Development and validation of cuproptosis molecular subtype-related signature for predicting immune prognostic characterization in gliomas.
J Cancer Res Clin Oncol
; 149(13): 11499-11515, 2023 Oct.
Article
em En
| MEDLINE
| ID: mdl-37392200
ABSTRACT
PURPOSE:
Cuproptosis, a novel programmed cell death, plays an important role in glioma growth, angiogenesis, and immune response. Nonetheless, the role of cuproptosis-related genes (CRGs) in the prognosis and tumor microenvironment (TME) of gliomas remains unknown.METHODS:
By non-negative matrix factorization consensus clustering, 1286 glioma patients were classified based on the mRNA expression levels of 27 CRGs and investigated the association of immune infiltration and clinical characteristics with cuproptosis subtypes. A CRG-score system was constructed using LASSO and multivariate Cox regression methods and validated in independent cohorts to predict the prognosis of glioma patients.RESULTS:
Glioma patients were divided into two cuproptosis subtypes. Cluster C2 was enriched in immune-related pathways, had higher macrophage M2, neutrophils, and CD8 + T cells, and poorer prognosis compared with cluster C1 which was enriched in metabolism-related pathways. We further constructed and validated the ten-gene CRG risk scores. Glioma patients in the high CRG-score group had higher tumor mutation burden, higher TME scores, and poorer prognoses compared with the low CRG-score group. Additionally, the AUC value of the CRG-score was 0.778 in predicting the prognosis of gliomas. WHO grading, IDH mutation, 1p/19q codeletion, and MGMT methylation were significant differences between high and low CRG-score groups.CONCLUSION:
This study demonstrated that CRG-score was related to immune cell infiltration and could accurately predict gliomas' prognosis. Our findings may provide a novel understanding of the potential role of cuproptosis molecular pattern and TME in the immune response and prognosis of glioma patients.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Glioma
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
J Cancer Res Clin Oncol
Ano de publicação:
2023
Tipo de documento:
Article