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    BIOMARKER:

    14-gene IGG signature

    almost2years
    Application of a machine learning model for identifying an ultra-low risk group of early breast cancer patients (ESMO-BC 2024)
    Conclusions We developed and validated a clinically feasible machine learning model for early-stage luminal BC, integrating gene expression and clinical data, that identified a larger ultra-low risk population than currently achieved by commercial tools. Further studies are needed to validate its analytical accuracy and clinical utility.
    Clinical • Machine learning
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    HER-2 (Human epidermal growth factor receptor 2) • ER (Estrogen receptor)
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    HER-2 negative • 14-gene IGG signature
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    Prosigna™ Breast Cancer Prognostic Gene Signature Assay • MammaPrint® • Oncotype DX Breast Recurrence Score®Test