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Updated: Feb 4, 2026

Studying TGF-β Signaling and TGF-β-induced Epithelial-to-mesenchymal Transition in Breast Cancer and Normal Cells
Published on: October 27, 2020
Mesenchymal glioblastoma constitutes a major ceRNA signature in the TGF-β pathway
Qixue Wang1, Jinquan Cai2, Chuan Fang3
1Laboratory of Neuro-Oncology, Tianjin Neurological Institute, Department of Neurosurgery, Tianjin Medical University General Hospital and Key Laboratory of Neurotrauma, Variation, and Regeneration, Ministry of Education and Tianjin Municipal Government, Tianjin 300052, China.
Abstract:
Rationale: Competitive endogenous RNA (ceRNA) networks play important roles in posttranscriptional regulation. Their dysregulation is common in cancer. However, ceRNA signatures have been poorly examined in the invasive and aggressive phenotypes of mesenchymal glioblastoma (GBM). This study aims to characterize mesenchymal glioblastoma at the mRNA-miRNA level and identify the mRNAs in ceRNA networks (micNET) markers and their mechanisms in tumorigenesis. Methods: The mRNAs in ceRNA networks (micNETs) of glioblastoma were investigated by constructing a GBM ceRNA network followed by integration with a STRING protein interaction network. The prognostic micNET markers of mesenchymal GBM were identified and validated across multiple datasets. ceRNA interactions were identified between micNETs and miR181 family members. LY2109761, an inhibitor of TGFBR2, demonstrated tumor-suppressive effects on both primary cultured cells and a patient-derived xenograft intracranial model. Results: We characterized mesenchymal glioblastoma at the mRNA-miRNA level and reported a ceRNA network that could separate the mesenchymal subtype from other subtypes. Six genes (TGFBR2, RUNX1, PPARG, ACSL1, GIT2 and RAP1B) that interacted with each other in both a ceRNA-related manner and in terms of their protein functions were identified as markers of the mesenchymal subtype. The coding sequence (CDS) and 3'-untranslated region (UTR) of TGFBR2 upregulated the expression of these genes, whereas TGFBR2 inhibition by siRNA or miR-181a/d suppressed their expression levels. Furthermore, mesenchymal subtype-related genes and the invasion phenotype could be reversed by suppressing the six mesenchymal marker genes. Conclusions: This study suggests that the micNETs may have translational significance in the diagnosis of mesenchymal GBM and may be novel therapeutic targets.
Insights
This study identifies key mRNA markers within competitive endogenous RNA (ceRNA) networks, called micNETs, that characterize aggressive mesenchymal glioblastoma (GBM). These micNETs offer potential diagnostic and therapeutic targets for GBM.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Competitive endogenous RNA (ceRNA) networks are crucial for posttranscriptional gene regulation and are frequently dysregulated in cancer.
- Mesenchymal glioblastoma (GBM) is an aggressive subtype with poorly understood ceRNA signatures.
- Characterizing ceRNA networks in mesenchymal GBM is essential for understanding tumorigenesis and identifying therapeutic targets.
Purpose of the Study:
- To characterize mesenchymal GBM at the mRNA-miRNA level.
- To identify messenger RNAs (mRNAs) within ceRNA networks (micNETs) that serve as markers for mesenchymal GBM.
- To elucidate the mechanisms of these micNET markers in glioblastoma development.
Main Methods:
- Constructed a GBM ceRNA network and integrated it with a STRING protein interaction network.
- Identified and validated prognostic micNET markers for mesenchymal GBM across multiple datasets.
- Investigated ceRNA interactions between micNETs and miR181 family members, and assessed the effects of TGFBR2 inhibition.
Main Results:
- Developed a ceRNA network capable of distinguishing the mesenchymal GBM subtype.
- Identified six genes (TGFBR2, RUNX1, PPARG, ACSL1, GIT2, RAP1B) as mesenchymal GBM markers, interacting via ceRNA and protein functions.
- Demonstrated that TGFBR2 upregulates these markers, while its inhibition by siRNA or miR-181a/d suppresses them; suppressing these markers reversed mesenchymal traits and invasion.
Conclusions:
- micNETs show translational potential for diagnosing mesenchymal GBM.
- The identified micNET markers represent novel therapeutic targets for glioblastoma.
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