Suppr超能文献

用于解析免疫细胞与癌细胞相互作用的单细胞对蛋白质组学

Single Cell-Pair Proteomics for Decoding Immune-Cancer Cell Interactions.

作者信息

Xu Qin-Qin, Jiang Yi-Rong, Chen Jian-Bo, Wu Jie, Chen Yi-Xue, Fan Qian-Xi, Wang Hui-Feng, Yang Yi, Pan Jian-Zhang, Fang Qun

机构信息

Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.

Key Laboratory of Excited-State Materials of Zhejiang Province, Zhejiang University, Hangzhou, 310007, China.

出版信息

Adv Sci (Weinh). 2025 Mar;12(11):e2414769. doi: 10.1002/advs.202414769. Epub 2025 Jan 22.

Abstract

The efficacy of cancer immunotherapy is significantly influenced by the heterogeneity of individual tumors and immune responses. To investigate this phenomenon, a microfluidic platform is constructed for profiling immune-cancer cell interactions at the single-cell proteomics level for the first time. Based on the platform, a comprehensive workflow is proposed for achieving accurate single-cell pairing of an immune cell and a cancer cell with low cell damage and high success rate up to 95%, cell pair co-culture, and real-time microscopic monitoring of the cell-pair interactions, cell pair retrieval, mass spectrometry-based proteomic analysis of singe cell pairs, and decoupling of the proteomic information for each cell within the cell pair with the stable-isotope labeling method. With the workflow, the interactions of single natural killer (NK) cells and single K562 tumor cells are investigated based on real-time images and single cell-pair proteomics. Notably, an identification depth of over 1000 protein groups in a single cell-pair is achieved, leading to the discovery of sub-clusters of NK cells with different functions and the identification of important biomarkers for cancer treatments. This demonstrates the unique capability of the present platform in providing substantial and comprehensive datasets for profiling immune-cancer cell interactions, discovering heterogeneous immune responses, and predicting biomarkers in the study of cancer immunotherapy.

摘要

癌症免疫疗法的疗效受到个体肿瘤异质性和免疫反应的显著影响。为了研究这一现象,首次构建了一个微流控平台,用于在单细胞蛋白质组学水平上分析免疫细胞与癌细胞的相互作用。基于该平台,提出了一个综合工作流程,以实现免疫细胞和癌细胞的精确单细胞配对,细胞损伤低,成功率高达95%,细胞对共培养,以及对细胞对相互作用的实时显微镜监测、细胞对检索、基于质谱的单细胞对蛋白质组学分析,以及用稳定同位素标记法解耦细胞对内每个细胞的蛋白质组信息。通过该工作流程,基于实时图像和单细胞对蛋白质组学研究了单个自然杀伤(NK)细胞与单个K562肿瘤细胞的相互作用。值得注意的是,在单个细胞对中实现了超过1000个蛋白质组的鉴定深度,从而发现了具有不同功能的NK细胞亚群,并鉴定了癌症治疗的重要生物标志物。这证明了本平台在为分析免疫细胞与癌细胞相互作用、发现异质免疫反应以及预测癌症免疫治疗中的生物标志物提供大量综合数据集方面的独特能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21bc/11923901/faac1de5b8a3/ADVS-12-2414769-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验