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Cited by 279

The DOI matches its Crossref record; 192 of the 192 references it cites were found in a registry or an index.

Insulin-Like Growth Factor System in Cancer: Novel Targeted Therapies

Open access
Brahmkhatri, Varsha P., Prasanna, Chinmayi, Atreya, Hanudatta S.·2015·BioMed Research International

Abstract

Insulin-like growth factors (IGFs) are essential for growth and survival that suppress apoptosis and promote cell cycle progression, angiogenesis, and metastatic activities in various cancers. The IGFs actions are mediated through the IGF-1 receptor that is involved in cell transformation induced by tumour. These effects depend on the bioavailability of IGFs, which is regulated by IGF binding proteins (IGFBPs). We describe here the role of the IGF system in cancer, proposing new strategies targeting this system. We have attempted to expand the general viewpoint on IGF-1R, its inhibitors, potential limitations of IGF-1R, antibodies and tyrosine kinase inhibitors, and IGFBP actions. This review discusses the emerging view that blocking IGF via IGFBP is a better option than blocking IGF receptors. This can lead to the development of novel cancer therapies.

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Crossref · 10.1155/2015/538019

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Metadata

Authors
Brahmkhatri, V. P., Prasanna, C., & Atreya, H. S.
Venue
BioMed Research International
Published
2015
Volume
2015
Pages
1-24
ISSN
  • 1110-7243 (ISSN-L)
  • 2314-6133
  • 2314-6141
OpenAlex
W1974502272
Cited by
279
References
192
FWCI
26.83
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Insulin-Like Growth Factor System in Cancer: Novel Targeted Therapies. https://app.cochat.ai/papers/10.1155/2015/538019
The paper
Brahmkhatri, V. P., Prasanna, C., & Atreya, H. S. (2015). Insulin-Like Growth Factor System in Cancer: Novel Targeted Therapies. BioMed Research International. https://doi.org/10.1155/2015/538019

Data sources

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.