Novel immune checkpoint-related gene model to predict prognosis and treatment responsiveness in low-grade gliomas
© 2023 The Authors..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:9 |
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| Enthalten in: |
Heliyon - 9(2023), 9 vom: 28. Sept., Seite e20178 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Guo, Yangyang [VerfasserIn] |
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| Links: |
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| Themen: |
Gene signature |
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| Anmerkungen: |
Date Revised 31.10.2023 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1016/j.heliyon.2023.e20178 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM363030808 |
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| 245 | 1 | 0 | |a Novel immune checkpoint-related gene model to predict prognosis and treatment responsiveness in low-grade gliomas |
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| 520 | |a © 2023 The Authors. | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Gene signature | |
| 650 | 4 | |a Immune checkpoints | |
| 650 | 4 | |a Low-grade gliomas | |
| 650 | 4 | |a Survival analysis | |
| 650 | 4 | |a Therapeutic response | |
| 700 | 1 | |a Bao, Jingxia |e verfasserin |4 aut | |
| 700 | 1 | |a Lin, Danfeng |e verfasserin |4 aut | |
| 700 | 1 | |a Hong, Kai |e verfasserin |4 aut | |
| 700 | 1 | |a Cen, Kenan |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Jie |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Zhepei |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Zhixuan |e verfasserin |4 aut | |
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