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Novel immune checkpoint-related gene model to predict prognosis and treatment responsiveness in low-grade gliomas

Recently, studies have shown that immune checkpoint-related genes (ICGs) are instrumental in maintaining immune homeostasis and can be regarded as potential therapeutic targets. However, the prognostic applications of ICGs require further elucidation in low-grade glioma (LGG) cases. In the present s...

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Detalles Bibliográficos
Autores principales: Guo, Yangyang, Bao, Jingxia, Lin, Danfeng, Hong, Kai, Cen, Kenan, Sun, Jie, Wang, Zhepei, Wu, Zhixuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10559968/
https://www.ncbi.nlm.nih.gov/pubmed/37809899
http://dx.doi.org/10.1016/j.heliyon.2023.e20178
Descripción
Sumario:Recently, studies have shown that immune checkpoint-related genes (ICGs) are instrumental in maintaining immune homeostasis and can be regarded as potential therapeutic targets. However, the prognostic applications of ICGs require further elucidation in low-grade glioma (LGG) cases. In the present study, a unique prognostic gene signature in LGG has been identified and validated as well based on ICGs as a means of facilitating clinical decision-making. The RNA-seq data as well as corresponding clinical data of LGG samples have been retrieved utilizing the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. ICG-defined non-negative matrix factorization (NMF) clustering was performed to categorize patients with LGG into two molecular subtypes with different prognoses, clinical traits, and immune microenvironments. In the TCGA database, a signature integrating 8 genes has been developed utilizing the LASSO Cox method and validated in the GEO database. The signature developed is superior to other well-recognized signatures in terms of predicting the survival probability of patients with LGG. This 8-gene signature was then subsequently applied to categorize patients into high- and low-risk groups, and differences between them in terms of gene alteration frequency were observed. There were remarkable variations in IDH1 (91% and 64%) across low-as well as high-risk groups. Additionally, various analyses like function enrichment, tumor immune microenvironment, and chemotherapy drug sensitivity revealed significant variations across high- and low-risk populations. Overall, this 8-gene signature may function as a useful tool for prognosis and immunotherapy outcome predictions among LGG patients.