Sharma Ankush, Cinti Caterina, Capobianco Enrico
Experimental Oncology Unit, UOS - Institute of Clinical Physiology, CNR, Siena, Italy.
Center for Computational Science, University of Miami, Miami, FL, United States.
Front Immunol. 2017 Jul 31;8:918. doi: 10.3389/fimmu.2017.00918. eCollection 2017.
This study highlights the relevance of network-guided controllability analysis as a precision oncology tool. Target controllability through networks is potentially relevant to cancer research for the identification of therapeutic targets. With reference to a recent study on multiple phenotypes from 22 osteosarcoma (OS) cell lines characterized both and , we found that a variety of critical proteins in OS regulation circuits were in part phenotype specific and in part shared. To generalize our inference approach and match cancer phenotypic heterogeneity, we employed multitype networks and identified targets in correspondence with protein sub-complexes. Therefore, we established the relevance for diagnostic and therapeutic purposes of inspecting interactive targets, namely those enriched by significant connectivity patterns in protein sub-complexes. Emerging targets appeared with reference to the OS microenvironment, and relatively to small leucine-rich proteoglycan members and D-type cyclins, among other collagen, laminin, and keratin proteins. These described were evidences shared across all phenotypes; instead, specific evidences were provided by critical proteins including IGFBP7 and PDGFRA in the invasive phenotype, and FGFR3 and THBS1 in the colony forming phenotype.
本研究强调了网络引导的可控性分析作为一种精准肿瘤学工具的相关性。通过网络实现的目标可控性对于癌症研究中治疗靶点的识别可能具有重要意义。参考最近一项对22种骨肉瘤(OS)细胞系的多种表型进行表征的研究,我们发现OS调控回路中的多种关键蛋白部分具有表型特异性,部分具有共享性。为了推广我们的推理方法并匹配癌症表型异质性,我们采用了多类型网络,并确定了与蛋白质亚复合物相对应的靶点。因此,我们确立了检查相互作用靶点(即在蛋白质亚复合物中由显著连接模式富集的靶点)对于诊断和治疗目的的相关性。出现了与OS微环境相关的新兴靶点,相对于富含亮氨酸的小分子蛋白聚糖成员和D型细胞周期蛋白,还有其他胶原蛋白、层粘连蛋白和角蛋白。这些是所有表型共有的证据;相反,侵袭性表型中的关键蛋白IGFBP7和PDGFRA,以及集落形成表型中的FGFR3和THBS1提供了特定证据。