ArticleFrontiers in pediatrics2022
A novel cuproptosis-related gene signature predicting overall survival in pediatric neuroblastoma patients.
Article in Frontiers in pediatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed, 4 citations in OpenAlex.
- Fatty acid metabolism-related risk signature revealing the immune landscape of neuroblastoma and predicting overall survival in pediatric neuroblastoma patients.Discover oncology · 2025Article
- Pharmacologically Targeting Ferroptosis and Cuproptosis in Neuroblastoma.Molecular neurobiology · 2025Review
- Study of an N6-methyladenosine- and ferroptosis-related prognostic model and the mechanisms underlying the molecular network in neuroblastoma based on multiple datasets.Discover oncology · 2025Article
- Article
- Synergistic machine learning models utilizing ferroptosis-related genes for improved neuroblastoma outcome prediction.Translational pediatrics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Cuproptosis is a novel cell death pathway, and the regulatory mechanism in pediatric neuroblastoma (NB) remains to be explored. We amid to investigate cuproptosis-related genes (CRGs) and construct a novel prognostic model for NB. Methods: To evaluate the role of CRGs on the clinical outcome of pediatric NB, the dataset of pediatric patients with NB of GSE49710 dataset was used to identify CRGs in association with patient overall survival (OS), and TARGET database was used to validate the predictive value of cuproptosis-related signature (CRG-score). The correlation between the CRG-score and the tumor microenvironment (TME), clinicopathological parameters, chemotherapy, and the response to immunotherapy was explored. Results: Overall, 31 CRGs were associated with OS in the univariate Cox regression analysis. Then, a prognostic model incorporating 9 CRGs was established with the LASSO regression analysis, which could classify all NB patients into two CRG-score groups. The performance of the signature was verified in both internal and external validation cohorts. Multivariate analysis indicated that the CRG-score was an independent prognostic indicator, and stratification analysis still showed a high predictive ability for survival prediction. The CRG-score was associated with age, MYCN status, INSS stage, and COG risk. Additionally, the higher CRG-score group exhibited lower immune scores, immune cell infiltration, and decreased expression of immune checkpoints. Meanwhile, the CRG-score could predict the drug sensitivity of administering chemotherapeutic agents for NB patients. Conclusions: Our comprehensive analysis of cuproptosis-associated genes in NB provides a new approach for the prediction of clinical outcomes and more effective treatment strategies.
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.