Wilms瘤（WT）是全球儿童常见的肾恶性肿瘤。总体而言，Wilms瘤的预后非常良好。然而，具有畸形肿瘤组织学或疾病复发的患者的预后仍然较差，并且与其他患者相比，他们的复发率、转移率和死亡率明显增加。目前，组织病理学检查和分子生物学的结合对于预测预后和指导治疗至关重要。然而，分子机制尚未得到深入研究。遗传分析可能在某种程度上有所帮助。因此，我们试图通过整合生物信息学分析来鉴定WT的新的有前途的生物标志物，并确定与WT发病机制相关的基因。在本研究中，我们使用NCBI基因表达异质性数据库下载了与WT患者相关的两个基因表达谱数据集，目的是检测重叠差异表达基因（DEGs）。然后，将DEGs上传到DAVID数据库进行富集分析。此外，通过模拟DEGs的蛋白质-蛋白质相互作用（PPI）网络来评估蛋白质之间的功能相互作用。使用在线工具R2：基因组分析和可视化平台分析了选择的枢纽基因对WT患者生存的影响。使用Estimation of Stromal and Immune cells in Malignant Tumor tissues using the Expression（ESTIMATE）算法和单样本GSEA来评估基因表达与免疫浸润程度之间的相关性。在构建PPI网络和筛选枢纽基因模块后，确定了前12个进行进一步研究的基因。鉴定出Kinesin家族成员2C（KIF2C）作为最显著的基因，可以预测WT患者的总体生存率。通过定量实时荧光定量PCR和免疫组织化学进一步验证了KIF2C在WT中的表达。此外，我们发现KIF2C与WT中的免疫细胞浸润显著相关。我们的研究表明，KIF2C的表达变化可能涉及到WT并且可能作为WT患者的潜在预后生物标志物。© 2023. Springer Nature Limited.

Wilms tumor (WT) is the most common pediatric renal malignant tumor in the world. Overall, the prognosis of Wilms tumor is very good. However, the prognosis of patients with anaplastic tumor histology or disease relapse is still poor, and their recurrence rate, metastasis rate and mortality are significantly increased compared with others. Currently, the combination of histopathological examination and molecular biology is essential to predict prognosis and guide the treatment. However, the molecular mechanism has not been well studied. Genetic profiling may be helpful in some way. Hence, we sought to identify novel promising biomarkers of WT by integrating bioinformatics analysis and to identify genes associated with the pathogenesis of WT. In the presented study, the NCBI Gene Expression Omnibus was used to download two datasets of gene expression profiles related to WT patients for the purpose of detecting overlapped differentially expressed genes (DEGs). The DEGs were then uploaded to DAVID database for enrichment analysis. In addition, the functional interactions between proteins were evaluated by simulating the protein-protein interaction (PPI) network of DEGs. The impact of selected hub genes on survival in WT patients was analyzed by using the online tool R2: Genomics Analysis and Visualization Platform. The correlation between gene expression and the degree of immune infiltration was assessed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using the Expression (ESTIMATE) algorithm and the single sample GSEA. Top 12 genes were identified for further study after constructing a PPI network and screening hub gene modules. Kinesin family member 2C (KIF2C) was identified as the most significant gene predicting the overall survival of WT patients. The expression of KIF2C in WT was further verified by quantitative real-time polymerase chain reaction and immunohistochemistry. Furthermore, we found that KIF2C was significantly correlated with immune cell infiltration in WT. Our present study demonstrated that altered expression of KIF2C may be involved in WT and serve as a potential prognostic biomarker for WT patients.© 2023. Springer Nature Limited.