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Usage Information

TGF-β induces miR-182 to sustain NF-κB activation in glioma subsets
Libing Song, Liping Liu, Zhiqiang Wu, Yun Li, Zhe Ying, Chuyong Lin, Jueheng Wu, Bo Hu, Shi-Yuan Cheng, Mengfeng Li, Jun Li
Libing Song, Liping Liu, Zhiqiang Wu, Yun Li, Zhe Ying, Chuyong Lin, Jueheng Wu, Bo Hu, Shi-Yuan Cheng, Mengfeng Li, Jun Li
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Research Article

TGF-β induces miR-182 to sustain NF-κB activation in glioma subsets

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Abstract

The strength and duration of NF-κB signaling are tightly controlled by multiple negative feedback mechanisms. However, in cancer cells, these feedback loops are overridden through unclear mechanisms to sustain oncogenic activation of NF-κB signaling. Previously, we demonstrated that overexpression of miR-30e* directly represses IκBα expression and leads to hyperactivation of NF-κB. Here, we report that miR-182 was overexpressed in a different set of gliomas with relatively lower miR-30e* expression and that miR-182 directly suppressed cylindromatosis (CYLD), an NF-κB negative regulator. This suppression of CYLD promoted ubiquitin conjugation of NF-κB signaling pathway components and induction of an aggressive phenotype of glioma cells both in vitro and in vivo. Furthermore, we found that TGF-β induced miR-182 expression, leading to prolonged NF-κB activation. Importantly, the results of these experiments were consistent with an identified significant correlation between miR-182 levels with TGF-β hyperactivation and activated NF-κB in a cohort of human glioma specimens. These findings uncover a plausible mechanism for sustained NF-κB activation in malignant gliomas and may suggest a new target for clinical intervention in human cancer.

Authors

Libing Song, Liping Liu, Zhiqiang Wu, Yun Li, Zhe Ying, Chuyong Lin, Jueheng Wu, Bo Hu, Shi-Yuan Cheng, Mengfeng Li, Jun Li

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Usage data is cumulative from July 2025 through July 2026.

Usage JCI PMC
Text version 1,202 61
PDF 166 12
Figure 948 3
Supplemental data 97 2
Citation downloads 228 0
Totals 2,641 78
Total Views 2,719
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Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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ISSN: 0021-9738 (print), 1558-8238 (online)

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