Wang Guanning, Lyudovyk Olga, Kim Justin Y, Lin Ya-Hui, Elhanati Yuval, Mathew Divij, Wherry E John, Herati Ramin S, Greenplate Allison R, Greenbaum Benjamin, Vardhana Santosha A, Huang Alexander C
Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Cancer Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Tri-institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY, USA.
STAR Protoc. 2023 May 8;4(2):102289. doi: 10.1016/j.xpro.2023.102289.
The current abundance of immunotherapy clinical trials presents an opportunity to learn about the underlying mechanisms and pharmacodynamic effects of novel drugs on the human immune system. Here, we present a protocol to study how these immune responses impact clinical outcomes using large-scale high-throughput immune profiling of clinical cohorts. We describe the Human Immune Profiling Pipeline, which comprises an end-to-end solution from flow cytometry results to computational approaches and unsupervised patient clustering based on lymphocyte landscape. For complete details on the use and execution of this protocol, please refer to Lyudovyk et al. (2022)..
目前丰富的免疫疗法临床试验提供了一个机会，来了解新型药物对人类免疫系统的潜在机制和药效学作用。在此，我们提出一项方案，通过对临床队列进行大规模高通量免疫分析，研究这些免疫反应如何影响临床结果。我们描述了人类免疫分析流程，它包括一个从流式细胞术结果到计算方法以及基于淋巴细胞格局的无监督患者聚类的端到端解决方案。有关此方案使用和执行的完整详细信息，请参考柳多维克等人（2022年）的研究。
