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Original Article
Spatial Transcriptomic Landscape of Brain Metastases from Triple-Negative Breast Cancer: Comparison of Primary Tumor and Brain Metastases Using Spatial Analysis
Jihwan Yoo1orcid , Inho Park2orcid , Hyun Jung Kim3orcid , Hun Ho Park1, Sora Lee3, Jee Hung Kim4,5orcid , Yoon Jin Cha2,5orcid

DOI: https://doi.org/10.4143/crt.2025.033 [Accepted]
Published online: April 15, 2025
1Department of Neurosurgery, Brain Tumor Center, Gangnam Severance Hospital, Yonsei University, College of Medicine, Seoul, Korea
2Department of Pathology, Gangnam Severance Hospital, Yonsei University, College of Medicine, Seoul, Korea
3Department of Anatomy, Korea University College of Medicine, Seoul, Korea
4Department of Medical Oncology, Gangnam Severance Hospital, Yonsei University, College of Medicine, Seoul, Korea
5Institute for Breast Cancer Precision Medicine, Yonsei University College of Medicine, Seoul, Korea
Corresponding author:  Jee Hung Kim
Tel: 02-2019-3305 
Email: ok8504@yuhs.ac
Yoon Jin Cha
Tel: 02-2019-3540 
Email: yooncha@yuhs.ac
Jihwan Yoo, Inho Park and Hyun Jung Kim contributed equally to this work.
Received: 8 January 2025   • Accepted: 13 April 2025
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Purpose
Triple-negative breast cancer (TNBC) is a particularly aggressive subtype of breast cancer, with approximately 30% of patients eventually developing brain metastases (BM), which result in poor outcomes. An understanding of the tumor microenvironment (TME) at both primary and metastatic sites offers insights into the mechanisms underlying BM and potential therapeutic targets.
Materials and Method
Spatial RNA sequencing (spRNA-seq) was performed on primary TNBC and paired BM tissues from three patients, one of whom had previously received immune checkpoint inhibitors before BM diagnosis. Specimen regions were categorized into tumor, proximal, and distal TME based on their spatial locations. Gene expression differences across these zones were analyzed, and immune cell infiltration was estimated using TIMER. A gene module analysis was conducted to identify key gene clusters associated with BM.
Results
Distinct gene expression profiles were noted in the proximal and distal TMEs. In BM, the proximal TME exhibited neuronal gene expression, suggesting neuron-tumor interactions compared to tumor, and upregulation of epithelial genes compared to the distal TME. Immune cell analysis revealed dynamic changes in CD8+ T cells and macrophages across the tumor and TME zones. Gene module analysis identified five key modules, including one related to glycolysis, which correlated with patient survival. Drug repurposing analysis identified potential therapeutic targets, including VEGFA, RAC1, EGLN3, and CAMK1D.
Conclusion
This study provides novel insights into the transcriptional landscapes in TNBC BM using spRNA-seq, emphasizing the role of neuron-tumor interactions and immune dynamics. These findings suggest new therapeutic strategies and underscore the importance of further research.

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