An analysis of prognostic risk and immunotherapy response of glioblastoma patients based on single-cell landscape and nitrogen metabolism
Glioblastoma (GBM) is a highly invasive brain tumor of astrocytic origin. Nitrogen metabolism plays an instrumental role in the growth and progression of various tumors, including GBM. This study intended to mine nitrogen metabolism-related biomarkers for GBM-related research of prognosis and immuno...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-07-01
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| Series: | Neurobiology of Disease |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0969996125001512 |
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| author | Minfeng Tong Zhijian Xu Lude Wang Huahui Chen Xing Wan Hu Xu Song Yang Qi Tu |
| author_facet | Minfeng Tong Zhijian Xu Lude Wang Huahui Chen Xing Wan Hu Xu Song Yang Qi Tu |
| author_sort | Minfeng Tong |
| collection | DOAJ |
| description | Glioblastoma (GBM) is a highly invasive brain tumor of astrocytic origin. Nitrogen metabolism plays an instrumental role in the growth and progression of various tumors, including GBM. This study intended to mine nitrogen metabolism-related biomarkers for GBM-related research of prognosis and immunotherapy. Through single-cell data analysis of GBM, we identified four cell types (Astrocytes, Macrophages, Fibroblasts, and Endothelial cells). We calculated the nitrogen metabolism scores and conducted trajectory analysis for the most abundant cells, Astrocytes, revealing 6 differentiation directions of Astrocytes, which included the main differentiation direction from cells with low nitrogen metabolism scores to cells with high nitrogen metabolism scores. Furthermore, based on the differentially expressed genes (DEGs) with high/low nitrogen metabolism scores, we constructed a 7-gene prognostic model by utilizing regression analysis. qRT-PCR analysis showed that IGFBP2, CHPF, CTSZ, UPP1, TCF12, ZBTB20 and RBP1 were all significantly up-regulated in the GBM cells. Through differential analysis, a protein-protein interaction (PPI) network, and enrichment analyses, we identified and analyzed the DEGs in the high RiskScore subgroup, revealing complex interactions among DEGs, which were mainly related to pathways such as TNF signaling pathway and NF-κB signaling pathway. By leveraging univariate analysis, survival-related genes were selected from the nitrogen metabolism-related gene sets. Clustering, survival, immune, and mutation analyses manifested that the collected nitrogen metabolism-related genes had good classification performance, presenting notable differences in survival rates, immune levels, gene mutations, and sensitivity to drugs between cluster1 and cluster2. In conclusion, the project investigated the prognosis and classification value of nitrogen metabolism-related genes in GBM from multiple perspectives, predicting the sensitivity of different subtypes of patients to immunotherapy response and drug sensitivity. These findings are expected to show new research directions for further exploration in these fields. |
| format | Article |
| id | doaj-art-b1d2dec874e84f67b9b51d4a4af37a23 |
| institution | OA Journals |
| issn | 1095-953X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Neurobiology of Disease |
| spelling | doaj-art-b1d2dec874e84f67b9b51d4a4af37a232025-08-20T02:15:23ZengElsevierNeurobiology of Disease1095-953X2025-07-0121110693510.1016/j.nbd.2025.106935An analysis of prognostic risk and immunotherapy response of glioblastoma patients based on single-cell landscape and nitrogen metabolismMinfeng Tong0Zhijian Xu1Lude Wang2Huahui Chen3Xing Wan4Hu Xu5Song Yang6Qi Tu7Department of Neurosurgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua 321000, ChinaDepartment of Neurosurgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua 321000, ChinaCentral Laboratory, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua 321000, ChinaDepartment of Neurosurgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua 321000, ChinaDepartment of Neurosurgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua 321000, ChinaDepartment of Neurosurgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua 321000, ChinaDepartment of Neurosurgery, Jiaozhou Branch, East Hospital