Metabolic Profiling in Cancer Cells

Cancer cells reprogramme their metabolism to sustain rapid proliferation, survive nutrient limitations and resist therapies. Metabolic profiling encompasses the quantitative measurement of metabolite pools and fluxes through biochemical pathways such as glycolysis, the tricarboxylic acid cycle, the pentose phosphate pathway and fatty acid synthesis. High-throughput mass spectrometry and nuclear magnetic resonance are combined with stable isotope tracing to reveal how nutrients are partitioned between energy production, biosynthesis and redox balance. Spatially resolved methods capture intratumoral heterogeneity, while computational models infer intracellular fluxes from isotopic labelling patterns. These insights have illuminated metabolic vulnerabilities driven by oncogenic signalling, tumour suppressor loss and microenvironmental constraints. Standardised correction for natural isotope abundance and advanced data-analysis pipelines now underpin reproducible flux estimation. Integration with transcriptomic and proteomic data is accelerating the identification of predictive biomarkers and therapeutic targets. Emerging frontiers include single‐cell metabolomics, real-time in vivo flux monitoring and the interplay between cancer metabolism and the immune microenvironment. By providing a comprehensive, quantitative framework, metabolic profiling is central to the development of precision oncology strategies and the discovery of novel metabolic interventions.

Research from Nature Portfolio

A novel mass spectrometry imaging approach has been coupled with stable isotope labelling and advanced spectral analysis to map nutrient contributions and metabolic turnover across the tumour ecosystem. In a murine glioma model, de novo fatty acid synthesis flux was shown to be elevated threefold in tumour regions, with elongation flux rising eightfold relative to adjacent healthy tissue, highlighting spatially distinct anabolic programmes. Another contribution is the development of a unified software solution for isotopic data correction. This tool implements comprehensive correction algorithms for natural isotope abundance and tracer impurities in both MS and MS/MS datasets, enhancing accuracy and reproducibility across platforms. Together, these advances bridge spatially resolved metabolic phenotyping with rigorous quantitation, enabling deeper insight into the biochemical heterogeneity of cancer.

Metabolic Profiling in Cancer Cells publication trend

The graph below shows the total number of articles in metabolic profiling in cancer cells across all publications each year (not limited to Nature Index journals).

Technical terms

Stable isotope tracing: the use of non-radioactive isotope-labelled substrates to follow nutrient incorporation into metabolic pathways.

Mass spectrometry imaging (MSI): a technique that maps the spatial distribution of metabolites directly in tissue sections.

Metabolic flux analysis (MFA): a quantitative framework for estimating rates of metabolic reactions based on isotopic labelling data.

Isotopologue: a molecular species that differs only in the isotopic composition of its constituent atoms.

Reductive carboxylation: a pathway in which glutamine-derived α-ketoglutarate is converted in reverse through isocitrate dehydrogenase to supply citrate for lipid synthesis.

References

1. Comprehensive isotopomer analysis of glutamate and aspartate in small tissue samples. Cell Metabolism (2023).
2. Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem. Nature Communications (2023).
3. Correcting for natural isotope abundance and tracer impurity in MS-, MS/MS- and high-resolution-multiple-tracer-data from stable isotope labeling experiments with IsoCorrectoR. Scientific Reports (2018).
4. A guide to 13C metabolic flux analysis for the cancer biologist. Experimental & Molecular Medicine (2018).