Publication | Open Access
Dissecting the immune suppressive human prostate tumor microenvironment via integrated single-cell and spatial transcriptomic analyses
206
Citations
75
References
2023
Year
EngineeringImmunologyImmunotherapySpatial OmicsTumor BiologyTumor HeterogeneitySingle Cell SequencingMolecular DiagnosticsRadiation OncologyImmune EscapeSpatial Transcriptomic AnalysesSingle-cell Rna SequencingSpatial TranscriptomicsIntegrated Single-cellProstatic DiseaseGene ExpressionSingle-cell AnalysisCell BiologyTumor MicroenvironmentCancer GenomicsSystems BiologyMedicine
Prostate cancer treatment ranges from active surveillance for low‑risk disease to multimodal therapy for high‑risk cases, yet recurrence and metastasis remain problematic due to unclear mechanisms of immune escape and tumor progression. The study aims to comprehensively characterize the tumor microenvironment of localized prostate cancer relative to adjacent normal tissue and healthy controls. The authors employed single‑cell RNA sequencing and high‑resolution spatial transcriptomics, coupled with ligand–receptor interaction analysis, to map cell–cell relationships and gene expression changes within undissociated tissue sections. The analyses reveal an immune‑suppressive microenvironment dominated by suppressive myeloid cells and exhausted T cells, alongside heightened stromal angiogenic activity, providing a detailed resource of prostate tumor–stroma interactions.
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.
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