EFNB1 Acts as a Novel Prognosis Marker in Glioblastoma through Bioinformatics Methods and Experimental Validation
| العنوان: | EFNB1 Acts as a Novel Prognosis Marker in Glioblastoma through Bioinformatics Methods and Experimental Validation |
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| المؤلفون: | Hongyan Cheng, Yuanyuan Sun, Chen Wang, Yaohong Shi |
| المصدر: | Journal of Oncology, Vol 2021 (2021) Journal of Oncology |
| بيانات النشر: | Hindawi Limited, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Article Subject, biology, business.industry, Cancer, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Computational biology, medicine.disease, Receptor tyrosine kinase, Biomarker (cell), Oncology, Downregulation and upregulation, Gene expression, biology.protein, Medicine, business, Gene, Survival analysis, Function (biology), RC254-282, Research Article |
| الوصف: | Purpose. Ephrin B1 (EFNB1), the Eph-associated receptor tyrosine kinase ligand, is suggested to have an important function in neurodevelopment. However, its contribution to glioblastoma multiforme (GBM) remains uncertain. This study aimed to determine the prognostic power and immune implication of EFNB1 in GBM. Methods. We first identified differentially coexpressed genes within GBM relative to noncarcinoma samples from GEO and TCGA databases by WGCNA. The STRING online database and the maximum cluster centrality (MCC) algorithm in Cytoscape software were used to design for predicting protein-protein interactions (PPI) and calculating pivot nodes, respectively. The expression of hub genes in cancer and noncancer tissues was verified by an online tool gene expression profile interactive analysis (GEPIA). Thereafter, the TISIDB online tool with Cox correlation regression method was employed to screen for immunomodulators associated with EFNB1 and to model the risk associated with immunomodulators. Results. Altogether 201 differentially expressed genes (DEGs) were discovered. After that, 10 hub genes (CALB2, EFNB1, ENO2, EPHB4, NES, OBSCN, RAB9B, RPL23A, STMN2, and THY1) were incorporated to construct the PPI network. As revealed by survival analysis, EFNB1 upregulation predicted poor overall survival (OS) for GBM cases. Furthermore, we developed a prognostic risk signature according to the EFNB1-associated immunomodulators. Kaplan–Meier survival analysis and receiver operating characteristic method were adopted for analysis, which revealed that our signature showed favorable accuracy of prognosis prediction. Finally, EFNB1 inhibition was found to block cell proliferation and migration in GBM cells. Conclusion. The above results indicate that EFNB1 participates in cancer immunity and progression, which is the candidate biomarker for GBM. |
| وصف الملف: | text/xhtml |
| اللغة: | English |
| تدمد: | 1687-8469 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c41bacce8a2377ea9fab8f7aa87623f7Test https://doaj.org/article/b9306f2e69474a2ead6cc1402b661412Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....c41bacce8a2377ea9fab8f7aa87623f7 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 16878469 |
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