Dissecting the immune suppressive human prostate tumor microenvironment via integrated single-cell and spatial transcriptomic analyses
The treatment of low-risk primary prostate cancer entails active surveillance only, while high-risk disease requires multimodal treatment including surgery, radiation therapy, and hormonal therapy. Recurrence and development of metastatic disease remains a clinical problem, without a clear understan...
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Veröffentlicht in: | NATURE COMMUNICATIONS 2023-02, Vol.14 (1), p.663-663, Article 663 |
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Hauptverfasser: | , , , , , , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The treatment of low-risk primary prostate cancer entails active surveillance only, while high-risk disease requires multimodal treatment including surgery, radiation therapy, and hormonal therapy. Recurrence and development of metastatic disease remains a clinical problem, without a clear understanding of what drives immune escape and tumor progression. Here, we comprehensively describe the tumor microenvironment of localized prostate cancer in comparison with adjacent normal samples and healthy controls. Single-cell RNA sequencing and high-resolution spatial transcriptomic analyses reveal tumor context dependent changes in gene expression. Our data indicate that an immune suppressive tumor microenvironment associates with suppressive myeloid populations and exhausted T-cells, in addition to high stromal angiogenic activity. We infer cell-to-cell relationships from high throughput ligand-receptor interaction measurements within undissociated tissue sections. Our work thus provides a highly detailed and comprehensive resource of the prostate tumor microenvironment as well as tumor-stromal cell interactions.
The immune suppressive tumour microenvironment drives recurrence and metastatic disease in prostate cancer. Here authors provide a detailed analysis of the microenvironment via single cell RNA sequencing and high-resolution spatial transcriptomics to identify tumour-dependent changes compared to healthy tissue. |
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ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-023-36325-2 |