Evidence map›Paper›PMID 41423669›Full record

ArticleCancer cell international2025

Development and validation of a novel glioblastoma prognostic model: identifying STOX1 and ZNF248 as ferroptosis-related biomarkers.

Shaowen Wang, Songyu Xing, Kunyu Li, Siyu Liu, Yulu Yang, Xinzhou Zhu, Wai Sang Poon

Abstract read
In one paragraph

Article in Cancer cell international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shaowen Wang *Neuromedicine Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, 518053, China.
Songyu Xing *The Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Kunyu Li *The Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Siyu Liu *The Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Yulu YangThe Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Xinzhou ZhuThe Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China. xz.zhu@siat.ac.cn.
Wai Sang PoonNeuromedicine Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, 518053, China. waipoon@hku-szh.org.

Funding

Shenzhen Key Laboratory of Neuroimmunomodulation for Neurological Diseases ZDSYS20220304163558001Shenzhen Science and Technology Program JCYJ20220818100803007
6 · The paper itself

Abstract

backgroundDespite recent advances in glioblastoma (GBM) therapies, patient survival remains dismal. Existing prognostic markers lack sufficient accuracy, and the resistance of GBM to chemotherapy underscores the need for both improved predictive models and new therapeutic targets.

methodsWe analyzed transcriptomic data from GBM and non-tumor brain tissues in the TCGA and GTEx databases to identify differentially expressed genes (DEGs). A prognostic signature was then constructed via univariate Cox regression, LASSO selection, and multivariate Cox analysis. The resulting prognostic model was validated in an independent GEO GBM cohort using Kaplan-Meier and log-rank testing. We further compared mutation patterns and immune infiltration between high- and low-risk groups. Multi-omics integration highlighted candidate tumor suppressors, which were functionally assessed in GBM cell lines and an orthotopic mouse model for the effects on ferroptosis sensitivity.

resultsA 14-gene prognostic signature was developed and robustly stratified GBM patients into high- and low-risk groups with significantly different overall survival. High-risk tumors showed elevated PTEN mutation frequency, enhanced immunosuppressive microenvironments with increased PD-L1 and regulatory T cells, and distinct co-mutation patterns. STOX1 and ZNF248 were remarkably downregulated in GBM tissues. Their overexpression in vitro suppressed GBM cell proliferation and sensitized cells to ferroptosis. In vivo, nude mice bearing STOX1-overexpressing GBM cells showed prolonged survival under ferroptosis-inducing conditions.

conclusionWe present a validated 14-gene prognostic model that accurately predicts GBM patient outcomes and reveals STOX1 and ZNF248 as novel tumor suppressors related to ferroptosis. Targeting STOX1 and ZNF248 may overcome the resistance of GBM to ferroptosis and improve therapeutic efficacy.

Indexed as

Ferroptosis resistanceGene signatureGlioblastomaPrognostic modelSTOX1Tumor suppressorZNF248

Identifiers

PMID41423669
PMCPMC12838421

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.