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Clinical implications of intrinsic molecular subtypes of breast cancer for sentinel node status

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  3. Using machine learning for predicting intensive care unit resource use during the COVID-19 pandemic in Denmark

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  3. Highly impaired platelet ultrastructure in two families with novel IKZF5 variants

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  4. Multiple endocrine neoplasia type 1 (MEN-1) and neuroendocrine neoplasms (NENs)

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Axillary lymph node status is an important prognostic factor for breast cancer patients and sentinel lymph node biopsy (SLNB) is a less invasive surgical proxy. We examined if consecutively derived molecular subtypes from primary breast cancers provide additional predictive value for SLNB status. 1556 patients with a breast cancer > 10 mm underwent primary surgical procedure including SLNB and tumor specimens were assigned with a transcriptomics-based molecular subtype. 1020 patients had a negative sentinel node (SN) and 536 a positive. A significant association between tumor size and SN status (p < 0.0001) was found across all samples, but no association between size and SN status (p = 0.14) was found for BasL tumors. A BasL subtype was a predictor of an SN-negative status (p = 0.001, OR 0.58, 95% CI 0.38;0.90) and among the BasL, postmenopausal status was a predictor for SN-negative status (p = 0.01). Overall survival was significantly lower (p = 0.02) in patients with BasL tumors and a positive SN. Interestingly, we identified a significant correlation between hormone receptor activity and SN status within the BasL subtype. Taken together, molecular subtypes and hormone receptor activity of breast cancers add predictive value for SLNB status.

Original languageEnglish
Article number2259
JournalScientific Reports
Volume11
Issue number1
Pages (from-to)2259
ISSN2045-2322
DOIs
Publication statusPublished - 26 Jan 2021

    Research areas

  • BRCA1 Protein/metabolism, BRCA2 Protein/metabolism, Breast Neoplasms/classification, Cohort Studies, Female, Humans, Logistic Models, Menopause, Principal Component Analysis, Receptors, Estrogen/metabolism, Sentinel Lymph Node/pathology, Survival Analysis, Tumor Burden

ID: 66207053