ArticleJournal of neuro-oncology2016
ZEB1 expression is increased in IDH1-mutant lower-grade gliomas.
Article in Journal of neuro-oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 15 citations in OpenAlex.
- Expression of Epithelial-Mesenchymal Transition-Related Genes in Primary Brain Tumors.Iranian biomedical journal · 2026Article
- Dualistic role of ZEB1 and ZEB2 in tumor progression.Biology direct · 2025Review
- Identification of EMT-associated prognostic features among grade II/III gliomas.Scientific reports · 2024Article
- Cyclin-dependent kinase subunit2 (CKS2) promotes malignant phenotypes and epithelial-mesenchymal transition-like process in glioma by activating TGFβ/SMAD signaling.Cancer medicine · 2023Article
- Overexpression of ZEB1 and YAP1 is related to poor prognosis in patients with gliomas with different IDH1 status.International journal of clinical and experimental pathology · 2023Article
- The role of the ZEB1-neuroinflammation axis in CNS disorders.Journal of neuroinflammation · 2022Review
- Role of EMT in the DNA damage response, double-strand break repair pathway choice and its implications in cancer treatment.Cancer science · 2022Review
- IDH Mutation Analysis in Glioma Patients by CADMA Compared with SNaPshot Assay and two Immunohistochemical Methods.Pathology oncology research : POR · 2019Article
- The Curious Case of ZEB1.Discoveries (Craiova, Romania) · 2018Review
- Prognostic Significance of Zinc Finger E-Box-Binding Homeobox Family in Glioblastoma.Medical science monitor : international medical journal of experimental and clinical research · 2018Article
- ZEB1 Is a Transcription Factor That Is Prognostic and Predictive in Diffuse Gliomas.Frontiers in neurology · 2018Article
- ZEB1 expression in Chinese lower-grade gliomas.Journal of neuro-oncology · 2017Article
- Cellular heterogeneity contributes to subtype-specific expression of ZEB1 in human glioblastoma.PloS one · 2017Article
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
Abstract
Transcription factors that induce epithelial-mesenchymal transition (EMT) promote invasion, chemoresistance and a stem-cell phenotype in epithelial tumors, but their roles in central nervous system tumors are not well-understood. We hypothesized these transcription factors have a functional impact in grades II-III gliomas. Using the National Cancer Institute (NCI) Repository for Molecular Brain Neoplasia Data (REMBRANDT) and the Cancer Genome Atlas (TCGA) Lower-Grade Glioma (LGG) data, we determined the impact of EMT-promoting transcription factors (EMT-TFs) on overall survival in grades II-III gliomas, compared their expression across common genetic subtypes and subsequently validated these findings in a set of 31 tumors using quantitative real-time polymerase chain reaction (PCR) and immunohistochemistry. Increased expression of the gene coding for the transcriptional repressor Zinc Finger E box-binding Homeobox 1 (ZEB1) was associated with a significant increase in overall survival (OS) on Kaplan-Meier analysis. Genetic subtype analysis revealed that ZEB1 expression was relatively increased in IDH1/2-mutant gliomas, and IDH1/2-mutant gliomas expressed significantly lower levels of many ZEB1 transcriptional targets. Similarly, IDH1/2-mutant tumors expressed significantly higher levels of targets of microRNA 200C (MIR200C), a key regulator of ZEB1. In a validation study, ZEB1 mRNA was significantly increased in IDH1-mutant grades II-III gliomas, and ZEB1 protein expression was more pronounced in these tumors. Our findings demonstrate a novel relationship between IDH1/2 mutations and expression of ZEB1 and its transcriptional targets. Therapy targeting ZEB1-associated pathways may represent a novel therapeutic avenue for this class of tumors.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.