Spatial transcriptomics: Visualising tumor biology

What is Spatial Transcriptomics, and Why Does It Matter?


Traditional gene expression methods like bulk or single-cell RNA sequencing offer transcriptomic data but lose spatial context. Yet in solid tumors—especially in urology, this information is crucial, as architecture and microenvironment influence behaviour, progression, and treatment response.

Spatial transcriptomics bridges molecular biology and histopathology by mapping RNA expression onto tissue sections. Platforms like 10x Genomics CytAssist Visium or Visium HD enable spatial localization of gene activity with preserved morphology, letting us see not only what genes are active but also where. (Figure 1)

In prostate and kidney cancers, where heterogeneity and resistance are major challenges, spatial transcriptomics is a powerful tool to uncover tumor biology and guide personalized management. Our group has been applying this approach to explore the pathobiology of urologic tumors—including their tumor microenvironment—through spatially resolved transcriptomic analysis.

Clinical Examples Across Urologic Cancers (Figure 2)

(a) Prostate Cancer – NEPC and IDC-P
In de novo neuroendocrine prostate cancer (NEPC), spatial transcriptomics revealed distinct gene clusters and immune-desert microenvironments. These “cold” areas showed minimal T-cell infiltration and unique signatures, helping explain resistance to immunotherapy.(1)

In intraductal carcinoma of the prostate (IDC-P), spatial mapping revealed isolated clusters expressing hypoxia-related genes (HIF1A, BNIP3L) and reduced immune/fibroblast access. High expression of MUC6 and MYO16 supported its high-grade and treatment-refractory nature.(2)

(b) Renal Cell Carcinoma – PSMA-positive Vasculature
PSMA, known from prostate cancer, was found in tumor-associated vasculature of clear cell RCC. Spatial analysis showed FOLH1 expression in endothelial, not tumor, cells. This may expand PSMA-targeted imaging and therapy into kidney cancer.(3)

(c) TSC-associated Angiomyolipoma (AML)
TSC-associated AMLs differ from sporadic forms in behavior and molecular features. Spatial transcriptomics revealed enriched expression of lipid metabolism (FABP4, APOC1), neural lineage (GRIA2, ASTN1), and immune-modulating genes (IL33), reflecting a unique mTOR-driven tumor environment.

Future Directions – From Research to Routine Practice
As spatial transcriptomics becomes more accessible, it may soon support diagnostics, especially in histologically ambiguous or therapy-resistant cases. Spatial gene panels could inform treatment planning and risk assessment.

Combining spatial transcriptomics with other omics—such as proteomics or single-cell data—may offer a fuller view of tumor biology. This approach could identify novel targets and mechanisms of resistance.(4)

By showing not only what genes are expressed, but where they act, spatial transcriptomics is reshaping our understanding of urologic cancer and bringing precision oncology into sharper focus. by Dr Ryuta Watanabe, Ehime University Hospital, Japan