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.