Literature DB >> 26057862

S100A4 and its role in metastasis – simulations of knockout and amplification of epithelial growth factor receptor and matrix metalloproteinases.

Antoine Buetti-Dinh1, Igor V Pivkin, Ran Friedman.   

Abstract

The calcium-binding signalling protein S100A4 enhances metastasis in a variety of cancers. Despite a wealth of data available, the molecular mechanism by which S100A4 drives metastasis is unknown. Integration of the current knowledge defies straightforward intuitive interpretation and requires computer-aided approaches to represent the complexity emerging from cross-regulating species. Here we carried out a systematic sensitivity analysis of the S100A4 signalling network in order to identify key control parameters for efficient therapeutic intervention. Our approach only requires limited details of the molecular interactions and permits a straightforward integration of the available experimental information. By integrating the available knowledge, we investigated the effects of combined inhibition of signalling pathways. Through selective knockout or inhibition of the network components, we show that the interaction between epidermal growth factor receptor (EGFR) and S100A4 modulates the sensitivity of angiogenesis development to matrix metalloproteinases (MMPs) activity. We also show that, in cells that express high EGFR, MMP inhibitors are not expected to be useful in tumours if high activity of S100A4 is present.

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Year:  2015        PMID: 26057862     DOI: 10.1039/c5mb00302d

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  11 in total

1.  Dexamethasone Induces Changes in Osteogenic Differentiation of Human Mesenchymal Stromal Cells via SOX9 and PPARG, but Not RUNX2.

Authors:  Elena Della Bella; Antoine Buetti-Dinh; Ginevra Licandro; Paras Ahmad; Valentina Basoli; Mauro Alini; Martin J Stoddart
Journal:  Int J Mol Sci       Date:  2021-04-30       Impact factor: 5.923

2.  Drug resistance in cancer: molecular evolution and compensatory proliferation.

Authors:  Ran Friedman
Journal:  Oncotarget       Date:  2016-03-15

3.  Increased S100A15 expression and decreased DNA methylation of its gene promoter are involved in high metastasis potential and poor outcome of lung adenocarcinoma.

Authors:  Yung-Che Chen; Meng-Chih Lin; Chang-Chun Hsiao; Yi-Xin Zheng; Kuang-Den Chen; Ming-Tse Sung; Chung-Jen Chen; Ting-Ya Wang; Yong-Yong Lin; Huang-Chih Chang; Yu-Mu Chen; Jen-Chieh Chang
Journal:  Oncotarget       Date:  2017-07-11

4.  Computer simulations of the signalling network in FLT3 +-acute myeloid leukaemia - indications for an optimal dosage of inhibitors against FLT3 and CDK6.

Authors:  Antoine Buetti-Dinh; Ran Friedman
Journal:  BMC Bioinformatics       Date:  2018-04-24       Impact factor: 3.169

5.  New Insights into the Occurrence of Matrix Metalloproteases -2 and -9 in a Cohort of Breast Cancer Patients and Proteomic Correlations.

Authors:  Gianluca Di Cara; Maria Rita Marabeti; Rosa Musso; Ignazio Riili; Patrizia Cancemi; Ida Pucci Minafra
Journal:  Cells       Date:  2018-07-28       Impact factor: 6.600

6.  Stochastic modelling of tyrosine kinase inhibitor rotation therapy in chronic myeloid leukaemia.

Authors:  H Jonathan G Lindström; Astrid S de Wijn; Ran Friedman
Journal:  BMC Cancer       Date:  2019-05-28       Impact factor: 4.430

7.  The effects of combination treatments on drug resistance in chronic myeloid leukaemia: an evaluation of the tyrosine kinase inhibitors axitinib and asciminib.

Authors:  H Jonathan G Lindström; Ran Friedman
Journal:  BMC Cancer       Date:  2020-05-07       Impact factor: 4.430

8.  Sensitivity Analysis of the NPM-ALK Signalling Network Reveals Important Pathways for Anaplastic Large Cell Lymphoma Combination Therapy.

Authors:  Antoine Buetti-Dinh; Thomas O'Hare; Ran Friedman
Journal:  PLoS One       Date:  2016-09-26       Impact factor: 3.240

9.  A computational study of hedgehog signalling involved in basal cell carcinoma reveals the potential and limitation of combination therapy.

Authors:  Antoine Buetti-Dinh; Rebecca Jensen; Ran Friedman
Journal:  BMC Cancer       Date:  2018-05-18       Impact factor: 4.430

10.  Reverse engineering directed gene regulatory networks from transcriptomics and proteomics data of biomining bacterial communities with approximate Bayesian computation and steady-state signalling simulations.

Authors:  Antoine Buetti-Dinh; Malte Herold; Stephan Christel; Mohamed El Hajjami; Francesco Delogu; Olga Ilie; Sören Bellenberg; Paul Wilmes; Ansgar Poetsch; Wolfgang Sand; Mario Vera; Igor V Pivkin; Ran Friedman; Mark Dopson
Journal:  BMC Bioinformatics       Date:  2020-01-21       Impact factor: 3.169

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