Studying metabolic flux adaptations in cancer through integrated experimental-computational approaches
Abstract The study of tumorigenic rewiring of metabolic flux is at the heart of cancer metabolic research. Here, we review two widely used computational flux inference approaches: isotope tracing coupled with Metabolic Flux Analysis (13C-MFA) and COnstraint-Based Reconstruction and Analysis (COBRA)....
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2019-07-01
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| Series: | BMC Biology |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12915-019-0669-x |
| Summary: | Abstract The study of tumorigenic rewiring of metabolic flux is at the heart of cancer metabolic research. Here, we review two widely used computational flux inference approaches: isotope tracing coupled with Metabolic Flux Analysis (13C-MFA) and COnstraint-Based Reconstruction and Analysis (COBRA). We describe the applications of these complementary modeling techniques for studying metabolic adaptations in cancer cells due to genetic mutations and the tumor microenvironment, as well as for identifying novel enzymatic targets for anti-cancer drugs. We further highlight the advantages and limitations of COBRA and 13C-MFA and the main challenges ahead. |
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| ISSN: | 1741-7007 |