Study on metabonomic characteristics of human lung cancer using high resolution magic-angle spinning 1H NMR spectroscopy and multivariate data analysis

Abstract

Lung cancer causes serious health problems. Clinical diagnosis of lung cancer relies on histopathological evalution of tissue specimen. However, extensive knowledge of the metabolic biochemistry of tumors can potentially provide important information for accurate diagnosis of lung cancer. High resolution magic-angle spinning NMR spectroscopy has emerged and be widely acknowledged as an excellent tool in investigating tissue metabolism. Moreover, the combination of high resolution magic-angle spinning NMR technique and multivariate data analysis has become an important metabonomics platform for studying the intact biological tissues. This study reported the metabonomic characteristics of 51 lung tissues from 17 patients with lung cancer using the high resolution magic-angle spinning 1H NMR spectroscopy and the multivariate data analysis methods including principal component analysis and orthogonal partial least squares-discriminant analysis. Clear differences among the metabonomic characteristics of lung cancer tissues at various sites were disclosed. Compared with the adjacent noninvolved tissues, the lung cancer tissues had significantly high levels of aspartate, phosphocholine, glycerophosphocholine and lactate but significantly low levels of glucose and valine. Furthermore, significantly positive (or negative) correlations were observed between the levels of some metabolites such as lactate, fatty acids, valine, phosphocholine, and glycerophosphocholine.