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To this end, we present an approach to infer regulatory mechanisms downstream of the HER2 driver oncogene in SUM-225 metastatic breast cancer cells from dynamic gene expression patterns using a succession of analytical techniques, including a novel MP grammars method to mathematically model putative regulatory interactions among sets of clustered genes.<\/jats:p>\n               <jats:p>Results: Our method highlighted regulatory interactions previously identified in the cell line and a novel finding that the HER2 oncogene, as opposed to the proto-oncogene, upregulates expression of the E2F2 transcription factor. By targeted gene knockdown we show the significance of this, demonstrating that cancer cell-matrix adhesion and outgrowth were markedly inhibited when E2F2 levels were reduced. Thus, validating in this context that upregulation of E2F2 represents a key intermediate event in a HER2 oncogene-directed gene expression-based signaling circuit. This work demonstrates how predictive modeling of longitudinal gene expression data combined with multiple systems-level analyses can be used to accurately predict downstream signaling pathways. Here, our integrated method was applied to reveal insights as to how the HER2 oncogene drives a specific cancer cell phenotype, but it is adaptable to investigate other oncogenes and model systems.<\/jats:p>\n               <jats:p>Availability and implementation: Accessibility of various tools is listed in methods; the Log-Gain Stoichiometric Stepwise algorithm is accessible at http:\/\/www.cbmc.it\/software\/Software.php .<\/jats:p>\n               <jats:p>Contact: \u00a0bollig@karmanos.org<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btu400","type":"journal-article","created":{"date-parts":[[2014,7,16]],"date-time":"2014-07-16T00:23:13Z","timestamp":1405470193000},"page":"3036-3043","source":"Crossref","is-referenced-by-count":22,"title":["Modeling time-dependent transcription effects of HER2 oncogene and discovery of a role for E2F2 in breast cancer cell-matrix adhesion"],"prefix":"10.1093","volume":"30","author":[{"given":"Aliccia","family":"Bollig-Fischer","sequence":"first","affiliation":[{"name":"1 Barbara Ann Karmanos Cancer Institute and 2 Department of Oncology, Wayne State University, Detroit, MI 48201, USA, 3 Department of Computer Science, University of Verona, 37134 Verona, Italy, 4 The Microsoft Research\u2013University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, 5 Department of Computer Science, Wayne State University and 6 Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI 48201, USA"},{"name":"1 Barbara Ann Karmanos Cancer Institute and 2 Department of Oncology, Wayne State University, Detroit, MI 48201, USA, 3 Department of Computer Science, University of Verona, 37134 Verona, Italy, 4 The Microsoft Research\u2013University of Trento Centre for Computational and Systems Biology, 38068 Rovereto, Italy, 5 Department of Computer Science, Wayne State 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