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  • Title: Concordance between ER, PR, Ki67, and HER2-low expression in breast cancer by MammaTyper RT-qPCR and immunohistochemistry: implications for the practising pathologist.
    Author: Badr NM, Zaakouk M, Zhang Q, Kearns D, Kong A, Shaaban AM.
    Journal: Histopathology; 2024 Sep; 85(3):437-450. PubMed ID: 38651302.
    Abstract:
    BACKGROUND: There are limited data on the role of multigene tests and their correlation with immunohistochemistry (IHC), especially on core biopsy. MammaTyper is a quantitative conformite Europeeanne (CE) marked, National Institute for Health and Care excellence (NICE) approved, in in vitro diagnostic quantitative real-time polymerase chain reaction (RT-qPCR) test for assessment of mRNA expression of four biomarkers (ESR1, PGR, ERBB2, MKI67). METHODS: We evaluated the concordance of MammaTyper with oestrogen receptor (ER), progesterone receptor (PR), HER2, and Ki67 by IHC on 133 core needle biopsies of breast cancer. HER2 was positive if IHC 3+ or 2+ and fluorescence in situ hybridization (FISH)-amplified. Global and hotspot Ki67 expression was analysed using a cutoff of ≥20% assessed manually and by digital image analysis. Agreements were expressed as overall percent agreement (OPA), positive percent agreement (PPA), negative percent agreement (NPA), and Cohen's kappa. RESULTS: RT-qPCR results of ESR1 were highly concordant with IHC with OPA of 94.7% using 1% cutoff and 91.7% when the low ER-positive category was included. The PPA and NPA between RT-qPCR and IHC for PR was 91.5% and 88.0%, respectively, when using the 1% cutoff. For ERBB2/HER2, the OPA was 95% and the PPA was 84.6%. 40 of 72 HER2 IHC score 0 tumours were classified as ERBB2 low. Best concordance between MKI67 by MammaTyper and Ki67 IHC was achieved using hotspot digital image analysis (OPA: 87.2%, PPA: 90.6%, NPA: 80%). CONCLUSION: RT-qPCR-based assessment of the mRNA expression of ESR1, PGR, ERBB2, and MKI67 showed high concordance with IHC, suggesting that the MammaTyper test on core needle biopsies represents a reliable, efficient, and reproducible alternative for breast cancer classification and refining HER2 low categorisation.
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