Abstract
PurposeRenal cell carcinoma (RCC) is a very aggressive and often fatal heterogeneous disease that is usually asymptomatic until late in the disease. There is an urgent need for RCC specific biomarkers that may be exploited clinically for diagnostic and prognostic purposes. Materials/methodsSerum and urine samples were collected from patients with diagnosed kidney cancer and assessed with gold nanoparticle enhanced target (AuNPET) surface assisted-laser desorption/ionization mass spectrometry (SALDI MS) based metabolomics and statistical analysis. ResultsA database search allowed providing assignment of signals for the most promising features with a satisfactory value of the area under the curve and accuracy. Four potential biomarkers were found in urine and serum samples to distinguish clear cell renal cell carcinoma (ccRCC) from controls, 4 for the ccRCC with and without metastases, and 6 metabolites to distinguish low and high stages or grades. ConclusionsThis pilot study suggests that serum and urine metabolomics based on AuNPET-LDI MS may be useful in distinguishing types, grades and stages of human RCC.
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