Dataset Information

Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling.

ABSTRACT: Aberrant activation of sonic Hegdehog (SHH) signaling has been found to disrupt cellular differentiation in many human cancers and to increase proliferation. The SHH pathway is known to cross-talk with EGFR dependent signaling. Recent studies experimentally addressed this interplay in Daoy cells, which are presumable a model system for medulloblastoma, a highly malignant brain tumor that predominately occurs in children. Currently ongoing are several clinical trials for different solid cancers, which are designed to validate the clinical benefits of targeting the SHH in combination with other pathways. This has motivated us to investigate interactions between EGFR and SHH dependent signaling in greater depth. To our knowledge, there is no mathematical model describing the interplay between EGFR and SHH dependent signaling in medulloblastoma so far. Here we come up with a fully probabilistic approach using Dynamic Bayesian Networks (DBNs). To build our model, we made use of literature based knowledge describing SHH and EGFR signaling and integrated gene expression (Illumina) and cellular location dependent time series protein expression data (Reverse Phase Protein Arrays). We validated our model by sub-sampling training data and making Bayesian predictions on the left out test data. Our predictions focusing on key transcription factors and p70S6K, showed a high level of concordance with experimental data. Furthermore, the stability of our model was tested by a parametric bootstrap approach. Stable network features were in agreement with published data. Altogether we believe that our model improved our understanding of the interplay between two highly oncogenic signaling pathways in Daoy cells. This may open new perspectives for the future therapy of Hedghog/EGF-dependent solid tumors.

SUBMITTER: Frohlich H

PROVIDER: S-EPMC4646463 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling.

Fröhlich Holger H Bahamondez Gloria G Götschel Frank F Korf Ulrike U

PloS one 20151116 11

Aberrant activation of sonic Hegdehog (SHH) signaling has been found to disrupt cellular differentiation in many human cancers and to increase proliferation. The SHH pathway is known to cross-talk with EGFR dependent signaling. Recent studies experimentally addressed this interplay in Daoy cells, which are presumable a model system for medulloblastoma, a highly malignant brain tumor that predominately occurs in children. Currently ongoing are several clinical trials for different solid cancers, ...[more]

PMID: 26571415

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Project description:Aberrant activation of Hedgehog (HH) signaling has been identified as a key etiologic factor of many human malignancies. Signal strength, target gene specificity, and oncogenic activity of HH signaling profoundly depend on interactions with other pathways such as epidermal growth factor receptor-mediated signaling which has been shown to cooperate with HH/GLI in basal cell carcinoma and pancreatic cancer. We demonstrate that the human medulloblastoma cell line Daoy possesses a fully inducible endogenous HH pathway. Treatment of Daoy cells with Sonic Hedgehog or Smoothened agonist induced expression of GLI1 protein and prevented processing of GLI3 to its repressor form. To study interactions between HH- and EGF-induced signaling in greater detail, time-resolved measurements were carried out and analyzed on the transcriptomic as well as proteomic level. Daoy cells responded to the co-treatment by downregulating GLI1, PTCH, and HHIP on the transcript level which was also seen when Amphiregulin (AREG) was used instead of EGF. The finding that EGFR signaling silences proteins acting as negative regulators of HH signaling is firstly described here as a novel crosstalk mechanism. Furthermore, combined EGFR/HH signaling maintains high GLI1 protein levels contrasting its downregulation on the transcript level. On the other hand, high level synergism was observed with respect to a strong and significant upregulation of numerous canonical EGF-targets with putative tumor-promoting properties such as MMP7, VEGFA, and IL-8. In conclusion, synergistic effects between EGFR and HH signaling can selectively induce a switch from a canonical HH/GLI profile to a modulated specific target gene profile pointing to more wide-spread, yet context-dependent, interactions between HH/GLI and growth factor receptor signaling in human malignancies. To study interactions between HH- and EGF-induced signaling, time-resolved measurements were carried out over a period of 24 h at 14 different time points after stimulation by EGF with and without additional stimulation by SHH. Furthermore, as a control, cells without any stimulation by EGF and SHH (control) and cells in the presents of SHH were analyzed. Overall, three biological replicates of 60 different treatment/timepoints were analyzed yielding 180 different samples.

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Project description:Wnt signaling and cadherin-mediated adhesion have been implicated in both processes of embryonic development and the progression of carcinomas. Recent experimental studies revealed that Wnt signaling and cadherin-mediated cell adhesion have close crosstalk with each other. A comprehensive model that investigates the dynamic balance of β-catenins in Wnt signaling and cell adhesion will improve our understanding to embryonic development and carcinomas. We constructed a network model to evaluate the dynamic interplay between adhesion and Wnt signaling. The network is decomposed into three interdependent modules: the cell adhesion, the degradation circle and the transcriptional regulation. In the cell adhesion module, we consider the effect of cadherin's lateral clustering. We found adhesion negatively contributes to Wnt signaling through competition for cytoplasmic β-catenins. In the network of degradation circle, we incorporated features from various existing models. Our simulations reproduced the most recent experimental phenomena with semi-quantitative accuracy. Finally, in the transcriptional regulation module, we developed a function selection strategy to analyze the outcomes of genetic feedback loops in modulating the gene expression of Wnt targets. The specific cellular phenomena such as cadherin switch and Axin oscillation were archived and their biological insights were discussed. Our model provides the theoretical basis of how spatial organization regulates the dynamics of cellular signaling pathways. We suggest that cell adhesion affects Wnt signaling in both negative and positive ways. Cadherins can inhibit Wnt signaling not only in a way as a stoichiometric binding partner of β-catenins that sequesters them from signaling, but also in a way through their clustering to impacts the rate at which β-catenins are involved in the destruction loop. Additionally, cadherin clustering increases the phosphorylation rate of β-catenins and promotes its signaling in nucleus.

Dataset Information

Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling.

Publications

Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling.

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