ArticleFrontiers in pediatrics2026
Identification and validation of feature genes using a ferroptosis-informed analytical framework in medulloblastoma.
Article in Frontiers in pediatrics, 2026. 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: This study aimed to identify potential biomarker signatures for medulloblastoma using a ferroptosis-informed analytical framework. Methods: Transcriptomic data from GEO datasets were used to identify differentially expressed ferroptosis-associated genes (DEFeGs) in medulloblastoma by intersecting differentially expressed genes with the FerrDb V2 database. A ferroptosis-related gene (FeRG) score was calculated using ssGSEA. Hub genes correlated with the FeRG score were identified using WGCNA. Candidate feature genes were selected using machine learning algorithms. A nomogram was constructed to predict the probability of medulloblastoma diagnosis. Immune infiltration analysis, drug sensitivity prediction, and qRT-PCR validation of feature gene expression in human samples were performed. Results: A total of 36 DEFeGs associated with medulloblastoma were identified. WGCNA identified 114 hub genes, of which 58 were differentially expressed. Machine learning algorithms identified Conclusion: This study identified
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.