Search

Liquid biopsies, as blood and urine, could offer an invaluable, easily accessible source of biomarkers, and evidences for elucidating the pathological processes. Only few studies integrated the proteomes driven by more than one biofluid. Furthermore, it is not clear which biofluid better mirrors the alterations triggered by disease. Venous infiltrating RCC(Renal Cell Carcinoma) could represent an advantageous model for exploring this aspect. Herein, we investigate how blood and urine “proteomically” reflect the changes occurring during RCC infiltration into renal vein(RV) by label-free nLC-ESI-MS/MS. We found 574 and 58 differentially expressed proteins(DEPs) in response to vascular involvement. To the augment of vascular involvement, the abundance of only three proteins in urine(UROM,RALA,CNDP1) and two in plasma(APOA1,K2C1) diminished while increased for twenty-six urinary proteins. 80 proteins were found both in urine and plasma, among which twenty-eight were DEPs. A huge overlap between the two biofluids was highlighted, as expected, being urine the filtrate of blood. However, this consistency decreases when RV-occlusion occurs suggesting alternative protein releases, and a loss of kidney architecture. Moreover, several proteomic and functional signatures were biofluid-specific. In conclusion, the complementarity between the specimens allowed to achieve a deeper level of molecular complexity of the RCC venous infiltration. Significance: Although plasma and urine are strongly interconnected, only few proteomic studies investigated the complementarity of these fluids as bio-sources of information. Moreover, none of them was focused to their analysis and comparison in the context of vascular infiltration of renal cancer. Herein, new insights were gained regarding the impact into urinary and plasma proteome of the changes triggered by the ccRCC invasion into vascular system and renal vein. Furthermore, the integration of the information driven by the two liquid biopsies permits to unravel biological processes otherwise lost.

The current TNM system for renal cell carcinoma (RCC) merges perirenal fat invasion (PFI) and renal vein invasion (RVI) as stage pT3a despite limited evidence concerning their prognostic equivalence. In addition, the prognostic value of PFI compared to pT1-pT2 tumors remains controversial.To analyze the prognostic significance of PFI, RVI, and tumor size in pT1-pT3a RCC.Data for 7384 pT1a-pT3a RCC patients were pooled from 12 centers. Patients were grouped according to stages and PFI/RVI presence as follows: pT1-2N0M0 (n=6137; 83.1%), pT3aN0M0 + PFI (n=1036; 14%), and pT3aN0M0 (RVI ± PFI; n=211; 2.9%).Radical nephrectomy or nephron-sparing surgery (NSS) (1992-2010).Cancer-specific survival was estimated using the Kaplan-Meier method. Univariate and multivariate Cox proportional-hazards regression models, as well as sensitivity and discrimination analyses, were used to evaluate the impact of clinicopathologic parameters on cancer-specific mortality (CSM).Compared to stage pT1-2, patients with stage pT3a RCC were significantly more often male (59.4% vs 53.1%) and older (64.9 vs 62.1 yr), more often had clear cell RCC (85.2% vs 77.7%), Fuhrman grade 3-4 (29.4% vs 13.4%), and tumor size7 cm (39.1% vs 13%), and underwent NSS less often (7.5% vs 36.6%; all p0.001). According to multivariate analysis, CSM was significantly higher for the PFI and RVI ± PFI groups compared to pT1-2 patients (hazard ratio [HR] 1.94 and 2.12, respectively; p0.001), whereas patients with PFI only and RVI ± PFI did not differ (HR 1.17; p=0.316). Tumor size instead enhanced CSM by 7% per cm in stage pT3a (HR 1.07; p0.001) with a 7 cm cutoff yielding the highest prediction accuracy.Since the prognostic impact of PFI and RVI on CSM seems to be comparable, merging both as stage pT3a RCC might be justified. Enhanced prognostic discrimination of stage pT3a RCC appears to be possible by applying a tumor size cutoff of 7 cm within an alternative staging system.Prognosis prediction for patients with localized renal cell carcinoma up to stage pT3a can be enhanced by including tumor size with a cutoff of 7 cm as an additional parameter in the TNM classification system.