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Gao W, Li Y, Zhang T, Lu J, Pan J, Qi Q, Dong S, Chen X, Su Z, Li J. Systematic Analysis of Chemokines Reveals CCL18 is a Prognostic Biomarker in Glioblastoma. J Inflamm Res 2022; 15:2731-2743. [PMID: 35509325 PMCID: PMC9059990 DOI: 10.2147/jir.s357787] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 04/12/2022] [Indexed: 12/30/2022] Open
Abstract
Background Glioblastoma (GBM) is the most common and aggressive brain tumor in adults, in which chemokines are often upregulated and may play pivotal roles in their development and progression. Chemokines are a large subfamily of cytokines with leukocyte chemotactic activities involved in various tumor progression. However, gene expression patterns of the chemokines on a global scale were not known in GBM. Methods Differentially expressed chemokine genes in glioma and normal samples were screened by using The Cancer Genome Atlas (TCGA) database. Cox regression identified the prognosis-related genes in each glioma subtype. The protein expression levels of chemokines in 72 glioma tissues were detected by ELISA. Results We found that the transcripts of seven chemokines, including CCL2, CCL8, CCL18, CCL28, CXCL1, CXCL5, and CXCL13, were highly expressed in GBM that evidenced by involving immune cell infiltration regulation and accompanied with worse outcomes of GBM patients. The prognostic nomogram construction demonstrated that CCL18 held the highest risk score in patients with GBM. Furthermore, experiments on 72 glioma tissue samples confirmed that CCL18 protein expression was positively associated with tumor grade and IDH1 status but inversely with glioma patients’ overall survival (OS). Conclusion Our study reveals comprehensive and comparable roles of chemokine members in glioblastoma, and identified CCL18 as a critical driver of GBM malignant behaviors, therefore providing a potential target for developing prognosis and therapy in human glioblastoma.
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Affiliation(s)
- Wenqing Gao
- State Key Laboratory of Genetic Engineering, Department of Neurology, Huashan Hospital and Institute of Neurology, School of Life Sciences, Shanghai Engineering Research Center of Industrial Microorganisms, Fudan University, Shanghai, 200438, People's Republic of China
| | - Yuanyuan Li
- State Key Laboratory of Genetic Engineering, Department of Neurology, Huashan Hospital and Institute of Neurology, School of Life Sciences, Shanghai Engineering Research Center of Industrial Microorganisms, Fudan University, Shanghai, 200438, People's Republic of China
| | - Teng Zhang
- State Key Laboratory of Genetic Engineering, Department of Neurology, Huashan Hospital and Institute of Neurology, School of Life Sciences, Shanghai Engineering Research Center of Industrial Microorganisms, Fudan University, Shanghai, 200438, People's Republic of China
| | - Jianglong Lu
- Department of Neurosurgery, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China
| | - Jiasong Pan
- State Key Laboratory of Genetic Engineering, Department of Neurology, Huashan Hospital and Institute of Neurology, School of Life Sciences, Shanghai Engineering Research Center of Industrial Microorganisms, Fudan University, Shanghai, 200438, People's Republic of China
| | - Qi Qi
- State Key Laboratory of Genetic Engineering, Department of Neurology, Huashan Hospital and Institute of Neurology, School of Life Sciences, Shanghai Engineering Research Center of Industrial Microorganisms, Fudan University, Shanghai, 200438, People's Republic of China
| | - Siqi Dong
- Department of Neurology, Huashan Hospital and Institute of Neurology, Fudan University, Shanghai, 200040, People's Republic of China
| | - Xiangjun Chen
- Department of Neurology, Huashan Hospital and Institute of Neurology, Fudan University, Shanghai, 200040, People's Republic of China.,National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, 200040, People's Republic of China
| | - Zhipeng Su
- Department of Neurosurgery, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China
| | - Jixi Li
- State Key Laboratory of Genetic Engineering, Department of Neurology, Huashan Hospital and Institute of Neurology, School of Life Sciences, Shanghai Engineering Research Center of Industrial Microorganisms, Fudan University, Shanghai, 200438, People's Republic of China.,National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, 200040, People's Republic of China
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Cai X, Yuan F, Zhu J, Yang J, Tang C, Cong Z, Ma C. Glioma-Associated Stromal Cells Stimulate Glioma Malignancy by Regulating the Tumor Immune Microenvironment. Front Oncol 2021; 11:672928. [PMID: 33996602 PMCID: PMC8117153 DOI: 10.3389/fonc.2021.672928] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 04/12/2021] [Indexed: 12/21/2022] Open
Abstract
