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Hub genes and their key effects on prognosis of Burkitt lymphoma

BACKGROUND: Burkitt lymphoma (BL) is an exceptionally aggressive malignant neoplasm that arises from either the germinal center or post-germinal center B cells. Patients with BL often present with rapid tumor growth and require high-intensity multi-drug therapy combined with adequate intrathecal che...

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Autores principales: Xu, Yan-Feng, Wang, Guan-Yun, Zhang, Ming-Yu, Yang, Ji-Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10631346/
https://www.ncbi.nlm.nih.gov/pubmed/37970111
http://dx.doi.org/10.5306/wjco.v14.i10.357
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author Xu, Yan-Feng
Wang, Guan-Yun
Zhang, Ming-Yu
Yang, Ji-Gang
author_facet Xu, Yan-Feng
Wang, Guan-Yun
Zhang, Ming-Yu
Yang, Ji-Gang
author_sort Xu, Yan-Feng
collection PubMed
description BACKGROUND: Burkitt lymphoma (BL) is an exceptionally aggressive malignant neoplasm that arises from either the germinal center or post-germinal center B cells. Patients with BL often present with rapid tumor growth and require high-intensity multi-drug therapy combined with adequate intrathecal chemotherapy prophylaxis, however, a standard treatment program for BL has not yet been established. It is important to identify biomarkers for predicting the prognosis of BLs and discriminating patients who might benefit from the therapy. Microarray data and sequencing information from public databases could offer opportunities for the discovery of new diagnostic or therapeutic targets. AIM: To identify hub genes and perform gene ontology (GO) and survival analysis in BL. METHODS: Gene expression profiles and clinical traits of BL patients were collected from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was applied to construct gene co-expression modules, and the cytoHubba tool was used to find the hub genes. Then, the hub genes were analyzed using GO and Kyoto Encyclopedia of Genes and Genomes analysis. Additionally, a Protein-Protein Interaction network and a Genetic Interaction network were constructed. Prognostic candidate genes were identified through overall survival analysis. Finally, a nomogram was established to assess the predictive value of hub genes, and drug-gene interactions were also constructed. RESULTS: In this study, we obtained 8 modules through WGCNA analysis, and there was a significant correlation between the yellow module and age. Then we identified 10 hub genes (SRC, TLR4, CD40, STAT3, SELL, CXCL10, IL2RA, IL10RA, CCR7 and FCGR2B) by cytoHubba tool. Within these hubs, two genes were found to be associated with OS (CXCL10, P = 0.029 and IL2RA, P = 0.0066) by survival analysis. Additionally, we combined these two hub genes and age to build a nomogram. Moreover, the drugs related to IL2RA and CXCL10 might have a potential therapeutic role in relapsed and refractory BL. CONCLUSION: From WGCNA and survival analysis, we identified CXCL10 and IL2RA that might be prognostic markers for BL.
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spelling pubmed-106313462023-11-15 Hub genes and their key effects on prognosis of Burkitt lymphoma Xu, Yan-Feng Wang, Guan-Yun Zhang, Ming-Yu Yang, Ji-Gang World J Clin Oncol Basic Study BACKGROUND: Burkitt lymphoma (BL) is an exceptionally aggressive malignant neoplasm that arises from either the germinal center or post-germinal center B cells. Patients with BL often present with rapid tumor growth and require high-intensity multi-drug therapy combined with adequate intrathecal chemotherapy prophylaxis, however, a standard treatment program for BL has not yet been established. It is important to identify biomarkers for predicting the prognosis of BLs and discriminating patients who might benefit from the therapy. Microarray data and sequencing information from public databases could offer opportunities for the discovery of new diagnostic or therapeutic targets. AIM: To identify hub genes and perform gene ontology (GO) and survival analysis in BL. METHODS: Gene expression profiles and clinical traits of BL patients were collected from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was applied to construct gene co-expression modules, and the cytoHubba tool was used to find the hub genes. Then, the hub genes were analyzed using GO and Kyoto Encyclopedia of Genes and Genomes analysis. Additionally, a Protein-Protein Interaction network and a Genetic Interaction network were constructed. Prognostic candidate genes were identified through overall survival analysis. Finally, a nomogram was established to assess the predictive value of hub genes, and drug-gene interactions were also constructed. RESULTS: In this study, we obtained 8 modules through WGCNA analysis, and there was a significant correlation between the yellow module and age. Then we identified 10 hub genes (SRC, TLR4, CD40, STAT3, SELL, CXCL10, IL2RA, IL10RA, CCR7 and FCGR2B) by cytoHubba tool. Within these hubs, two genes were found to be associated with OS (CXCL10, P = 0.029 and IL2RA, P = 0.0066) by survival analysis. Additionally, we combined these two hub genes and age to build a nomogram. Moreover, the drugs related to IL2RA and CXCL10 might have a potential therapeutic role in relapsed and refractory BL. CONCLUSION: From WGCNA and survival analysis, we identified CXCL10 and IL2RA that might be prognostic markers for BL. Baishideng Publishing Group Inc 2023-10-24 2023-10-24 /pmc/articles/PMC10631346/ /pubmed/37970111 http://dx.doi.org/10.5306/wjco.v14.i10.357 Text en ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.
spellingShingle Basic Study
Xu, Yan-Feng
Wang, Guan-Yun
Zhang, Ming-Yu
Yang, Ji-Gang
Hub genes and their key effects on prognosis of Burkitt lymphoma
title Hub genes and their key effects on prognosis of Burkitt lymphoma
title_full Hub genes and their key effects on prognosis of Burkitt lymphoma
title_fullStr Hub genes and their key effects on prognosis of Burkitt lymphoma
title_full_unstemmed Hub genes and their key effects on prognosis of Burkitt lymphoma
title_short Hub genes and their key effects on prognosis of Burkitt lymphoma
title_sort hub genes and their key effects on prognosis of burkitt lymphoma
topic Basic Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10631346/
https://www.ncbi.nlm.nih.gov/pubmed/37970111
http://dx.doi.org/10.5306/wjco.v14.i10.357
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