ArticleTranslational pediatrics2024
Synergistic machine learning models utilizing ferroptosis-related genes for improved neuroblastoma outcome prediction.
Article in Translational pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A multidimensional risk prediction framework for malignant intestinal obstruction based on machine learning: computational model development and clinical validation.Scientific reports · 2026Article
- Ferroptosis in Glioblastoma and Neuroblastoma: Molecular Mechanisms and Novel Therapeutic Strategies.Current issues in molecular biology · 2026Review
- Review
- Identification and tissue-level validation of ferroptosis-related genes in small intestinal neuroendocrine neoplasms based on machine learning.BMC gastroenterology · 2025Article
- Development of a prognostic model for overall survival in neuroblastoma based on Schwann cell-specific genes, clinical predictors, and MYCN amplification.Translational cancer research · 2025Article
- Molecular regulation and therapeutic targeting ofFrontiers in cell and developmental biology · 2025Review
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Authors and funding
6 authors.
Funding
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Abstract
Background: Neuroblastoma (NB) is a highly heterogeneous and common pediatric malignancy with a poor prognosis. Ferroptosis, an iron-dependent cell death pathway, may play a crucial role in NB tumor progression and immune response. This study aimed to investigate ferroptosis in NB to identify potential therapeutic targets and develop predictive models for prognosis and recurrence. Methods: Six datasets were accessed from the ArrayExpress database and Gene Expression Omnibus. Ferroptosis-related genes (FRGs) were selected from the FerrDb website. Unsupervised clustering, differential expression analysis, weighted correlation network analysis (WGCNA), and gene set enrichment analysis (GSEA) were adopted to investigate potential pathways associated with ferroptosis in NB and identify the key genes involved. We used the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression to develop the ferroptosis-related prognostic signatures (FRPS) while using machine learning (ML) algorithms to construct the recurrence model. Results: Ribosome and cell cycle may be the potential pathways for ferroptosis involved in NB, with Conclusions: We investigated the potential ferroptosis-related pathways and hub- FRGs in NB and developed prognosis and recurrence models, providing new potential targets for prognostic evaluation and treatment in NB patients.
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