Petsalaki Evangelia, Helbig Andreas O, Gopal Anjali, Pasculescu Adrian, Roth Frederick P, Pawson Tony
Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, M5G 1X8, Canada
Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, M5G 1X8, Canada Program in Developmental and Stem Cell Biology, Hospital for Sick Children, Toronto, Ontario, M5G 1X5, Canada.
Nucleic Acids Res. 2015 Jul 1;43(W1):W276-82. doi: 10.1093/nar/gkv459. Epub 2015 May 6.
While phospho-proteomics studies have shed light on the dynamics of cellular signaling, they mainly describe global effects and rarely explore mechanistic details, such as kinase/substrate relationships. Tools and databases, such as NetworKIN and PhosphoSitePlus, provide valuable regulatory details on signaling networks but rely on prior knowledge. They therefore provide limited information on less studied kinases and fewer unexpected relationships given that better studied signaling events can mask condition- or cell-specific 'network wiring'. SELPHI is a web-based tool providing in-depth analysis of phospho-proteomics data that is intuitive and accessible to non-bioinformatics experts. It uses correlation analysis of phospho-sites to extract kinase/phosphatase and phospho-peptide associations, and highlights the potential flow of signaling in the system under study. We illustrate SELPHI via analysis of phospho-proteomics data acquired in the presence of erlotinib-a tyrosine kinase inhibitor (TKI)-in cancer cells expressing TKI-resistant and -sensitive variants of the Epidermal Growth Factor Receptor. In this data set, SELPHI revealed information overlooked by the reporting study, including the known role of MET and EPHA2 kinases in conferring resistance to erlotinib in TKI sensitive strains. SELPHI can significantly enhance the analysis of phospho-proteomics data contributing to improved understanding of sample-specific signaling networks. SELPHI is freely available via http://llama.mshri.on.ca/SELPHI.
虽然磷酸化蛋白质组学研究揭示了细胞信号传导的动态过程，但它们主要描述的是全局效应，很少探究激酶/底物关系等机制细节。诸如NetworKIN和PhosphoSitePlus等工具和数据库提供了有关信号网络的宝贵调控细节，但依赖于先验知识。因此，鉴于研究较多的信号事件可能掩盖特定条件或细胞的“网络连接”，它们对于研究较少的激酶提供的信息有限，意外关系也较少。SELPHI是一个基于网络的工具，可对磷酸化蛋白质组学数据进行深入分析，非生物信息学专家也能直观地使用。它利用磷酸化位点的相关性分析来提取激酶/磷酸酶和磷酸肽关联，并突出显示所研究系统中信号的潜在流动。我们通过分析在存在厄洛替尼（一种酪氨酸激酶抑制剂，TKI）的情况下，在表达表皮生长因子受体TKI抗性和敏感性变体的癌细胞中获取的磷酸化蛋白质组学数据来说明SELPHI。在这个数据集中，SELPHI揭示了报告研究中忽略的信息，包括MET和EPHA2激酶在赋予TKI敏感菌株对厄洛替尼抗性中的已知作用。SELPHI可以显著增强对磷酸化蛋白质组学数据的分析，有助于更好地理解样本特异性信号网络。可通过http://llama.mshri.on.ca/SELPHI免费获取SELPHI。
