Raimondo Francesca, Corbetta Samuele, Savoia Andrea, Chinello Clizia, Cazzaniga Marta, Rocco Francesco, Bosari Silvano, Grasso Marco, Bovo Giorgio, Magni Fulvio, Pitto Marina
Department of Health Sciences, Univ. of Milano-Bicocca, Via Cadore 48, 20900, Monza, Italy.
Mol Biosyst. 2015 Jun;11(6):1708-16. doi: 10.1039/c5mb00020c.
Renal Cell Carcinoma (RCC) is the most common kidney cancer, accounting for 3% of adult malignancies, with high metastatic potential and radio-/chemo-resistance. To investigate the protein profile of membrane microdomains (MD), plasma membrane supramolecular structures involved in cell signaling, transport, and neoplastic transformation, we set up a proteomic bottom-up approach as a starting point for the identification of potential RCC biomarkers. We purified MD from RCC and adjacent normal kidney (ANK) tissues, through their resistance to non-ionic detergents followed by ultracentrifugation in sucrose density gradient. MD from 5 RCC/ANK tissues were then pooled and analysed by LC-ESI-MS/MS. In order to identify the highest number of proteins and increase the amount of membrane and hydrophobic ones, we first optimized an enzymatic digestion protocol based on Filter Aided Sample Preparation (FASP), coupled to MD delipidation. The MS analysis led to the identification of 742 ANK MD and 721 RCC MD proteins, of which, respectively, 53.1% and 52.6% were membrane- bound. Additionally, we evaluated RCC MD differential proteome by label-free quantification; 170 and 126 proteins were found to be, respectively, up-regulated and down-regulated in RCC MD. Some differential proteins, namely CA2, CD13, and ANXA2, were subjected to validation by immunodecoration. These results show the importance of setting up different protocols for the proteomic analysis of membrane proteins, specific to the different molecular features of the samples. Furthermore, the subcellular proteomic approach provided a list of differentially expressed proteins among which RCC biomarkers may be looked for.
肾细胞癌（RCC）是最常见的肾癌，占成人恶性肿瘤的3%，具有高转移潜能和放射/化学抗性。为了研究膜微区（MD）的蛋白质谱，膜微区是参与细胞信号传导、运输和肿瘤转化的质膜超分子结构，我们建立了一种自下而上的蛋白质组学方法，作为鉴定潜在RCC生物标志物的起点。我们通过对非离子去污剂的抗性，然后在蔗糖密度梯度中进行超速离心，从RCC和相邻正常肾（ANK）组织中纯化MD。然后将来自5个RCC/ANK组织的MD合并，并通过LC-ESI-MS/MS进行分析。为了鉴定最多数量的蛋白质并增加膜蛋白和疏水蛋白的数量，我们首先基于滤膜辅助样品制备（FASP）优化了一种酶消化方案，并结合MD脱脂。质谱分析鉴定出742种ANK MD蛋白和721种RCC MD蛋白，其中分别有53.1%和52.6%是膜结合蛋白。此外，我们通过无标记定量评估RCC MD差异蛋白质组；发现分别有170种和126种蛋白质在RCC MD中上调和下调。一些差异蛋白，即CA2、CD13和ANXA2，通过免疫染色进行验证。这些结果表明，针对样品的不同分子特征，建立不同的膜蛋白蛋白质组学分析方案非常重要。此外，亚细胞蛋白质组学方法提供了一份差异表达蛋白列表，从中可以寻找RCC生物标志物。
