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pmid:26484143

Small molecule inhibition of FOXM1: How to bring a novel compound into genomic context.

Giovanni Marsico · Michael V Gormally

Genomics data · 2015 doi:10.1016/j.gdata.2014.10.012

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

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Small molecule inhibition of FOXM1: How to bring a novel compound into genomic context.
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10.1016/j.gdata.2014.10.012
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Giovanni Marsico
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Michael V Gormally
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Genomics data
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2015
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Deregulation of transcription factor (TF) networks is emerging as a major pathogenic event in many human cancers (Darnell, 2002 [1]; Libermann and Zerbini, 2006 [2]; Laoukili et al., 2007 [3]). Small molecule intervention is an attractive avenue to understand TF regulatory mechanisms in healthy and disease state, as well as for exploiting these targets therapeutically (Koehler et al., 2003 [4]; Berg, 2008 [5]; Koehler, 2010 [6]). However, because of their physico-chemical properties, TF targeting has been proven to be difficult (Verdine and Walensky, 2007 [7]). The TF FOXM1 is an important mitotic player (Wonsey and Follettie, 2005 [8]; Laoukili et al., 2005 [9]; McDonald, 2005 [10]) also implicated in cancer progression (Laoukili et al., 2007 [3]; Teh, 2011 [11]; Koo, 2012 [12]) and drug resistance development (Kwok et al., 2010 [13]; Carr et al., [14]). Therefore, its inhibition is an attractive goal for cancer therapy. Here, we describe a computational biology approach, by giving detailed insights into methodologies and technical results, which was used to analyze the transcriptional RNA-Seq data presented in our previous work (Gormally et al., 2014 [20]). Our Bioinformatics analysis shed light on the cellular effect of a novel FOXM1 inhibitor (FDI-6) newly identified through a biophysical screen. The data for this report is available at the public GEO repository (accession number http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE58626).
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:26484143", "kind": "science-record", "revision": 4, "content_hash": "sha256:6577bbf4db70f0230a30d55ffc603a24c609cb5993d906ceb4f8dadcf4260663", "created_at": "2026-11-01T15:40:12Z", "updated_at": "2026-11-01T21:20:10Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Small molecule inhibition of FOXM1: How to bring a novel compound into genomic context.", "doi": "10.1016/j.gdata.2014.10.012", "pmid": "26484143", "authors": ["Giovanni Marsico", "Michael V Gormally"], "journal": "Genomics data", "year": 2015, "abstract": "Deregulation of transcription factor (TF) networks is emerging as a major pathogenic event in many human cancers (Darnell, 2002 [1]; Libermann and Zerbini, 2006 [2]; Laoukili et al., 2007 [3]). Small molecule intervention is an attractive avenue to understand TF regulatory mechanisms in healthy and disease state, as well as for exploiting these targets therapeutically (Koehler et al., 2003 [4]; Berg, 2008 [5]; Koehler, 2010 [6]). However, because of their physico-chemical properties, TF targeting has been proven to be difficult (Verdine and Walensky, 2007 [7]). The TF FOXM1 is an important mitotic player (Wonsey and Follettie, 2005 [8]; Laoukili et al., 2005 [9]; McDonald, 2005 [10]) also implicated in cancer progression (Laoukili et al., 2007 [3]; Teh, 2011 [11]; Koo, 2012 [12]) and drug resistance development (Kwok et al., 2010 [13]; Carr et al., [14]). Therefore, its inhibition is an attractive goal for cancer therapy. Here, we describe a computational biology approach, by giving detailed insights into methodologies and technical results, which was used to analyze the transcriptional RNA-Seq data presented in our previous work (Gormally et al., 2014 [20]). Our Bioinformatics analysis shed light on the cellular effect of a novel FOXM1 inhibitor (FDI-6) newly identified through a biophysical screen. 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