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The Tumor Microenvironment

The Tumor Microenvironment

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...

The Tumor Microenvironment

The Tumor Microenvironment

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: Jun 18, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Spatial Visual Proteomics: Insights into Tumor Microenvironment Dynamics.

Peiwu Huang^1,2, Changying Fu², Qian Kong²

¹School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China.

Genomics, Proteomics & Bioinformatics

|June 16, 2026

Summary

This summary is machine-generated.

Spatial proteomics reveals tumor microenvironment complexity, improving understanding of tumor progression and therapeutic resistance. This technology enables precise analysis of cellular interactions for advanced precision oncology applications.

Keywords:

Multi-omics integration Multiplexed imaging Precision medicine Spatial proteomics Tumor microenvironment

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Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment

Published on: June 2, 2023

Related Experiment Videos

Last Updated: Jun 18, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

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Published on: July 6, 2022

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

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Published on: March 25, 2020

Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment

Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment

Published on: June 2, 2023

Area of Science:

Oncology
Proteomics
Cell Biology

Background:

The tumor microenvironment (TME) is crucial for tumor progression and treatment resistance.
Traditional proteomics lacks spatial context, hindering the study of tumor heterogeneity.
Understanding TME complexity requires advanced spatial analysis techniques.

Purpose of the Study:

To review advancements in spatial proteomic technologies for TME analysis.
To highlight methods preserving spatial architecture for detailed cellular insights.
To explore applications in precision oncology and therapeutic development.

Main Methods:

Laser capture microdissection for cell segmentation.
Multiplexed proteomic profiling using antibody-based platforms.
Tissue expansion microscopy and chemical biology probes for enhanced resolution and specificity.
Microfluidic systems and automated workflows for single-cell resolution.
Computational tools for data deconvolution and multi-omics integration.

Main Results:

Spatial proteomics decodes TME complexity, revealing tumor heterogeneity and stromal-immune interactions.
Spatially resolved metabolic reprogramming insights into immune evasion.
Demonstrates potential for biomarker discovery and prognostic stratification.
Highlights challenges in cell segmentation, data deconvolution, and multi-omics integration.

Conclusions:

Spatial proteomics offers transformative potential for precision oncology.
Enables the development of tailored therapies by understanding TME dynamics.
Future directions include multimodal data integration and AI-driven tool refinement for clinical translation.