Chen Xiaobin, Li Yugen, Huang Jing, Zhang Qiang, Tan Chunlin, Liu Yang, Du Zhongbo
Department of Urology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Discov Oncol. 2024 Nov 6;15(1):622. doi: 10.1007/s12672-024-01505-z.
The biological significance of cancer-associated fibroblasts (CAFs) in bladder urothelial carcinoma (BUC) warrants further investigation. There is an urgent need to explore the predictive utility of CAF-related genes for prognosis in BUC.
The transcriptome and clinical data of 407 BUC patients in The Cancer Genome Atlas (TCGA) database were analyzed and a prognostic model was established. A total of 476 BUC cases from the E-MTAB-4321 database were used for validation. A risk model was constructed utilizing CAF-related genes through LASSO Cox regression, investigating its association with prognosis, gene mutations, immune cell infiltration, and drug sensitivity in BUC.
We identified five CAF-related genes (EGFL6, NRSN2, SEMA3D, TM4SF1 and TPST1) in both the TCGA and E-MTAB-4321 datasets, and established a prognostic model using LASSO Cox regression. The high-risk group showed a significant correlation with poor survival. Furthermore, the low-risk group exhibited higher tumor mutational burden and lower levels of immune cell infiltration, and this model holds promise for guiding drug selection in BUC patients.
These findings underscore the pivotal role of CAF-related genes in prognostic prediction for BUC patients. Clinical decision-making and tailored therapeutics stand to benefit from these results, providing a valuable reference for future research endeavors.
癌症相关成纤维细胞(CAFs)在膀胱尿路上皮癌(BUC)中的生物学意义值得进一步研究。迫切需要探索CAF相关基因对BUC预后的预测效用。
分析了癌症基因组图谱(TCGA)数据库中407例BUC患者的转录组和临床数据,并建立了预后模型。来自E-MTAB-4321数据库的476例BUC病例用于验证。通过LASSO Cox回归利用CAF相关基因构建风险模型,研究其与BUC预后、基因突变、免疫细胞浸润和药物敏感性的关系。
我们在TCGA和E-MTAB-4321数据集中鉴定出五个CAF相关基因(EGFL6、NRSN2、SEMA3D、TM4SF1和TPST1),并使用LASSO Cox回归建立了预后模型。高危组与较差的生存率显著相关。此外,低危组表现出更高的肿瘤突变负担和更低的免疫细胞浸润水平,该模型有望指导BUC患者的药物选择。
这些发现强调了CAF相关基因在BUC患者预后预测中的关键作用。临床决策和个性化治疗可能会从这些结果中受益,为未来的研究工作提供有价值的参考。