Bioinformatic profiling of prognostic microenvironment-related genes in Wilms tumors

Wilms tumor (WT), is one of the most common types of extracranial solid tumors found in early childhood, and it needs positive attention worldwide. The tumor microenvironment (TME) serves as a key role in the aggressiveness of tumors and has been investigated in many kinds of tumors, primarily in adult-onset cancers. However, the TME is not well studied in childhood tumors, especially in Wilms tumors. In the present study, we performed a systematic investigation of the genetic factors associated with the Wilms tumor microenvironment with the help of bioinformatics and TARGET database (Therapeutically Applicable Research to Generate Effective Treatments, https:// ocg.cancer.gov/programs/target). The stromal and immune scores of patients were calculated with an "ESTIMATE" algorithm and the TME-related differentially expressed genes (TME-related DEGs) were detected with the R package "limma". Then their functional analysis was further revealed by "ClusterProfiler". The direct/indirect correlations between TME-related DEGs were assessed with STRING and the protein-protein interaction (PPI) network was then reconstructed by Cytoscape. The DEGs in the top two clusters selected by Molecular Complex Detection (MCODE) were taken as hub genes. Survival analysis of all the DEGs was studied and the prognostic immune-related biomarkers for Wilms tumors were detected. In this study, stromal scores were found to be closely associated with the overall survival of Wilms tumor patients. TME-related DEGs and hub genes were suggested to participate in the migration and function of immune cells. What's more, 11 of them including GSDMA, TRIM55, SPARCL1, EPYC, LRRC2, LAPTM5, PTGFR, APOD, IGF1, CEBPD and SFRP2, were significantly associated with overall survival of patients. In brief, our study arrived at a more comprehensive understanding of the tumor microenvironment and provided more data for decoding the complicated microenvironment in Wilms tumors by identified several prognostic biomarkers.