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Updated: Sep 3, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
High-definition spatial transcriptomics visualizes the cellular and molecular architecture underlying perineural
Paul Vinu Salachan1,2, Line Raaby1,2,3, Jacob Fredsøe1,2
1Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Abstract:
Distinguishing indolent from aggressive tumors remains a key challenge in the clinical management of prostate cancer (PC), highlighting the need for better tools for accurate risk stratification. A defining feature of aggressive PC is its propensity for perineural invasion (PNI), a pathological finding that is associated with poor prognosis. Despite its clinical significance, very little is known about the spatial and molecular determinants of PNI in PC. To address this, we used high-definition spatial transcriptomics (Visium HD) to profile the PNI-associated tumor microenvironment (TME) of a representative PC patient at near single-cell resolution. Spatial mapping of the expressed genes and inferred cell types revealed transcriptionally divergent malignant cell states spatially linked to PNI within this patient. Nerve-invasive PC cells were organized within a distinct spatially localized niche that exhibited altered TME characteristics, including increased proportions of macrophages, CD4 T-cells, and endothelial cells, suggesting coordinated changes in the tumor- and immune microenvironments. The PNI-associated niche in this patient further displayed enrichment of pathways involved in immune regulation and extracellular matrix remodeling, consistent with PNI-associated niche remodeling. APP-CD74 was identified as a potential signaling axis associated with tumor-nerve, nerve-macrophage, and nerve-endothelial cell interactions, suggesting PNI in this patient may be associated with distinct microenvironmental signaling programs. We further revealed a PNI-associated PC signature that held biomarker potential at the early-localized and advanced-metastatic disease stages. Although based on a single patient, these results contribute to our understanding of the spatial and molecular features of PNI in PC and may help guide personalized treatment choices for PC patients in the future.
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