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Cited by 179

The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.

The insulin receptor substrate (IRS) proteins: At the intersection of metabolism and cancer

Open access
Shaw, Leslie M.·2011·Cell Cycle

Abstract

Increasing evidence supports a connection between cancer and metabolism and emphasizes the need to understand how tumors respond to the metabolic microenvironment and how tumor cell metabolism is regulated. The insulin receptor (IR) and its close family member the insulin-like growth factor-1 receptor (IGF-1R) mediate the cellular response to insulin in normal cells and their function is tightly regulated to maintain metabolic homeostasis. These receptors are also expressed on tumor cells and their expression correlates with tumor progression and poor prognosis. Understanding how the IR/IGF-1R pathway functions in tumors is increasing in importance as the efficacy of drugs that target metabolic pathways, such as metformin, are investigated in prospective clinical trials. This review will focus on key signaling intermediates of the IR and IGF-1R, the Insulin Receptor Substrate (IRS) proteins, with an emphasis on IRS-2, and discuss how these adaptor proteins play a pivotal role at the intersection of metabolism and cancer.

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Metadata

Authors
Shaw, L. M.
Venue
Cell Cycle
Published
2011-06
Volume
10
Issue
11
Pages
1750-1756
ISSN
  • 1538-4101 (ISSN-L)
  • 1551-4005
OpenAlex
W2056533726
Cited by
179
References
20
FWCI
3.06
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: The insulin receptor substrate (IRS) proteins: At the intersection of metabolism and cancer. https://app.cochat.ai/papers/10.4161/cc.10.11.15824
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Shaw, L. M. (2011). The insulin receptor substrate (IRS) proteins: At the intersection of metabolism and cancer. Cell Cycle. https://doi.org/10.4161/cc.10.11.15824

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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.