biostudies-literatureNiziol JNIH SIGThe National Science FoundationNCRR NIH HHSNarodowe Centrum Naukithe Murdock Charitable Trust Foundation5827-5841https://www.ebi.ac.uk/biostudies/studies/S-EPMC7413895biostudies-literatureUnknown412(23)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 (<sup>1</sup>H NMR) and silver-109 nanoparticle-enhanced steel target laser desorption/ionization mass spectrometry (<sup>109</sup>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 <sup>1</sup>H NMR metabolomics and nine mass spectral features which differed significantly (p < 0.0Analytical and bioanalytical chemistryNuclear magnetic resonance and surface-assisted laser desorption/ionization mass spectrometry-based serum metabolomics of kidney cancer.PMC74138951S10RR13878 and 1S10RR0266592015066:MNL2016/23/B/ST4/00062S10 RR026659NSF-MRI:DBI-1532078Copie VTripet BPArendowski ANiziol JRuman TOssolinski KfalseNuclear magnetic resonance and surface-assisted laser desorption/ionization mass spectrometry-based serum metabolomics of kidney cancer.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 (<sup>1</sup>H NMR) and silver-109 nanoparticle-enhanced steel target laser desorption/ionization mass spectrometry (<sup>109</sup>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 <sup>1</sup>H NMR metabolomics and nine mass spectral features which differed significantly (p < 0.02020-01-01T00:00:00Z2020 Sep2026-06-01T18:16:22.507Z2025-02-19T00:59:12.545ZS-EPMC74138953266167710.1007/s00216-020-02807-1