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Related Concept Videos

The Tumor Microenvironment02:17

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 Microenvironment02:17

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: Jul 4, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

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

Published on: July 6, 2022

Spatial Transcriptomics Recontextualizes the Cellular Environment of Conjunctival Melanoma.

Jeffrey Maurer, Yoko Suzuki-Horiuchi, Bryant Duong

    Medrxiv : the Preprint Server for Health Sciences
    |July 3, 2026
    PubMed
    Summary
    This summary is machine-generated.

    Conjunctival melanoma (CM) progression involves changes in cell populations and gene expression. Spatial transcriptomics identified potential biomarkers for diagnosing and understanding this rare eye cancer.

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    Mining Spatial Transcriptomics Datasets using DeepSpaceDB
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    Mining Spatial Transcriptomics Datasets using DeepSpaceDB

    Published on: September 5, 2025

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    Last Updated: Jul 4, 2026

    Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
    09:19

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

    Published on: July 6, 2022

    Mining Spatial Transcriptomics Datasets using DeepSpaceDB
    10:16

    Mining Spatial Transcriptomics Datasets using DeepSpaceDB

    Published on: September 5, 2025

    Area of Science:

    • Ophthalmology
    • Oncology
    • Genomics

    Background:

    • Conjunctival melanoma (CM) is a rare eye cancer with poorly understood progression and molecular characteristics.
    • Current diagnosis relies heavily on pathologist expertise due to a lack of reliable biomarkers.
    • Existing molecular techniques cannot reliably distinguish lesion severity or predict outcomes.

    Purpose of the Study:

    • To investigate the spatial and molecular landscape of conjunctival melanoma progression.
    • To identify potential diagnostic and prognostic biomarkers for CM.
    • To elucidate the mechanisms underlying CM development and malignancy.

    Main Methods:

    • Spatial transcriptomic analysis of formalin-fixed paraffin-embedded (FFPE) conjunctival melanoma biopsies from three patients.
    • Histopathological grading of disease progression across tissue regions.
    • Differential gene expression and cell composition analysis between disease states.

    Main Results:

    • Melanoma tissues showed depletion of fibroblasts and epithelial cells, with concurrent melanocyte proliferation.
    • Distinct differential gene expression signatures correlated with stages of CM progression: inflammation, cellular restructuring, and malignancy.
    • Spatial transcriptomics revealed changes in cell proportions and gene expression patterns associated with disease severity.

    Conclusions:

    • Spatial transcriptomics provides insights into the cellular and molecular changes during CM progression.
    • Identified gene expression patterns may serve as objective diagnostic and prognostic biomarker candidates.
    • Findings contribute to understanding CM pathogenesis and may inform future therapeutic strategies.