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Spatial Transcriptomic Profiling Reveals Gene Expression Characteristics in Lymph Node-positive Breast Carcinoma

  • Kangbuk Samsung Hospital

Research output: Contribution to journalArticlepeer-review

Abstract

Background/Aim: Studies on the differences in gene expression characteristics according to lymph node metastasis in breast carcinoma are lacking. This study aimed to compare the spatially resolved transcriptomic profiles between node-positive and negative breast carcinomas. Patients and Methods: Eight patients with breast carcinoma were included, and digital spatial profiling and bioinformatic analysis were conducted to investigate the spatial transcriptomes. Results: In the epithelial compartment, the top two most up-regulated genes were nuclear receptor subfamily 4 group A member 1 (NR4A1) and Jun proto-oncogene, activating protein-1 transcription factor subunit (JUN). The gene ontology (GO) enrichment analysis of the node-positive group revealed a significant up-regulation of genes associated with myeloid differentiation, mononuclear cell differentiation, and hematopoietic regulation. The gene set enrichment analysis (GSEA) revealed significant enrichment of gene sets associated with the regulation of inflammatory cytokines in both the epithelial and stromal compartments of the node-positive group. Conclusion: Our study highlights significant differences in gene expression profiles and spatially resolved transcriptional activities between node-positive and negative breast carcinomas. These findings underscore the importance of developing personalized treatment strategies for lymph node metastasis of breast carcinoma.

Original languageEnglish
Pages (from-to)3381-3395
Number of pages15
JournalAnticancer Research
Volume44
Issue number8
DOIs
StatePublished - Aug 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Breast
  • invasive carcinoma
  • lymph node metastasis
  • spatial transcriptomics
  • tumor microenvironment

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