Background The glioma-associated stromal cell (GASC) is a recently identified type of cell in the glioma microenvironment and may be a prognostic marker for glioma. However, the potential mechanisms of GASCs in the glioma microenvironment remain largely unknown. In this work, we aimed to explore the mechanisms of GASCs in gliomas, particularly in high-grade gliomas (HGG). Methods We used glioma datasets from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). We utilized the Single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm to discriminate between patients with high or low GASC composition. The xCELL and CIBERSORT algorithms were used to analyze the composition of stromal cells and immune cells. Risk score and a nomogram model were constructed for prognostic prediction of glioma. Results We observed for the first time that the levels of M2 macrophages and immune checkpoints (PD-1, PD-L1, PD-L2, TIM3, Galectin-9, CTLA-4, CD80, CD86, CD155, and CIITA) were significantly higher in the high GASC group and showed positive correlation with the GASC score in all glioma population and the HGG population. Copy number variations of DR3 and CIITA were higher in the high-GASC group. THY1, one of the GASC markers, exhibited lower methylation in the high GASC group. The constructed risk score was an independent predictor of glioma prognostics. Finally, a credible nomogram based on the risk score was established. Conclusions GASCs stimulate glioma malignancy through the M2 macrophage, and are associated with the level of immune checkpoints in the glioma microenvironment. The methylation of THY1 could be used as prognostic indicator and treatment target for glioma. However, further studies are required to verify these findings.
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Affiliation(s)
- Xiangming Cai
- School of Medicine, Southeast University, Nanjing, China
| | - Feng Yuan
- School of Medicine, Nanjing University, Nanjing, China.,Department of Neurosurgery, Jinling Hospital, Nanjing, China
| | - Junhao Zhu
- School of Medicine, Nanjing Medical University, Nanjing, China
| | - Jin Yang
- Department of Neurosurgery, Jinling Hospital, Nanjing, China
| | - Chao Tang
- Department of Neurosurgery, Jinling Hospital, Nanjing, China
| | - Zixiang Cong
- School of Medicine, Nanjing University, Nanjing, China.,Department of Neurosurgery, Jinling Hospital, Nanjing, China
| | - Chiyuan Ma
- School of Medicine, Southeast University, Nanjing, China.,School of Medicine, Nanjing University, Nanjing, China.,Department of Neurosurgery, Jinling Hospital, Nanjing, China.,School of Medicine, Nanjing Medical University, Nanjing, China
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Luo H, Tao C, Wang P, Li J, Huang K, Zhu X. Development of a prognostic index based on immunogenomic landscape analysis in glioma. IMMUNITY INFLAMMATION AND DISEASE 2021; 9:467-479. [PMID: 33503296 PMCID: PMC8127549 DOI: 10.1002/iid3.407] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 01/05/2021] [Accepted: 01/09/2021] [Indexed: 12/21/2022]
Abstract
Background Glioma is the most common intracranial tumor. The inflammatory response actively participates in the malignancy of gliomas. There is still limited knowledge about the biological function of immune‐related genes (IRGs) and their potential involvement in the malignancy of gliomas. Methods We screened differentially expressed and survival‐associated IRGs, and explored their potential molecular characteristics. Then we developed a prognostic index derived from seven hub IRGs. A prognostic nomogram was built to indicate the prognostic value of the prognostic index and seven IRGs. We characterized the immune infiltration landscape to analyze tumor‐immune interactions. The real‐time quantitative polymerase chain reaction assay was performed to validate bioinformatics results. Results The differentially expressed IRGs are involved in cell chemotaxis, cytokine activity, and the chemokine‐mediated signaling pathway. The prognostic index derived from seven IRGs had clinical prognostic value in glioma, and positively correlated with the malignant clinicopathological characteristics. A nomogram further indicated that the prognostic index and seven hub IRGs had clinical prognostic value for gliomas. We revealed that the prognostic index could reflect the state of the glioma immune microenvironment. Conclusion This study demonstrates the importance of an IRG‐based prognostic index as a potential biomarker for predicting malignancy in gliomas.
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Affiliation(s)
- Haitao Luo
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Chuming Tao
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.,East China Institute of Digital Medical Engineering, Shangrao, Jiangxi, China
| | - Peng Wang
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Jingying Li
- Department of Comprehensive Intensive Care Unit, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China
| | - Kai Huang
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.,Institute of Neuroscience, Nanchang University, Nanchang, Jiangxi, China
| | - Xingen Zhu
- Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.,Institute of Neuroscience, Nanchang University, Nanchang, Jiangxi, China
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