ArticleBreast cancer research : BCR2015
Alternative signaling network activation through different insulin receptor family members caused by pro-mitogenic antidiabetic insulin analogues in human mammary epithelial cells.
Article in Breast cancer research : BCR, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Identification of mortality-risk-related missense variant for renal clear cell carcinoma using deep learning.Therapeutic advances in chronic disease · 2021Article
- Lipid mediators of insulin signaling in diabetic kidney disease.American journal of physiology. Renal physiology · 2019Review
- A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy.BMC systems biology · 2017Article
- Insulin Receptor Isoforms in Physiology and Disease: An Updated View.Endocrine reviews · 2017Review
- Cellular adhesome screen identifies critical modulators of focal adhesion dynamics, cellular traction forces and cell migration behaviour.Scientific reports · 2016Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
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Abstract
introductionInsulin analogues are designed to have improved pharmacokinetic parameters compared to regular human insulin. This provides a sustained control of blood glucose levels in diabetic patients. All novel insulin analogues are tested for their mitogenic side effects, however these assays do not take into account the molecular mode of action of different insulin analogues. Insulin analogues can bind the insulin receptor and the insulin-like growth factor 1 receptor with different affinities and consequently will activate different downstream signaling pathways.
methodsHere we used a panel of MCF7 human breast cancer cell lines that selectively express either one of the isoforms of the INSR or the IGF1R. We applied a transcriptomics approach to assess the differential transcriptional programs activated in these cells by either insulin, IGF1 or X10 treatment.
resultsBased on the differentially expressed genes between insulin versus IGF1 and X10 treatment, we retrieved a mitogenic classifier gene set. Validation by RT-qPCR confirmed the robustness of this gene set. The translational potential of these mitogenic classifier genes was examined in primary human mammary cells and in mammary gland tissue of mice in an in vivo model. The predictive power of the classifier genes was evaluated by testing all commercial insulin analogues in the in vitro model and defined X10 and glargine as the most potent mitogenic insulin analogues.
conclusionsWe propose that these mitogenic classifier genes can be used to test the mitogenic potential of novel insulin analogues as well as other alternative molecules with an anticipated affinity for the IGF1R.
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