Department of Oncology, Third Xiangya Hospital, Central South University, 283 Tongzipo Road, Changsha, 410013, China.
Medical school, Hunan University of Chinese Medicine, No. 300, Xueshi Road, Hanpu kejiao Park, Yuelu District, Changsha, 410208, China.
Oncogene. 2021 Oct;40(43):6223-6234. doi: 10.1038/s41388-021-02019-6. Epub 2021 Sep 22.
Immune-checkpoint blockade (ICB) has been routinely implemented to treat bladder cancer; however, most patients have little or no clinical benefit. In this study, 348 pretreated metastatic urothelial cancer samples from the IMvigor210 cohort were used to identify important genes significantly associated with CD8+ T effector and immune checkpoint signatures. The immune checkpoint inhibitor score (IMS) scoring system was constructed to predict the immunotherapy responsiveness. Transcriptome analysis confirmed that the high IMS score group had significant immune activation with better prognosis and higher immunotherapy responsiveness, which was a powerful biomarker for predicting the prognosis and responsiveness of ICB. Tumor immune dysfunction and exclusion (TIDE) scores were calculated using 2031 external bladder cancer samples for further validation. We selected the important Hub genes as potential therapeutic targets, and validated the genes using genomic, transcriptomic, immunomic, and other multi-omics methods. In addition, we construct a risk prediction model which could stratify patients with bladder cancer and predict patient prognosis and ICB treatment responsiveness. In conclusion, this study identified effective biomarkers for the prediction of immune checkpoint inhibitor treatment responsiveness in bladder cancer patients and provided new immunotherapeutic targets.
免疫检查点阻断（ICB）已常规用于治疗膀胱癌；然而，大多数患者几乎没有或没有临床获益。在这项研究中，使用了来自 IMvigor210 队列的 348 个预处理转移性尿路上皮癌样本，以鉴定与 CD8+ T 效应器和免疫检查点特征显著相关的重要基因。构建了免疫检查点抑制剂评分（IMS）评分系统，以预测免疫治疗反应性。转录组分析证实，高 IMS 评分组具有显著的免疫激活，预后更好，免疫治疗反应性更高，这是预测 ICB 预后和反应性的有力生物标志物。使用 2031 个外部膀胱癌样本计算了肿瘤免疫功能障碍和排斥（TIDE）评分以进一步验证。我们选择了重要的 Hub 基因作为潜在的治疗靶点，并使用基因组、转录组、免疫组学和其他多组学方法验证了这些基因。此外，我们构建了一个风险预测模型，该模型可以对膀胱癌患者进行分层，并预测患者的预后和 ICB 治疗反应性。总之，这项研究确定了有效的生物标志物，可预测膀胱癌患者免疫检查点抑制剂治疗反应性，并提供了新的免疫治疗靶点。
