Biased random walk model for the prioritization of drug resistance associated proteins.
作者： Hao Guo , Jiaqiang Dong , Sijun Hu , Xiqiang Cai , Guangbo Tang
DOI: 10.1038/SREP10857
关键词:
摘要: Multi-drug resistance is the main cause of treatment failure in cancer patients. How to identify molecules underlying drug from multi-omics data remains a great challenge. Here, we introduce biased strategy, ProteinRank, prioritize drug-resistance associated proteins cells. First, identified differentially expressed Adriamycin and Vincristine resistant gastric cells compared their parental using iTRAQ combined with LC-MS/MS experiments, then mapped them human protein-protein interaction network; second, applied ProteinRank analyze whole network rank similar known related proteins. Cross validations demonstrated better performance method without usage MS data. Further confirmed altered expressions or activities several top ranked Functional study showed PIM3 CAV1 silencing was sufficient reverse phenotype. These results indicated could key provided important clues for research.
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