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222-H A single-cell spatial cancer atlas of solid malignancies
  1. Colles Price,
  2. Kazuho Nishimura,
  3. Michael Zhou,
  4. Som Bandyopadhyay,
  5. Russell Weiner and
  6. Darrell Borger
  1. Takeda Pharmaceuticals, Cambridge, MA, 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.


Background Deep single-cell genomics has provided a monumental leap in our understanding and categorical analysis of cancer cells and their unique molecular properties. With the advent of innovative spatial omics platforms that preserve the tissue architecture, an emerging understanding of complex cell interactions and local environment influences is providing new perspectives for targeted therapies. Here we describe a comprehensive approach at profiling the tumor immune microenvironment across multiple solid malignancies to provide an unparalleled atlas of tumor biology.

Methods To generate this atlas, we created a panel of 500 genes representing over 40 cell phenotyping pathways and dozens of signaling pathways including chemokines, cytokines, interferon, and ligand-receptor interactions. This gene list was used by the MERFISH platform across 15 patients representing 8 different solid malignancies including triple-negative breast cancer (TNBC), colon cancer, non-small cell lung cancer (NSCLC), pancreatic cancer, prostate cancer, kidney cancer, liver cancer and melanoma. After initial filtering and quality control this produced a total dataset with over 7.5 million cells and greater than 1 billion transcripts.

Results We report that a 500 gene panel was adequate to reveal complex relationships between diverse cell types within the tumor microenvironment. While the presence of major immune cell types was observed in all cancer tissues, the ratio and spatial relationship to cancer cells differed between each tumor. Accordingly, we observed differences in cellular composition of the microenvironment corresponded with associated changes in cellular signaling. Using the alpha manifold approach to generate cellular neighborhoods, we quantified the spatial overlap between cellular clusters across multiple tissues. Patient-to-patient differences in neighborhood clusters and spatial relationships provided novel signatures that can be leveraged as translational biomarkers for emerging cancer therapies.

Conclusions This comprehensive map of the tumor immune microenvironment is a deep exploration into the cellular architecture of solid malignancies which will provide the foundation for our future investigations. This effort will be expanded in the future with more patient samples across a greater number of disease indications and will include several other spatial -omic technologies. This will serve as a critical resource for the development of novel therapeutics together with directions toward an integrated precision medicine approach.

Acknowledgements We would like to thank Vizgen Lab Services for running the study and supporting the project.

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

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