A REVIEW ON IDENTIFYING THE TUMOR MICROENVIRONMENT THROUGH SPATIAL TRANSCRIPTOMICS: INSIGHTS, CHALLENGES, APPLICATIONS AND ADVANCEMENTS

As a tumor develops, the cancer cells come into contact with different types of normal cells (non-cancer cells), but it's not obvious how tumours change to fit in with these new surroundings. Tumor microenvironment describes about what type of cells presents near and surrounding the tumor. The tumor microenvironment consists of structural components, such as the extracellular matrix, together with various supportive cell types. These include stromal fibroblasts, fat cells, endothelial cells, and a wide range of immune populations, for example T and B lymphocytes, natural killer cells, dendritic cells, macrophages, myeloid-derived suppressor cells, and lymphatic cells. The tumour microenvironment (TME) influences metastasis and responsiveness to treatment, making it a crucial component of cancer progression. The tumour microenvironment (TME) can be better understood with spatial transcriptomics (ST). ST makes it possible to quantify and visualize the gene expression patterns that are present within the spatial context of tissues, especially cancer cells and the environment. As the traditional single cell sequencing (scRNA) technique that is next generation sequencing (NGS) profiling is based on bulk approaches that lack spatial context. We can now obtain spatial information by capturing tumour diversity and multifocality. By using the ST we can plan the cancer treatment, prevent the cancer progression and drug resistance. This article explains about the techniques that are used in identifying the TME, insights, challenges and their applications in the cancer.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-01
DOI
https://doi.org/10.5281/zenodo.19875042
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

A REVIEW ON IDENTIFYING THE TUMOR MICROENVIRONMENT THROUGH SPATIAL TRANSCRIPTOMICS: INSIGHTS, CHALLENGES, APPLICATIONS AND ADVANCEMENTS

Dr. D. Swarnalatha1*, Chittanoori Varsha2, Gundala Anu3, Ravilla Varshini Sree4, Kalyani Vanarasi5
Zenodo (CERN European Organization for Nuclear Research)
Single-cell and spatial transcriptomics
article

A REVIEW ON IDENTIFYING THE TUMOR MICROENVIRONMENT THROUGH SPATIAL TRANSCRIPTOMICS: INSIGHTS, CHALLENGES, APPLICATIONS AND ADVANCEMENTS

Dr. D. Swarnalatha1*, Chittanoori Varsha2, Gundala Anu3, Ravilla Varshini Sree4, Kalyani Vanarasi5
article en

Abstract

As a tumor develops, the cancer cells come into contact with different types of normal cells (non-cancer cells), but it's not obvious how tumours change to fit in with these new surroundings. Tumor microenvironment describes about what type of cells presents near and surrounding the tumor. The tumor microenvironment consists of structural components, such as the extracellular matrix, together with various supportive cell types. These include stromal fibroblasts, fat cells, endothelial cells, and a wide range of immune populations, for example T and B lymphocytes, natural killer cells, dendritic cells, macrophages, myeloid-derived suppressor cells, and lymphatic cells. The tumour microenvironment (TME) influences metastasis and responsiveness to treatment, making it a crucial component of cancer progression. The tumour microenvironment (TME) can be better understood with spatial transcriptomics (ST). ST makes it possible to quantify and visualize the gene expression patterns that are present within the spatial context of tissues, especially cancer cells and the environment. As the traditional single cell sequencing (scRNA) technique that is next generation sequencing (NGS) profiling is based on bulk approaches that lack spatial context. We can now obtain spatial information by capturing tumour diversity and multifocality. By using the ST we can plan the cancer treatment, prevent the cancer progression and drug resistance. This article explains about the techniques that are used in identifying the TME, insights, challenges and their applications in the cancer.

Zenodo (CERN European Organization for Nuclear Research)
Good health and well-being
Openalex Percentile: Top 7%
Single-cell and spatial transcriptomics
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