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Cited by 275

The DOI matches its Crossref record; 107 of the 107 references it cites were found in a registry or an index.

Current treatment strategies for inhibiting mTOR in cancer

Open access
Chiarini, Francesca, Evangelisti, Camilla, McCubrey, James A., Martelli, Alberto M.·2015·Trends in Pharmacological Sciences

Abstract

Mammalian target of rapamycin (mTOR) is a Ser/Thr kinase that regulates a wide range of functions, including cell growth, proliferation, survival, autophagy, metabolism, and cytoskeletal organization. mTOR activity is dysregulated in several human disorders, including cancer. The crucial role of mTOR in cancer cell biology has stimulated interest in mTOR inhibitors, placing mTOR on the radar of the pharmaceutical industry. Several mTOR inhibitors have already undergone clinical trials for treating tumors, without great success, although mTOR inhibitors are approved for the treatment of some types of cancer, including advanced renal cell carcinoma. However, the role of mTOR inhibitors in cancer treatment continues to evolve as new compounds are continuously being disclosed. Here we review the three classes of mTOR inhibitors currently available for treating cancer patients. Moreover, we highlight efforts to identify markers of resistance and sensitivity to mTOR inhibition that could prove useful in the emerging field of personalized medicine.

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Metadata

Authors
Chiarini, F., Evangelisti, C., McCubrey, J. A., & Martelli, A. M.
Venue
Trends in Pharmacological Sciences
Publisher
Elsevier BV
Published
2015-02
Volume
36
Issue
2
Pages
124-135
ISSN
0165-6147 (ISSN-L)
OpenAlex
W1980402007
Cited by
275
References
107
FWCI
2.22
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Current treatment strategies for inhibiting mTOR in cancer. https://app.cochat.ai/papers/10.1016/j.tips.2014.11.004
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Chiarini, F., Evangelisti, C., McCubrey, J. A., & Martelli, A. M. (2015). Current treatment strategies for inhibiting mTOR in cancer. Trends in Pharmacological Sciences. https://doi.org/10.1016/j.tips.2014.11.004

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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.