MALDI imaging mass spectrometry reveals multiple clinically relevant masses in colorectal cancer using large-scale tissue microarrays.
A HinschM BuchholzS OdingaC BorkowskiC KoopJ R IzbickiM WurlitzerT KrechW WilczakS SteurerF JacobsenE-C BurandtP StahlRonald SimonG SauterH SchlüterPublished in: Journal of mass spectrometry : JMS (2018)
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.
Keyphrases
- mass spectrometry
- high resolution
- liquid chromatography
- fine needle aspiration
- contrast enhanced
- cell proliferation
- ultrasound guided
- gas chromatography
- high performance liquid chromatography
- big data
- high throughput
- magnetic resonance imaging
- data analysis
- computed tomography
- machine learning
- single cell
- radiation therapy
- magnetic resonance
- high density
- prognostic factors
- squamous cell carcinoma
- lymph node
- social media
- neoadjuvant chemotherapy
- locally advanced
- artificial intelligence
- ms ms