Abstract
Kidney cancer is a disease diagnosed annually in 400,000 people for which there are no specific biomarkers found to date. It is therefore important to search for new chemical compounds to detect cancer state. Laser desorption/ionization mass spectrometry on gold nanoparticle-enhanced target (AuNPET) method was used in this work for rapid metabolic analysis of blood serum of fifty patients with renal cancer. Comparison with data from sera of fifty healthy volunteers allowed discovering potential biomarkers of renal cell carcinoma (RCC). Statistical analysis of m/z values that had the greatest impact on group differentiation allowed. Database search allowed providing assignment of signals for the most promising eleven features among them: dihydrouracil, creatinine, glutamine, tyrosine, 2,3-diaminosalicylic acid, 3-hydroxykynurenine, 2-hydroxylauroylcarnitine, melatonin glucuronide, palmitoyl glucuronide, triglyceride(52:4) or phosphatidylcholine(42:0). This work demonstrate that the differences in metabolite profiles in serum of kidney cancer patients and that of healthy subjects could be identified by gold nanostructures LDI MS – based metabolomics and exploited as metabolic serum markers for the early detection of kidney cancer.
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