Theranostics 2018; 8(17):4733-4749. doi:10.7150/thno.26550
Mesenchymal glioblastoma constitutes a major ceRNA signature in the TGF-β pathway
1. Laboratory 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
2. Department of Neurosurgery, the Second Affiliated Hospital of Harbin Medical University, Neuroscience Institute, Heilongjiang Academy of Medical Sciences, Harbin 150086, China
3. Department of Neurosurgery, Hebei University Affiliated Hospital, Baoding 071000, China
4. Department of Pathology, Medical College of Hebei University, Baoding, Hebei 071000, China
5. Institute for Cancer Genetics, Columbia University Medical Center, Columbia University, New York, New York 10032, USA
*These authors contributed equally to this work as first authors.
Wang Q, Cai J, Fang C, Yang C, Zhou J, Tan Y, Wang Y, Li Y, Meng X, Zhao K, Yi K, Zhang S, Zhang J, Jiang C, Zhang J, Kang C. Mesenchymal glioblastoma constitutes a major ceRNA signature in the TGF-β pathway. Theranostics 2018; 8(17):4733-4749. doi:10.7150/thno.26550. Available from https://www.thno.org/v08p4733.htm
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.
Keywords: ceRNA network, micNETs, TGFBR2, mesenchymal subtype