Atlas of Cancer Signalling Network: a systems biology resource for integrative analysis of cancer data with Google Maps.
Atlas of Cancer Signalling Network: a systems biology resource for integrative analysis of cancer data with Google Maps.
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DOI：
10.1038/oncsis.2015.19
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发表时间：
2015-07-20
期刊：
影响因子：
6.2
通讯作者：
Zinovyev A
中科院分区：
文献类型：
--
作者：
Kuperstein I;Bonnet E;Nguyen HA;Cohen D;Viara E;Grieco L;Fourquet S;Calzone L;Russo C;Kondratova M;Dutreix M;Barillot E;Zinovyev A
癌症发生是由突变驱动的，导致复杂的分子相互作用网络的功能异常，同时影响多种细胞功能。因此，成功应用生物信息学和系统生物学方法分析癌症研究中的高通量数据在很大程度上取决于全球和详细的重建信号网络的可用性，适合计算分析。我们在这里介绍了癌症信号网络（ACSN）的地图集，这是一个涉及癌症的分子机制的交互式和全面的地图。该资源包括用于在信号网络地图的背景下进行地图导航、可视化和分子数据分析的工具。ACSN的构建和更新涉及到对分子生物学文献的仔细人工整理和相应领域专家的参与。ACSN以癌症为导向的内容是完全原创的，涵盖了癌症进展的主要机制，包括DNA修复，细胞存活，细胞凋亡，细胞周期，EMT和细胞运动。详细描述了细胞信号传导机制，共同创建了癌症中经常失调的分子相互作用的无缝“地理”地图。该地图可使用NaviCell Web界面使用Google地图引擎和语义缩放原理进行浏览。相关的网络博客为评论和策划ACSN内容提供了一个论坛。ACSN允许上传异构组学数据从用户的地图上的可视化和执行功能分析。我们提出了几种ACSN在癌症研究中的应用方案，特别是用于可视化高通量数据，从基于小干扰RNA的筛选结果或突变频率到探索转录组和磷酸化蛋白质组的创新方法。在ACSN的背景下，这些数据的整合和分析可能有助于解释其生物学意义，并制定机制假说。ACSN还可以支持患者分层，预测治疗反应和对癌症药物的耐药性，以及设计新的治疗策略。
Cancerogenesis is driven by mutations leading to aberrant functioning of a complex network of molecular interactions and simultaneously affecting multiple cellular functions. Therefore, the successful application of bioinformatics and systems biology methods for analysis of high-throughput data in cancer research heavily depends on availability of global and detailed reconstructions of signalling networks amenable for computational analysis. We present here the Atlas of Cancer Signalling Network (ACSN), an interactive and comprehensive map of molecular mechanisms implicated in cancer. The resource includes tools for map navigation, visualization and analysis of molecular data in the context of signalling network maps. Constructing and updating ACSN involves careful manual curation of molecular biology literature and participation of experts in the corresponding fields. The cancer-oriented content of ACSN is completely original and covers major mechanisms involved in cancer progression, including DNA repair, cell survival, apoptosis, cell cycle, EMT and cell motility. Cell signalling mechanisms are depicted in detail, together creating a seamless ‘geographic-like' map of molecular interactions frequently deregulated in cancer. The map is browsable using NaviCell web interface using the Google Maps engine and semantic zooming principle. The associated web-blog provides a forum for commenting and curating the ACSN content. ACSN allows uploading heterogeneous omics data from users on top of the maps for visualization and performing functional analyses. We suggest several scenarios for ACSN application in cancer research, particularly for visualizing high-throughput data, starting from small interfering RNA-based screening results or mutation frequencies to innovative ways of exploring transcriptomes and phosphoproteomes. Integration and analysis of these data in the context of ACSN may help interpret their biological significance and formulate mechanistic hypotheses. ACSN may also support patient stratification, prediction of treatment response and resistance to cancer drugs, as well as design of novel treatment strategies.