MSACL 2026 Abstract

Comprehensive Multi-omics Profiling of Cancer Metabolism with Spatial Precision

Kevin Hau (1), Antonia Fecke (1), Felix-Levin Hormann (1), Ann-Cathrin Groba (1), Luiza Martins Nascentes Melo (2), Feyza Cansiz (2), Gabrielle Allies (2), Andreas Hentschel (1), Jianxu Chen (1), Sven Heiles (1, 3), Alpaslan Tasdogan (1, 2), Albert Sickmann (1, 4), Karl Smith (1)
(1) Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V., Dortmund, Germany, (2) University Hospital Essen, Department of Dermatology, Essen, Germany, (3) University of Duisburg-Essen, Faculty of Chemistry, Essen, Germany, (4) Ruhr-University Bochum, Medizinisches Proteom-Center, Bochum, Germany

Kevin Hau, B. Eng., M. Sc. (Presenter) Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Dortmund

Presenter Bio: I am a PhD student at Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., in Dortmund, Germany. We are highly interested in developing novel, comprehensive analytical technologies to cover unmet clinical needs. In my PhD project i try to characterize lipidome, metabolome and proteome changes in human left ventricular cardiomycocytes before and after ventricular unloading with a left-ventricular assist device (LVAD).

Relevant Financial Disclosures (within past 24 months, reported on Apr 21, 2026) No relevant financial relationship(s) to disclose.

INTRODUCTION:
Understanding metabolic alterations in specific cell populations across tissues remains challenging in clinical research. Current multi-omics approaches still lack the spatial information required for comprehensive multimodal profiling within a single tissue section, necessitating the usage of consecutive sections to capture complementary molecular information. Cancer cells, with altered central carbon metabolism (CCM), demand extensive methods to study associated modalities, i.e. proteins, lipids and metabolites. Here, we present a single section integrative multi-omics workflow combining mass spectrometry-based imaging (MSI) for lipids and metabolites with immunohistochemistry-guided laser microdissection (LMD) and LC-MS/MS based proteomics on a single tissue section. This method unravels unbiased metabolic shifts of the central carbon metabolism on multimolecular levels in differently sized metastases in a patient-derived xenograft (PDX).

METHODS:
A multi-omics approach was employed to analyze a preclinical patient-derived xenograft on multi-molecular levels. To this end, we used a combination of matrix-assisted laser desorption ionisation (MALDI) MSI for lipids and metabolites, immunohistochemistry-guided laser microdissection, and subsequent proteomics analysis on the same tissue section. First, fresh frozen tissue sections were prepared at 12 µm thickness and analyzed using MSI with a lateral resolution of 25 µm per pixel. After imaging, the MALDI matrix was removed, and the tissue section was stained using hematoxylin and eosin (H & E) staining. Based on the MALDI-MSI images and subsequent H & E staining, regions of interest (ROIs), i.e. micro- and macro metastases, were defined and extracted by laser microdissection following proteolytic digestion via single pot, solid phase, sample preparation (SP3) and LC-MS/MS analysis on a Thermo Orbitrap Astral Mass Spectrometer.

RESULTS:
By application of the multi-omics approach onto a human PDX model of melanoma liver metastasis, we identified, that different sized metastases exhibit distinguishable molecular profiles. To that end, we size-stratified metastases into micro-metastases (< 5 mm diameter), intermediate metastases (5-10 mm diameter) and macro-metastases (> 10 mm) and they revealed size-dependent changes in their metabolite, lipid and protein profiles. Aconitic acid, e.g., is strongly enriched in macro-metastases but remains low in micro-metastases. This indicates, as aconitic acid is a tricarboxylic acid (TCA) cycle intermediate, an accumulation due to altered TCA-cycle activity. Pronounced hypoxia due to limited vascularization may promote a shift towards anaerobic glycolysis and reduced TCA-cycle flux, resulting in accumulation of upstream intermediates. Proteomic results showed consistent metabolic states between metastasis size. Glycolysis- and pentose-phosphate pathway-associated (PPP) proteins were found elevated in micro-metastases including aldolase B (Aldob), pyruvate carboxylase (Pc), pyruvate kinase (Pklr; liver isoform) and phosphoenolpyruvate carboxykinase 1 (Pck1), consistent with increased glycolytic and anaplerotic capacity relative to macro-metastases.

CONCLUSION:
Integration and seamless combination of spatial multi-molecular information is a crucial step to elucidate local-specific mechanisms in diseased tissue to gain profound knowledge of pathogenesis of plethoric diseases. We demonstrate a reproducible and robust workflow for single-section spatial lipidomics and metabolomics, histopathological staining and regionally defined proteomic analysis. The method validation demonstrated the justification of using this single-section method, enabling comprehensive, high precision data with minimal variation across similar samples and displaying the high potential of heterogenous spatial analysis. Our method outperforms previously reported multi-omics workflows multiple serial sections for correlating methods. This approach has great potential for in-depth characterization of highly lethal, tissue-invasive diseases at various molecular levels. This paves the way for personalized precision medicine. However, it does not currently offer high-throughput potential.