Affiliated to Tongji University, Jiaozhou 266300, China; Correspondence to: Song Yang, Department of Neurosurgery, Jiaozhou Branch, East Hospital Affiliated to Tongji University, No.89, Zhanqian Avenue, Jiaozhou, Qingdao 266300, China.Department of Neurosurgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua 321000, China; Correspondence to: Qi Tu, Department of Neurosurgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, No. 365, Renmin East Road, Jinhua, Zhejiang 321000, China.Glioblastoma (GBM) is a highly invasive brain tumor of astrocytic origin. Nitrogen metabolism plays an instrumental role in the growth and progression of various tumors, including GBM. This study intended to mine nitrogen metabolism-related biomarkers for GBM-related research of prognosis and immunotherapy. Through single-cell data analysis of GBM, we identified four cell types (Astrocytes, Macrophages, Fibroblasts, and Endothelial cells). We calculated the nitrogen metabolism scores and conducted trajectory analysis for the most abundant cells, Astrocytes, revealing 6 differentiation directions of Astrocytes, which included the main differentiation direction from cells with low nitrogen metabolism scores to cells with high nitrogen metabolism scores. Furthermore, based on the differentially expressed genes (DEGs) with high/low nitrogen metabolism scores, we constructed a 7-gene prognostic model by utilizing regression analysis. qRT-PCR analysis showed that IGFBP2, CHPF, CTSZ, UPP1, TCF12, ZBTB20 and RBP1 were all significantly up-regulated in the GBM cells. Through differential analysis, a protein-protein interaction (PPI) network, and enrichment analyses, we identified and analyzed the DEGs in the high RiskScore subgroup, revealing complex interactions among DEGs, which were mainly related to pathways such as TNF signaling pathway and NF-κB signaling pathway. By leveraging univariate analysis, survival-related genes were selected from the nitrogen metabolism-related gene sets. Clustering, survival, immune, and mutation analyses manifested that the collected nitrogen metabolism-related genes had good classification performance, presenting notable differences in survival rates, immune levels, gene mutations, and sensitivity to drugs between cluster1 and cluster2. In conclusion, the project investigated the prognosis and classification value of nitrogen metabolism-related genes in GBM from multiple perspectives, predicting the sensitivity of different subtypes of patients to immunotherapy response and drug sensitivity. These findings are expected to show new research directions for further exploration in these fields.http://www.sciencedirect.com/science/article/pii/S0969996125001512GlioblastomaNitrogen metabolismSingle cellPrognostic modelSubtypeImmune infiltration |
| spellingShingle | Minfeng Tong Zhijian Xu Lude Wang Huahui Chen Xing Wan Hu Xu Song Yang Qi Tu An analysis of prognostic risk and immunotherapy response of glioblastoma patients based on single-cell landscape and nitrogen metabolism Neurobiology of Disease Glioblastoma Nitrogen metabolism Single cell Prognostic model Subtype Immune infiltration |
| title | An analysis of prognostic risk and immunotherapy response of glioblastoma patients based on single-cell landscape and nitrogen metabolism |
| title_full | An analysis of prognostic risk and immunotherapy response of glioblastoma patients based on single-cell landscape and nitrogen metabolism |
| title_fullStr | An analysis of prognostic risk and immunotherapy response of glioblastoma patients based on single-cell landscape and nitrogen metabolism |
| title_full_unstemmed | An analysis of prognostic risk and immunotherapy response of glioblastoma patients based on single-cell landscape and nitrogen metabolism |
| title_short | An analysis of prognostic risk and immunotherapy response of glioblastoma patients based on single-cell landscape and nitrogen metabolism |
| title_sort | analysis of prognostic risk and immunotherapy response of glioblastoma patients based on single cell landscape and nitrogen metabolism |
| topic | Glioblastoma Nitrogen metabolism Single cell Prognostic model Subtype Immune infiltration |
| url | http://www.sciencedirect.com/science/article/pii/S0969996125001512 |
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