ArticleBreast cancer research and treatment2022
A triple-negative breast cancer surrogate subtype classification that correlates with gene expression subtypes.
Article in Breast cancer research and treatment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Molecular subtyping and target identification in triple negative breast cancer through immunohistochemistry biomarkers.BMC cancer · 2025Article
- p16 Immunohistochemical Patterns in Triple-Negative Breast Cancer: Clinical and Genomic Similarities of the p16 Diffuse Pattern to pRB Deficiency.Pathobiology : journal of immunopathology, molecular and cellular biology · 2025Article
- Triple-Negative Breast Cancer Subclassified by Immunohistochemistry: Correlation with Clinical and Pathological Outcomes in Patients Receiving Neoadjuvant Chemotherapy.International journal of molecular sciences · 2024Article
- Luminal androgen receptor subtype and tumor-infiltrating lymphocytes groups based on triple-negative breast cancer molecular subclassification.Scientific reports · 2024Article
- Triple-negative breast cancer: from none to multiple therapeutic targets in two decades.Frontiers in oncology · 2023Review
- Article
- Molecular Classification, Treatment, and Genetic Biomarkers in Triple-Negative Breast Cancer: A Review.Technology in cancer research & treatmentReview
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Abstract
backgroundThis study developed a triple-negative breast cancer (TNBC) surrogate subtype classification that represents TNBC subtypes based on the Vanderbilt subtype classification.
methodsPatients who underwent primary curative surgery for TNBC were included. Representative FFPE blocks were used for gene expression analysis and tissue microarray construction for immunohistochemical (IHC) staining. The Vanderbilt subtypes were re-classified into four groups: basal-like (BL), mesenchymal-like (M), immunomodulatory (IM) and luminal androgen receptor (LAR) subtype. Classification and regression tree (CART) modeling was applied to develop a surrogate subtype classification.
resultsA total of 145 patients were included. The study cohort was allocated to the Vanderbilt 4 subtypes as LAR (n = 22, 15.2%), IM (n = 32, 22.1%), M (n = 38, 26.2%), BL (n = 25, 17.2%) and unclassified (n = 28, 19.3%). After excluding nine (6.2%) patients due to poor IHC staining quality, CART modeling was performed. TNBC surrogate subtypes were defined as follows: LAR subtype, androgen receptor Allred score 8; IM subtype, LAR-negative with a tumor-infiltrating lymphocyte (TIL) score > 70%; M subtype, LAR-negative with a TIL score < 20%; BL subtype, LAR-negative with a TIL score 20-70% and diffuse, strong p16 staining. The study cohort was classified by the surrogate subtypes as LAR (n = 26, 17.9%), IM (n = 21, 14.5%), M (n = 44, 30.3%), BL1 (n = 27, 18.6%) and unclassified (n = 18, 12.4%). Surrogate subtypes predicted TNBC Vanderbilt 4 subtypes with an accuracy of 0.708.
conclusionWe have developed a TNBC surrogate subtype classification that correlates with the Vanderbilt subtype. It is a practical and accessible diagnostic test that can be easily applied in clinical practice.
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