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Regular and Young Investigator Award Abstracts
Biomarkers, Immune Monitoring and Novel Technologies
73 AI-powered spatial proteomics analysis reveals a diverse immune landscape in the syngeneic 4T1 murine tumor model
  1. Arindam Bose1,
  2. Emily Alonzo2,
  3. Sophie Struble1,
  4. Gabriella Spang2,
  5. Rick Heil-Chapdelaine1,
  6. Natasha Fernandez Diaz Granados1,
  7. Michael Smith3,
  8. Matthew Norton2,
  9. Samuel Jensen2 and
  10. Vasundhara Agrawal1
  1. 1Leica Microsystems, Waltham, MA, USA
  2. 2Cell Signaling Technology, Inc., Danvers, MA, USA
  3. 3Leica Microsystems, Buffalo Grove, IL, USA

  • Journal for ImmunoTherapy of Cancer (JITC) preprint. The copyright holder for this preprint are the authors/funders, who have granted JITC permission to display the preprint. All rights reserved. No reuse allowed without permission.

Abstract

Background Immune cells play a pivotal role in cancer biology and response to therapy. Immunocompetent murine models are important tools to identify immune-dependent events in tumor development and progression. Characterizing murine tumor models with intact immune systems where multiple cellular components interact requires a multiplexed approach. Spatial mapping of untreated tumor provides an overview of the tumor immune architecture, which can be applied to understand response to therapies at the preclinical stage.

Methods To understand the tumor-immune landscape in mouse mammary carcinoma 4T1, we performed Cell DIVE multiplexed imaging on FFPE tissue slides. A directly conjugated and previously validated panel of 25-biomarkers from Cell Signaling Technology (CST) was used for this study. In every round, the tissue was imaged on the Cell DIVE Imager using four channels plus DAPI, with automatic autofluorescence removal, corrections, and stitching. Fully stitched imaging data were analyzed using AIVIA.

Results Using an unsupervised clustering approach, we characterized the presence and positioning of a variety of immune cell subtypes and their relationships within the tumor immune landscape in 4T1 syngeneic tumor tissue. We found heterogeneous distributions of immune cell types including T cell populations expressing immune checkpoint and regulatory markers, M2-like macrophages, and dendritic cell populations within the 4T1 tissue. We also observed variable Glut1 expression throughout the tumor tissue as well as a large necrotic region. Using spatial relational analysis, we found localized enrichment of specific immune cell subtypes as a function of spatial distance from the necrotic tumor boundaries, suggesting important roles for necrotic regions in tumor progression and immune response.

Conclusions By utilizing multiplexed whole tissue imaging and AI-powered image analysis with Cell DIVE and AIVIA, we were able to chart deep spatial relationships between immune cell subtypes and tumor cells within the mouse mammary carcinoma tissue. The study highlights the importance of simultaneously observing multiple immune cell types and tumor characteristics in spatial context.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/jitc-2024-SITC2024.0073

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