Deciphering Metabolic Heterogeneity in Lung Cancer Cell Lines Using High-Resolution MALDI Mass Spectrometry Imaging

Significance of the topic

Spatially resolved metabolomics at near single-cell resolution reveals how metabolic interactions between tumor cells and immune cells shape functional states in the tumor microenvironment. Understanding macrophage metabolic heterogeneity in lung cancer is crucial because macrophage metabolic programs drive immune phenotypes, influence tumor progression, and represent potential therapeutic targets or biomarkers. High-resolution MALDI mass spectrometry imaging (MSI) enables direct mapping of metabolites and lipids in co-culture systems to resolve phenotype-specific metabolic signatures that are obscured in bulk analyses.

Objectives and study overview

• Establish a robust workflow for high-resolution MALDI MSI to achieve near single-cell metabolic profiling in macrophage–cancer co-cultures.
• Characterize metabolic signatures of naïve, pro-inflammatory and anti-inflammatory macrophage phenotypes.
• Investigate how co-culture with A549 lung cancer cells reprograms macrophage metabolism, focusing on nucleotide, amino acid, lipid and TCA-cycle metabolites.
• Demonstrate segmentation strategies to assign metabolic profiles to individual cells within co-cultures.

Methods

• Cell models: Human PBMC-derived macrophages and THP-1–derived macrophages were used in mono- and co-culture with A549 lung adenocarcinoma cells.
• Differentiation and polarization: PBMCs differentiated with 20 ng/mL M-CSF or human serum for 10 days; THP-1 cells differentiated with 10 ng/mL PMA for 24 h plus 24 h recovery. Polarization employed LPS+IFN-γ for pro-inflammatory and IL-4 for anti-inflammatory phenotypes.
• Sample preparation: Cells grown on ITO-coated slides, vacuum-dried, and NEDC matrix applied by sublimation using a Bruker superlimator to minimize analyte delocalization.
• Data acquisition: MALDI Imaging performed on a timsTOF fleX with MALDI-2 at 5 µm spatial resolution; adenine and selected lipid ions used to guide cellular segmentation.
• Data analysis: Spectra processed using SCiLS Lab and MetaboScape for peak picking, centroiding and spatial segmentation. Immunofluorescence staining was used to support segmentation where appropriate.

Used instrumentation

• timsTOF fleX MALDI-2 mass spectrometer (Bruker).
• Bruker superlimator for sublimation-based matrix application.
• ITO-coated IntelliSlides for sample support.
• NEDC (1,5-diaminonaphthalene derivative) matrix applied by sublimation.
• Data processing software: SCiLS Lab and MetaboScape.
• Immunofluorescence microscopy used to complement segmentation.

Main results and discussion

• Technical performance: Sublimation-based matrix deposition yielded artifact-free, high-quality spectra with minimal analyte delocalization, enabling reliable detection of both small metabolites and lipids at 5 µm resolution.
• Segmentation strategy: Adenine served as a nuclear marker while several fatty acids (linoleic, oleic, stearic) improved cytoplasmic coverage to achieve single-cell metabolic segmentation.
• Phenotype-specific metabolic signatures:
  • Pro-inflammatory macrophages showed significantly elevated ATP and succinate, indicating increased nucleotide turnover and a pro-inflammatory TCA metabolite profile.
  • Anti-inflammatory macrophages exhibited enhanced glutamine-related metabolism, with higher oxoproline and glutamate levels.
  • Naïve macrophages displayed higher malate levels compared with anti-inflammatory cells.
• Effect of cancer cell co-culture: Naïve macrophages co-cultured with A549 cells exhibited reduced ATP, succinate and malate levels compared with pro-inflammatory or mono-cultured naïve cells. This metabolic shift suggests that cancer cells can reprogram macrophage energy and TCA-cycle metabolism toward an anti-inflammatory–like state.
• Biological interpretation: The observed changes are consistent with metabolic rewiring in tumor-associated macrophages (TAMs) where altered nucleotide and TCA-cycle metabolites (ATP, succinate, malate) and amino-acid pathways (glutamine/glutamate/oxoproline) correlate with immune phenotype and functional status. Spatially resolved detection confirms heterogeneity at the single-cell level within co-cultures.

Benefits and practical applications of the method

• Spatial single-cell metabolomics: Enables direct linkage between cellular phenotype and local metabolic state without bulk averaging artifacts.
• Phenotyping and biomarker discovery: Identification of metabolite signatures that distinguish macrophage activation states and their reprogramming by tumor cells.
• Preclinical research and drug development: Tool for evaluating immunometabolic effects of candidate therapeutics and modifiers in co-culture or tissue models.
• Workflow robustness: Sublimation matrix application minimizes delocalization, improving reproducibility for high-resolution MSI studies.

Future trends and opportunities for application

• Multimodal integration: Combining high-resolution MALDI MSI with single-cell transcriptomics, proteomics, and immunohistochemistry to map metabolism to molecular phenotype and function.
• Isotope tracing: Applying stable isotope labeling to resolve pathway fluxes at cellular resolution within co-cultures or ex vivo tissues.
• Improved molecular identification: Routine integration of MS/MS and orthogonal techniques to raise confidence in metabolite annotation for complex samples.
• Clinical translation: Adapting spatial metabolomics pipelines for patient biopsy analysis to aid immune stratification, treatment selection, or pharmacodynamic monitoring—pending validation in tissue and clinical cohorts.
• Advanced data analytics: Machine learning and computational segmentation to better deconvolve cell types and metabolic states in highly heterogeneous samples.

Conclusion

• High-resolution (5 µm) MALDI-2 imaging with sublimation-based matrix deposition enables near single-cell mapping of metabolites and lipids in macrophage–cancer co-cultures.
• Macrophage activation states show distinct metabolic fingerprints: pro-inflammatory cells are characterized by elevated ATP and succinate, while anti-inflammatory cells favor glutamine-related metabolism.
• Co-culture with A549 lung cancer cells reprograms naïve macrophage metabolism toward lower TCA intermediates and reduced ATP, consistent with an anti-inflammatory-like metabolic shift.
• The approach provides a robust platform for studying immune–tumor metabolic crosstalk, with clear applications in mechanistic immunometabolism research and preclinical evaluation.

Reference

• Mansouri S., Bien T., Henkel C., Oetjen J., Kiss A., Easterling M., Boecker M.A., Nikulina N., Hoehndorf J., Savai R. Deciphering Metabolic Heterogeneity in Lung Cancer Cell Lines Using High-Resolution MALDI Mass Spectrometry Imaging. Life Sciences Mass Spectrometry. 2026. Bruker Corporation involvement noted; For Research Use Only. Not for diagnostic use.
• Conflict of interest: T. Bien, C. Henkel, J. Oetjen, A. Kiss, M. Easterling and J. Hoehndorf are employees of Bruker Corporation; Bruker provided instrument and software used in this study.