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.