drug Prediction in Thyroid Cancer

机译:甲状腺癌中基于分子网络的药物预测

获取原文
获取原文并翻译 | 示例
       

摘要

As a common malignant tumor disease, thyroid cancer lacks effective preventive and therapeutic drugs. Thus, it is crucial to provide an effective drug selection method for thyroid cancer patients. The connectivity map (CMAP) project provides an experimental validated strategy to repurpose and optimize cancer drugs, the rationale behind which is to select drugs to reverse the gene expression variations induced by cancer. However, it has a few limitations. Firstly, CMAP was performed on cell lines, which are usually different from human tissues. Secondly, only gene expression information was considered, while the information about gene regulations and modules/pathways was more or less ignored. In this study, we first measured comprehensively the perturbations of thyroid cancer on a patient including variations at gene expression level, gene co-expression level and gene module level. After that, we provided a drug selection pipeline to reverse the perturbations based on drug signatures derived from tissue studies. We applied the analyses pipeline to the cancer genome atlas (TCGA) thyroid cancer data consisting of 56 normal and 500 cancer samples. As a result, we obtained 812 up-regulated and 213 down-regulated genes, whose functions are significantly enriched in extracellular matrix and receptor localization to synapses. In addition, a total of 33,778 significant differentiated co-expressed gene pairs were found, which form a larger module associated with impaired immune function and low immunity. Finally, we predicted drugs and gene perturbations that could reverse the gene expression and co-expression changes incurred by the development of thyroid cancer through the Fisher's exact test. Top predicted drugs included validated drugs like baclofen, nevirapine, glucocorticoid, formaldehyde and so on. Combining our analyses with literature mining, we inferred that the regulation of thyroid hormone secretion might be closely related to the inhibition of the proliferation of thyroid cancer cells.
机译:作为一种常见的恶性肿瘤疾病,甲状腺癌缺乏有效的预防和治疗药物。因此,为甲状腺癌患者提供有效的药物选择方法至关重要。连接地图(CMAP)项目提供了一种实验验证的策略来重新培养和优化癌症药物,其后面的基本原理是选择药物以逆转癌症诱导的基因表达变化。但是,它有一些限制。首先,对细胞系进行CMAP,其通常与人组织不同。其次,只考虑基因表达信息,而有关基因规则和模块/途径的信息,则忽略了这些信息。在这项研究中,我们首先全面地测量甲状腺癌对患者的扰动,包括基因表达水平,基因共表达水平和基因模块水平的变化。之后,我们提供了一种药物选择管道,以基于来自组织研究的药物签名来逆转扰动。我们将分析管道应用于由56个正常和500种癌症样品组成的癌症基因组地图集(​​TCGA)甲状腺癌数据。结果,我们获得了812个上调的和213个下调基因,其功能在细胞外基质和受体定位中显着富集为突触。此外,还发现了总共33,778个显着的分化的共表达基因对,其形成与免疫功能受损和低免疫相关的更大模块。最后,我们预测药物和基因扰动,可以通过Fisher的确切测试逆转甲状腺癌产生的基因表达和共同表达的变化。顶级预测药物包括验证的药物,如Baclofen,Nevirapine,糖皮质激素,甲醛等。与文献采矿的分析相结合,我们推断甲状腺激素分泌的调节可能与抑制甲状腺癌细胞的增殖密切相关。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号