INTRODUCTION: Alterations of serum metabolites may allow us to identify individuals with lung cancer and advance our understanding of the nature and treatment of their cancer. We aimed to identify serum metabolites that differentiate patients with lung cancer from at-risk controls. METHODS: Serum samples from patients with biopsy-confirmed untreated stage I through stage III non-small cell lung cancer 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 patients had lung cancer (50 had adenocarcinoma and 44 had squamous cell carcinoma), 44% had stage I disease, 17% had stage II disease, and 39% had stage III disease. The patients with cancer 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 cancer and control groups (70 were lower in the cancer group and 79 were higher), and 9723 metabolite ratios differed significantly (q values <0.001) between the cancer and control groups. The accuracies of the models (cancer and cancer 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 patients with stage I through stage III non-small cell lung cancer and matched controls.
INTRODUCTION: Alterations of serum metabolites may allow us to identify individuals with lung cancer and advance our understanding of the nature and treatment of their cancer. We aimed to identify serum metabolites that differentiate patients with lung cancer from at-risk controls. METHODS: Serum samples from patients with biopsy-confirmed untreated stage I through stage III non-small cell lung cancer 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 patients had lung cancer (50 had adenocarcinoma and 44 had squamous cell carcinoma), 44% had stage I disease, 17% had stage II disease, and 39% had stage III disease. The patients with cancer 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 cancer and control groups (70 were lower in the cancer group and 79 were higher), and 9723 metabolite ratios differed significantly (q values <0.001) between the cancer and control groups. The accuracies of the models (cancer and cancer 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 patients with stage I through stage III non-small cell lung cancer and matched controls.
Authors: Inês Laíns; Rachel S Kelly; John B Miller; Rufino Silva; Demetrios G Vavvas; Ivana K Kim; Joaquim N Murta; Jessica Lasky-Su; Joan W Miller; Deeba Husain Journal: Ophthalmology Date: 2017-09-12 Impact factor: 12.079
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Authors: Sonia T Anand; Kelli K Ryckman; Rebecca J Baer; Mary E Charlton; Patrick J Breheny; William W Terry; Kord Kober; Scott Oltman; Elizabeth E Rogers; Laura L Jelliffe-Pawlowski; Elizabeth A Chrischilles Journal: J Matern Fetal Neonatal Med Date: 2021-05-12
Authors: Shuguang Leng; Guodong Wu; Donna M Klinge; Cynthia L Thomas; Elia Casas; Maria A Picchi; Christine A Stidley; Sandra J Lee; Seena Aisner; Jill M Siegfried; Suresh Ramalingam; Fadlo R Khuri; Daniel D Karp; Steven A Belinsky Journal: Oncotarget Date: 2017-07-15