Breast Cancer Subtype Classification Using 4-Plex Droplet Digital PCR

Abstract BACKGROUND Infiltrating ductal carcinoma (IDCA) is the most common form of invasive breast cancer. Immunohistochemistry (IHC) is widely used to analyze estrogen receptor 1 (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) that can help classify the tumor to guide the medical treatment. IHC examinations require experienced pathologists to provide interpretations that are subjective, thereby lowering the reproducibility of IHC-based diagnosis. In this study, we developed a 4-plex droplet digital PCR (ddPCR) for the simultaneous and quantitative analyses of estrogen receptor 1 (ESR1), progesterone receptor (PGR), erb-b2 receptor tyrosine kinase 2 (ERBB2), and pumilio RNA binding family member 1 (PUM1) expression levels in formalin-fixed paraffin-embedded (FFPE) samples. METHODS We evaluated the sensitivity, reproducibility, and linear dynamic range of 4-plex ddPCR. We applied this method to analyze 95 FFPE samples from patients with breast IDCA and assessed the agreement rates between ddPCR and IHC to evaluate its potential in classifying breast cancer subtypes. RESULTS The limits of quantification (LOQ) were 25, 50, 50, and 50 copies per reaction for ERBB2, ESR1, PGR, and PUM1, respectively. The dynamic ranges of ESR1, PGR, and PUM1 extended over 50–1600 copies per reaction and those of ERBB2 from 25 to 1600 copies per reaction. The concordance correlation coefficients between 4-plex ddPCR and IHC were 96.8%, 91.5%, and 85.1% for ERBB2, ESR1, and PGR, respectively. Receiver operating characteristic curve area under the curve values of 0.991, 0.977, and 0.920 were generated for ERBB2, ESR1, and PGR, respectively. CONCLUSIONS Evaluation of breast cancer biomarker status by 4-plex ddPCR was highly concordant with IHC in this study.