Table 2.

Examples of proteomic approaches for characterizing RCC tissue, blood-associated (plasma/serum), or urine specimens

Biological source	# of samples	Experimental approach	# of differentially expressed targets	Citing report
Tissue	50	Used LFQ approach to identify proteins associated with tumor grade, profiling NAT and ccRCC tissues with Furman grades between 1 and 4	105	[42]
Tissue	75	Employed MALDI-MSI to identify differential expressed proteins associated with the tumor, tumor margin, and NAT regions	12	[56]
Tissue	194	Utilized proteogenomic approach; TMT-based quantitation for delineating differential global protein and phosphopeptide/phosphosite profiles between tumors and NATs	820	[20]
Serum	162	Profiled the serum peptidome in healthy controls, ccRCC patients, and ccRCC patients before and after surgical resection	18	[86]
Serum	99	Examined urine proteome profiles to discriminate ccRCC from healthy controls, benign kidney masses, and non-ccRCC urological tumors	27	[80]
Urine	254	Examined serum peptidome profiles to discriminate ccRCC from healthy controls, prioritizing discriminatory clinicopathological-associated features (stage, grade, tumor size)	15	[101]
Urine	90	Used LFQ to characterize the urinary proteome of ccRCC patients and healthy controls; stratifying ccRCC patients into good or poor prognosis groups based on Furhman grading	49	[92]
Tissue/EVs	40	Used an ex vivo model to profile extracellular vesicles (EVs) derived from ccRCC tumors and NATs	397	[112]