Metabolomics Applications in Cancer Systems
Summary
Metabolomics has emerged as a powerful approach to characterise the small-molecule environment of cancer cells and tissues, offering insights into the biochemical adaptations that underpin tumour growth, survival and metastasis. By combining mass spectrometry or nuclear magnetic resonance spectrometry with computational analytics, researchers can quantify hundreds to thousands of metabolites, profile dynamic fluxes of isotopically labelled substrates and map pathway alterations in response to genetic mutations, microenvironmental cues or therapeutic interventions. In cancer systems, metabolomics facilitates discovery of metabolic vulnerabilities, stratifies tumours according to metabolic phenotypes and supports development of precision therapies. Recent advances extend beyond bulk measurements to spatially and temporally resolved analyses, revealing metabolic heterogeneity within tumours and between microenvironmental compartments. Integration of metabolomics with transcriptomics, proteomics and imaging now enables system-level modelling of metabolic networks and their regulation, guiding both mechanistic understanding and clinical translation of metabolic biomarkers and treatment strategies.
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Metabolomics Applications in Cancer Systems publication trend
The graph below shows the total number of articles in metabolomics applications in cancer systems across all publications each year (not limited to Nature Index journals).
Technical terms
Metabolomics: The comprehensive analysis and quantification of small molecules (metabolites) within cells, tissues or organisms.
Stable isotope-resolved metabolomics (SIRM): A technique that traces labelled atoms (e.g., ¹³C, ¹⁵N) through metabolic pathways to measure fluxes and pathway usage.
Metabolic flux analysis: The quantitative determination of rates at which substrates are converted into products through metabolic networks, often using isotopic labelling data.
Metabolic reprogramming: Alterations in cellular metabolic pathways driven by oncogenes, tumour suppressors or microenvironmental factors to support cancer phenotypes.
Spatially resolved metabolomics: Approaches that preserve tissue architecture to measure metabolite distributions and fluxes at high spatial resolution within heterogeneous tumour regions.
References
- Challenges of Spatially Resolved Metabolism in Cancer Research. Metabolites (2024).
- DIMet: an open-source tool for differential analysis of targeted isotope-labeled metabolomics data. Bioinformatics (2024).
- Cyclin D1 extensively reprograms metabolism to support biosynthetic pathways in hepatocytes. Journal of Biological Chemistry (2023).
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