ArticleDisease markers2022
A Novel Inflammation-Related Gene Signature for Overall Survival Prediction and Comprehensive Analysis in Pediatric Patients with Wilms Tumor.
Article in Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Exploring the causal relationship between hemoglobin and pancreatic cancer and its potential mechanisms through bioinformatics and Mendelian randomization.Discover oncology · 2025Article
- The pan-immune-inflammation value predicts prognosis and chemotherapy-related adverse events in Wilms' tumor patients.BMC cancer · 2025Article
- Wilms' Tumor: A Review of Clinical Characteristics, Treatment Advances, and Research Opportunities.Medicina (Kaunas, Lithuania) · 2025Review
- Lymph node metastasis related gene BICC1 promotes tumor progression by promoting EMT and immune infiltration in pancreatic cancer.BMC medical genomics · 2023Article
- A novel molecular subtypes and risk model based on inflammatory response-related lncrnas for bladder cancer.Hereditas · 2022Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wilms tumor (WT) is a common pediatric renal cancer, with a poor prognosis and high-risk recurrence in some patients. The inflammatory microenvironment is gradually gaining attention in WT. In this study, novel inflammation-related signatures and prognostic model were explored and integrated using bioinformatics analysis. The mRNA profile of pediatric patients with WT and inflammation-related genes (IRGs) were acquired from Therapeutically Available Research to Generate Effective Treatments (TARGET) and Gene Set Enrichment Analysis (GSEA) databases, respectively. Then, a novel prognostic model founded on 7-IRGs signature (BICC1, CSPP1, KRT8, MYCN, NELFA, NXN, and RNF113A) was established by the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression to stratify pediatric patients with WT into high- and low-risk groups successfully. And a stable performance of the prognostic risk model was verified in predicting overall survival (OS) by receiver-operating characteristic (ROC) curves, Kaplan-Meier (KM) curves, and independent prognostic analysis (
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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 Socratic graph.