Metabolite Profiles of the Serum of XXXX with Non-Small Cell Carcinoma.

@entity1 @entity5 @entity957 @entity2 @entity420 @entity34
INTRODUCTION: Alterations of serum metabolites may allow us to identify individuals with @entity2 and advance our understanding of the nature and treatment of their @entity5 . We aimed to identify serum metabolites that differentiate @entity1 with @entity2 from at-risk controls. METHODS: Serum samples from @entity1 with biopsy-confirmed untreated stage I through @entity5 and at-risk controls were divided into fractions for analysis by ultrahigh-performance liquid chromatography-tandem mass spectrometry and gas chromatography-mass spectrometry. Compounds were identified by comparison with library entries of purified standards. Differences in concentrations of single metabolites and metabolite ratios were identified. Prediction models were developed. RESULTS: Serum samples from 284 subjects was analyzed. The subjects' mean age was 67 and 48% were female. Ninety-four @entity1 had @entity2 (50 had @entity420 and 44 had @entity957 ), 44% had stage I disease, 17% had @entity34 , and 39% had @entity5 . The @entity1 with @entity5 were slightly older than the controls (68.7 versus 66.2 years, p  = 0.013). A total of 534 metabolites were identified in eight metabolite superpathways and 73 subpathways. The concentrations of 149 metabolites differed significantly (q values <0.05) between the @entity5 and control groups (70 were lower in the @entity5 group and 79 were higher), and 9723 metabolite ratios differed significantly (q values <0.001) between the @entity5 and control groups. The accuracies of the models ( @entity5 and @entity5 subtypes versus control) trained on 70% of the subjects and tested on 30% (expressed as C-statistics) ranged from 0.748 to 0.858. CONCLUSIONS: Differences in the serum metabolite profile exist between @entity1 with stage I through @entity5 and matched controls.
