Kanikah Mehndiratta, MSc, University of Glasgow
Cancer pathophysiology and devising its treatment approaches have been major areas of interest for scientists and doctors globally. Understanding cancer pathophysiology could help in checking for vulnerabilities and targeting the tumour therapeutically. To identify such metabolic pathways, metabolites need to be identified and/or quantified using tracing methods such as stable isotope tracing. But the physiological routes and associated nutritional demands can differ significantly in a lab tumour cell culture and the actual tumorous region in the body. Recent research published in the Molecular Metabolism journal under Elsevier reviews the same tracing approach and the physiological effect of the exogenous application of the isotope tracer in animal models. The study also discusses how to counter limitations associated with such a technique.
Isotopic tracing in tumour cells
Metabolomics gives a representation of the molecular phenotype and is considered an important field in cancer research. It helps in the quantification of various pools of metabolites in tumoral mass via techniques such as chromatography and spectrometry. Nuclear magnetic resonance (NMR) in particular, offers a non-invasive way of visualizing biochemical changes in tumour cells. The metabolite identification can help in picking pathways that have been altered due to tumour transformation stages. Stable isotope tracing can help monitor the activity of metabolic sources in different pathways and metabolic interconversions that help tumoral tissues survive.
Carbon, hydrogen and nitrogen’s stable isotopes 13C, 2H, 15N tracing from tracers into downstream metabolites involved in tumour physiology is the approach being explored here. The heavier stable isotopes help in distinguishing labelled molecules from unlabelled ones. This could help follow the catabolic and anabolic reactions taking place in vivo. Since tumours are mostly inhabiting poorly vascularized regions, the metabolic phenotype automatically differs majorly in comparison to its lab counterpart. As an example, the Ras-driven tumours in mice lung tissues depend less on glutamine and more on glucose in their Krebs cycle pathway which is opposite to the situation in vitro. Interaction between tumour cells and other somatic body cells also affects this metabolic adaptation. The differential patterns of labelling the intermediate compounds in the cycle can help in the comparison of activities of different enzymes in tumour conditions and healthy cells.
Challenges with tracer usage
Different types of reforms are becoming prevalent to support such metabolic reprogramming in tumour cells. A basic experimental design entails fasting of animal models before tracers are administered, supplementation of tracers and tissue and biofluid collection. This can be followed by the extraction of metabolites from samples and their analysis using chromatographic techniques. The tracer administration poses some challenges such as the delivery of tracers in a way that allows for proper enrichment in cancer cells. An enrichment equivalent of 10-30% prevents disruption of homeostasis at a physiological level. The intravenous application can cause an intense boost of tracers in the blood that can lead to difficulty in metabolic profiling. Using bolus injections and then a tracer infusion in sedated mice helps in a continuous delivery of tracers to help attain a metabolic steady-state throughout the process.
Conclusion
A lot of factors affect the metabolic vulnerabilities in cancer cells such as genetic alterations, the tumour tissue environment etc. The experimental design that avoids the use of anaesthesia will prove advantageous in maintaining a normal metabolic state. Considering the variable percentage of the natural abundance of these stable isotopes is also an important factor during metabolite analysis.
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Source:
1. Grima-Reyes, M., Martinez-Turtos, A., Abramovich, I., Gottlieb, E., Chiche, J., & Ricci, J.-E. (2021). Physiological impact of in vivo stable isotope tracing on cancer metabolism. Molecular Metabolism, 101294. https://doi.org/10.1016/j.molmet.2021.101294
2. Kaushik, A. K., & DeBerardinis, R. J. (2018). Applications of metabolomics to study cancer metabolism. Biochimica et Biophysica Acta (BBA) – Reviews on Cancer, 1870(1), 2–14. https://doi.org/10.1016/j.bbcan.2018.04.009
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