Journal Article

Novel pathway compendium analysis elucidates mechanism of pro-angiogenic synthetic small molecule

Kristen A. Wieghaus, Erwin P. Gianchandani, Mikell A. Paige, Milton L. Brown, Edward A. Botchwey and Jason A. Papin

in Bioinformatics

Volume 24, issue 20, pages 2384-2390
Published in print October 2008 | ISSN: 1367-4803
Published online August 2008 | e-ISSN: 1460-2059 | DOI:
Novel pathway compendium analysis elucidates mechanism of pro-angiogenic synthetic small molecule

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Motivation: Computational techniques have been applied to experimental datasets to identify drug mode-of-action. A shortcoming of existing approaches is the requirement of large reference databases of compound expression profiles. Here, we developed a new pathway-based compendium analysis that couples multi-timepoint, controlled microarray data for a single compound with systems-based network analysis to elucidate drug mechanism more efficiently.

Results: We applied this approach to a transcriptional regulatory footprint of phthalimide neovascular factor 1 (PNF1)—a novel synthetic small molecule that exhibits significant in vitro endothelial potency—spanning 1–48 h post-supplementation in human micro-vascular endothelial cells (HMVEC) to comprehensively interrogate PNF1 effects. We concluded that PNF1 first induces tumor necrosis factor-alpha (TNF-α) signaling pathway function which in turn affects transforming growth factor-beta (TGF-β) signaling. These results are consistent with our previous observations of PNF1-directed TGF-β signaling at 24 h, including differential regulation of TGF-β-induced matrix metalloproteinase 14 (MMP14/MT1-MMP) which is implicated in angiogenesis. Ultimately, we illustrate how our pathway-based compendium analysis more efficiently generates hypotheses for compound mechanism than existing techniques.

Availability: The microarray data generated as part of this study are available in the Gene Expression Omnibus (


Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  4599 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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