A simple preparation step to remove excess liquid lipids in white adipose tissue enabling improved detection of metabolites via MALDI-FTICR imaging MS.

Matrix-assisted laser desorption ionization (MALDI) Fourier transform ion cyclotron resonance (FTICR) imaging mass spectrometry (MS) is a powerful technology used to analyze metabolites in various tissues. However, it faces significant challenges in studying adipose tissues. Poor matrix distribution and crystallization caused by excess liquid lipids on the surface of tissue sections hamper m/z species detection, an adverse effect that particularly presents in lipid-rich white adipose tissue (WAT). In this study, we integrated a simple and low-cost preparation step into the existing MALDI-FTICR imaging MS pipeline. The new method-referred to as filter paper application-is characterized by an easy sample handling and high reproducibility. The aforementioned filter paper is placed onto the tissue prior to matrix application in order to remove the layer of excess liquid lipids. Consequently, MALDI-FTICR imaging MS detection was significantly improved, resulting in a higher number of detected m/z species and higher ion intensities. After analyzing various durations of filter paper application, 30 s was found to be optimal, resulting in the detection of more than 3700 m/z species. Apart from the most common lipids found in WAT, other molecules involved in various metabolic pathways were detected, including nucleotides, carbohydrates, and amino acids. Our study is the first to propose a solution to a specific limitation of MALDI-FTICR imaging MS in investigating lipid-rich WAT. The filter paper approach can be performed quickly and is particularly effective for achieving uniform matrix distribution on fresh frozen WAT while maintaining tissue integrity. It thus helps to gain insight into the metabolism in WAT.

Inter-organ cross-talk in human cancer cachexia revealed by spatial metabolomics.

BACKGROUND: Cancer cachexia (CCx) presents a multifaceted challenge characterized by negative protein and energy balance and systemic inflammatory response activation. While previous CCx studies predominantly focused on mouse models or human body fluids, there's an unmet need to elucidate the molecular inter-organ cross-talk underlying the pathophysiology of human CCx. METHODS: Spatial metabolomics were conducted on liver, skeletal muscle, subcutaneous and visceral adipose tissue, and serum from cachectic and control cancer patients. Organ-wise comparisons were performed using component, pathway enrichment and correlation network analyses. Inter-organ correlations in CCx altered pathways were assessed using Circos. Machine learning on tissues and serum established classifiers as potential diagnostic biomarkers for CCx. RESULTS: Distinct metabolic pathway alteration was detected in CCx, with adipose tissues and liver displaying the most significant (P ≤ 0.05) metabolic disturbances. CCx patients exhibited increased metabolic activity in visceral and subcutaneous adipose tissues and liver, contrasting with decreased activity in muscle and serum compared to control patients. Carbohydrate, lipid, amino acid, and vitamin metabolism emerged as highly interacting pathways across different organ systems in CCx. Muscle tissue showed decreased (P ≤ 0.001) energy charge in CCx patients, while liver and adipose tissues displayed increased energy charge (P ≤ 0.001). We stratified CCx patients by severity and metabolic changes, finding that visceral adipose tissue is most affected, especially in cases of severe cachexia. Morphometric analysis showed smaller (P ≤ 0.05) adipocyte size in visceral adipose tissue, indicating catabolic processes. We developed tissue-based classifiers for cancer cachexia specific to individual organs, facilitating the transfer of patient serum as minimally invasive diagnostic markers of CCx in the constitution of the organs. CONCLUSIONS: These findings support the concept of CCx as a multi-organ syndrome with diverse metabolic alterations, providing insights into the pathophysiology and organ cross-talk of human CCx. This study pioneers spatial metabolomics for CCx, demonstrating the feasibility of distinguishing cachexia status at the organ level using serum.