Bohnenberger Hanibal, Ströbel Philipp, Mohr Sebastian, Corso Jasmin, Berg Tobias, Urlaub Henning, Lenz Christof, Serve Hubert, Oellerich Thomas
Institute of Pathology, University Medical Center, Göttingen;
Institute of Pathology, University Medical Center, Göttingen.
J Vis Exp. 2015 Feb 27(96):e52435. doi: 10.3791/52435.
In-depth analyses of cancer cell proteomes are needed to elucidate oncogenic pathomechanisms, as well as to identify potential drug targets and diagnostic biomarkers. However, methods for quantitative proteomic characterization of patient-derived tumors and in particular their cellular subpopulations are largely lacking. Here we describe an experimental set-up that allows quantitative analysis of proteomes of cancer cell subpopulations derived from either liquid or solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry followed by bioinformatic data analysis. To enrich specific cellular subsets, liquid tumors are first immunophenotyped by flow cytometry followed by FACS-sorting; for solid tumors, laser-capture microdissection is used to purify specific cellular subpopulations. In a second step, proteins are extracted from the purified cells and subsequently combined with a tumor-specific, SILAC-labeled spike-in standard that enables protein quantification. The resulting protein mixture is subjected to either gel electrophoresis or Filter Aided Sample Preparation (FASP) followed by tryptic digestion. Finally, tryptic peptides are analyzed using a hybrid quadrupole-orbitrap mass spectrometer, and the data obtained are processed with bioinformatic software suites including MaxQuant. By means of the workflow presented here, up to 8,000 proteins can be identified and quantified in patient-derived samples, and the resulting protein expression profiles can be compared among patients to identify diagnostic proteomic signatures or potential drug targets.
深入分析癌细胞蛋白质组对于阐明致癌病理机制以及识别潜在的药物靶点和诊断生物标志物至关重要。然而,用于对患者来源肿瘤尤其是其细胞亚群进行定量蛋白质组学表征的方法在很大程度上尚付阙如。在此,我们描述了一种实验方案,该方案能够对源自液体或实体肿瘤的癌细胞亚群的蛋白质组进行定量分析。这是通过将细胞富集策略与基于Super-SILAC的定量质谱联用,随后进行生物信息数据分析来实现的。为了富集特定的细胞亚群,首先通过流式细胞术对液体肿瘤进行免疫表型分析,然后进行荧光激活细胞分选(FACS);对于实体肿瘤,则使用激光捕获显微切割技术来纯化特定的细胞亚群。第二步,从纯化的细胞中提取蛋白质,随后与肿瘤特异性的、经SILAC标记的内标标准品混合,以实现蛋白质定量。将所得的蛋白质混合物进行凝胶电泳或滤膜辅助样品制备(FASP),随后进行胰蛋白酶消化。最后,使用混合四极杆-轨道阱质谱仪分析胰蛋白酶肽段,并使用包括MaxQuant在内的生物信息学软件套件对获得的数据进行处理。通过本文介绍的工作流程,在患者来源的样本中可识别和定量多达8000种蛋白质,并且可以在患者之间比较所得的蛋白质表达谱,以识别诊断性蛋白质组特征或潜在的药物靶点。