Non-coding RNA model improves prognostic prediction in patients with nephroblastoma

Background. Nephroblastoma (Wilms tumor) is a common abdominal malignancy in children, ranking second among abdominal malignancies in children, but the pathogenesis is still unclear, and further research on their molecular mechanisms is needed.Method. We obtained lncRNA expression and clinical data from the TARGET database of the GDC data portal of the American Cancer Institute. Effective patient samples were determined based on gene differential expression analysis and clinical data screening. The risk calculation model was established by univariate and multivariate Cox regression analysis, after which the samples were divided into training group and test group to predict the prognosis of patients with nephroblastoma, and then the independent validation on gender was carried out for all samples. Finally, the corresponding target genes of lncRNA were predicted for functional enrichment analysis to explore the enrichment of genes and the interaction between them.Result. 125 valid samples were identified after screening 136 samples. After experimental analysis, five significant lncRNAs (AC004233.3, AC055764.1, SCAT8, LINC02623, AL118505.1) associated with the prognosis of nephroblastoma were found and validated. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve on the test set was 0.732, which indicated that the model was accurate and the independence verification had good discrimination. In the enrichment analysis, we can intuitively see the significant situation and promotion or inhibition of genes. It can be inferred that the experimental five lncRNAs may regulate the expression of related protein-coding genes and the production process of nephroblastoma, thus affecting the relevant pathways of cancer development.Conclusions. This study systematically analyzed the lncRNA expression and clinical data of patients with nephroblastoma. The data obtained by establishing Cox proportional hazard regression model can further understand the molecular mechanism related to nephroblastoma and play an auxiliary role in the clinical diagnosis of doctors, thereby improving the diagnosis, treatment and prognosis of patients with nephroblastoma.