A Novel Inflammation-Related Gene Signature for Overall Survival Prediction and Comprehensive Analysis in Pediatric Patients with Wilms Tumor

Author:

Zhang Jiahao1ORCID,Lai Yongchang2ORCID,Zhu Langjing3ORCID,Lu Zechao2ORCID,Hu Chuxian1ORCID,Zhou Haobin4ORCID,Lu Zeguang5ORCID,Tang Zhicheng6ORCID,He Zhaohui2ORCID,Tang Fucai2ORCID

Affiliation:

1. The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan, Guangdong 511500, China

2. Department of Urology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong 518033, China

3. Department of Nephrology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong 518033, China

4. The First Clinical College of Guangzhou Medical University, Guangzhou, Guangdong 511436, China

5. The Second Clinical College of Guangzhou Medical University, Guangzhou, Guangdong 511436, China

6. The Third Clinical College of Guangzhou Medical University, Guangzhou, Guangdong 511436, China

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 ( p < 0.05 ). In addition, a novel nomogram integrating risk scores with good robustness was developed and validated by C -index, ROC, and calibration plots. The potential function and pathway were explored via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and GSEA, with mainly inflammation and immune-related biological processes. The higher-risk scores, the lower immune infiltration, as shown in the single-sample GSEA (ssGSEA) and tumor microenvironment (TME) analysis. The drug sensitivity analysis showed that regulating 7-IRGs signature has a significant correlation with the chemotherapy drugs of WT patients. In summary, this study defined a prognostic risk model and nomogram based on 7-IRGs signature, which may provide novel insights into clinical prognosis and inflammatory study in WT patients. Besides, enhancing immune infiltration based on inflammatory response and regulating 7-IRGs signature are beneficial to ameliorating the efficacy in WT patients.

Funder

Guangzhou Medical University

Publisher

Hindawi Limited

Subject

Biochemistry (medical),Clinical Biochemistry,Genetics,Molecular Biology,General Medicine

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