基于离子通道相关基因（ICRG）的表达构建膀胱癌患者预后的预测模型。通过从癌症基因组图谱数据库中获取临床信息和乳腺癌患者的ICRG mRNA表达情况，使用Cox回归分析、最小绝对收缩选择操作回归分析筛选与乳腺癌预后相关基因，并通过免疫组织化学和实时荧光定量PCR进行验证。构建预测膀胱癌患者预后的风险评分方程，并根据风险得分的中位数将患者分为高风险组和低风险组。比较两组之间的免疫细胞浸润丰度。使用Kaplan-Meier生存曲线和接受者操作特征曲线（ROC曲线）评估风险评分方程的准确性和临床应用价值。通过单因素和多因素Cox回归分析，分析与膀胱癌患者预后相关的因素，并构建预测膀胱癌患者预后的诺莫图。通过比较膀胱癌组织和正常膀胱组织中ICRG的表达水平，筛选出了73个差异表达的ICRG，其中11个与膀胱癌患者预后相关。Kaplan-Meier生存曲线显示，基于这11个基因的风险评分与患者的预后呈负相关。风险评分预测患者1、3和5年预后的ROC曲线下面积（AUC）分别为0.634、0.665和0.712。分层分析显示，基于ICRG的风险评分在预测美国癌症联合委员会( AJCC)Ⅲ-Ⅳ期膀胱癌患者预后方面表现良好（P<0.05），而在预测AJCCⅠ-Ⅱ期患者预后方面价值较差（P>0.05）。高风险组与低风险组之间的浆细胞、活化的自然杀伤细胞、静止的肥大细胞和M2型巨噬细胞的浸润水平存在显著差异。Cox回归分析显示，风险评分、吸烟、年龄和AJCC分期与膀胱癌患者预后独立相关（P<0.05）。将风险评分与临床参数结合构建的诺莫图在预测膀胱癌患者1、3和5年全身生存率方面具有较高的准确性。该研究显示了ICRG在膀胱癌患者预后风险评估中的潜在价值。基于ICRG风险评分构建的预后诺莫图在预测膀胱癌患者预后方面具有较高的准确性。

To construct a prediction model for the prognosis of bladder cancer patients based on the expression of ion channel-related genes (ICRG).The clinical information and the expression of ICRG mRNA in breast cancer patients were obtained from the Cancer Genome Atlas database. Cox regression analysis, minimum absolute shrinkage and selection operator regression analysis were used to screen breast cancer prognosis related genes, which were verified by immunohistochemistry and real-time fluorescence quantitative PCR. The risk scoring equation for predicting the prognosis of patients with bladder cancer was constructed, and the patients were divided into high-risk group and low-risk group according to the median of risk score. The immune cell infiltration abundance was compared between the two groups. Kaplan-Meier survival curve and receiver operating characteristic curve (ROC curve) were used to evaluate the accuracy and clinical application value of the risk scoring equation. The factors related to the prognosis of bladder cancer patients were analyzed by univariate and multivariate Cox regression, and a nomogram for predicting the prognosis of bladder cancer patients was constructed.By comparing the expression levels of ICRG in bladder cancer tissues and normal bladder tissues, 73 differentially expressed ICRGs were screened out, of which 11 were related to the prognosis of bladder cancer patients. Kaplan-Meier survival curve suggested that the risk score based on these 11 genes was negatively correlated with the prognosis of patients. The area under the ROC curve (AUC) of the risk score for predicting the prognosis of patients at 1, 3 and 5 year was 0.634, 0.665 and 0.712, respectively. Stratified analysis showed that the ICRG-based risk score performed well in predicting the prognosis of patients with American Joint Committee on Cancer (AJCC) stage Ⅲ-Ⅳ bladder cancer (P<0.05), while it had a poor value in predicting the prognosis of patients with AJCC stage Ⅰ-Ⅱ (P>0.05). There were significant differences in the infiltration levels of plasma cells, activated natural killer cells, resting mast cells and M2 macrophages between the high-risk group and the low-risk group. Cox regression analysis showed that risk score, smoking, age and AJCC stage were independently associated with the prognosis of patients with bladder cancer (P<0.05). The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1-, 3-and 5-year overall survival rate of bladder cancer patients.The study shows the potential value of ICRG in the prognostic risk assessment of bladder cancer patients. The constructed prognostic nomogram based on ICRG risk score has high accuracy in predicting the prognosis of bladder cancer patients.