For identification of clinically relevant masses to predict status, grade, relapse and prognosis of colorectal cancer, we applied Matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS) to a tissue micro array containing formalin-fixed and paraffin-embedded tissue samples from 349 patients. Analysis of our MALDI-IMS data revealed 27 different m/z signals associated with epithelial structures. Comparison of these signals showed significant association with status, grade and Ki-67 labeling index. Fifteen out of 27 IMS signals revealed a significant association with survival. For seven signals (m/z 654, 776, 788, 904, 944, 975 and 1013) the absence and for eight signals (m/z 643, 678, 836, 886, 898, 1095, 1459 and 1477) the presence were associated with decreased life expectancy, including five masses (m/z 788, 836, 904, 944 and 1013) that provided prognostic information independently from the established prognosticators pT and pN. Combination of these five masses resulted in a three-step classifier that provided prognostic information superior to univariate analysis. In addition, a total of 19 masses were associated with tumor stage, grade, metastasis and cell proliferation. Our data demonstrate the suitability of combining IMS and large-scale tissue micro arrays to simultaneously identify and validate clinically useful molecular marker. Copyright © 2017 John Wiley & Sons, Ltd.
Keywords: MALDI; colon cancer; tissue microarray.
Copyright © 2017 John Wiley & Sons, Ltd.