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Development of a novel glycolysis-related genes signature for isocitrate dehydrogenase 1-associated glioblastoma multiforme.
Cai, Xiaomin; Chen, Zheng; Huang, Caiquan; Shen, Jie; Zeng, Wenxian; Feng, Shuang; Liu, Yu; Li, Shiting; Chen, Ming.
Afiliação
  • Cai X; Department of Neurosurgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
  • Chen Z; Department of Neurosurgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
  • Huang C; Department of Neurosurgery, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
  • Shen J; Department of Neurosurgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
  • Zeng W; Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
  • Feng S; Department of Encephalopathy, The Third Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
  • Liu Y; Department of Neurosurgery, Shanghai Children's Hospital, Shanghai Jiaotong University, Shanghai, China.
  • Li S; Department of Neurosurgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, the Cranial Nerve Disease Center of Shanghai Jiaotong University, Shanghai, China.
  • Chen M; Department of Neurosurgery, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Front Immunol ; 13: 950917, 2022.
Article em En | MEDLINE | ID: mdl-36389748
ABSTRACT

Background:

The significant difference in prognosis between IDH1 wild-type and IDH1 mutant glioblastoma multiforme (GBM) may be attributed to their metabolic discrepancies. Hence, we try to construct a prognostic signature based on glycolysis-related genes (GRGs) for IDH1-associated GBM and further investigate its relationships with immunity.

Methods:

Differentially expressed GRGs between IDH1 wild-type and IDH1 mutant GBM were screened based on the TCGA database and the Molecular Signature Database (MSigDB). Consensus Cluster Plus analysis and KEGG pathway analyses were used to establish a new GRGs set. WGCNA, univariate Cox, and LASSO regression analyses were then performed to construct the prognostic signature. Then, we evaluated association of the prognostic signature with patients' survival, clinical characteristics, tumor immunogenicity, immune infiltration, and validated one hub gene.

Results:

956 differentially expressed genes (DEGs) between IDH1 wild-type and mutant GBM were screened out and six key prognostically related GRGs were rigorously selected to construct a prognostic signature. Further evaluation and validation showed that the signature independently predicted GBM patients' prognosis with moderate accuracy. In addition, the prognostic signature was also significantly correlated with clinical traits (sex and MGMT promoter status), tumor immunogenicity (mRNAsi, EREG-mRNAsi and HRD-TAI), and immune infiltration (stemness index, immune cells infiltration, immune score, and gene mutation). Among six key prognostically related GRGs, CLEC5A was selected and validated to potentially play oncogenic roles in GBM.

Conclusion:

Construction of GRGs prognostic signature and identification of close correlation between the signature and immune landscape would suggest its potential applicability in immunotherapy of GBM in the future.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Glioblastoma Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Front Immunol Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Glioblastoma Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Front Immunol Ano de publicação: 2022 Tipo de documento: Article