Sequential Detection of Lipids, Metabolites, and Proteins in One Tissue for Improved Cancer Differentiation Accuracy.

Abstract

Traditionally, molecular information on metabolites, lipids, and proteins is collected from separate individual tissue samples using different analytical approaches. Herein a novel strategy to minimize the potential material losses and the mismatch between metabolomics, lipidomics, and proteomics data has been demonstrated based on internal extractive electrospray ionization mass spectrometry (iEESI-MS). Sequential detection of lipids, metabolites, and proteins from the same tissue sample was achieved without sample reloading and hardware alteration to MS instrument by sequentially using extraction solutions with different chemical compositions. With respect to the individual compound class analysis, the sensitivity, specificity, and accuracy obtained with the integrative information on metabolites, lipids, and proteins from 57 samples of 13 patients for lung cancer prediction was substantially improved from 54.0%, 51.0%, and 76.0% to 100.0%, respectively. The established method is featured by low sample consumption (ca. 2.0 mg) and easy operation, which is important to minimize systematic errors in precision molecular diagnosis and systems biology studies.