Nuclear magnetic resonance and surface-assisted laser desorption/ionization mass spectrometry-based serum metabolomics of kidney cancer

• Published in: Analytical and bioanalytical chemistry Vol. 412; no. 23; pp. 5827 - 5841
• Main Authors: Nizioł, Joanna, Ossoliński, Krzysztof, Tripet, Brian P., Copié, Valérie, Arendowski, Adrian, Ruman, Tomasz
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2020; Springer; Springer Nature B.V
• Subjects: Adult; Aged; Aged, 80 and over; Analytical Chemistry; Biochemistry; Biomarkers; Biomarkers, Tumor - blood; Cancer; Care and treatment; Case-Control Studies; Characterization and Evaluation of Materials; Chemistry; Chemistry and Materials Science; Choline; Data analysis; Desorption; Diagnosis; Discriminant analysis; Female; Food Science; Glycerol; Glycine; Humans; Identification methods; Information management; Inositol; Ionization; Ions; Kidney cancer; Kidney Neoplasms - blood; Kidneys; Laboratory Medicine; Lactic acid; Leucine; Magnetic resonance spectroscopy; Magnetic Resonance Spectroscopy - methods; Male; Mass spectrometry; Mass Spectrometry - methods; Mass spectroscopy; Metabolism; Metabolites; Metabolomics; Metabolomics - methods; Middle Aged; Monitoring/Environmental Analysis; Multivariate analysis; Nanoparticles; NMR; Nuclear magnetic resonance; Nuclear magnetic resonance spectroscopy; Research Paper; Scientific imaging; Silver; Poland; Taiwan; Biomarkers; Proton nuclear magnetic resonance; Mass spectrometry; Kidney; Cancer
• ISSN: 1618-2642; 1618-2650
• DOI: 10.1007/s00216-020-02807-1

Kidney cancer is one of the most frequently diagnosed and the most lethal urinary cancer. Despite all the efforts made, no serum-specific biomarker is currently used in the clinical management of patients with this tumor. In this study, comprehensive high-resolution proton nuclear magnetic resonance spectroscopy ( 1 H NMR) and silver-109 nanoparticle-enhanced steel target laser desorption/ionization mass spectrometry ( 109 AgNPET LDI MS) approaches were conducted, in conjunction with multivariate data analysis, to discriminate the global serum metabolic profiles of kidney cancer ( n  = 50) and healthy volunteers ( n  = 49). Eight potential biomarkers have been identified using 1 H NMR metabolomics and nine mass spectral features which differed significantly ( p  < 0.05) between kidney cancer patients and healthy volunteers, as observed by LDI MS. A partial least squares discriminant analysis (OPLS-DA) model generated from metabolic profiles obtained by both analytical approaches could robustly discriminate normal from cancerous samples (Q 2  > 0.7), area under the receiver operative characteristic curve (ROC) AUC > 0.96. Compared with healthy human serum, kidney cancer serum had higher levels of glucose and lower levels of choline, glycerol, glycine, lactate, leucine, myo -inositol, and 1-methylhistidine. Analysis of differences between these metabolite levels in patients with different types and grades of kidney cancer was undertaken. Our results, derived from the combination of LDI MS and 1 H NMR methods, suggest that serum biomarkers identified herein appeared to have great potential for use in clinical prognosis and/or diagnosis of kidney cancer. Graphical abstract