BostonGene, Corp., Waltham, MA, USA.
Department of Medical Oncology, Thomas Jefferson University, Philadelphia, PA, USA.
Cancer Cell. 2024 May 13;42(5):759-779.e12. doi: 10.1016/j.ccell.2024.04.008.
The lack of comprehensive diagnostics and consensus analytical models for evaluating the status of a patient's immune system has hindered a wider adoption of immunoprofiling for treatment monitoring and response prediction in cancer patients. To address this unmet need, we developed an immunoprofiling platform that uses multiparameter flow cytometry to characterize immune cell heterogeneity in the peripheral blood of healthy donors and patients with advanced cancers. Using unsupervised clustering, we identified five immunotypes with unique distributions of different cell types and gene expression profiles. An independent analysis of 17,800 open-source transcriptomes with the same approach corroborated these findings. Continuous immunotype-based signature scores were developed to correlate systemic immunity with patient responses to different cancer treatments, including immunotherapy, prognostically and predictively. Our approach and findings illustrate the potential utility of a simple blood test as a flexible tool for stratifying cancer patients into therapy response groups based on systemic immunoprofiling.
缺乏全面的诊断和共识分析模型来评估患者免疫系统的状态,这阻碍了免疫分析在癌症患者的治疗监测和反应预测中的更广泛应用。为了解决这一未满足的需求,我们开发了一种免疫分析平台,该平台使用多参数流式细胞术来描述健康供体和晚期癌症患者外周血中免疫细胞的异质性。通过无监督聚类,我们确定了五个具有不同细胞类型和基因表达谱独特分布的免疫类型。采用相同方法对 17800 个开源转录组进行的独立分析证实了这些发现。连续的基于免疫类型的特征评分用于将系统性免疫与患者对不同癌症治疗的反应相关联,包括免疫治疗、预后和预测。我们的方法和发现说明了一种简单的血液测试作为一种灵活的工具的潜在效用,可根据系统性免疫分析将癌症患者分为治疗反应组。