Basic Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Oct 24, 2023; 14(10): 357-372
Published online Oct 24, 2023. doi: 10.5306/wjco.v14.i10.357
Hub genes and their key effects on prognosis of Burkitt lymphoma
Yan-Feng Xu, Guan-Yun Wang, Ming-Yu Zhang, Ji-Gang Yang
Yan-Feng Xu, Guan-Yun Wang, Ming-Yu Zhang, Ji-Gang Yang, Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
Author contributions: Xu YF and Yang JG designed the research; Xu YF, Wang GY and Zhang MY performed the research; Xu YF, Wang GY contributed new reagents/analytic tools; Xu YF analyzed the data; Xu YF, Zhang MY, Wang GY and Yang JG wrote the paper.
Supported by National Natural Science Foundation of China (General Program), No. 82272034.
Institutional review board statement: Institutional review board statement is not applied to our manuscript.
Institutional animal care and use committee statement: Institutional animal care and use committee statement is not applied to our manuscript.
Conflict-of-interest statement: All authors declare that they have no conflicts of interest and have never published the manuscript.
Data sharing statement: The datasets analyzed (GSE4475 and GSE69051) during this study are publicly available in the GEO database (https://www.ncbi.nlm.nih.gov/geo/), the original contributions presented in this study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author (yangjigang@ccmu.edu.cn).
ARRIVE guidelines statement: The authors have read the ARRIVE Guidelines, and the manuscript was prepared and revised according to the ARRIVE Guidelines.
Open-Access: 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. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ji-Gang Yang, MD, PhD, Chief Doctor, Professor, Researcher, Department of Nuclear Medicine, Beijing Friendship Hospital, Capital Medical University, No. 95 Yong An Road, Xicheng District, Beijing 100050, China. yangjigang@ccmu.edu.cn
Received: July 19, 2023
Peer-review started: July 19, 2023
First decision: August 24, 2023
Revised: September 6, 2023
Accepted: September 18, 2023
Article in press: September 18, 2023
Published online: October 24, 2023
Processing time: 96 Days and 20.1 Hours
ARTICLE HIGHLIGHTS
Research background

Burkitt lymphoma (BL) is an exceptionally aggressive malignant neoplasm originating from either the germinal center or post-germinal center B cells. However, a standardized treatment regimen for BL has yet to be established. The utilization of microarray data and sequencing information retrieved from public databases presents promising prospects for the identification of novel diagnostic or therapeutic targets.

Research motivation

It is crucial to identify biomarkers that can predict the prognosis of BLs and distinguish patients who would benefit from specific therapies.

Research objectives

The aim of our study was to identify hub genes and conduct gene ontology analysis specifically in BL, as well as perform functional enrichment analysis. Additionally, we performed survival analysis and developed a novel prognostic model incorporating candidate genes along with clinical features.

Research methods

The gene expression profiles and clinical traits of BL patients were obtained from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was employed to construct gene co-expression modules, while the cytoHubba tool was utilized to identify hub genes. Prognostic candidate genes were identified through overall survival (OS) analysis. A nomogram was developed to evaluate the predictive value of the hub genes.

Research results

In this study, we identified 8 modules through WGCNA analysis and found a significant correlation between the yellow module and age. By using the cytoHubba tool, we identified 10 hub genes (SRC, TLR4, CD40, STAT3, SELL, CXCL10, IL2RA, IL10RA, CCR7, and FCGR2B). Among these hubs, two genes (CXCL10 with P = 0.029 and IL2RA with P = 0.0066) were associated with OS based on our survival analysis.

Research conclusions

This study is the first to investigate gene expression in BL using WGCNA. We have identified and validated 10 hub genes, demonstrating that the overexpression of CXCL10 and IL2RA in BL can serve as robust prognostic indicators. Furthermore, the integration of an mRNA signature with age nomogram holds promising potential for predicting patient outcomes in BLs.

Research perspectives

Further genetic and experimental investigations are imperative to elucidate the underlying mechanism and functional significance of these hub genes in the carcinogenesis and progression of BLs.