Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, NY 14260 USA.
New York State Center of Excellence in Bioinformatics and Life Sciences, 701 Ellicott Street, Buffalo, NY 14203 USA.
J Proteomics. 2012 Dec 21;77:187-201. doi: 10.1016/j.jprot.2012.08.020. Epub 2012 Sep 7.
Proteome-level investigation of the molecular targets in anticancer action of promising pharmaceutical candidates is highly desirable but remains challenging due to the insufficient proteome coverage, limited capacity for biological replicates, and largely unregulated false positive biomarker discovery of current methods. This study described a practical platform strategy to address these challenges, using comparison of drug response proteomic signatures by two promising anti-cancer agents (KX01/KX02) as the model system for method development/optimization. Drug-treated samples were efficiently extracted followed by precipitation/on-pellet-digestion procedure that provides high, reproducible peptide recovery. High-resolution separations were performed on a 75-cm-long, heated nano-LC column with a 7-h gradient, with a highly reproducible nano-LC/nanospray configuration. An LTQ Orbitrap hybrid mass spectrometer with a charge overfilling approach to enhance sensitivity was used for detection. Analytical procedures were optimized and well-controlled to achieve high run-to-run reproducibility that permits numerous replicates in one set, and an ion-current-based approach was utilized for quantification. The false positives of biomarker discovery arising from technical variability was controlled based on FBDR measurement by comparing biomarker numbers in each drug-treated group vs. "sham samples", which were analyzed in an order randomly interleaved with the analysis drug-treated samples. More than 1500 unique protein groups were quantified under stringent criteria, and of which about 30% displayed differential expression with FBDR of 0.3-2.1% across groups. Comparison of drug-response proteomic signatures and the subsequent immunoassay revealed that the action mechanisms of KX01/KX02 are similar but significantly different from vinblastine, which correlates well with clinical and pre-clinical observations. Furthermore, the results strongly supported the hypothesis that KX01/KX02 are dual-action agents (through inhibition of tubulin and Src). Moreover, informative insights into the drug-actions on cell cycle, growth/proliferation, and apoptosis were obtained. This platform technology provides extensive evaluation of drug candidates and facilitates in-depth mechanism studies.
对有前景的药物候选物在抗癌作用中的分子靶标进行蛋白质组水平的研究是非常需要的,但由于目前方法的蛋白质组覆盖不足、生物重复能力有限以及大量不受监管的假阳性生物标志物发现,这仍然具有挑战性。本研究描述了一种实用的平台策略,以解决这些挑战,使用两种有前景的抗癌药物(KX01/KX02)的药物反应蛋白质组特征比较作为方法开发/优化的模型系统。通过沉淀/沉淀上消化程序有效地提取药物处理的样品,该程序提供了高、可重复的肽回收。在具有 7 小时梯度的 75cm 长加热纳升 LC 柱上进行高分辨率分离,并采用高度可重复的纳升 LC/纳升喷雾配置。使用带有电荷过充方法的 LTQ Orbitrap 混合质谱仪进行检测,以提高灵敏度。优化了分析程序,并进行了很好的控制,以实现高运行到运行的重现性,从而在一组中实现多个重复,并采用基于离子电流的方法进行定量。通过比较每个药物处理组与“假样本”中的生物标志物数量,基于 FBDR 测量控制生物标志物发现中的假阳性,“假样本”以与分析药物处理样本随机交错的顺序进行分析。在严格的标准下定量了超过 1500 个独特的蛋白质组,其中约 30%的蛋白质组在组间显示出差异表达,FBDR 为 0.3-2.1%。药物反应蛋白质组特征的比较和随后的免疫测定表明,KX01/KX02 的作用机制与长春碱相似但有显著差异,这与临床和临床前观察结果很好地相关。此外,结果强烈支持了 KX01/KX02 是双重作用剂(通过抑制微管蛋白和 Src)的假设。此外,还获得了关于药物对细胞周期、生长/增殖和凋亡作用的有意义的见解。该平台技术提供了对候选药物的广泛评估,并促进了深入的机制研究。