ArticleFrontiers in oncology2022
Identification of a 12-Gene Signature and Hub Genes Involved in Kidney Wilms Tumor
Article in Frontiers in oncology, 2022. 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, 9 citations in OpenAlex.
- Article
- Federated transfer learning with differential privacy for multi-omics survival analysis.Briefings in bioinformatics · 2025Article
- Screening of potential hub genes involved in Kidney Wilms tumor via bioinformatics analysis and experimental validation.BMC cancer · 2024Article
- [Identification of key genes in Wilms tumor based on high-throughput RNA sequencing and their impacts on prognosis and immune responses].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024Article
- Identification of m6A-associated genes as prognostic and immune-associated biomarkers in Wilms tumor.Discover oncology · 2023Article
- KIAA1363-A Multifunctional Enzyme in Xenobiotic Detoxification and Lipid Ester Hydrolysis.Metabolites · 2022Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wilms tumor (WT), also known as nephroblastoma, is a rare primary malignancy in all kinds of tumor. With the development of second-generation sequencing, the discovery of new tumor markers and potential therapeutic targets has become easier. This study aimed to explore new WT prognostic biomarkers. In this study, WT-miRNA datasets GSE57370 and GSE73209 were selected for expression profiling to identify differentially expressed genes. The key gene miRNA, namely hsa-miR-30c-5p, was identified by overlapping, and the target gene of candidate hsa-miR-30c-5p was predicted using an online database. Furthermore, 384 genes were obtained by intersecting them with differentially expressed genes in the TARGET-WT database, and the genes were analyzed for pathway and functional enrichment. Kaplan-Meier survival analysis of the 384 genes yielded a total of 25 key genes associated with WT prognosis. Subsequently, a prediction model with 12 gene signatures (BCL6, CCNA1, CTHRC1, DGKD, EPB41L4B, ERRFI1, LRRC40, NCEH1, NEBL, PDSS1, ROR1, and RTKN2) was developed. The model had good predictive power for the WT prognosis at 1, 3, and 5 years (AUC: 0.684, 0.762, and 0.774). Finally, ERRFI1 (hazard ratios [HR] = 1.858, 95% confidence intervals [CI]: 1.298-2.660) and ROR1 (HR = 0.780, 95% CI: 0.609-0.998) were obtained as independent predictors of prognosis in WT patients by single, multifactorial Cox analysis.
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