Metabonomic profiling: A novel approach in neuroendocrine neoplasias

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 MEN were prospectively recruited: small bowel MEN,.n = 8; panthwatic MEN, 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 SIMGA and MATLAB for supervised and unsupervised multivariate analysis. Results. Partial least squares-discriminant analysis differentiated between MEN and healthy samples with accuracy (R2Y = 0.79, Q2Y = 0.53, area under the curve [AUG] 0.90). Orthogonal partial least squares-discriminant analysis was able to distinguish between small bowel MEN and pancreatic MEN (R2Y = 0.91, Q2Y = 0.35). Subclass analysis also demonstrated class separation between functional and nonfunctional MEN (R2Y = 0.98, Q2Y = 0.77, AUG 0.6) and those with metastases (1?2Y = 0.72,. Q2 Y = 0.41, AUG 0.86) due to variations in kippurate metabolism (P <.0001). Conclusion. Metabonomic analysis suggests that subgroups of.NEN may possess a stratified metabolic phenotype. Metabolic profiling could provide novel biomarkers for MEN