ArticleDiscover oncology2024
Identification and validation of a novel five-gene signature in high-risk MYCN-not-amplified neuroblastoma.
Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
objectiveHigh-risk neuroblastoma patients often have poor outcomes despite multi-treatment options. The risk stratification of high-risk MYCN-not-amplified (HR-MYCN-NA) patients remains difficult. This study aims to identify a gene set signature that can help further stratify HR-MYCN-NA patients for a potential personalized therapeutic strategy.
methodsThree microarrays and one single-cell RNA sequence dataset were acquired and analyzed. Firstly, the prognostic-related genes (PRGs) in HR-MYCN-NA tumor cells were identified using TARGET-NB and GSE137804 datasets. Then, the prognostic model was established by LASSO-Cox regression, and verified in external cohort (GSE49710, GSE45547). Moreover, a time-dependent receiver operating characteristic curve (ROC) and area under the ROC (AUC) was used to assess survival prediction. A nomogram was established to predict the 1-, 3- and 5-year overall survival (OS) of HR-MYCN-NA patients.
resultsIn the training set, a five-PRGs signature, which include GAL, GFRA3, MARCKS, PSMD13, and ZNHIT3 genes, was identified and successfully stratified HR-MYCN-NA patients into ultra-high risk (UHR) and high-risk (HR) subtypes (HR = 4.29, P < 0.001). ROC curve analysis confirmed its predictive power (AUC = 0.74-0.82), suggesting a good predictive efficacy. Consistently, high-risk scores also predicted worse OS (HR = 2, P = 0.033) in the external validation dataset (AUC = 0.67-0.71). Moreover, the overall C-index of the nomogram was 0.75 (P < 0.001), which indicated good agreement between the observed and predicted survival rates. Further integrating the five PRGs signature with clinical factors, these 5 gene signature (HR = 4.45, P < 0.001) and tumor grade (HR = 4.15, P = 0.02) were found to be independent prognostic factors for HR-MYCN-NA patients.
conclusionThe novel five PRGs signature could well predict the survival of HR-MYCN-NA patients, which may provide constructive information for these subsets.
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.