探讨T淋巴细胞内抗原1（TIA1）基因在膀胱癌中的表达情况及对膀胱癌发生发展和生存预后的影响。

基于TCGA数据库，使用Kaplan-Meier曲线和ROC曲线分析TIA1基因表达与膀胱癌生存预后的关系和诊断价值。采用秩和检验分析TIA1表达与临床特征的关联。单因素和多因素Cox回归分析TIA1及临床特征预测膀胱癌（BLCA）患者预后的可能，并构建诺模图预测BLCA患者的无进展生存率。基因集富集分析（GSEA）用于探索TIA1在膀胱癌中的潜在作用机制。免疫蛋白印迹实验（WB）验证TIA1蛋白在膀胱癌和癌旁组织中的表达差异。

生存分析表明TAI1高表达组的总生存率（P=0.00135）、无进展生存率（P=0.00154）和无疾病生存率（P=0.00116）均高于低表达组。TIA1在低龄组（≤60岁）中表达明显高于高龄组（P=0.007），解剖分期和T分期越高，TIA1表达越低（P<0.01）。COX回归分析表明TIA1（P=0.047）、年龄（P<0.001）、解剖分期（P<0.001）是BLCA患者的独立预后因素。诺模图的C指数等于0.661（0.619～0.704），提示该模型具有较好的预测能力。GSEA分析表明TIA1富集在"KEGG-Bladder cancer"和"KEGG-natural killer cell-mediated cytotoxicity"相关的通路。WB实验证明TIA1蛋白在BLCA组织中的表达也低于癌旁组织。

TIA1基因在膀胱癌组织中表达下调,可能是BLCA发生发展的独立预后因素，用TIA1基因表达水平、年龄、临床分期共同构建的预后模型对BLCA患者无进展生存有较好的预测能力。

To investigate the expression of TIA1 gene in bladder cancer (BLCA) and its effect on the occurrence, development and prognosis of BLCA.

Based on TCGA database, the relationship between TIA1 gene expression and bladder cancer survival prognosis and diagnostic value were analyzed using Kaplan-Meier curve and ROC curve.The association between TIA1 expression and clinical features were analyzed by rank sum test. Univariate and multivariate Cox regression analysis of TIA1 and clinical features predicted the possibility of prognosis in BLCA patients, and a nomogram was constructed to predict the progression-free survival of BLCA patients. Gene set enrichment analysis (GSEA) was used to explore the potential mechanism of action of TIA1 in bladder cancer. Western blot (WB) validated the differential expression of TIA1 protein in bladder cancer and paracancerous tissues.

Survival analysis indicated that overall survival (P=0.00135), progression-free survival (P=0.00154) and disease-free survival (P=0.00116) were higher in the high TAI1 expression group than in the low expression one. TIA1 expression was obviously higher in the low age group (Age≤60 years) than in the high age group (P=0.007), and the higher the anatomical stage and T stage, the lower the TIA1 expression (P<0.01). COX regression analysis demonstrated that TIA1 (P=0.047), age (P<0.001), and anatomical stage (P<0.001) were independent prognostic factors for BLCA patients. The C-index of the nomogram was equal to 0.661 (0.619-0.704), which suggested that this model had a good predictive capacity. GSEA analysis demonstrated that TIA1 was abundant in "KEGG-Bladder cancer" and "KEGG-natural killer cell-mediated cytotoxicity" related pathways. WB assays also demonstrated that TIA1 protein expression was lower in BLCA tissues than in paracancerous tissues.

TIA1 gene expression is down-regulated in bladder cancer tissues, which may be an independent prognostic factor for the development of BLCA. The prognostic model constructed by TIA1 gene, age and clinical stage have a good predictive ability for progression-free survival of BLCA patients.