Unveiling spatial complexity in solid tumor immune microenvironments through multiplexed imaging

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, PD1high 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.

Keywords: MACSima™; multiplexed tissue imaging; single-cell analysis; spatial analysis workflow; tumor immunophenotyping; tumor microenvironment (TME).

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Carcinoma, Hepatocellular* / pathology
  • Diagnostic Imaging
  • Humans
  • Liver Neoplasms* / pathology
  • Phenotype
  • T-Lymphocytes / pathology
  • Tumor Microenvironment

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by Germany’s excellence strategy, EXC 2180-390900677, Image Guided and Functionally Instructed Tumor Therapies (iFIT) and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), 458891500. This research was funded in part by the Zentrum für Seltene Erkrankungen (ZSE), Tübingen.