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Related Concept Videos

The Tumor Microenvironment02:17

The Tumor Microenvironment

7.0K
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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Tumor Progression02:07

Tumor Progression

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Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
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Related Experiment Video

Updated: Oct 15, 2025

Organotypic Slice Cultures as Preclinical Models of Tumor Microenvironment in Primary Pancreatic Cancer and Metastasis
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Sub-Tumor Microenvironments Influence PDAC Progression and Therapy Response

    Cancer Discovery
    |October 23, 2021
    PubMed
    Summary

    Pancreatic cancer exhibits two distinct tumor microenvironment states. These states significantly impact patient survival, offering potential therapeutic targets.

    Area of Science:

    • Oncology
    • Cancer Biology
    • Immunology

    Background:

    • The tumor microenvironment (TME) is a complex ecosystem crucial for cancer progression.
    • Understanding TME heterogeneity is vital for developing effective pancreatic cancer therapies.

    Purpose of the Study:

    • To identify and characterize distinct tumor microenvironment states in pancreatic cancer.
    • To investigate the association between TME states and patient outcomes.

    Main Methods:

    • Analysis of patient tumor samples.
    • Multi-omic profiling of the TME.
    • Correlation analysis with clinical data.

    Main Results:

    • Identification of two prevalent and distinct pancreatic cancer TME states.

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  • Differential expression of key immune and stromal markers between states.
  • Significant correlation between TME states and patient survival rates.

    • Conclusions:

    • Pancreatic cancer TME is not uniform and can be classified into distinct states.
    • These TME states serve as prognostic biomarkers for patient outcome.
    • Targeting specific TME states may represent a novel therapeutic strategy.