Abstract：
BACKGROUND: Wilm\'s tumor (WT) is one of the most common childhood urological tumors, ranking second in the incidence of pediatric abdominal tumors. The development of WT is associated with various factors, and the correlation with autophagy is currently unclear.
OBJECTIVE: To develop a new prognostic model of autophagy-related genes (ATG) for WT.
METHODS: Using the Therapeutically applicable research to generate effective treatments (TARGET) database to screen for differentially expressed ATGs in WT and normal tissues. ATGs were screened for prognostic relevance to WT using one-way and multifactorial Cox regression analyses and prognostic models were constructed. The risk score was calculated according to the model, and the predictive ability of the constructed model was analyzed using the ROC (receiver operating characteristic) curve to verify the significance of the model for the prognosis of WT.
RESULTS: Sixty-eight differentially expressed ATGs were identified by univariate Cox regression analysis, and two critical prognostic ATGs (CXCR4 and ERBB2) were identified by multivariate Cox regression analysis. Patients were divided into high-risk and low-risk groups according to the differential expression of these two ATGs. Kaplan-Meier (KM) curves showed a significant difference in survival time between the two groups. The critical prognostic ATGs were combined with race, age, and stage in a multifactorial regression analysis, and the final prognostic model was produced as a line graph.
CONCLUSIONS: The prognostic model of autophagy-related genes composed of the CXCR4 gene and ERBB2 gene has a specific predictive value for the prognosis of WT, and the present study provides a clear basis for future research on biomarkers and therapeutic targets.
OBJECTIVE: To develop a new prognostic model of autophagy-related genes (ATG) for WT.
METHODS: Using the Therapeutically applicable research to generate effective treatments (TARGET) database to screen for differentially expressed ATGs in WT and normal tissues. ATGs were screened for prognostic relevance to WT using one-way and multifactorial Cox regression analyses and prognostic models were constructed. The risk score was calculated according to the model, and the predictive ability of the constructed model was analyzed using the ROC (receiver operating characteristic) curve to verify the significance of the model for the prognosis of WT.
RESULTS: Sixty-eight differentially expressed ATGs were identified by univariate Cox regression analysis, and two critical prognostic ATGs (CXCR4 and ERBB2) were identified by multivariate Cox regression analysis. Patients were divided into high-risk and low-risk groups according to the differential expression of these two ATGs. Kaplan-Meier (KM) curves showed a significant difference in survival time between the two groups. The critical prognostic ATGs were combined with race, age, and stage in a multifactorial regression analysis, and the final prognostic model was produced as a line graph.
CONCLUSIONS: The prognostic model of autophagy-related genes composed of the CXCR4 gene and ERBB2 gene has a specific predictive value for the prognosis of WT, and the present study provides a clear basis for future research on biomarkers and therapeutic targets.
摘要：
背景：Wilm\'s肿瘤（WT）是最常见的儿童泌尿系统肿瘤之一，小儿腹部肿瘤发病率排名第二。WT的发展与各种因素有关，与自噬的相关性目前尚不清楚。
目的：建立一种新的自噬相关基因（ATG）的WT预后模型。
方法：使用治疗上适用的研究来生成有效治疗（TARGET）数据库，以筛选WT和正常组织中差异表达的ATG。使用单向和多因素Cox回归分析筛选ATG与WT的预后相关性，并构建预后模型。根据模型计算风险评分，用ROC(受试者工作特征)曲线分析所构建模型的预测能力,验证模型对WT预后的意义。
结果：通过单变量Cox回归分析确定了68个差异表达的ATGs，通过多变量Cox回归分析确定了两个关键预后ATG（CXCR4和ERBB2）。根据这两种ATG的差异表达将患者分为高危和低危组。Kaplan-Meier(KM)曲线显示两组生存时间差异有统计学意义。关键的预后ATG与种族相结合，年龄,在多因素回归分析中，并将最终的预后模型制作为折线图。
结论：由CXCR4基因和ERBB2基因组成的自噬相关基因的预后模型对WT的预后具有特异性预测价值。本研究为未来生物标志物和治疗靶点的研究提供了明确的基础。
目的：建立一种新的自噬相关基因（ATG）的WT预后模型。
方法：使用治疗上适用的研究来生成有效治疗（TARGET）数据库，以筛选WT和正常组织中差异表达的ATG。使用单向和多因素Cox回归分析筛选ATG与WT的预后相关性，并构建预后模型。根据模型计算风险评分，用ROC(受试者工作特征)曲线分析所构建模型的预测能力,验证模型对WT预后的意义。
结果：通过单变量Cox回归分析确定了68个差异表达的ATGs，通过多变量Cox回归分析确定了两个关键预后ATG（CXCR4和ERBB2）。根据这两种ATG的差异表达将患者分为高危和低危组。Kaplan-Meier(KM)曲线显示两组生存时间差异有统计学意义。关键的预后ATG与种族相结合，年龄,在多因素回归分析中，并将最终的预后模型制作为折线图。
结论：由CXCR4基因和ERBB2基因组成的自噬相关基因的预后模型对WT的预后具有特异性预测价值。本研究为未来生物标志物和治疗靶点的研究提供了明确的基础。
