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Journal Article Ppublish 4 citations

PubMed: 40482645 DOI: 10.1016/j.xcrm.2025.102164

Spatial and genomic profiling of residual breast cancer after neoadjuvant chemotherapy unveil divergent fates for each breast cancer subtype.

Cell Rep Med 6(6):102164

Authors: Eun Seop Seo, Sabin Park, Eun Yoon Cho, Jeong Eon Lee, Hae Hyun Jung, Jiyeon Hyeon, Sepil An, Seok Won Kim, Junghoon Shin, Jin Seok Ahn, Yeon Hee Park, Young-Hyuck Im, Hoon Kim, Semin Lee, Woong-Yang Park, Ji-Yeon Kim

Affiliations

  • Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology, Seoul 06355, Republic of Korea; Geninus Inc. Seoul 05836, Republic of Korea.
  • Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea.
  • Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea.
  • Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Seoul 06355, Republic of Korea.
  • Biomedical Research Institute, Samsung Medical Center, Seoul 06351, Republic of Korea.
  • Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea.
  • Department of Biopharmaceutical Convergence, School of Pharmacy, Sungkyunkwan University, Suwon-si, Gyeonggi-do 16419, Republic of Korea.
  • Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea.
  • Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Seoul 06355, Republic of Korea; Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea.
  • Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Seoul 06355, Republic of Korea; Biomedical Research Institute, Samsung Medical Center, Seoul 06351, Republic of Korea; Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea.
  • Department of Biopharmaceutical Convergence, School of Pharmacy, Sungkyunkwan University, Suwon-si, Gyeonggi-do 16419, Republic of Korea; Department of Biohealth Regulatory Science, School of Pharmacy, Sungkyunkwan University, Suwon-si, Gyeonggi-do 16419, Republic of Korea; Epigenome Dynamics Control Research Center, Sungkyunkwan University, Suwon-si, Gyeonggi-do 16419, Republic of Korea.
  • Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea.
  • Geninus Inc. Seoul 05836, Republic of Korea; Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Seoul 06355, Republic of Korea; Translational Genomics Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon, Gyeonggi-do 16419, Republic of Korea.
  • Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology, Seoul 06355, Republic of Korea; Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Seoul 06355, Republic of Korea; Biomedical Research Institute, Samsung Medical Center, Seoul 06351, Republic of Korea; Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea.

Abstract

Residual cancer burden (RCB) is a strong prognostic marker after neoadjuvant chemotherapy (NAC) in breast cancer (BC), yet some BCs defy their predicted outcomes. Using single-cell spatial transcriptomics and genomic profiling, we investigate mechanisms underlying divergent fates of BCs with high RCB across subtypes. In triple-negative BC (TNBC), CXCL9+ macrophage-CD8 + T cell interactions via chemokines and interferon-gamma signaling promote favorable outcomes, while SPP1+ macrophage-cancer cell interactions driven by hypoxia signaling correlate with poor prognosis. In non-TNBC, the extent of basal-like cancer cells and their proximity to scarce immune cells are linked to prognosis. Additionally, tumor-intrinsic features-such as homologous recombination deficiency in hormone receptor (HR)-positive cancers and structural variations, including extrachromosomal ERBB2 DNA in human epidermal growth factor receptor 2 (HER2)-positive cancers-predict worse outcomes. This study highlights distinct genomic and microenvironmental strategies governing BC subtype-specific fates after NAC.

MeSH

Interferon-Gamma, Cells, Breast Neoplasms, Macrophages, Neoplasms, Drug Therapy, Cell Communication, Breast, Neoadjuvant Therapy, Prognosis, Chemotherapy, Spatial Transcriptomics

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