Machine learning unveils immune-related signature in multicenter glioma studies
Summary: In glioma molecular subtyping, existing biomarkers are limited, prompting the development of new ones. We present a multicenter study-derived consensus immune-related and prognostic gene signature (CIPS) using an optimal risk score model and 101 algorithms. CIPS, an independent risk factor,...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-04-01
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| Series: | iScience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004224005388 |
| _version_ | 1797262877204152320 |
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| author | Sha Yang Xiang Wang Renzheng Huan Mei Deng Zhuo Kong Yunbiao Xiong Tao Luo Zheng Jin Jian Liu Liangzhao Chu Guoqiang Han Jiqin Zhang Ying Tan |
| author_facet | Sha Yang Xiang Wang Renzheng Huan Mei Deng Zhuo Kong Yunbiao Xiong Tao Luo Zheng Jin Jian Liu Liangzhao Chu Guoqiang Han Jiqin Zhang Ying Tan |
| author_sort | Sha Yang |
| collection | DOAJ |
| description | Summary: In glioma molecular subtyping, existing biomarkers are limited, prompting the development of new ones. We present a multicenter study-derived consensus immune-related and prognostic gene signature (CIPS) using an optimal risk score model and 101 algorithms. CIPS, an independent risk factor, showed stable and powerful predictive performance for overall and progression-free survival, surpassing traditional clinical variables. The risk score correlated significantly with the immune microenvironment, indicating potential sensitivity to immunotherapy. High-risk groups exhibited distinct chemotherapy drug sensitivity. Seven signature genes, including IGFBP2 and TNFRSF12A, were validated by qRT-PCR, with higher expression in tumors and prognostic relevance. TNFRSF12A, upregulated in GBM, demonstrated inhibitory effects on glioma cell proliferation, migration, and invasion. CIPS emerges as a robust tool for enhancing individual glioma patient outcomes, while IGFBP2 and TNFRSF12A pose as promising tumor markers and therapeutic targets. |
| first_indexed | 2024-04-25T00:04:05Z |
| format | Article |
| id | doaj.art-c30e4f902d0c4c39a4be8d159ed6bb9f |
| institution | Directory Open Access Journal |
| issn | 2589-0042 |
| language | English |
| last_indexed | 2024-04-25T00:04:05Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj.art-c30e4f902d0c4c39a4be8d159ed6bb9f2024-03-14T06:15:49ZengElsevieriScience2589-00422024-04-01274109317Machine learning unveils immune-related signature in multicenter glioma studiesSha Yang0Xiang Wang1Renzheng Huan2Mei Deng3Zhuo Kong4Yunbiao Xiong5Tao Luo6Zheng Jin7Jian Liu8Liangzhao Chu9Guoqiang Han10Jiqin Zhang11Ying Tan12Guizhou University Medical College, Guiyang 550025, Guizhou Province, ChinaDepartment of Neurosurgery, the Affiliated Hospital of Guizhou Medical University, Guiyang 550004, ChinaDepartment of Neurosurgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, ChinaDepartment of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, ChinaDepartment of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, ChinaDepartment of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, ChinaDepartment of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, ChinaDepartment of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, ChinaGuizhou University Medical College, Guiyang 550025, Guizhou Province, China; Department of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, ChinaDepartment of Neurosurgery, the Affiliated Hospital of Guizhou Medical University, Guiyang 550004, ChinaDepartment of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China; Corresponding authorDepartment of Anesthesiology, Guizhou Provincial People’s Hospital, Guiyang, China; Corresponding authorDepartment of Neurosurgery, Guizhou Provincial People’s Hospital, Guiyang, China; Corresponding authorSummary: In glioma molecular subtyping, existing biomarkers are limited, prompting the development of new ones. We present a multicenter study-derived consensus immune-related and prognostic gene signature (CIPS) using an optimal risk score model and 101 algorithms. CIPS, an independent risk factor, showed stable and powerful predictive performance for overall and progression-free survival, surpassing traditional clinical variables. The risk score correlated significantly with the immune microenvironment, indicating potential sensitivity to immunotherapy. High-risk groups exhibited distinct chemotherapy drug sensitivity. Seven signature genes, including IGFBP2 and TNFRSF12A, were validated by qRT-PCR, with higher expression in tumors and prognostic relevance. TNFRSF12A, upregulated in GBM, demonstrated inhibitory effects on glioma cell proliferation, migration, and invasion. CIPS emerges as a robust tool for enhancing individual glioma patient outcomes, while IGFBP2 and TNFRSF12A pose as promising tumor markers and therapeutic targets.http://www.sciencedirect.com/science/article/pii/S2589004224005388ImmunologyMachine learning |
| spellingShingle | Sha Yang Xiang Wang Renzheng Huan Mei Deng Zhuo Kong Yunbiao Xiong Tao Luo Zheng Jin Jian Liu Liangzhao Chu Guoqiang Han Jiqin Zhang Ying Tan Machine learning unveils immune-related signature in multicenter glioma studies iScience Immunology Machine learning |
| title | Machine learning unveils immune-related signature in multicenter glioma studies |
| title_full | Machine learning unveils immune-related signature in multicenter glioma studies |
| title_fullStr | Machine learning unveils immune-related signature in multicenter glioma studies |
| title_full_unstemmed | Machine learning unveils immune-related signature in multicenter glioma studies |
| title_short | Machine learning unveils immune-related signature in multicenter glioma studies |
| title_sort | machine learning unveils immune related signature in multicenter glioma studies |
| topic | Immunology Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S2589004224005388 |
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