title: Metabonomic profiling: a novel  approach in neuroendocrine  neoplasias.
abstract: BACKGROUND
  A metabonomic phenotyping strategy was developed as part of a pilot study to define a diagnostic metabolic phenotype for neuroendocrine neoplasms (NEN).
  
  
  METHODS
  Twenty-eight patients with NEN were prospectively recruited: small bowel NEN, n = 8; pancreatic NEN, n = 10; and others, n = 10 (mean age 49.4 years [26–81] male/female ratio 17:11). There were 17 healthy control patients. Urine samples were subjected to 1H nuclear magnetic resonance spectroscopic profiling via the use of a Bruker Avance 600-MHz spectrometer (Bruker, Rheinstetten, Germany). Acquired spectral data were imported into SIMCA and MATLAB for supervised and unsupervised multivariate analysis.
  
  
  RESULTS
  Partial least squares-discriminant analysis differentiated between NEN and healthy samples with accuracy (R(2)Y = 0.79, Q2Y = 0.53, area under the curve [AUC] 0.90). Orthogonal partial least squares-discriminant analysis was able to distinguish between small bowel NEN and pancreatic NEN (R2Y = 0.91, Q2Y = 0.35). Subclass analysis also demonstrated class separation between functional and nonfunctional NEN (R2Y = 0.98, Q2Y = 0.77, AUC 0.6) and those with metastases (R2Y = 0.72 , Q2 Y = 0.41, AUC 0.86) due to variations in hippurate metabolism (P < .0001).
  
  
  CONCLUSIONS
  Metabonomic analysis suggests that subgroups of NEN may possess a stratified metabolic phenotype. Metabolic profiling could provide novel biomarkers for NEN.
authors.forename: James M
authors.initials: JM
authors.lastname: Kinross
authors.forename: Panagiotis
authors.initials: P
authors.lastname: Drymousis
authors.forename: Beatriz
authors.initials: B
authors.lastname: Jiménez
authors.forename: Andrea
authors.initials: A
authors.lastname: Frilling
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D016022:Case-Control Studies; D015331:Cohort Studies; D005260:Female; D006801:Humans; D009682:Magnetic Resonance Spectroscopy; D008297:Male; D055442:Metabolome; D055432:Metabolomics / Q000379:methods / Q000706:statistics & numerical data; D008875:Middle Aged; D018358:Neuroendocrine Tumors / Q000175:diagnosis / Q000378:metabolism* / Q000652:urine; D010865:Pilot Projects; D011446:Prospective Studies