Metabonomic signature analysis of cervical carcinoma and precancerous lesions in women by (1)H NMR spectroscopy

Exp Ther Med. 2012 Jun;3(6):945-951. doi: 10.3892/etm.2012.509. Epub 2012 Mar 12.

Abstract

(1)H nuclear magnetic resonance (NMR)-based metabonomics has been used to characterize the metabolic profiles of cervical intraepithelial neoplasia (CIN) and cervical squamous cell carcinoma (CSCC). Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were used to model the systematic variation related to patients with CIN or CSCC with healthy controls. Potential metabolic biomarkers were identified using database comparisons, and the one-way analysis of variance (ANOVA) test was used to examine the significance of the metabolites. Compared with plasma obtained from the healthy controls, plasma from patients with CIN had higher levels of very-low density lipoprotein (VLDL), acetone, unsaturated lipid and carnitine, together with lower levels of creatine, lactate, isoleucine, leucine, valine, alanine, glutamine, histidine, glycine, acetylcysteine, myo-inositol, choline and glycoprotein. Plasma from patients with CSCC had higher levels of acetate and formate, together with lower levels of creatine, lactate, isoleucine, leucine, valine, alanine, glutamine, histidine and tyrosine compared with the plasma of the healthy controls. In addition, compared with the plasma of patients with CIN, the plasma of CSCC patients had higher levels of acetate, formate, lactate, isoleucine, leucine, valine, alanine, glutamine, histidine, tyrosine, acetylcysteine, myo-inositol, glycoprotein, α-glucose and β-glucose, together with lower levels of acetone, unsaturated lipid and carnitine. Moreover, the profiles showed high feasibility and specificity by statistical analysis with OPLS-DA compared to the Thinprep cytology test (TCT) by setting the histopathological outcome as standard. The metabolic profile obtained for cervical cancer is significant, even for the precancerous disease. This suggests a systemic metabolic response to cancer, which may be used to identify potential early diagnostic biomarkers of the cancer and to establish clinical diagnostic methods.