Challenges and Advantages of Using Spatially Resolved Lipidomics to Assess the Pathological State of Human Lung...

Background: Mass spectrometry imaging (MSI) lipidomics is a subset of spatially resolved techniques wherein lipids are detected by mass spectrometry, allowing their multiplexed detection and acquiring position-correlated spectra along a tissue section. Rapid advances in the field provide solid evidence demonstrating how specific and regulated lipid distribution is in any biological context. Objectives: Herein, we describe the MSI, particularly matrix-assisted laser desorption/ionization (MALDI-MSI), challenges and advantages in defining human lung pathophysiology, particularly in lung cancer and chronic obstructive pulmonary disease, leading causes of death. Methods: MALDI-MSI analysis of lung tissue sections at 25 μm of lateral resolution allowed associating specific lipid profiles with the main tissues present and independently assessing the impact on lipid composition of smoking, chronic inflammation, and lung cancer. Results: Consistent with MALDI-MSI studies in tumor epithelia, arachidonic acid-containing phospholipids increased, agreeing with its role as a precursor of numerous bioactive molecules participating in cell differentiation and malignization. Next, a gene expression dataset of epithelial human non-small cell lung cancer samples was analyzed using system biology approaches, revealing that, consistent with the most relevant changes in lipid profiles, the network dominated by the tumor-associated module included genes tightly involved in phosphatidylinositol and sphingolipid metabolism. Hence, despite the intrinsic difficulties entailed by lung tissue handling, the results strongly encourage future analysis at higher lateral resolutions so that the lipidome changes associated with each lung cellular type, even subtype, could be fully mapped. Therefore, MALDI-MSI lipidomics definitively broadens the options, some still rather unexplored, to delve into pathophysiology at the cell-type level.