Mei Jie, Cai Yun, Xu Rui, Zhu Yichao, Zhao Xinyuan, Zhang Yan, Mao Wenjun, Xu Junying, Yin Yongmei
Department of Oncology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi 214023, China; Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China; Wuxi Clinical College of Nanjing Medical University, Wuxi 214023, China.
Wuxi Clinical College of Nanjing Medical University, Wuxi 214023, China.
STAR Protoc. 2023 Apr 28;4(2):102258. doi: 10.1016/j.xpro.2023.102258.
Immune checkpoint inhibitors have transformed the management of advanced cancers, but biomarkers for the prediction of therapeutic responses have not been fully uncovered. Here, we provide a step-by-step approach for the identification of novel biomarkers from public transcriptomic datasets. We comprehensively summarize the available transcriptomic datasets containing immunotherapy information and describe the necessary procedures to evaluate the effectiveness of a novel immunotherapy biomarker, which may accelerate the identification of novel immunotherapy biomarkers. For complete details on the use and execution of this protocol, please refer to Mei et al..
免疫检查点抑制剂已经改变了晚期癌症的治疗方式，但用于预测治疗反应的生物标志物尚未完全被发现。在此，我们提供了一种从公开的转录组数据集识别新型生物标志物的分步方法。我们全面总结了包含免疫治疗信息的可用转录组数据集，并描述了评估新型免疫治疗生物标志物有效性的必要程序，这可能会加速新型免疫治疗生物标志物的识别。有关本方案使用和执行的完整详细信息，请参考梅等人的研究。
