Department of Protein Biochemistry and Proteomics, Technological Centre of the Palacký University, Centre of the Region Haná for Biotechnological and Agricultural Research, Olomouc, Czech Republic.
J Proteome Res. 2013 Sep 6;12(9):4005-17. doi: 10.1021/pr400309p. Epub 2013 Aug 20.
While targeted therapy based on the idea of attenuating the activity of a preselected, therapeutically relevant protein has become one of the major trends in modern cancer therapy, no truly specific targeted drug has been developed and most clinical agents have displayed a degree of polypharmacology. Therefore, the specificity of anticancer therapeutics has emerged as a highly important but severely underestimated issue. Chemical proteomics is a powerful technique combining postgenomic drug-affinity chromatography with high-end mass spectrometry analysis and bioinformatic data processing to assemble a target profile of a desired therapeutic molecule. Due to high demands on the starting material, however, chemical proteomic studies have been mostly limited to cancer cell lines. Herein, we report a down-scaling of the technique to enable the analysis of very low abundance samples, as those obtained from needle biopsies. By a systematic investigation of several important parameters in pull-downs with the multikinase inhibitor bosutinib, the standard experimental protocol was optimized to 100 μg protein input. At this level, more than 30 well-known targets were detected per single pull-down replicate with high reproducibility. Moreover, as presented by the comprehensive target profile obtained from miniaturized pull-downs with another clinical drug, dasatinib, the optimized protocol seems to be extendable to other drugs of interest. Sixty distinct human and murine targets were finally identified for bosutinib and dasatinib in chemical proteomic experiments utilizing core needle biopsy samples from xenotransplants derived from patient tumor tissue. Altogether, the developed methodology proves robust and generic and holds many promises for the field of personalized health care.
虽然基于减弱预先选定的、治疗相关蛋白的活性的靶向治疗理念已成为现代癌症治疗的主要趋势之一，但目前还没有真正特异性的靶向药物被开发出来，而且大多数临床药物都表现出一定程度的多药理学。因此，抗癌治疗的特异性已成为一个非常重要但严重被低估的问题。化学蛋白质组学是一种强大的技术，它将基于基因组的药物亲和色谱与高端质谱分析和生物信息学数据处理相结合，以构建所需治疗分子的靶标图谱。然而，由于对起始材料的高要求，化学蛋白质组学研究大多局限于癌细胞系。在此，我们报告了该技术的缩小规模，使其能够分析非常低丰度的样品，如来自针吸活检的样品。通过对多激酶抑制剂博舒替尼的下拉实验中的几个重要参数进行系统研究，我们将标准实验方案优化至 100 μg 蛋白质输入。在这个水平上，每个下拉重复实验可以检测到 30 多个已知靶点，且具有很高的重现性。此外，通过从小型下拉实验中获得的另一种临床药物达沙替尼的综合靶标图谱，优化后的方案似乎可以扩展到其他感兴趣的药物。最终，在利用源自患者肿瘤组织的异种移植的核心针活检样本进行的化学蛋白质组学实验中，鉴定出博舒替尼和达沙替尼的 60 个独特的人类和鼠类靶标。总之，开发的方法学证明是稳健和通用的，并为个性化医疗保健领域带来了许多希望。
