ArticleBioengineered2021
Early 2 factor (E2F) transcription factors contribute to malignant progression and have clinical prognostic value in lower-grade glioma.
Article in Bioengineered, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Single-nucleus multiomics unveils malignant cellular states, regulatory architectures and microenvironmental reorganization across the G-CIMP epigenomic transition in IDH-mutant glioma.bioRxiv : the preprint server for biology · 2026Article
- E2F transcription factors as multimodal biomarkers for pan-cancer management.Scientific reports · 2025Article
- Artificial Intelligence Algorithm-Based Intraoperative Magnetic Resonance Navigation for Glioma Resection.Contrast media & molecular imaging · 2022Article
- A specific immune signature for predicting the prognosis of glioma patients with IDH1-mutation and guiding immune checkpoint blockade therapy.Frontiers in immunology · 2022Article
- E2F transcription factor 1 is involved in the phenotypic modulation of esophageal squamous cell carcinoma cells via microRNA-375.Bioengineered · 2021Article
- SNRPD2-dependency Fuels an Oncogenic Alternative Splicing Repertoire Driving Disease Aggressiveness in Glioma.Cancer genomics & proteomicsArticle
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
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Abstract
Early 2 factor (E2F) genes encoding a family of transcription factors are significantly associated with apoptosis, metabolism, and angiogenesis in several tumor types. However, the biological functions of E2F transcription factors (E2Fs) and their potential involvement in the malignancy of lower-grade glioma (LGG) remain unclear. We explored the effects of the expression of eight E2F family members on the clinical characteristics of LGG based on the Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), and GSE16011 datasets. Two LGG subgroups were identified according to the consensus clustering of the eight E2Fs. We employed the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm for further functional experiments and the development of a potential risk score. Two categories of patients with LGG were identified based on the median risk scores. We then developed a nomogram based on the results of the multivariate analysis. Real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry were performed to validate the bioinformatics results. Our results indicated that E2F family members were significantly involved in the malignancy of LGG and might serve as effective prognostic biomarkers of the disease.
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