Table_1_A Novel TGF-β Risk Score Predicts the Clinical Outcomes and Tumour Microenvironment Phenotypes in Bladder Cancer.xlsx

BackgroundThe TGF-β pathway plays critical roles in numerous malignancies. Nevertheless, its potential role in prognosis prediction and regulating tumour microenvironment (TME) characteristics require further elucidation in bladder cancer (BLCA).
MethodsTGF-β-related genes were comprehensively summarized from several databases. The TCGA-BLCA cohort (training cohort) was downloaded from the Cancer Genome Atlas, and the independent validation cohorts were gathered from Xiangya Hospital (Xinagya cohort) and Gene Expression Omnibus. Initially, we identified differentially expressed TGF-β genes (DEGs) between cancer and normal tissues. Subsequently, univariate Cox analysis was applied to identify prognostic DEGs, which were further used to develop the TGF-β risk score by performing LASSO and multivariate Cox analyses. Then, we studied the role of the TGF-β risk score in predicting prognosis and the TME phenotypes. In addition, the role of the TGF-β risk score in guiding precision treatments for BLCA has also been assessed.
ResultsWe successfully constructed a TGF-β risk score with an independent prognostic prediction value. A high TGF-β risk score indicated an inflamed TME, which was supported by the positive relationships between the risk score, enrichment scores of anticancer immunity steps, and the infiltration levels of tumour-infiltrating immune cells. In addition, the risk score positively correlated with the expression of several immune checkpoints and the T cell inflamed score. Consistently, the risk score was positively related to the enrichment scores of most immunotherapy-positive pathways. In addition, the sensitivities of six common chemotherapeutic drugs were positively associated with the risk score. Furthermore, higher risk score indicated higher sensitivity to radiotherapy and EGFR-targeted therapy. On the contrary, patients with low-risk scores were more sensitive to targeted therapies, including the blockade of FGFR3 and WNT-β-catenin networks.
ConclusionsWe first constructed and validated a TGF-β signature that could predict the prognosis and TME phenotypes for BLCA. More importantly, the TGF-β risk score could aid in individual precision treatment for BLCA.

背景：转化生长因子-β（TGF-β）信号通路在多种恶性肿瘤中发挥关键作用。然而，其在膀胱癌（BLCA）中的预后预测价值以及对肿瘤微环境（TME）特征的调控机制，仍有待进一步阐明。
方法：从多个数据库中全面汇总了TGF-β相关基因。将从癌症基因组图谱（TCGA）下载的TCGA-BLCA队列作为训练队列，独立验证队列分别取自湘雅医院（湘雅队列）与基因表达综合数据库（GEO）。本研究首先鉴定了癌组织与正常组织间的差异表达TGF-β相关基因（DEGs）；随后采用单变量Cox回归分析筛选预后相关差异表达基因，并进一步通过LASSO回归与多变量Cox回归分析构建TGF-β风险评分模型。此后，我们探究了TGF-β风险评分在预后预测及肿瘤微环境表型分析中的作用；此外，还评估了该风险评分对膀胱癌精准治疗的指导价值。
结果：本研究成功构建了具有独立预后预测价值的TGF-β风险评分模型。高TGF-β风险评分对应炎症型肿瘤微环境，这一结论得到了风险评分与抗肿瘤免疫步骤富集得分、肿瘤浸润免疫细胞浸润水平均呈正相关的支持。此外，该风险评分与多种免疫检查点的表达及T细胞炎症得分呈正相关。一致性分析显示，该风险评分与多数免疫治疗阳性通路的富集得分呈正相关。同时，六种常见化疗药物的敏感性与该风险评分呈正相关。进一步分析表明，高风险评分患者对放疗及表皮生长因子受体（EGFR）靶向治疗的敏感性更高。相反，低风险评分患者对包括成纤维细胞生长因子受体3（FGFR3）阻断及WNT-β-连环蛋白（WNT-β-catenin）通路调控在内的靶向治疗敏感性更佳。
结论：本研究首次构建并验证了可用于预测膀胱癌预后及肿瘤微环境表型的TGF-β基因特征模型。更为重要的是，该TGF-β风险评分可为膀胱癌患者的个体化精准治疗提供参考依据。