The DOI matches its Crossref record; 222 of the 222 references it cites were found in a registry or an index.
Cancer as a metabolic disease: implications for novel therapeutics
Open accessAbstract
Emerging evidence indicates that cancer is primarily a metabolic disease involving disturbances in energy production through respiration and fermentation. The genomic instability observed in tumor cells and all other recognized hallmarks of cancer are considered downstream epiphenomena of the initial disturbance of cellular energy metabolism. The disturbances in tumor cell energy metabolism can be linked to abnormalities in the structure and function of the mitochondria. When viewed as a mitochondrial metabolic disease, the evolutionary theory of Lamarck can better explain cancer progression than can the evolutionary theory of Darwin. Cancer growth and progression can be managed following a whole body transition from fermentable metabolites, primarily glucose and glutamine, to respiratory metabolites, primarily ketone bodies. As each individual is a unique metabolic entity, personalization of metabolic therapy as a broad-based cancer treatment strategy will require fine-tuning to match the therapy to an individual's unique physiology.
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Metadata
- Authors
- Seyfried, T. N., Flores, R. E., Poff, A. M., & D'Agostino, D. P.
- Venue
- Carcinogenesis
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-12-16
- Volume
- 35
- Issue
- 3
- Pages
- 515-527
- ISSN
- 0143-3334 (ISSN-L)
- 1460-2180
- OpenAlex
- W2111253773
- Cited by
- 472
- References
- 222
- FWCI
- 8.49
- Type
- journal article
- Language
- en
- Open access
- green
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- Seyfried, T. N., Flores, R. E., Poff, A. M., & D'Agostino, D. P. (2014). Cancer as a metabolic disease: implications for novel therapeutics. Carcinogenesis. https://doi.org/10.1093/carcin/bgt480
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
