Defining breast cancer intrinsic subtypes by quantitative receptor expression
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Updated: Apr 14, 2026
Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
Published on: August 1, 2018
Maggie C U Cheang1, Miguel Martin1, Torsten O Nielsen1
1Lineberger Comprehensive Cancer Center and Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA; Clinical Trials and Statistics Unit at The Institute of Cancer Research, London, United Kingdom; Servicio de Oncología Médica, Instituto de Investigacion Sanitaria Hospital Universitario Gregorio Marañón, Facultad de Medicina, Universidad Complutense, Madrid, Spain; Department of Pathology, University of British Columbia, Vancouver, British Columbia, Canada; Translation Genomics Unit, Vall d´Hebron Institute of Oncology, Barcelona, Spain; British Columbia Cancer Agency, Vancouver, British Columbia, Canada; Department of Medical Oncology, Hospital General Universitario de Elche, Alicante, Spain; Department of Medical Oncology, Instituto Valenciano de Oncologia, Valencia, Spain; National Cancer Institute of Canada Clinical Trials Group, Kingston, Ontario, Canada; Department of Medical Oncology, Hospital Universitario Virgen del Rocio, Seville, Spain; Department of Medical Oncology, Complejo Hospitalario Universitario A Coruña, Coruña, Spain; Department of Medical Oncology, Hospital Universitario Virgen de la Victoria, Málaga, Spain; GEICAM, Madrid, Spain; Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, Ontario, Canada; McMaster University, Hamilton, Ontario, Canada; Department of Oncology, Tom Baker Cancer Centre, University of Calgary, Calgary, Alberta, Canada; Department of Pathology, University of Utah Health Sciences Center, Salt Lake City, Utah, USA; Department of Medicine, Washington University, St. Louis, Missouri, USA; Department of Oncology, Hospital of Prato, Istituto Toscani Tumori, Florence, Italy.
Purpose:
To determine intrinsic breast cancer subtypes represented within categories defined by quantitative hormone receptor (HR) and HER2 expression.
Methods:
We merged 1,557 cases from three randomized phase III trials into a single data set. These breast tumors were centrally reviewed in each trial for quantitative ER, PR, and HER2 expression by immunohistochemistry (IHC) stain and by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), with intrinsic subtyping by research-based PAM50 RT-qPCR assay.
Results:
Among 283 HER2-negative tumors with <1% HR expression by IHC, 207 (73%) were basal-like; other subtypes, particularly HER2-enriched (48, 17%), were present. Among the 1,298 HER2-negative tumors, borderline HR (1%-9% staining) was uncommon (n = 39), and these tumors were heterogeneous: 17 (44%) luminal A/B, 12 (31%) HER2-enriched, and only 7 (18%) basal-like. Including them in the definition of triple-negative breast cancer significantly diminished enrichment for basal-like cancer (p < .05). Among 106 HER2-positive tumors with <1% HR expression by IHC, the HER2-enriched subtype was the most frequent (87, 82%), whereas among 127 HER2-positive tumors with strong HR (>10%) expression, only 69 (54%) were HER2-enriched and 55 (43%) were luminal (39 luminal B, 16 luminal A). Quantitative HR expression by RT-qPCR gave similar results. Regardless of methodology, basal-like cases seldom expressed ER/ESR1 or PR/PGR and were associated with the lowest expression level of HER2/ERBB2 relative to other subtypes.
Conclusion:
Significant discordance remains between clinical assay-defined subsets and intrinsic subtype. For identifying basal-like breast cancer, the optimal HR IHC cut point was <1%, matching the American Society of Clinical Oncology and College of American Pathologists guidelines. Tumors with borderline HR staining are molecularly diverse and may require additional assays to clarify underlying biology.
