Here we describe clinical research into FFPE tissue sections obtained from human intraocular disease UM, which remains the most common intraocular malignancy in adults, with poor prognosis for UM within the choroid region and distant sites UM metastasis. Two imaging MS techniques Matrix Assisted Laser Desorption/Ionisation (MALDI) and Desorption Electrospray Ionisation (DESI) MSI were applied. Molecular profiles were obtained and analysed by multivariate statistical approaches, providing insight into the biochemical and biological differences/similarities within the patient sample cohort (n=15).
Enucleations were collected over a 6 year time period and subjected to the standard fixation and paraffin embedding protocols. In preparation for MS, 5 µm sections were produced with removal of the paraffin followed by heat induced antigen retrieval.
Tissue sections were prepared for analysis by MALDI MSI by applying a solution of matrix onto the tissue sections to help the ionisation of molecules directly from the tissue. All MSI experiments (MALDI and DESI) were carried out using a version of SYNAPT mass spectrometer (Waters Corporation, Manchester, UK). Multivariate analysis were performed using MATLAB (MathWorks, Inc., Natick, MA, US) in conjunction with the Eigenvector PLS_Toolbox.
Initial MALDI MSI images acquired with a spatial resolution of 100 µm x 100 µm in positive ion mode showed the distinct spatial distribution of many molecular species throughout the various regions of the eye; choroid, cornea, retina, lens and UM tumour regions. Further MALDI MSI experiments using consecutive tissue sections at 50 µm x 50 µm spatial resolution show substantial variation in the spatial distribution of species within the low molecular mass range. Furthermore, DESI MSI experiments were carried out at 200 µm x 200 µm in negative ionization mode. Deprotonated molecular ions could be detected, from a variety of lipid related species, localized to specific regions within the eye including the tumour region.
Multivariate statistical analysis was used to classify between UM samples (good vs. poor prognosis). Using unsupervised PCA, an unbiased representation of the data was generated, with clear sample grouping and differentiation observed based upon tumour status. Use of the supervised PLS-DA technique provided even clearer separation between the selected samples, with the tumour profiles displaying dominant discriminatory peaks. These peaks could be identified as sphingolipids and Lyso-phosphocholine, a phosphatidylcholine degradation product.
It was possible to analyze clinical research FFPE tissue sections by MALDI and DESI MSI, illustrating that specific small molecular species remained localized to certain tissue types, including the UM tumour. Initial correlation with tumour status was determined from the statistical analysis of the MALDI MSI datasets.
AACR 2016, Session: Molecular and Cellular Imaging of Cancer 2; Session Category: Tumor Biology.