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Updated: Aug 28, 2026

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
Published on: March 25, 2020
Spatial Immune Coding in Tumor-Draining Lymph Nodes: Functional Compartmentalization of Immune Activation and
Jinjie Li1, Wei Ping2, Ruijie Zhang2
1Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Abstract:
Tumor-draining lymph nodes (TDLNs) are important immune organs linking primary tumors with systemic immune responses. They support tumor antigen presentation, T-cell priming, and effector immune responses, but under sustained tumor influence they can also be remodeled into microenvironments that promote immune escape and metastatic colonization. Conventional methods, including flow cytometry, bulk RNA sequencing, and routine immunohistochemistry, have advanced our understanding of TDLN immunity but cannot simultaneously preserve tissue architecture, cell identity, and spatial cell-cell relationships. Recent advances in spatial transcriptomics, spatial proteomics, and multiplexed imaging enable in situ analysis of immune cells, stromal cells, vascular structures, and their interactions within TDLNs. Emerging evidence suggests that TDLNs are not immunologically homogeneous organs, but gradually develop spatially distinct immune-activation and immunosuppressive regions during tumor progression. Activation regions are associated with HEV-mediated lymphocyte entry, DC-T-cell priming, B-cell follicles, and germinal-center reactions, whereas suppressive regions are enriched in Treg cells, exhausted T cells, suppressive myeloid cells, tumor-reprogrammed FRCs, and myeloid-CAF niches. This review summarizes spatial multi-omics studies of TDLN functional compartmentalization and discusses the potential value of TDLN spatial immune states in predicting immunotherapy response, assessing metastatic risk, and guiding precision treatment, thereby providing a reference for future spatial multi-omics studies of TDLNs.
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