RORα Suppresses Breast Tumor Invasion by Inducing SEMA3F Expression is a research paper published in Cancer Research (2012). On theSindex it has a DataRank of 4.8. It has been cited 126 times, with 105 citing works in its 1-hop citation network.
Inactivation of tumor suppressors and inhibitory microenvironmental factors is necessary for breast cancer invasion; therefore, identifying those suppressors and factors is crucial not only to advancing our knowledge of breast cancer, but also to discovering potential therapeutic targets. By analyzing gene expression profiles of polarized and disorganized human mammary epithelial cells in a physiologically relevant three-dimensional (3D) culture system, we identified retinoid orphan nuclear receptor alpha (RORα) as a transcription regulator of semaphorin 3F (SEMA3F), a suppressive microenvironmental factor. We showed that expression of RORα was downregulated in human breast cancer tissue and cell lines, and that reduced mRNA levels of RORα and SEMA3F correlated with poor prognosis. Restoring RORα expression reprogrammed breast cancer cells to form noninvasiveness structures in 3D culture and inhibited tumor growth in nude mice, accompanied by enhanced SEMA3F expression. Inactivation of RORα in nonmalignant human mammary epithelial cells inhibited SEMA3F transcription and impaired polarized acinar morphogenesis. Using chromatin immunoprecipitation and luciferase reporter assays, we showed that transcription of SEMA3F is directly regulated by RORα. Knockdown of SEMA3F in RORα-expressing cancer cells rescued the aggressive 3D phenotypes and tumor invasion. These findings indicate that RORα is a potential tumor suppressor and inhibits tumor invasion by inducing suppressive cell microenvironment.
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Base Score Contribution
0.727
From this paper's citation signal
Citation Network Contribution
4.1
From 94 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 15% comes from its base citations and 85% from the citation network (94 citing papers contributed measurable signal).
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