A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma
BackgroundGlioma is a highly aggressive brain cancer with a poor prognosis. Necroptosis is a form of programmed cell death occurring during tumor development and in immune microenvironments. The prognostic value of necroptosis in glioma is unclear. This study aimed to develop a prognostic glioma mod...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-10-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.1027794/full |
| _version_ | 1798030541307510784 |
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| author | Ying-Shi Yuan Ying-Shi Yuan Xin Jin Lu Chen Jia-Min Liao Yang Zhang Ke-Wei Yu Wei-Kang Li Shun-Wang Cao Xian-Zhang Huang Xian-Zhang Huang Chun-Min Kang Chun-Min Kang |
| author_facet | Ying-Shi Yuan Ying-Shi Yuan Xin Jin Lu Chen Jia-Min Liao Yang Zhang Ke-Wei Yu Wei-Kang Li Shun-Wang Cao Xian-Zhang Huang Xian-Zhang Huang Chun-Min Kang Chun-Min Kang |
| author_sort | Ying-Shi Yuan |
| collection | DOAJ |
| description | BackgroundGlioma is a highly aggressive brain cancer with a poor prognosis. Necroptosis is a form of programmed cell death occurring during tumor development and in immune microenvironments. The prognostic value of necroptosis in glioma is unclear. This study aimed to develop a prognostic glioma model based on necroptosis.MethodsA necroptosis-related risk model was constructed by Cox regression analysis based on The Cancer Genome Atlas (TCGA) training set, validated in two Chinese Glioma Genome Atlas (CGGA) validation sets. We explored the differences in immune infiltration and immune checkpoint genes between low and high risk groups and constructed a nomogram. Moreover, we compiled a third validation cohort including 43 glioma patients. The expression of necroptosis-related genes was verified in matched tissues using immunochemical staining in the third cohort, and we analyzed their relationship to clinicopathological features.ResultsThree necroptosis-related differentially expressed genes (EZH2, LEF1, and CASP1) were selected to construct the prognostic model. Glioma patients with a high risk score in the TCGA and CGGA cohorts had significantly shorter overall survival. The necroptosis-related risk model and nomogram exhibited good predictive performance in the TCGA training set and the CGGA validation sets. Furthermore, patients in the high risk group had higher immune infiltration status and higher expression of immune checkpoint genes, which was positively correlated with poorer outcomes. In the third validation cohort, the expression levels of the three proteins encoded by EZH2, LEF1, and CASP1 in glioma tissues were significantly higher than those from paracancerous tissues. They were also closely associated with disease severity and prognosis.ConclusionsOur necroptosis-related risk model can be used to predict the prognosis of glioma patients and improve prognostic accuracy, which may provide potential therapeutic targets and a theoretical basis for treatment. |
| first_indexed | 2024-04-11T19:41:54Z |
| format | Article |
| id | doaj.art-8d1ed84e8078406082909cf89e861a8b |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-04-11T19:41:54Z |
| publishDate | 2022-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-8d1ed84e8078406082909cf89e861a8b2022-12-22T04:06:41ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-10-011310.3389/fimmu.2022.10277941027794A novel model based on necroptosis-related genes for predicting immune status and prognosis in gliomaYing-Shi Yuan0Ying-Shi Yuan1Xin Jin2Lu Chen3Jia-Min Liao4Yang Zhang5Ke-Wei Yu6Wei-Kang Li7Shun-Wang Cao8Xian-Zhang Huang9Xian-Zhang Huang10Chun-Min Kang11Chun-Min Kang12Department of Laboratory Medicine, The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, ChinaDepartment of Laboratory Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, Guangdong, ChinaDepartment of Neurosurgery, Guangdong 999 Brain Hospital, Guangzhou, Guangdong, ChinaDepartment of Laboratory Medicine, The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, ChinaDepartment of Laboratory Medicine, The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, ChinaDepartment of Laboratory Medicine, The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, ChinaDepartment of Laboratory Medicine, The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, ChinaDepartment of Laboratory Medicine, The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, ChinaDepartment of Laboratory Medicine, The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, ChinaDepartment of Laboratory Medicine, The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, ChinaDepartment of Laboratory Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, Guangdong, ChinaDepartment of Laboratory Medicine, The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, ChinaDepartment of Laboratory Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, Guangdong, ChinaBackgroundGlioma is a highly aggressive brain cancer with a poor prognosis. Necroptosis is a form of programmed cell death occurring during tumor development and in immune microenvironments. The prognostic value of necroptosis in glioma is unclear. This study aimed to develop a prognostic glioma model based on necroptosis.MethodsA necroptosis-related risk model was constructed by Cox regression analysis based on The Cancer Genome Atlas (TCGA) training set, validated in two Chinese Glioma Genome Atlas (CGGA) validation sets. We explored the differences in immune infiltration and immune checkpoint genes between low and high risk groups and constructed a nomogram. Moreover, we compiled a third validation cohort including 43 glioma patients. The expression of necroptosis-related genes was verified in matched tissues using immunochemical staining in the third cohort, and we analyzed their relationship to clinicopathological features.ResultsThree necroptosis-related differentially expressed genes (EZH2, LEF1, and CASP1) were selected to construct the prognostic model. Glioma patients with a high risk score in the TCGA and CGGA cohorts had significantly shorter overall survival. The necroptosis-related risk model and nomogram exhibited good predictive performance in the TCGA training set and the CGGA validation sets. Furthermore, patients in the high risk group had higher immune infiltration status and higher expression of immune checkpoint genes, which was positively correlated with poorer outcomes. In the third validation cohort, the expression levels of the three proteins encoded by EZH2, LEF1, and CASP1 in glioma tissues were significantly higher than those from paracancerous tissues. They were also closely associated with disease severity and prognosis.ConclusionsOur necroptosis-related risk model can be used to predict the prognosis of glioma patients and improve prognostic accuracy, which may provide potential therapeutic targets and a theoretical basis for treatment.https://www.frontiersin.org/articles/10.3389/fimmu.2022.1027794/fullgliomanecroptosisprognostic modelimmune infiltrationimmune checkpoint |
| spellingShingle | Ying-Shi Yuan Ying-Shi Yuan Xin Jin Lu Chen Jia-Min Liao Yang Zhang Ke-Wei Yu Wei-Kang Li Shun-Wang Cao Xian-Zhang Huang Xian-Zhang Huang Chun-Min Kang Chun-Min Kang A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma Frontiers in Immunology glioma necroptosis prognostic model immune infiltration immune checkpoint |
| title | A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma |
| title_full | A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma |
| title_fullStr | A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma |
| title_full_unstemmed | A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma |
| title_short | A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma |
| title_sort | novel model based on necroptosis related genes for predicting immune status and prognosis in glioma |
| topic | glioma necroptosis prognostic model immune infiltration immune checkpoint |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.1027794/full |
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