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Challenges and Advantages of Using Spatially Resolved Lipidomics to Assess the Pathological State of Human Lung Tissue
by
, , and
Ibai Calvo
1
,
Albert Maimó-Barceló
2,3,
Jone Garate
1,
Joan Bestard-Escalas
2,3,
Sergio Scrimini
2,3,4,5,
Jaume Sauleda
2,3,4,5,
Borja G. Cosío
2,3,4,5
,
José Andrés Fernández
1,* and
Gwendolyn Barceló-Coblijn
2,3,* 1
Department of Physical Chemistry, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), 48940 Leioa, Spain
2
Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain
3
Research Unit, Hospital Universitari Son Espases, 07120 Palma, Spain
4
Department of Respiratory Medicine, Hospital Universitari Son Espases, 07120 Palma, Spain
5
Centro de Investigación Biomédica en Red in Respiratory Diseases (CIBERES), 28029 Madrid, Spain
*
Authors to whom correspondence should be addressed.
Cancers 2025, 17(13), 2160; https://doi.org/10.3390/cancers17132160
Submission received: 20 March 2025
/
Revised: 23 June 2025
/
Accepted: 24 June 2025
/
Published: 26 June 2025
(This article belongs to the Section Cancer Biomarkers)
Simple Summary
Mass spectrometry imaging (MSI) lipidomics is a cutting-edge technique that maps the spatial distribution of hundreds of lipids within a tissue section. We used MSI to study the lipid patterns found in the human lung, in particular in two important pathological conditions: lung cancer and chronic obstructive pulmonary disease. We could associate differential lipid profiles with the main tissue types found in the lung thanks to the spatial resolution used: 25 μm. The main result in tumor tissue was the accumulation of lipids containing arachidonic acid, a precursor to molecules that actively participate in cell differentiation and cancer development. We also used public databases of lung cancer studies and established that lung cancer impacts two different families of lipids: phosphatidylinositol and sphingolipids. Overall, this study underscores the great potential of MSI lipidomics to provide underexplored insights into lung diseases.
Abstract
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.
