背景:免疫检查点阻断(ICB)治疗已成为不符合顺铂标准的转移性尿路上皮癌(mUC)患者的一线治疗选择。尽管如此,只有少数人能从中受益,所以需要有用的预测标记。
方法:下载基于ICB的mUC和基于化疗的膀胱癌队列,提取焦亡相关基因(PRG)的表达数据。采用LASSO算法构建mUC队列中的PRG预后指数(PRGPI),我们验证了PRGPI在两个mUC和两个膀胱癌队列中的预后能力。
结果:mUC队列中的大多数PRG是免疫激活基因,还有一些是免疫抑制基因。由GZMB组成的PRGPI,IRF1和TP63可以分层MUC的风险。在IMswific210和GSE176307队列中,KaplanMeier分析的P值分别<0.01和0.002。PRGPI还可以预测ICB反应,两组的卡方检验的P值分别为0.002和0.046.此外,PRGPI还可以预测两个没有ICB治疗的膀胱癌队列的预后。PRGPI与PDCD1/CD274的表达具有高度的协同相干性。低PRGPI组表现出突出的免疫浸润特征,并富集于免疫信号激活通路。
结论:我们构建的PRGPI可以有效预测ICB治疗mUC患者的治疗反应和总体生存率。PRGPI可以帮助MUC患者在未来实现个性化和准确的治疗。
BACKGROUND: Immune checkpoint blockade (
ICB) therapy has become a first-line treatment option for metastatic urothelial carcinoma (mUC) patients who do not meet the criteria of cisplatin. Still, only a few people can benefit from it, so useful predictive markers are needed.
METHODS: Download the
ICB-based mUC and chemotherapy-based bladder cancer cohorts, and extract the expression data of pyroptosis-related genes (PRG). The LASSO algorithm was used to construct the PRG prognostic index (PRGPI) in the mUC cohort, and we verified the prognostic ability of PRGPI in two mUC and two bladder cancer cohorts.
RESULTS: Most of the PRG in the mUC cohort were immune-activated genes, and a few were immunosuppressive genes. The PRGPI composed of GZMB, IRF1, and TP63 can stratify the risk of mUC. In IMvigor210 and GSE176307 cohorts, the P-values of Kaplan Meier analysis was < 0.01 and 0.002, respectively. PRGPI could also predict
ICB response, and the chi-square test of the two cohorts had P-values of 0.002 and 0.046, respectively. In addition, PRGPI can also predict the prognosis of two bladder cancer cohorts without
ICB therapy. The PRGPI and the expression of PDCD1/CD274 had a high degree of synergistic correlation. The Low PRGPI group showed prominent characteristics of immune infiltration and was enriched in the immune signal activation pathway.
CONCLUSIONS: The PRGPI we constructed can effectively predict the treatment response and overall survival rate of mUC patients treated with
ICB. The PRGPI can help mUC patients achieve individualized and accurate treatment in the future.