The functional diversity of natural killer (NK) cell repertoires stems from differentiation, homeostatic, receptor–ligand interactions and adaptive-like responses to viral infections. In the present study, we generated a single-cell transcriptional reference map of healthy human blood- and tissue-derived NK cells, with temporal resolution and fate-specific expression of gene-regulatory networks defining NK cell differentiation. Transfer learning facilitated incorporation of tumor-infiltrating NK cell transcriptomes (39 datasets, 7 solid tumors, 427 patients) into the reference map to analyze tumor microenvironment (TME)-induced perturbations. Of the six functionally distinct NK cell states identified, a dysfunctional stressed CD56^bright state susceptible to TME-induced immunosuppression and a cytotoxic TME-resistant effector CD56^dim state were commonly enriched across tumor types, the ratio of which was predictive of patient outcome in malignant melanoma and osteosarcoma. This resource may inform the design of new NK cell therapies and can be extended through transfer learning to interrogate new datasets from experimental perturbations or disease conditions.

自然杀伤 (NK) 细胞库的功能多样性源于分化、稳态、受体-配体相互作用以及对病毒感染的适应性反应。在本研究中，我们生成了健康人类血液和组织来源的 NK 细胞的单细胞转录参考图，具有定义 NK 细胞分化的基因调控网络的时间分辨率和命运特异性表达。迁移学习有助于将肿瘤浸润 NK 细胞转录组（39 个数据集、7 个实体瘤、427 名患者）纳入参考图谱中，以分析肿瘤微环境 (TME) 引起的扰动。在确定的六种功能不同的 NK 细胞状态中，对 TME 诱导的免疫抑制敏感的功能失调应激 CD56 ^bright 状态和细胞毒性 TME 抗性效应器 CD56 ^dim 状态通常在肿瘤类型中丰富，其比率可预测恶性黑色素瘤和骨肉瘤的患者预后。该资源可以为新 NK 细胞疗法的设计提供信息，并且可以通过迁移学习进行扩展，以询问来自实验扰动或疾病条件的新数据集。