The use of matrix coating assisted by an electric field (MCAEF) to enhance mass spectrometric imaging of human prostate cancer biomarkers.

J Mass Spectrom. 2016 Jan;51(1):86-95. doi: 10.1002/jms.3728.
Wang X, Han J, Hardie DB, Yang J, Borchers CH

In this work, we combined a newly developed matrix coating technique - matrix coating assisted by an electric field (MCAEF) and matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) to enhance the imaging of peptides and proteins in tissue specimens of human prostate cancer. MCAEF increased the signal-to-noise ratios of the detected proteins by a factor of 2 to 5, and 232 signals were detected within the m/z 3500-37500 mass range on a time-of-flight mass spectrometer and with the sinapinic acid MALDI matrix. Among these species, three proteins (S100-A9, S100-A10, and S100-A12) were only observed in the cancerous cell region and 14 proteins, including a fragment of mitogen-activated protein kinase/extracellular signal-regulated kinase kinase kinase 2, a fragment of cAMP-regulated phosphoprotein 19, 3 apolipoproteins (C-I, A-I, and A-II), 2 S100 proteins (A6 and A8), β-microseminoprotein, tumor protein D52, α-1-acid glycoprotein 1, heat shock protein β-1, prostate-specific antigen, and 2 unidentified large peptides at m/z 5002.2 and 6704.2, showed significantly differential distributions at the p < 0.05 (t-test) level between the cancerous and the noncancerous regions of the tissue. Among these 17 species, the distributions of apolipoprotein C-I, S100-A6, and S100-A8 were verified by immunohistological staining. In summary, this study resulted in the imaging of the largest group of proteins in prostate cancer tissues by MALDI-MS reported thus far, and is the first to show a correlation between S100 proteins and prostate cancer in a MS imaging study. The successful imaging of the three proteins only found in the cancerous tissues, as well as those showing differential expressions demonstrated the potential of MCAEF-MALDI/MS for the in situ detection of potential cancer biomarkers.