Asadzadeh-Aghdaei Hamid, Okhovatian Farshad, Razzaghi Zahra, Heidari Mohammadhossein, Vafaee Reza, Nikzamir Abdolrahim
Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Physiotherapy Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
J Lasers Med Sci. 2019 Fall;10(Suppl 1):S59-S63. doi: 10.15171/jlms.2019.S11. Epub 2019 Dec 1.
Radiation therapy (RT) as a common method for cancer treatment could result in some side effects. The molecular investigation is one of the approaches that could assist in decrypting the molecular mechanisms of this incident. For this aim, protein-protein interaction (PPI) network analysis as a complementary study of the proteome is conducted to explore the RT effect on brain cancer after the early stage of exposure prior to the appearance of the skin lesion. Cytoscape 3.7.2 and its plug-ins were used to analyze the network of differential expression of proteins (DEPs) in the treatment condition, and the centrality and pathway enrichment was conducted by the use of NetworkAnalyzer and ClueGO+CluePedia. A network of 15 DEPs indicated that 6 nodes were key players in the network stability and SERPINC1 and F5 were from the query proteins. The pathways of post-translational protein phosphorylation, platelet degranulation, and complement and coagulation cascades were the most highlighted ones for the central nodes that could be affected in RT. The central proteins of the network of early-stage treatments could have additional importance in the mechanisms of radiotherapy response prior to skin lesions. Introduced biomarkers can be used for the patients' follow-up. These candidates are worth precise attention for this type of therapy after approving by validation studies.
放射治疗（RT）作为一种常见的癌症治疗方法，可能会导致一些副作用。分子研究是有助于解密这一事件分子机制的方法之一。为此，作为蛋白质组补充研究的蛋白质-蛋白质相互作用（PPI）网络分析，在皮肤病变出现之前的早期暴露后，用于探索RT对脑癌的影响。使用Cytoscape 3.7.2及其插件分析治疗条件下蛋白质差异表达（DEP）网络，并通过NetworkAnalyzer和ClueGO+CluePedia进行中心性和通路富集分析。一个由15个DEP组成的网络表明，6个节点是网络稳定性的关键参与者，SERPINC1和F5来自查询蛋白质。蛋白质翻译后磷酸化、血小板脱颗粒以及补体和凝血级联反应通路是RT中可能受影响的中心节点最突出的通路。早期治疗网络的中心蛋白在皮肤病变出现之前的放射治疗反应机制中可能具有额外的重要性。引入的生物标志物可用于患者随访。经过验证研究批准后，这些候选物对于此类治疗值得给予精确关注。
