Genomic Landscape and Therapeutic Implications of Metaplastic Breast Carcinoma: Insights from a Nationwide Database Including Diagnostic Mimickers

Background/Objectives: Metaplastic breast carcinoma (MpBC) is a rare and aggressive malignancy characterized by significant histological heterogeneity and limited response to standard chemotherapy. Due to its morphological diversity, MpBC often presents diagnostic challenges and can overlap with other mesenchymal tumors. This study aimed to characterize the genomic landscape of MpBC using a nationwide Japanese database and to explore the molecular basis of its diagnostic ambiguities and therapeutic responses. Methods: We retrospectively analyzed genomic and clinical data from 123 MpBC cases registered in the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database. To evaluate diagnostic boundaries, genomic profiles of histological mimickers, including 19 cases of angiosarcoma and eight cases of myoepithelial carcinoma, were also examined. Furthermore, an exploratory single-cell RNA-sequencing analysis was performed on 3274 cells from independent MpBC datasets to investigate cellular heterogeneity and potential lineage plasticity. Results: TP53 (73.2%) and PIK3CA (46.0%) were the most prevalent genomic alterations in the MpBC cohort. Exploratory analysis suggested that PIK3CA mutations may be associated with an improved disease control rate in patients receiving taxane-based therapy (p = 0.028). Comparisons with mimickers identified distinctive molecular signatures, such as MED12 and HRAS hotspot mutations, across entities. Single-cell transcriptomics identified a distinct subpopulation (7.02% of malignant cells) co-expressing epithelial and phyllodes-like signatures. Conclusions: These findings suggest that MpBC harbors hybrid malignant cell populations that may contribute to its complex morphological diversity. While the therapeutic associations are based on a limited cohort and require prospective validation, the integration of comprehensive genomic and single-cell profiling provides an exploratory framework that may potentially enhance diagnostic accuracy in the future. However, these associations remain preliminary and require prospective validation to confirm their clinical utility.