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吉西他滨与比瑞那潘联合作用于胰腺癌细胞的蛋白质组学分析

Proteomic Analysis of Combined Gemcitabine and Birinapant in Pancreatic Cancer Cells.

作者信息

Zhu Xu, Shen Xiaomeng, Qu Jun, Straubinger Robert M, Jusko William J

机构信息

Department of Pharmaceutical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States.

Department of Biochemistry, University at Buffalo, The State University of New York, Buffalo, NY, United States.

出版信息

Front Pharmacol. 2018 Feb 19;9:84. doi: 10.3389/fphar.2018.00084. eCollection 2018.

Abstract

Pancreatic cancer is characterized by mutated signaling pathways and a high incidence of drug resistance. Comprehensive, large-scale proteomic analysis can provide a system-wide view of signaling networks, assist in understanding drug mechanisms of action and interactions, and serve as a useful tool for pancreatic cancer research. In this study, liquid chromatography-mass spectrometry-based proteomic analysis was applied to characterize the combination of gemcitabine and birinapant in pancreatic cancer cells, which was shown previously to be synergistic. A total of 4069 drug-responsive proteins were identified and quantified in a time-series proteome analysis. This rich dataset provides broad views and accurate quantification of signaling pathways. Pathways relating to DNA damage response regulations, DNA repair, anti-apoptosis, pro-migration/invasion were implicated as underlying mechanisms for gemcitabine resistance and for the beneficial effects of the drug combination. Promising drug targets were identified for future investigation. This study also provides a database for systems mathematical modeling to relate drug effects and interactions in various signaling pathways in pancreatic cancer cells.

摘要

胰腺癌的特征是信号通路发生突变且耐药性发生率高。全面、大规模的蛋白质组学分析可以提供信号网络的全系统视图,有助于理解药物作用机制和相互作用,并作为胰腺癌研究的有用工具。在本研究中,基于液相色谱-质谱的蛋白质组学分析被用于表征吉西他滨和比瑞那潘在胰腺癌细胞中的联合作用,此前已证明二者具有协同作用。在一项时间序列蛋白质组分析中,共鉴定并定量了4069种药物反应蛋白。这个丰富的数据集提供了信号通路的广泛视图和准确量化。与DNA损伤反应调节、DNA修复、抗凋亡、促迁移/侵袭相关的通路被认为是吉西他滨耐药以及药物联合有益作用的潜在机制。确定了有前景的药物靶点以供未来研究。本研究还为系统数学建模提供了一个数据库,以关联胰腺癌细胞中各种信号通路中的药物作用和相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/375b/5827530/5d08704acd05/fphar-09-00084-g001.jpg

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