ArticleOncoTargets and therapy2024
Identification of Cuproptosis-Related Genes for Molecular Subtyping: Predicting Prognostic and Therapeutic Response in Glioma.
Article in OncoTargets and therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Cuproptosis, a metal-ion-dependent form of regulated cell death induced by copper overload, is emerging as a potential mechanism in high-grade glioma (HGG). Despite its significance, the role of cuproptosis in predicting the prognostic and therapeutic response in HGG remains poorly understood. Methods: We performed unsupervised clustering to stratify patients with HGG in the Chinese Glioma Genome Atlas (CGGA) according to the expression of 14 cuproptosis-related genes (CRGs) and validated in The Cancer Genome Atlas (TCGA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied to explore the biological processes and pathways involved within distinct groups. We constructed the CupScore model to predict the responsiveness to immune checkpoint inhibitors (ICIs) therapy and chemotherapy in patients with HGG. Additionally, in vivo and in vitro experiments were performed to investigate the potential biological function of CDKN2A in HGG. Results: We identified two cuproptosis-related molecular subgroups with significantly different survival probabilities. Patients with HGG in cluster 1 were characterized as immune-desert phenotype with higher CupScore and lower expression of MHC complex, interferons, chemokines, interleukins, and immune checkpoints. In contrast, cluster 2 showed an immune-inflamed signature. We screened PI-103 as the most promising candidate for patients with higher CupScore and confirmed its experimental evidence and clinical trial status. Patients with lower CupScore showed higher response rates to anti-PD-L1 and anti-PD1 combined with anti-CTLA4 ICI therapy. Furthermore, in vivo and in vitro experiments revealed that CDKN2A enhanced the malignant phenotype of HGG. Conclusion: Cuproptosis has the ability to reprogram the tumor microenvironment (TME) in HGG, leading to the stratification of patients into two distinct molecular subgroups. The CupScore model emerged as a robust metric for predicting the prognostic and therapeutic benefits, as well as may therefore facilitate personalized treatment strategies for patients with HGG.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.