Mapping Tumor Immune Landscape with AI-Powered Spatial Proteomics

An AI-powered spatial proteomics analysis approach to study the tumor-immune interactions using a murine cancer model

Cell DIVE multiplexed image of FFPE tissue section from syngeneic murine cancer model, 4T1. FFPE_tissue_section_from_syngeneic_murine_cancer_model.jpg

Spatial mapping of untreated tumors provides an overview of the tumor immune architecture, useful for understanding therapeutic responses. Immunocompetent murine models are essential for identifying immune-dependent events in tumor development and progression. Characterizing these models, with intact immune systems and interacting cellular components, requires a multiplexed approach. We show an AI-powered spatial proteomics approach to study the tumor-immune interactions in murine cancer tissue.

Key Learnings

  • Discover how Cell DIVE multiplexed imaging along with IHC-validated antibodies from Cell Signaling Technology enables precise detection of diverse cell types.
  • Learn about the role of tumor cell metabolism and immununosuppresive mechanisms in cancer progression.
  • Explore how AI-guided image analysis using Aivia can simplify spatial proteomics analysis.
  • Identify specific immune cell subtypes, their distribution relative to tumor regions, and their interactions, offering deeper insights into the complex dynamics driving tumor progression and response to therapy.

Multiplexed imaging using Cell DIVE and AI-driven analysis using Aivia can simplify the spatial proteomics analysis. Such a workflow enables researchers to perform detailed characterization and spatial mapping of various immune cell subtypes and tumor cells within the tumor microenvironment, revealing complex interactions and heterogeneity within the tissue.

Integration of Multiplexed Imaging and AI Analysis

This study explores the intricate relationships between the immune system and tumor cells in the context of cancer progression and therapy. Cell DIVE is a multiplex imaging solution capable of probing dozens of biomarkers on a single tissue section, providing a detailed molecular map of the whole tissue showcasing various cell types. Cell Signaling Technology offers IHC-validated antibodies that work seamlessly with Cell DIVE, enhancing the detection and phenotyping of various cell types in tissue samples. The integration of Aivia software simplifies spatial biology workflow by providing AI-guided segmentation, phenotyping and clustering analysis. A case study on the 4T1 murine tumor model demonstrates the utility of this spatial proteomics worfklow, revealing a heterogeneous immune landscape and complex spatial relationships within the tumor.

Using AI-assisted segmentaion and phenotyping on Aivia, the expression of all the markers within the Cell DIVE multiplexed whole tissue images was characterized (Figure 1).

The Impact of Tumor Microenvironment on Immune Cell Distribution

The study highlights how specific immune cell types, such as T cells, macrophages, and dendritic cells, exhibit distinct spatial distributions relative to hypoxic and necrotic regions within the tumor, suggesting the influence of the tumor microenvironment on immune cell behavior and potential implications for therapy effectiveness.
AI-powered spatial proteomics analysis using Cell DIVE and Aivia in the syngeneic 4T1 murine tumor model revealed a complex and diverse immune landscape. Overall, this study underscores the importance of combined use of multiplexed imaging and AI-powered analysis for understanding the spatial relationships and interactions within the tumor microenvironment, providing insights that could inform more effective cancer therapies.

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