Lipidomic Typing of Colorectal Cancer Tissue Containing Tumour-Infiltrating Lymphocytes by MALDI Mass Spectrometry Imaging

Abstract

Predicting the prognosis of colorectal cancer (CRC) patients remains challenging and a characterisation of the tumour immune environment represents one of the most crucial avenues when attempting to do so. For this reason, molecular approaches which are capable of classifying the immune environments associated with tumour infiltrating lymphocytes (TILs) are being readily investigated. In this proof of concept study, we aim to explore the feasibility of using spatial lipidomics by MALDI-MSI to distinguish CRC tissue based upon their TIL content. Formalin-fixed paraffin-embedded tissue from human thymus and tonsil was first analysed by MALDI-MSI to obtain a curated mass list from a pool of single positive T lymphocytes, whose putative identities were annotated using an LC-MS-based lipidomic approach. A CRC tissue microarray (TMA, n = 30) was then investigated to determine whether these cases could be distinguished based upon their TIL content in the tumour and its microenvironment. MALDI-MSI from the pool of mature T lymphocytes resulted in the generation of a curated mass list containing 18 annotated m/z features. Initially, subsets of T lymphocytes were then distinguished based on their state of maturation and differentiation in the human thymus and tonsil tissue. Then, when applied to a CRC TMA containing differing amounts of T lymphocyte infiltration, those cases with a high TIL content were distinguishable from those with a lower TIL content, especially within the tumour microenvironment, with three lipid signals being shown to have the greatest impact on this separation (p < 0.05). On the whole, this preliminary study represents a promising starting point and suggests that a lipidomics MALDI-MSI approach could be a promising tool for subtyping the diverse immune environments in CRC.

Lipid Metabolism Interplay in CRC—An Update

“…MALDI-IMS has already revealed the characteristic distribution of several kinds of lipids in various tissues, states or diseases opening a new frontier in the field of lipidomics [ 162 ]. Several studies used this method to describe the lipid profile in a variety of cancer types, including CRC [ 163 , 164 , 165 , 166 ].…”

Human Group IIA Phospholipase A2—Three Decades on from Its Discovery

“…This coupled with emerging advances in network pharmacology approaches [ 154 , 155 ] will enable the integration of complex omics data as well as known biochemistry of the metabolic pathways and cellular interactions into testable in silico models to assess the system-level effect and efficacy of hGIIA inhibitors in different cellular and tissue contexts. Further, advances in imaging techniques coupled with omics technologies in both physiological and pathological states [ 156 , 157 , 158 ] have created opportunities to examine the dynamic intracellular organization of hGIIA and its protein interaction partners to explore the temporal and spatial organization of the enzyme in cellular and tissue contexts.…”

Spatial Multiomics of Lipids, N-Glycans, and Tryptic Peptides on a Single FFPE Tissue Section

“…22 The mass spectrometer voltages applied are described in a previous publication. 24 N-Glycan and tryptic peptide mass spectra were acquired in positive-ion mode. The measurements were performed in the m/z range from 1000 to 3000 for the analysis of N-glycans and from m/z 700 to 3000 in the case of tryptic peptides.…”

“…In order to annotate the m/z features present within the ccRCC lipid imaging data set, consecutive tissue sections were prepared as described in the lipidomic paragraph of the MALDI-MSI workflow and lipids were extracted from the tissue as previously described. 24 An Agilent 1290 Infinity II LC, equipped with an ACQUITY UPLC BEH C18 1.7 μm, 2.1× 100 mm Column (Waters) coupled to a 6546 LC/Q-TOF system, was used for the LC-MS analysis. The gradient was set as previously described.…”