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Early 2 factor (E2F) transcription factors contribute to malignant progression and have clinical prognostic value in lower-grade glioma.

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.

SUBMITTER: Luo H

PROVIDER: S-EPMC8806968 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Early 2 factor (E2F) transcription factors contribute to malignant progression and have clinical prognostic value in lower-grade glioma.

Luo Haitao H Tao Chuming C Long Xiaoyan X Zhu Xingen X Huang Kai K

Bioengineered 20211201 1

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 ...[more]

PMID: 34617871

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Project description:IntroductionPatients with high-grade glioma (HGG) suffered poor survival due to inherent or acquired therapeutic resistance and refractory recurrence. The outcome of HGG patients has improved little during the past decade. Therefore, molecular signatures are urgently needed for improving diagnosis, survival prediction and identification of therapeutic targets for HGG. E2F transcription factors (E2Fs), a family of transcription factors recognized as master regulators of cell proliferation, have been found to be involved in the pathogenesis of various tumor types.AimsTo investigate the expression of E2Fs and their prognosis value in high-grade glioma (HGG).ResultsExpression of E2Fs was analyzed in 394 HGG samples from TCGA dataset. E2Fs were generally expressed in HGG. Except for E2F3 and E2F5, expression of E2Fs was significantly upregulated and linked with grade progression. E2F1, E2F2, E2F7, and E2F8 were highly correlated with aggressive proliferation oncogenes, as well as potential therapeutic resistance oncogenes. Elevated E2Fs (not E2F3) were associated with adverse tumor features and poorer outcome. E2F7 and E2F8 exhibited superior outcome prediction performance compared with other E2Fs. Additionally, E2F7 and E2F8 independently predicted poorer survival in HGG patients. Gene set enrichment analysis identified a variety of critical oncogenic pathways that were tightly associated with E2F7 or E2F8, including epithelial-mesenchymal transition, NFκB, STAT3, angiogenesis pathways. Furthermore, elevated expression of E2F7 indicated worse therapeutic response of HGG to irradiation and silencing of E2F7 conferred higher cell-killing effect when combined with irradiation treatment. Mechanically, E2F7 directly regulates the transcriptional activity of EZH2 via binding at the corresponding promoter area.ConclusionsE2Fs (except for E2F3 and E2F5) are highly expressed in HGG and indicate adverse outcome. E2F7 and E2F8 were identified as novel potential prognostic markers in HGG. E2F7 was further validated to be closely associated with radioresistance of HGG and a critical transcriptional regulator of EZH2.

Project description:ObjectiveAs a prevalent and infiltrative cancer type of the central nervous system, the prognosis of lower-grade glioma (LGG) in adults is highly heterogeneous. Recent evidence has demonstrated the prognostic value of the mRNA expression-based stemness index (mRNAsi) in LGG. Our aim was to develop a stemness index-based signature (SI-signature) for risk stratification and survival prediction.MethodsDifferentially expressed genes (DEGs) between LGG in the Cancer Genome Atlas (TCGA) and normal brain tissue samples from the Genotype-Tissue Expression (GTEx) project were screened out, and the weighted gene correlation network analysis (WGCNA) was employed to identify the mRNAsi-related gene sets. Meanwhile, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed for the functional annotation of the key genes. ESTIMATE was used to calculate tumor purity for acquiring the correct mRNAsi. Differences in overall survival (OS) between the high and low mRNAsi (corrected mRNAsi) groups were compared using the Kaplan Meier analysis. By combining the Lasso regression with univariate and multivariate Cox regression, the SI-signature was constructed and validated using the Chinese Glioma Genome Atlas (CGGA).ResultsThere was a significant difference in OS between the high and low mRNAsi groups, which was also observed in the two corrected mRNAsi groups. Based on threshold limits, 86 DEGs were most significantly associated with mRNAsi via WGCNA. Seven genes (ADAP2, ALOX5AP, APOBEC3C, FCGRT, GNG5, LRRC25, and SP100) were selected to establish a risk signature for primary LGG. The ROC curves showed a fair performance in survival prediction in both the TCGA and the CGGA validation cohorts. Univariate and multivariate Cox regression revealed that the risk group was an independent prognostic factor in primary LGG. The nomogram was developed based on clinical parameters integrated with the risk signature, and its accuracy for predicting 3- and 5-years survival was assessed by the concordance index, the area under the curve of the time-dependent receiver operating characteristics curve, and calibration curves.ConclusionThe SI-signature with seven genes could serve as an independent predictor, and suggests the importance of stemness features in risk stratification and survival prediction in primary LGG.

Project description:BackgroundCD86 has great potential to be a new target of immunotherapy by regulating cancer immune response. However, it remains unclear whether CD86 is a friend or foe in lower-grade glioma (LGG).MethodsThe prognostic value of CD86 expression in pan-cancer was analyzed using Cox regression and Kaplan-Meier analysis with data from the cancer genome atlas (TCGA). Cancer types where CD86 showed prognostic value in overall survival and disease-specific survival were identified for further analyses. The Chinese Glioma Genome Atlas (CGGA) dataset were utilized for external validation. Quantitative real-time PCR (qRT-PCR), Western blot (WB), and Immunohistochemistry (IHC) were conducted for further validation using surgical samples from Jiangsu Province hospital. The correlations between CD86 expression and tumor immunity were analyzed using the Estimation of Stromal and Immune cells in Malignant Tumours using Expression data (ESTIMATE) algorithm, Tumor IMmune Estimation Resource (TIMER) database, and expressions of immune checkpoint molecules. Gene Set Enrichment Analysis (GSEA) was performed using clusterprofiler r package to reveal potential pathways.ResultsPan-cancer survival analysis established CD86 expression as an unfavorable prognostic factor in tumor progression and survival for LGG. CD86 expression between Grade-II and Grade-III LGG was validated using qRT-PCR and WB. Additionally, CD86 expression in LGG with unmethylated O(6)-methylguanine-DNA-methyltransferase (MGMT) promoter was significantly higher than those with methylated MGMT (P<0.05), while in LGG with codeletion of 1p/19q it was significantly downregulated as opposed to those with non-codeletion (P<2.2*10-16). IHC staining validated that CD86 expression was correlated with MGMT status and X1p/19q subtypes, which was independent of tumor grade. Multivariate regression validated that CD86 expression acts as an unfavorable prognostic factor independent of clinicopathological factors in overall survival of LGG patients. Analysis of tumor immunity and GSEA revealed pivotal role of CD86 in immune response for LGG.ConclusionsIntegrated analysis shows that CD86 is an unfavorable prognostic biomarker in LGG patients. Targeting CD86 may become a novel approach for immunotherapy of LGG.

Dataset Information

Early 2 factor (E2F) transcription factors contribute to malignant progression and have clinical prognostic value in lower-grade glioma.

Publications

Early 2 factor (E2F) transcription factors contribute to malignant progression and have clinical prognostic value in lower-grade glioma.

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