LC-MS-based serum metabolic profiling for genitourinary cancer classification and cancer type-specific biomarker discovery.
Bladder cancer (BC) and kidney cancer (KC) are the first two commonly occurring genitourinary cancers in China. In this study, a comprehensive LC-MS-based method, which utilizes both reversed phase liquid chromatography (RPLC) and hydrophilic interaction chromatography (HILIC) separations, has been carried out in conjunction with multivariate data analysis to discriminate the global serum profiles of BC, KC, and noncancer controls. An independent test set consisting of different patients has been used to objectively evaluate the predictive ability of the analysis platform. Excellent sensitivity and specificity have been achieved in detection of KC and BC. The results suggest that serum metabolic profiling could be used for different types of genitourinary cancer diagnosis. Furthermore, cancer type-specific biomarkers were found through a critical selection criterion. As a result, eicosatrienol, azaprostanoic acid, docosatrienol, retinol, and 14'-apo-beta-carotenal  were found as specific biomarkers for BC; and PE(P-16:0e/0:0), glycerophosphorylcholine, ganglioside GM3 (d18:1/22:1), C17 sphinganine, and SM(d18:0/16:1(9Z)) were found as specific biomarkers for KC. Receiver operating characteristic (ROC) analysis was used for the preliminary evaluation of the biomarkers. These biomarkers have great potential to be used in the clinical diagnosis after further rigorous assessment.
Department of Chemistry, Key Laboratory of Analytical Sciences, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China.
Lin
L
Lin
Zhenzhen
Z
Huang
Yao
Y
Gao
Yongjing
Y
Chen
Wei
W
Hang
Jinchun
J
Xing
Xiaomei
X
Yan
D014408:Biomarkers, Tumor / Q000097:blood*; D056148:Chromatography, Reverse-Phase / Q000379:methods; D006801:Humans; D007680:Kidney Neoplasms / Q000097:blood* / Q000145:classification*; D013058:Mass Spectrometry / Q000379:methods; D055442:Metabolome; D055432:Metabolomics / Q000379:methods*; D015999:Multivariate Analysis; D025341:Principal Component Analysis; D012372:ROC Curve; D012680:Sensitivity and Specificity; D001749:Urinary Bladder Neoplasms / Q000097:blood* / Q000145:classification*
D014408:Biomarkers, Tumor