Abstract

Metabolism plays a crucial role in regulating the function of immune cells in both health and disease, with altered metabolism contributing to the pathogenesis of cancer and many inflammatory diseases. The local microenvironment has a profound impact on the metabolism of immune cells. Therefore, immunological and metabolic heterogeneity as well as the spatial organization of cells in tissues should be taken into account when studying immunometabolism. Here, we highlight challenges of investigating metabolic communication. Additionally, we review the capabilities and limitations of current technologies for studying metabolism in inflamed microenvironments, including single-cell omics techniques, flow cytometry-based methods (Met-Flow, single-cell energetic metabolism by profiling translation inhibition (SCENITH)), cytometry by time of flight (CyTOF), cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), and mass spectrometry imaging. Considering the importance of metabolism in regulating immune cells in diseased states, we also discuss the applications of metabolomics in clinical research, as well as some hurdles to overcome to implement these techniques in standard clinical practice. Finally, we provide a flowchart to assist scientists in designing effective strategies to unravel immunometabolism in disease-relevant contexts.

Original languageEnglish
Pages (from-to)1759-1776
Number of pages18
JournalMolecular Oncology
Volume18
Issue number7
Early online date26 Jan 2024
DOIs
Publication statusPublished - Jul 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

Keywords

  • advanced metabolomics methods
  • immunometabolism
  • inflammatory diseases
  • metabolic crosstalk
  • metabolic heterogeneity
  • microenvironment

Fingerprint

Dive into the research topics of 'Deciphering metabolic crosstalk in context: lessons from inflammatory diseases'. Together they form a unique fingerprint.

Cite this