aRenal cell carcinoma (RCC) accounts for about 3% of all human malignancies and its incidence is increasing. There are no standard biomarkers currently used in the clinical management of patients with renal cell carcinoma. A promising strategy for new biomarker detection is comparative proteomics of urinary exosomes (UE), nanovesicles released by every epithelial cell facing the urinary space, enriched in renal proteins and excluding high-abundance plasmatic proteins, such as albumin. Aim of the work is to establish the protein profile of exosomes isolated from urines of RCC patient compared with control subjects. We enrolled 29 clear cell RCC patients and 23 control healthy subjects (CTRL), age and sex-matched, for urine collection and vesicle isolation by differential centrifugation. Such vesicles were morphologically and biochemically characterized and proved to share exosome properties.Proteomic analysis, performed on 9 urinary exosome (UE) pooled samples by gel based digestion followed by LC-MS/MS, led to the identification of 261 proteins from CTRL subject UE and 186 from RCC patient UE, and demonstrated that most of the identified proteins are membrane associated or cytoplasmic. Moreover, about a half of identified proteins are not shared between RCC and control UE.Starting from these observations, and from the literature, we selected a panel of 10 proteins, whose UE differential content was subjected to immunoblotting validation. Results show for the first time that RCC UE protein content is substantially and reproducibly different from control UE, and that these differences may provide clues for new RCC biomarker discovery.

UE phenotyping may be useful in the diagnosis of GS and BS, thus providing an alternative/complementary, urine-based diagnostic tool for SLT patient recognition and a diagnostic guidance in complex cases.

Urinary exosomes (UE) are nanovesicles released by every epithelial cell facing the urinary space and they are considered a promising source of molecular markers for renal dysfunction and structural injury. Exosomal proteomics has emerged as a powerful tool for understanding the molecular composition of exosomes and has potential to accelerate biomarker discovery. We employed this strategy in the study of diabetic nephropathy (DN) and the consequent end stage renal disease, which represent the dramatic evolution of diabetes, often leading the patients to dialysis or kidney transplantation. The identification of DN biomarkers is likely to help monitoring the disease onset and progression. A label free LC-MS/MS approach was applied to investigate the alteration of the proteome of urinary exosomes isolated from the Zucker diabetic fatty rats (ZDF), as a model of type 2 DN. We collected 24 hour urine samples from 7 ZDF and from 7 control rats at different ages (6, 12 and 20 weeks old) to monitor the development of DN. Exosomes were isolated by ultracentrifugation and their purity assessed by immunoblotting for known exosomal markers. Exosomal proteins from urine samples of 20 week old rats were pooled and analyzed by nLC-ESI-UHR-QToF-MS/MS after pre-filtration and tryptic digestion, leading to the identification and label free quantification of 286 proteins. Subcellular localization and molecular functions were assigned to each protein by UniprotKB, showing that the majority of identified proteins were membrane-associated or cytoplasmic and involved in transport, signalling and cellular adhesion, typical functions of exosomal proteins. We further validated label free mass spectrometry results by immunoblotting, as exemplified by: Xaa-Pro dipeptidase, Major Urinary Protein 1 and Neprilysin, which resulted increased, decreased and not different, respectively, in exosomes isolated from diabetic urine samples compared to controls, by both techniques. In conclusion we show the potential of exosome proteomics for DN biomarker discovery.

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.

Renal cell carcinomas, originating from the renal cortex, account for about 80% of kidney primary malignancies. Small localized tumors rarely produce symptoms and diagnosis is often delayed until the disease is advanced. In contrast to other urological cancers, renal cell carcinomas are associated with a high degree of metastases and a low 5-year survival rate. The identification of diagnostic and prognostic markers, especially in the urine, remains an area of intense investigation. Different proteomic strategies have been applied so far to biomarker discovery in urine at the proteome or the peptidome level. Gel-based and gel-free strategies combined with mass spectrometry are the most-used strategies, have different success rates, and will be depicted here. We also prefigure a scenario in which the limitations of a single approach are overcome by applying new and complementary research strategies, relying on the excellent availability coupled to the intrinsic richness typical of urine samples.