Affiliations: [a] Department of Chemistry, Fudan University, Shanghai, China | [b] Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China | [c] Department of Respiratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, China | [d] Department of Thoracic Surgery, Tongji hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China | [e] Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, Hubei, China
Abstract: BACKGROUND: The combination of NMR spectroscopy and multivariate data
analysis (MVDA), such as orthogonal partial least squares-discriminant
analysis (OPLS-DA), has been collectively acknowledged as an excellent tool
to investigate tissue metabolism and provide metabolite information for the
diagnosis of disease, and become an important metabonomic platform for
studies in biological tissues so far. METHODS: Both ex vivo high resolution magic-angle spinning1H NMR and
in vitro1H NMR spectroscopy technique were synchronously employed to analyze
the metabonomic characteristics of 102 lung tissues from 34 patients with
lung cancer in hope to identify potential diagnostic biomarkers for
malignancy detection in lung tissues. RESULTS: Significant elevations in the levels of lipids and lactate
and significant reductions in the levels of myo-inositol and valine in the
cancer tissues had been identified when compared with the adjacent
non-involved tissues. Furthermore, the OPLSDA models calculated by
two1H NMR spectra provided for relatively high sensitivity,
specificity and good prediction accuracy in the identification of class
membership regardless of the number of metabolites involved. CONCLUSIONS: MVDA in combination with1H NMR spectra highlighted
the potential of metabonomics in clinical settings so that the techniques
might be further exploited for future lung cancer biomarker research or
identification.
