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CYBB作为胶质瘤预后标志物和治疗靶点的综合分析：一种生物信息学方法

Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach.

作者信息

Wang Yu, Wang Yuhao, Wang Shuai, Wang Chengcheng, Tang Yuhang, Zhang Chao, Yu Dong, Hou Shiqiang, Lin Ning

机构信息

Department of Neurosurgery, The Affliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, 239000, China.

出版信息

Heliyon. 2024 Apr 14;10(8):e29549. doi: 10.1016/j.heliyon.2024.e29549. eCollection 2024 Apr 30.

DOI:10.1016/j.heliyon.2024.e29549
PMID:38655339
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11036048/
Abstract

BACKGROUND

In the central nervous system, glioma is the most common malignant tumor, and patients have a poor prognosis. Identification of novel marker genes and establishment of prognostic models are important for early diagnosis and prognosis determination.

METHODS

Download glioma data from the CGGA and TCG databases. Application of bioinformatics to analyze the impact of CYBB on the clinicopathological characteristics, immunological features and prognosis of gliomas. Using single-cell sequencing data from 7 glioblastoma patients in the CGGA database, the role of CYBB in the tumor microenvironment was analyzed. In addition, a prognostic model was constructed based on CYBB high and low differentially expressed genes and mitochondrial genes.

RESULTS

The expression of CYBB is closely related to various clinical features, immune cell infiltration level, immune checkpoint and survival time of patients. A 10-gene prediction model was constructed based on the differentially expressed genes of low and high CYBB and mitochondria-related genes. Glioma patients with higher risk scores had significantly lower survival probabilities. Receiver operating characteristic curves and nomograms were plotted over time to show the predictive accuracy and predictive value of the 10-gene prognostic model.

CONCLUSIONS

Our study shows that CYBB is strongly correlated with clinical characteristics features and prognosis of glioma patients, and can be used as a potential therapeutic target. Prognostic models based on CYBB and mitochondrial genes have good performance in predicting prognosis of glioma patients.

摘要

背景

在中枢神经系统中，胶质瘤是最常见的恶性肿瘤，患者预后较差。鉴定新的标志物基因并建立预后模型对于早期诊断和预后判定至关重要。

方法

从CGGA和TCG数据库下载胶质瘤数据。应用生物信息学分析CYBB对胶质瘤临床病理特征、免疫特征和预后的影响。利用CGGA数据库中7例胶质母细胞瘤患者的单细胞测序数据，分析CYBB在肿瘤微环境中的作用。此外，基于CYBB高低差异表达基因和线粒体基因构建预后模型。

结果

CYBB的表达与患者的各种临床特征、免疫细胞浸润水平、免疫检查点和生存时间密切相关。基于CYBB高低差异表达基因和线粒体相关基因构建了一个10基因预测模型。风险评分较高的胶质瘤患者生存概率显著较低。绘制了随时间变化的受试者工作特征曲线和列线图，以显示10基因预后模型的预测准确性和预测价值。

结论

我们的研究表明，CYBB与胶质瘤患者的临床特征和预后密切相关，可作为潜在的治疗靶点。基于CYBB和线粒体基因的预后模型在预测胶质瘤患者预后方面具有良好性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/7ea20be49d6e/gr10.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/c8dd5e54d9c1/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/56ea542991e1/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/490acd96f04f/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/c506598b7d3e/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/ab0018674157/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/75daad7e5d78/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/ae6cb5ddd062/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/e539b1d2ee59/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/2af0b4269141/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/7ea20be49d6e/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/c37814cc0e80/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/c8dd5e54d9c1/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/56ea542991e1/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/490acd96f04f/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/c506598b7d3e/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/ab0018674157/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/75daad7e5d78/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/ae6cb5ddd062/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/e539b1d2ee59/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/2af0b4269141/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11dc/11036048/7ea20be49d6e/gr10.jpg

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