The DOI matches its OpenAlex record; 34 of the 34 references it cites were found in a registry or an index.
Cancer metabolic reprogramming: importance, main features, and potentials for precise targeted anti-cancer therapies.
Open accessAbstract
Cancer cells are well documented to rewire their metabolism and energy production networks to support and enable rapid proliferation, continuous growth, survival in harsh conditions, invasion, metastasis, and resistance to cancer treatments. Since Dr. Otto Warburg's discovery about altered cancer cell metabolism in 1930, thousands of studies have shed light on various aspects of cancer metabolism with a common goal to find new ways for effectively eliminating tumor cells by targeting their energy metabolism. This review highlights the importance of the main features of cancer metabolism, summarizes recent remarkable advances in this field, and points out the potentials to translate these scientific findings into life-saving diagnosis and therapies to help cancer patients.
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Citations
Cites
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Hanahan, D., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.02.013 · Cited by 66,590
Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation
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Inflammation and insulin resistance
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Metabolic Reprogramming: A Cancer Hallmark Even Warburg Did Not Anticipate
Ward, P. S., & Thompson, C. B. (2012) · Cancer Cell · doi:10.1016/j.ccr.2012.02.014 · Cited by 3,233
Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis
Menendez, J. A., & Lupu, R. (2007) · Nature Reviews Cancer · doi:10.1038/nrc2222 · Cited by 2,941
The AMPK signalling pathway coordinates cell growth, autophagy and metabolism
Mihaylova, M. M., & Shaw, R. J. (2011) · Nature Cell Biology · doi:10.1038/ncb2329 · Cited by 2,923
Cancer cell metabolism: warburg and beyond
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Mechanisms for Insulin Resistance: Common Threads and Missing Links
Samuel, V. T., & Shulman, G. I. (2012) · Cell · doi:10.1016/j.cell.2012.02.017 · Cited by 2,294
Gao, P., Tchernyshyov, I., Chang, T.-C., Lee, Y.-S., Kita, K., Ochi, T., Zeller, K. I., De Marzo, A. M., Van Eyk, J. E., Mendell, J. T., et al. (2009) · Nature · doi:10.1038/nature07823 · Cited by 2,124
Cited by
Vaupel, P., Schmidberger, H., & Mayer, A. (2019) · International Journal of Radiation Biology · doi:10.1080/09553002.2019.1589653 · Cited by 893
Unveiling the mechanisms and challenges of cancer drug resistance
Khan, S. U., Fatima, K., Aisha, S., & Malik, F. (2024) · Cell Communication and Signaling · doi:10.1186/s12964-023-01302-1 · Cited by 417
Tumor microenvironment signaling and therapeutics in cancer progression
Goenka, A., Khan, F., Verma, B., Sinha, P., Dmello, C. C., Jogalekar, M. P., Gangadaran, P., & Ahn, B. (2023) · Cancer Communications · doi:10.1002/cac2.12416 · Cited by 323
Targeting T cell metabolism in the tumor microenvironment: an anti‐cancer therapeutic strategy
Yin, Z., Bai, L., Li, W., Zeng, T., Tian, H., & Cui, J. (2019) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-019-1409-3 · Cited by 133
Targeting glycolysis in non-small cell lung cancer: Promises and challenges
Xu, J.-Q., Fu, Y.-L., Zhang, J., Zhang, K.-Y., Ma, J., Tang, J.-Y., Zhang, Z.-W., & Zhou, Z.-Y. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.1037341 · Cited by 75
Metadata
- Authors
- Phan, L. M., Yeung, S. J., & Lee, M. H.
- Venue
- PubMed
- Publisher
- National Institutes of Health
- Published
- 2014-03-01
- Volume
- 11
- Issue
- 1
- Pages
- 1-19
- OpenAlex
- W1490655572
- Cited by
- 490
- References
- 34
- FWCI
- 8.46
- Type
- journal article
- Language
- en
- Open access
- green
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- Phan, L. M., Yeung, S. J., & Lee, M. H. (2014). Cancer metabolic reprogramming: importance, main features, and potentials for precise targeted anti-cancer therapies. PubMed. https://doi.org/10.7497/j.issn.2095-3941.2014.01.001
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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.
