Dataset Information

Insulin-IGF signaling affects cell transformation in the BALB/c 3T3 cell model.

ABSTRACT: The increased cancer mortality of diabetes type 2 patients is most likely an evidence of the tight connection between tumor development and energy metabolism. A major focus of today's research is still the identification of key proteins of both diseases and the development of corresponding inhibitors. In this study we combined the two-stage BALB/c-3T3 cell transformation assay (BALB-CTA) with the IR/IGF-1R inhibitor OSI-906 (linsitinib) and analyzed alterations in protein activity and energy parameters in non-transformed as well as transformed cells. OSI-906 successfully inhibited the phosphorylation of IR/IGF-1R and decreased cell growth in non-transformed cells. In the BALB-CTA, a permanent treatment with OSI-906 reduced cellular transformation dose-dependently, whereas a temporary treatment gave evidence for a preventive effect in the promotion phase. Furthermore, even though several key proteins were affected, it was possible to show that the phosphorylation of GSK3, Erk 1/2 and the S6 protein are not crucial for the cell foci reducing effect of OSI-906. Taken together, the BALB-CTA confirmed results of OSI-906 from animal studies and enhanced the knowledge of its mode of action. Therefore, the BALB-CTA offers the opportunity to analyze alterations in the transformation process more precisely and will be helpful to identify effective cancer treatments.

SUBMITTER: Poburski D

PROVIDER: S-EPMC5111065 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Insulin-IGF signaling affects cell transformation in the BALB/c 3T3 cell model.

Poburski Doerte D Leovsky Christiane C Boerner Josefine Barbara JB Szimmtenings Luisa L Ristow Michael M Glei Michael M Thierbach René R

Scientific reports 20161116

The increased cancer mortality of diabetes type 2 patients is most likely an evidence of the tight connection between tumor development and energy metabolism. A major focus of today's research is still the identification of key proteins of both diseases and the development of corresponding inhibitors. In this study we combined the two-stage BALB/c-3T3 cell transformation assay (BALB-CTA) with the IR/IGF-1R inhibitor OSI-906 (linsitinib) and analyzed alterations in protein activity and energy par ...[more]

PMID: 27849005

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Project description:BackgroundCellular response to external stimuli requires propagation of corresponding signals through molecular signaling pathways. However, signaling pathways are not isolated information highways, but rather interact in a number of ways forming sophisticated signaling networks. Since defects in signaling pathways are associated with many serious diseases, understanding of the crosstalk between them is fundamental for designing molecularly targeted therapy. Unfortunately, we still lack technology that would allow high throughput detailed measurement of activity of individual signaling molecules and their interactions. This necessitates developing methods to prioritize selection of the molecules such that measuring their activity would be most informative for understanding the crosstalk. Furthermore, absence of the reaction coefficients necessary for detailed modeling of signal propagation raises the question whether simple parameter-free models could provide useful information about such pathways.ResultsWe study the combined signaling network of three major pro-survival signaling pathways: Epidermal Growth Factor Receptor (EGFR), Insulin-like Growth Factor-1 Receptor (IGF-1R), and Insulin Receptor (IR). Our study involves static analysis and dynamic modeling of this network, as well as an experimental verification of the model by measuring the response of selected signaling molecules to differential stimulation of EGF, IGF and insulin receptors. We introduced two novel measures of the importance of a node in the context of such crosstalk. Based on these measures several molecules, namely Erk1/2, Akt1, Jnk, p70S6K, were selected for monitoring in the network simulation and for experimental studies. Our simulation method relies on the Boolean network model combined with stochastic propagation of the signal. Most (although not all) trends suggested by the simulations have been confirmed by experiments.ConclusionThe simple model implemented in this paper provides a valuable first step in modeling signaling networks. However, to obtain a fully predictive model, a more detailed knowledge regarding parameters of individual interactions might be necessary.

Dataset Information

Insulin-IGF signaling affects cell transformation in the BALB/c 3T3 cell model.

Publications

Insulin-IGF signaling affects cell transformation in the BALB/c 3T3 cell model.

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