Institute for Biomedical Engineering, Science and Technology (I BEST), Partnership between Ryerson University and St. Michael's Hospital, Toronto, ON, M5B 1W8, Canada.
Ultrashort Laser Nanomanufacturing Research Facility, Faculty of Engineering and Architectural Sciences, Ryerson University, 350 Victoria Street, Toronto, ON, M5B 2K3, Canada.
Nat Commun. 2022 Aug 4;13(1):4527. doi: 10.1038/s41467-022-32308-x.
Natural Killer (NK) cells, a subset of innate immune cells, undergo cancer-specific changes during tumor progression. Therefore, tracking NK cell activity in circulation has potential for cancer diagnosis. Identification of tumor associated NK cells remains a challenge as most of the cancer antigens are unknown. Here, we introduce tumor-associated circulating NK cell profiling (CNKP) as a stand-alone cancer diagnostic modality with a liquid biopsy. Metabolic profiles of NK cell activation as a result of tumor interaction are detected with a SERS functionalized OncoImmune probe platform. We show that the cancer stem cell-associated NK cell is of value in cancer diagnosis. Through machine learning, the features of NK cell activity in patient blood could identify cancer from non-cancer using 5uL of peripheral blood with 100% accuracy and localization of cancer with 93% accuracy. These results show the feasibility of minimally invasive cancer diagnostics using circulating NK cells.
自然杀伤 (NK) 细胞是先天免疫细胞的一个亚群，在肿瘤进展过程中会发生肿瘤特异性变化。因此，跟踪循环中的 NK 细胞活性具有癌症诊断的潜力。由于大多数癌症抗原尚不清楚，因此鉴定与肿瘤相关的 NK 细胞仍然具有挑战性。在这里，我们引入了与肿瘤相关的循环 NK 细胞分析 (CNKP)，作为一种带有液体活检的独立癌症诊断方式。通过 SERS 功能化的 OncoImmune 探针平台检测由于肿瘤相互作用而导致的 NK 细胞激活的代谢谱。我们表明，与癌症干细胞相关的 NK 细胞在癌症诊断中具有价值。通过机器学习，使用外周血 5uL 即可从非癌症患者中以 100%的准确率和 93%的准确率准确识别癌症和定位癌症，患者血液中 NK 细胞活性的特征可以识别癌症。这些结果表明使用循环 NK 细胞进行微创癌症诊断是可行的。
