EFNB1 Acts as a Novel Prognosis Marker in Glioblastoma through Bioinformatics Methods and Experimental Validation

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 E...

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Autores principales:	Yaohong Shi, Yuanyuan Sun, Hongyan Cheng, Chen Wang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/b9306f2e69474a2ead6cc1402b661412
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spelling	oai:doaj.org-article:b9306f2e69474a2ead6cc1402b6614122021-11-29T00:56:13ZEFNB1 Acts as a Novel Prognosis Marker in Glioblastoma through Bioinformatics Methods and Experimental Validation1687-846910.1155/2021/4701680https://doaj.org/article/b9306f2e69474a2ead6cc1402b6614122021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/4701680https://doaj.org/toc/1687-8469Purpose. 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.Yaohong ShiYuanyuan SunHongyan ChengChen WangHindawi LimitedarticleNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENJournal of Oncology, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Yaohong Shi Yuanyuan Sun Hongyan Cheng Chen Wang EFNB1 Acts as a Novel Prognosis Marker in Glioblastoma through Bioinformatics Methods and Experimental Validation
description	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.
format	article
author	Yaohong Shi Yuanyuan Sun Hongyan Cheng Chen Wang
author_facet	Yaohong Shi Yuanyuan Sun Hongyan Cheng Chen Wang
author_sort	Yaohong Shi
title	EFNB1 Acts as a Novel Prognosis Marker in Glioblastoma through Bioinformatics Methods and Experimental Validation
title_short	EFNB1 Acts as a Novel Prognosis Marker in Glioblastoma through Bioinformatics Methods and Experimental Validation
title_full	EFNB1 Acts as a Novel Prognosis Marker in Glioblastoma through Bioinformatics Methods and Experimental Validation
title_fullStr	EFNB1 Acts as a Novel Prognosis Marker in Glioblastoma through Bioinformatics Methods and Experimental Validation
title_full_unstemmed	EFNB1 Acts as a Novel Prognosis Marker in Glioblastoma through Bioinformatics Methods and Experimental Validation
title_sort	efnb1 acts as a novel prognosis marker in glioblastoma through bioinformatics methods and experimental validation
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/b9306f2e69474a2ead6cc1402b661412
work_keys_str_mv	AT yaohongshi efnb1actsasanovelprognosismarkeringlioblastomathroughbioinformaticsmethodsandexperimentalvalidation AT yuanyuansun efnb1actsasanovelprognosismarkeringlioblastomathroughbioinformaticsmethodsandexperimentalvalidation AT hongyancheng efnb1actsasanovelprognosismarkeringlioblastomathroughbioinformaticsmethodsandexperimentalvalidation AT chenwang efnb1actsasanovelprognosismarkeringlioblastomathroughbioinformaticsmethodsandexperimentalvalidation
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EFNB1 Acts as a Novel Prognosis Marker in Glioblastoma through Bioinformatics Methods and Experimental Validation

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