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通过多重成像技术揭示实体瘤免疫微环境中的空间复杂性。

Unveiling spatial complexity in solid tumor immune microenvironments through multiplexed imaging.

机构信息

Department of Haematology, Oncology, Gastroenterology, Nephrology, Rheumatology, University Children's Hospital Tuebingen, Tuebingen, Germany.

iFIT Cluster of Excellence EXC 2180 'Image-Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany.

出版信息

Front Immunol. 2024 Mar 19;15:1383932. doi: 10.3389/fimmu.2024.1383932. eCollection 2024.

Abstract

Deciphering cellular components and the spatial interaction network of the tumor immune microenvironment (TIME) of solid tumors is pivotal for understanding biologically relevant cross-talks and, ultimately, advancing therapies. Multiplexed tissue imaging provides a powerful tool to elucidate spatial complexity in a holistic manner. We established and cross-validated a comprehensive immunophenotyping panel comprising over 121 markers for multiplexed tissue imaging using MACSima™ imaging cyclic staining (MICS) alongside an end-to-end analysis workflow. Applying this panel and workflow to primary cancer tissues, we characterized tumor heterogeneity, investigated potential therapeutical targets, conducted in-depth profiling of cell types and states, sub-phenotyped T cells within the TIME, and scrutinized cellular neighborhoods of diverse T cell subsets. Our findings highlight the advantage of spatial profiling, revealing immunosuppressive molecular signatures of tumor-associated myeloid cells interacting with neighboring exhausted, PD1 T cells in the TIME of hepatocellular carcinoma (HCC). This study establishes a robust framework for spatial exploration of TIMEs in solid tumors and underscores the potency of multiplexed tissue imaging and ultra-deep cell phenotyping in unraveling clinically relevant tumor components.

摘要

解析实体肿瘤的肿瘤免疫微环境(TIME)的细胞成分和空间相互作用网络对于理解生物学相关的串扰以及最终推进治疗至关重要。多重组织成像提供了一种强大的工具,可以全面阐明空间复杂性。我们使用 MACSima™成像循环染色(MICS)建立并交叉验证了一个包含超过 121 个标记物的用于多重组织成像的综合免疫表型面板,同时还采用了端到端分析工作流程。将该面板和工作流程应用于原发性癌症组织,我们对肿瘤异质性进行了特征分析,研究了潜在的治疗靶点,深入分析了细胞类型和状态,对 TIME 中的 T 细胞进行了亚表型分析,并仔细研究了不同 T 细胞亚群的细胞邻域。我们的研究结果强调了空间分析的优势,揭示了肝癌(HCC)TIME 中与邻近耗尽型 PD1 T 细胞相互作用的肿瘤相关髓样细胞的免疫抑制分子特征。这项研究建立了用于实体肿瘤 TIME 空间探索的强大框架,并强调了多重组织成像和超深度细胞表型分析在揭示临床相关肿瘤成分方面的强大功能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a9/10985204/f27a625196d0/fimmu-15-1383932-g001.jpg

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