An Integrated Genomic Approach Identifies HOXC8 as an Upstream Regulator in Ovarian Endometrioma.

JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM(2020)

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摘要
PURPOSE:To identify the upstream regulators (URs) involved in the onset and pathogenesis of ovarian endometrioma. METHODS:Recently, a method called Significance-based Modules Integrating the Transcriptome and Epigenome (SMITE) that uses transcriptome data in combination with publicly available data for identifying URs of cellular processes has been developed. Here, we used SMITE with transcriptome data from ovarian endometrioma stromal cells (ovESCs) and eutopic endometrium stromal cells (euESCs) in combination with publicly available gene regulatory network data. To confirm the URs identified by SMITE, we developed a Boolean network simulation to see if correcting aberrant expressions of the identified genes could restore the entire gene expression profile of ovESCs to a profile similar to that of euESCs. We then established euESCs overexpressing the identified gene and characterized them by cell function assays and transcriptome analysis. RESULTS:SMITE identified 12 potential URs in ovarian endometrioma that were confirmed by the Boolean simulation. One of the URs, HOXC8, was confirmed to be overexpressed in ovESCs. HOXC8 overexpression significantly enhanced cell proliferation, migration, adhesion, and fibrotic activities, and altered expression statuses of the genes involved in transforming growth factor (TGF)-β signaling. HOXC8 overexpression also increased the expression levels of phosphorylated SMAD2/SMAD3. The increased adhesion and fibrosis activities by HOXC8 were significantly inhibited by E-616452, a selective inhibitor of TGF-β receptor type I kinases. MAIN CONCLUSIONS:Integrated genomic approaches identified HOXC8 as an UR in ovarian endometrioma. The pathological features of ovarian endometrioma including cell proliferation, adhesion, and fibrosis were induced by HOXC8 and its subsequent activation of TGF-β signaling.
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关键词
ovarian endometrioma, upstream regulator, gene regulatory network, bioinformatics, mathematical modeling
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