ArticleBiochemistry research international2021
Identification of Prognostic Genes in Neuroblastoma in Children by Weighted Gene Coexpression Network Analysis.
Article in Biochemistry research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Prognostic implications of store-operated calcium entry signatures and immune dynamics in neuroblastoma via machine learning.Translational cancer research · 2025Article
- Identification of IFI27 involvement in the progression of neuroblastoma through bioinformatics analysis and experimental assays.Journal of molecular histology · 2025Article
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Authors and funding
4 authors.
Funding
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Abstract
backgroundNeuroblastoma is a malignant neuroendocrine tumor from the sympathetic nervous system, the most common extracranial tumor in children. Identifying potential prognostic markers of neuroblastoma can provide clues for early diagnosis, recurrence, and treatment.
methodsRNA sequence data and clinical features of 147 neuroblastomas were obtained from the TARGET (Therapeutically Applicable Research to Generate Effective Treatments project) database. Application weighted gene coexpression network analysis (WGCNA) was used to construct a free-scale gene coexpression network, to study the interrelationship between its potential modules and clinical features, and to identify hub genes in the module. We performed Lasso regression and Cox regression analyses to identify the three most important genes and develop a new prognostic model. Data from the GSE85047 cohort verified the predictive accuracy of the prognostic model.
results14 coexpression modules were constructed using WGCNA. Brown coexpression modules were found to be significantly associated with disease survival status. Multivariate Cox analysis was performed on genes from univariate Cox regression and Lasso regression analyses using the Cox proportional hazards regression model. Finally, we constructed a three-gene prognostic model: risk score = (0.003812659
conclusionOur study constructed a neuroblastoma coexpressing gene module and identified a prognostic potential risk model for prognosis in neuroblastoma.
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Registered trials
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