A Cuproptosis Activation Scoring model predicts neoplasm-immunity interactions and personalized treatments in glioma.
Cell-cell communication
Cuproptosis
Drug prediction
Glioma
Immunocyte
Mesenchymal
Journal
Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250
Informations de publication
Date de publication:
09 2022
09 2022
Historique:
received:
08
05
2022
revised:
21
07
2022
accepted:
30
07
2022
pubmed:
15
8
2022
medline:
31
8
2022
entrez:
14
8
2022
Statut:
ppublish
Résumé
Gliomas are malignant tumors in the central nervous system. Cuproptosis is a newly discovered cell death mechanism targeting lipoylated tricarboxylic acid cycle proteins. Previous studies have found that cuproptosis participates in tumor progression, but its role in gliomas is still elusive. Here, we systematically explored the bulk-tumor and single-cell transcriptome data to reveal its role in gliomas. The cuproptosis activity score (CuAS) was constructed based on cuproptosis-related genes, and machine learning techniques validated the score stability. High CuAS gliomas were more likely to have a poor prognosis and an aggressive mesenchymal (MES) subtype. Subsequently, the SCENIC algorithm predicted 20 CuAS-related transcription factors (TFs) in gliomas. Function enrichment and microenvironment analyses found that CuAS was associated with tumor immune infiltration. Accordingly, intercellular communications between neoplasm and immunity were explored by the R package "Cellchat". Five signaling pathways and 8 ligand-receptor pairs including ICAM1, ITGAX, ITGB2, ANXA1-FRR1, and the like, were identified to suggest how cuproptosis activity connected neoplastic and immune cells. Critically, 13 potential drugs targeting high CuAs gliomas were predicted according to the CTRP and PRISM databases, including oligomycin A, dihydroartemisinin, and others. Taken together, cuproptosis is involved in glioma aggressiveness, neoplasm-immune interactions, and may be used to assist in drug selection.
Identifiants
pubmed: 35964468
pii: S0010-4825(22)00665-5
doi: 10.1016/j.compbiomed.2022.105924
pii:
doi:
Substances chimiques
Copper
789U1901C5
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
105924Informations de copyright
Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.