Understand the acquired resistance of RTK inhibitors by computational receptor tyrosine kinases network. (October 2018)

• Record Type: Journal Article
• Authors: Tian, Yuanxin; Ma, Yunci; Wu, Shaoyu; Zhang, Tingting; Li, Zhonghuang; Wang, Guangfa; Zhang, Jiajie
• Is Part Of: Computational biology and chemistry. Volume 76(2018)
• Page Start: 275
• Page End: 282
• Publication Date: 2018-10
• Subjects: Tyrosine kinase inhibitors -- Resistance -- Protein-protein interaction -- Network analysis; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2018.07.017
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Based on the PPI network retrieved from 52 RTKs, a global view to understand the acquired resistance of RTK inhibitors was presented. The results indicated that most RTKs proteins were the key controllers of the protein-protein network. Direct or indirect interactions with EGFR (shortest path of 2) were often associated with resistance to RTK inhibitors in the literature. The pathway analysis also reminded Rap1 pathway might contribute to the resistance of RTKs. Our results provided clues to combining the different targets or pathways for synergy of targeted RTKs inhibitors. Highlights: The acquired resistance of RTKs inhibitors was investigated based on the protein-protein interaction network with a global view. The protein RTKs were the controller in the PPI network, their interactions directly or by shortest path of 2 were associated with resistance. The Rap1 pathway would be another pathway which contribute to the resistance of RTKs inhibitor besides the known Ras or PI3K/Akt pathway. Abstract: Receptor Tyrosine Kinase inhibitors are the most popular anti-cancer drug types. But the resistance is the major challenge. Our study on the network with 1334 proteins and their 2623 interactions which retrieved from 52 RTKs indicated that most RTKs proteins were the key controllers of the protein-protein network. Direct or indirect interactions with RTKs (shortest path of 2) were often associated with resistance to RTKs inhibitors in the literature. The results based on the KEGG pathway analysis demonstrated the Rap1 signal pathway would also contribute to the resistance of RTKs inhibitor as well as the known Ras pathway and PI3K/Akt pathway. The pathways can crosstalk within and between complex signals transduction networks, then activate the upstream or downstream pathway, and/or activate the other oncogenes, which lead to the acquired resistance. Our results gave a systematically global view to understand the drug resistance and provided a clue to how to combine the different targets or pathways for synergy of targeted RTKs inhibitors.