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Related Concept Videos

The Tumor Microenvironment02:17

The Tumor Microenvironment

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Every normal cell or tissue is embedded in a complex local environment called stroma, consisting of different cell types, a basal membrane, and blood vessels. As normal cells mutate and develop into cancer cells, their local environment also changes to allow cancer progression. The tumor microenvironment (TME) consists of a complex cellular matrix of stromal cells and the developing tumor. The cross-talk between cancer cells and surrounding stromal cells is critical to disrupt normal tissue...
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Related Experiment Video

Updated: Dec 24, 2025

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
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Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment.

Manuel Flores Molina1, Thomas Fabre1, Aurélie Cleret-Buhot2

  • 1Centre de Recherche du Centre hospitalier de l'Université de Montréal (CRCHUM); Département de Microbiologie, Infectiologie et Immunologie, Faculté de Médecine, Université de Montréal.

Journal of Visualized Experiments : Jove
|April 14, 2020
PubMed
Summary

This study introduces a new method for analyzing the tumor microenvironment (TME) by creating virtual slides from tissue sections. This approach allows for detailed spatial mapping of immune cells, enhancing cancer diagnostics and treatment insights.

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Area of Science:

  • Immunology
  • Oncology
  • Computational Pathology

Background:

  • The tumor microenvironment (TME) immune landscape critically influences cancer progression and therapeutic outcomes.
  • Immune cell density and location within the TME hold significant diagnostic and prognostic value.
  • Current multiomic profiling advances TME understanding but lacks spatial resolution of cell interactions.

Purpose of the Study:

  • To develop an accessible, spatial multiplexing technique for immune cell profiling in tissue sections.
  • To complement single-cell technologies by providing whole-tissue spatial context.
  • To enable automated identification, quantification, and mapping of immune cells within the TME.

Main Methods:

  • Integration of serial imaging, sequential labeling, and image alignment to create virtual multiparameter slides.
  • Automated analysis of virtual slides using user-defined protocols.
  • Application of specific analysis modules: Tissuealign, Author, and HISTOmap.

Main Results:

  • Successful generation of virtual multiparameter slides from whole tissue sections.
  • Demonstrated automated identification, quantification, and spatial mapping of immune cell populations.
  • Maximized information retrieval from limited clinical tissue samples.

Conclusions:

  • The described strategy offers an affordable and accessible method for high-resolution TME spatial analysis.
  • This approach provides an unbiased, comprehensive view of the immune landscape across entire tissue sections.
  • The technique enhances the utility of limited tissue samples for cancer research and clinical applications.