Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach
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...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-04-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024055804 |
| _version_ | 1797203061260681216 |
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| author | Yu Wang Yuhao Wang Shuai Wang Chengcheng Wang Yuhang Tang Chao Zhang Dong Yu Shiqiang Hou Ning Lin |
| author_facet | Yu Wang Yuhao Wang Shuai Wang Chengcheng Wang Yuhang Tang Chao Zhang Dong Yu Shiqiang Hou Ning Lin |
| author_sort | Yu Wang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-24T08:13:20Z |
| format | Article |
| id | doaj.art-e2273af8a5c64f2789a1c9f2a60f9e3f |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-24T08:13:20Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-e2273af8a5c64f2789a1c9f2a60f9e3f2024-04-17T04:49:32ZengElsevierHeliyon2405-84402024-04-01108e29549Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approachYu Wang0Yuhao Wang1Shuai Wang2Chengcheng Wang3Yuhang Tang4Chao Zhang5Dong Yu6Shiqiang Hou7Ning Lin8Department of Neurosurgery, The Affliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, 239000, ChinaDepartment of Neurosurgery, The Affliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, 239000, ChinaDepartment of Neurosurgery, The Affliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, 239000, ChinaDepartment of Neurosurgery, The Affliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, 239000, ChinaDepartment of Neurosurgery, The Affliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, 239000, ChinaDepartment of Neurosurgery, The Affliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, 239000, ChinaDepartment of Neurosurgery, The Affliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, 239000, ChinaDepartment of Neurosurgery, The Affliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, 239000, ChinaCorresponding author.; Department of Neurosurgery, The Affliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou, 239000, ChinaBackground: 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.http://www.sciencedirect.com/science/article/pii/S2405844024055804GliomaCYBBGene expressionMitochondriaPrognostic model |
| spellingShingle | Yu Wang Yuhao Wang Shuai Wang Chengcheng Wang Yuhang Tang Chao Zhang Dong Yu Shiqiang Hou Ning Lin Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach Heliyon Glioma CYBB Gene expression Mitochondria Prognostic model |
| title | Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach |
| title_full | Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach |
| title_fullStr | Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach |
| title_full_unstemmed | Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach |
| title_short | Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach |
| title_sort | comprehensive analysis of cybb as a prognostic marker and therapeutic target in glioma a bioinformatics approach |
| topic | Glioma CYBB Gene expression Mitochondria Prognostic model |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024055804 |
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