The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
PI3K/Akt/mTOR pathway as a target for cancer therapy
Abstract
The PI3K/Akt/mTOR pathway regulates several normal cellular functions that are also critical for tumorigenesis, including cellular proliferation, growth, survival and mobility. Components of this pathway are frequently abnormal in a variety of tumors, making them an attractive target for anti-cancer therapy. Inhibition of mTOR in patients with cancer became more feasible after the development of rapamycin analogs with improved pharmacologic properties. The promising activity of these agents in early clinical trials has led to the development of ongoing phase III trials in renal cell carcinoma and breast cancer. Future studies are needed to identify the patients most likely to benefit from this form of therapy, and to define its role in combination with chemotherapy, hormones and growth factor inhibitors.
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Cites
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Cited by
Branched Chain Amino Acids: Beyond Nutrition Metabolism
Nie, C., He, T., Zhang, W., Zhang, G., & Ma, X. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19040954 · Cited by 786
Metformin in cancer: translational challenges
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Characterization of an Akt Kinase Inhibitor with Potent Pharmacodynamic and Antitumor Activity
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Metadata
- Authors
- Morgensztern, D., & McLeod, H. L.
- Venue
- Anti-Cancer Drugs
- Published
- 2005-09
- Volume
- 16
- Issue
- 8
- Pages
- 797-803
- ISSN
- 0959-4973 (ISSN-L)
- OpenAlex
- W1977943009
- Cited by
- 468
- References
- 64
- FWCI
- 6.57
- Type
- journal article
- Language
- en
- Open access
- closed
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- Morgensztern, D., & McLeod, H. L. (2005). PI3K/Akt/mTOR pathway as a target for cancer therapy. Anti-Cancer Drugs. https://doi.org/10.1097/01.cad.0000173476.67239.3b
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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.