The tumor immune microenvironment is a main contributor to cancer progression and a promising therapeutic target for oncology. However, immune microenvironments vary profoundly between patients, and biomarkers for prognosis and treatment response lack precision. A comprehensive compendium of tumor immune cells is required to pinpoint predictive cellular states and their spatial localization. We generated a single-cell tumor immune atlas, jointly analyzing published data sets of >500,000 cells from 217 patients and 13 cancer types, providing the basis for a patient stratification based on immune cell compositions. Projecting immune cells from external tumors onto the atlas facilitated an automated cell annotation system. To enable in situ mapping of immune populations for digital pathology, we applied SPOTlight, combining single-cell and spatial transcriptomics data and identifying colocalization patterns of immune, stromal, and cancer cells in tumor sections. We expect the tumor immune cell atlas, together with our versatile toolbox for precision oncology, to advance currently applied stratification approaches for prognosis and immunotherapy.

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用于精准肿瘤学的单细胞肿瘤免疫图谱

肿瘤免疫微环境是癌症进展的主要贡献者，也是肿瘤学有希望的治疗靶点。然而，患者之间的免疫微环境差异很大，预后和治疗反应的生物标志物缺乏精确度。需要全面的肿瘤免疫细胞纲要来确定可预测的细胞状态及其空间定位。我们生成了一个单细胞肿瘤免疫图谱，联合分析了来自 217 名患者和 13 种癌症类型的 >500,000 个细胞的已发表数据集，为基于免疫细胞组成的患者分层提供了基础。将来自外部肿瘤的免疫细胞投射到图谱上有助于自动细胞注释系统。为了能够对数字病理学的免疫群体进行原位绘图，我们应用了 SPOTlight，结合单细胞和空间转录组学数据，识别肿瘤切片中免疫细胞、基质细胞和癌细胞的共定位模式。我们希望肿瘤免疫细胞图谱与我们用于精准肿瘤学的多功能工具箱一起，推动目前应用的预后和免疫治疗分层方法。