Abstract

Breast cancer is the commonest cause of cancer-related mortality in African females where patients often present later and with advanced disease. Causes for delayed diagnosis include restricted diagnostic access and international controversy on interpretation of ancillary tests like immunohistochemistry (IHC). Fine needle aspirates (FNAC) are an attractive alternative although may have reduced sensitivity. The Xpert Breast Cancer STRAT4 (STRAT4) (CE-IVD*) assay (Cepheid, Sunnyvale) is a semi-quantitative reverse-transcription polymerase chain reaction assay which detects messenger RNA (mRNA) expression in breast samples for estrogen receptor ( ESR1 ), progesterone receptor ( PGR1 ), human epidermal growth factor receptor/Erb-B2 receptor tyrosine kinase 2 (HER2/ ERBB2 ) and the proliferation marker, MKi67 . We assessed the performance of this assay on both formalin-fixed paraffin-embedded (FFPE, n=31) and matched FNAC (n=20) samples from patients presenting with breast cancer to the Johannesburg academic hospitals. IHC and Fluorescent in situ hybridization analysis (performed on HER2-indeterminate samples) was compared with the mRNA expression of the corresponding target genes in FFPE samples, and mRNA expression on FNAC samples was compared with the FFPE results for both mRNA expression and IHC. Concordance between IHC/FISH and Xpert Breast Cancer STRAT4 in FFPE and FNAC samples using the Quick lysis (Q) method (a research-use-only modification of the validated FFPE-lysis method), showed an overall percentage agreement for ESR1 expression of 90.3% and 81.3%, and for PGR1 expression at 86.7% and 81.3% respectively in FFPE and FNAC samples. Concordance was lowest for Ki67 expression, using a binary IHC cutoff for Ki67 positivity at ≥20% staining) at 83.9% and 62.5%, for FFPE and FNAC samples, respectively. This suggests that the STRAT4 assay may be a useful ancillary test in determining HR and Ki67 status in FFPE samples and that use on FNAC samples may be feasible. Future studies should expand the sample numbers and establish locally relevant cutoffs.

Full Text
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