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A Novel Immune-Related Prognostic Biomarker and Target Associated With Malignant Progression of Glioma.
Zhang, Yu; Yang, Xin; Zhu, Xiao-Lin; Wang, Zhuang-Zhuang; Bai, Hao; Zhang, Jun-Jie; Hao, Chun-Yan; Duan, Hu-Bin.
Afiliação
  • Zhang Y; Department of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China.
  • Yang X; Department of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China.
  • Zhu XL; Department of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China.
  • Wang ZZ; Department of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China.
  • Bai H; Department of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China.
  • Zhang JJ; Department of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China.
  • Hao CY; Department of Geriatrics, First Hospital of Shanxi Medical University, Taiyuan, China.
  • Duan HB; Department of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China.
Front Oncol ; 11: 643159, 2021.
Article em En | MEDLINE | ID: mdl-33937046
BACKGROUND: Glioma is one of the most common malignancies in the central nervous system and has limited effective therapeutic options. Therefore, we sought to identify a suitable target for immunotherapy. MATERIALS AND METHODS: We screened prognostic genes for glioma in the CGGA database and GSE43378 dataset using survival analysis, receiver operating characteristic (ROC) curves, independent prognostic analysis, and clinical correlation analysis. The results were intersected with immune genes from the ImmPort database through Venn diagrams to obtain likely target genes. The target genes were validated as prognostically relevant immune genes for glioma using survival, ROC curve, independent prognostic, and clinical correlation analyses in samples from the CGGA database and GSE43378 dataset, respectively. We also constructed a nomogram using statistically significant glioma prognostic factors in the CGGA samples and verified their sensitivity and specificity with ROC curves. The functions, pathways, and co-expression-related genes for the glioma target genes were assessed using PPI networks, enrichment analysis, and correlation analysis. The correlation between target gene expression and immune cell infiltration in glioma and the relationship with the survival of glioma patients were investigated using the TIMER database. Finally, target gene expression in normal brain, low-grade glioma, and high-grade glioma tissues was detected using immunohistochemical staining. RESULTS: We identified TNFRSF12A as the target gene. Satisfactory results from survival, ROC curve, independent prognosis, and clinical correlation analyses in the CGGA and GSE43378 samples verified that TNFRSF12A was significantly associated with the prognosis of glioma patients. A nomogram was constructed using glioma prognostic correlates, including TNFRSF12A expression, primary-recurrent-secondary (PRS) type, grade, age, chemotherapy, IDH mutation, and 1p19q co-deletion in CGGA samples with an AUC value of 0.860, which illustrated the accuracy of the prognosis prediction. The results of the TIMER analysis validated the significant correlation of TNFRSF12A with immune cell infiltration and glioma survival. The immunohistochemical staining results verified the progressive up-regulation of TNFRSF12A expression in normal brain, low-grade glioma, and high-grade glioma tissues. CONCLUSION: We concluded that TNFRSF12A was a viable prognostic biomarker and a potential immunotherapeutic target for glioma.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article