title: [Urinary metabolomics study of renal cell carcinoma based on gas chromatography-mass spectrometry].
abstract: OBJECTIVE
  To identify the biomarkers of renal cell cancer (RCC) through urine metabolic analysis.
  
  
  METHODS
  Urine samples of 27 RCC patients, 26 patients with other urinary cancers and 26 healthy volunteers were examined with gas chromatography-mass spectrometry (GC-MS). SIMCA-P+12.0.1.0 software was used for principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) to screen for the differential metabolites.
  
  
  RESULTS
  PCA (R2X=0.846, Q2=0.575) and OPLS-DA (R2X=0.736, R2Y=0.974, Q2Y=0.897) model were established for the RCC patients and control subjects. Fourteen metabolites were selected as the characteristic metabolites, including pentanoic acid, malonic acid, glutaric acid, adipic acid, amino quinoline, quinoline, indole acetic acid, and tryptophan, whose levels in the urine were significantly higher in the RCC patients than in the normal subjects (P<0.01); the RCC patients showed significantly higher urine contents of pentanoic acid, phenylalanine, and 6-methoxy-nitro quinoline than those with other urinary tumors (P<0.01).
  
  
  CONCLUSIONS
  The urine metabolites identified based on GC-MS analysis can distinguish RCC patients from patients with other urinary cancers and healthy subjects, suggesting their potential as diagnostic markers for RCC.
authors.affiliation: Laboratory Medicine Center, Southern Medical University, Nanfang Hospital, Guangzhou 510515, China.E-mail: jzhanglin@126.com.
authors.forename: Lin
authors.initials: L
authors.lastname: Zhang
authors.forename: Ling
authors.initials: L
authors.lastname: Li
authors.forename: Hairui
authors.initials: H
authors.lastname: Kong
authors.forename: Fangyin
authors.initials: F
authors.lastname: Zeng
mesh_terms: D015415:Biomarkers / Q000652:urine*; D002292:Carcinoma, Renal Cell / Q000652:urine*; D016002:Discriminant Analysis; D008401:Gas Chromatography-Mass Spectrometry; D006801:Humans; D016018:Least-Squares Analysis; D055442:Metabolome; D055432:Metabolomics; D025341:Principal Component Analysis; D012984:Software
chemical_list: D015415:Biomarkers