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Recreating metabolic interactions of the tumour microenvironment.
- Source :
-
Trends in Endocrinology & Metabolism . Jun2024, Vol. 35 Issue 6, p518-532. 15p. - Publication Year :
- 2024
-
Abstract
- There is a paucity of experimental and mathematical models that take the extracellular and cellular components of the tumour microenvironment into account. Basic models only integrate cancer cells in isolation of the stromal and matrix surrounding and are flawed due to the lack of cancer-supporting cells and factors of the extracellular matrix, which are both essential for cell–cell and cell–matrix interactions and to produce metabolites that fuel cancer cells. The tumour microenvironment has a poor oxygen diffusion, low nutrient levels, and high interstitial pressure and, as a consequence, to exist in this nutrient-limiting conditions, cancer cells reprogram their metabolism, uptake of glucose, and mitochondrial pathways. We summarise approaches to model the metabolic crosstalk within the tumour microenvironment from a biological, engineering, and mathematical perspective, by discussing the perspectives and limitations. Biomaterial-based platforms and tumour-engineered systems are better approaches to model the tumour metabolism. Tumours are heterogeneous tissues containing diverse populations of cells and an abundant extracellular matrix (ECM). This tumour microenvironment prompts cancer cells to adapt their metabolism to survive and grow. Besides epigenetic factors, the metabolism of cancer cells is shaped by crosstalk with stromal cells and extracellular components. To date, most experimental models neglect the complexity of the tumour microenvironment and its relevance in regulating the dynamics of the metabolism in cancer. We discuss emerging strategies to model cellular and extracellular aspects of cancer metabolism. We highlight cancer models based on bioengineering, animal, and mathematical approaches to recreate cell–cell and cell–matrix interactions and patient-specific metabolism. Combining these approaches will improve our understanding of cancer metabolism and support the development of metabolism-targeting therapies. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10432760
- Volume :
- 35
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Trends in Endocrinology & Metabolism
- Publication Type :
- Academic Journal
- Accession number :
- 177752821
- Full Text :
- https://doi.org/10.1016/j.tem.2023.12.005