Abstract
Context.— Breast cancers (BCs) with low levels of human epidermal growth factor receptor 2 (HER2) expression (HER2-low) have become a targetable subset because of novel antibody-drug conjugates. HER2 immunohistochemistry (IHC) is the recommended assay for HER2 classification but is associated with limited interobserver agreement concerning HER2-low identification. Objective.— To investigate whether mRNA expression quantified via quantitative reverse transcription–polymerase chain reaction (RT-qPCR) could serve as a valuable complementary and more objective method to identify HER2-low BCs. Design.— We selected all cases from a previously published interobserver study, which included 105 needle biopsies from HER2 nonamplified BC cases. HER2 IHC was evaluated by 16 pathologists. For the current study, mRNA was extracted from microdissected invasive tumor cells. RT-qPCR was performed for quantitative evaluation of HER2, using the cutoff values of the MammaTyper assay. We compared the mRNA expression levels with the IHC scores of the majority agreement (IHC 0, IHC >0, <1+ [ultralow], 1+, 2+) and the following HER2 subcategories: HER2 0/ultralow and HER2-low (IHC 1+ and 2+/fluorescence in situ hybridization negative). Results.— In total, 88 nonamplified HER2 cases could be analyzed. Based on IHC, 17 cases were HER2 0/ultralow and 71 were HER2-low. The mean rank HER2 mRNA level was significantly higher in HER2-low cases than in the HER2 0/ultralow group (P < .001). However, 10 of 17 HER2 0/ultralow cases by IHC (58.8%) were classified as HER2-low by MammaTyper, 2 of 71 cases (2.8%) were HER2-low by IHC and HER2 0/ultralow by MammaTyper, and 2 (2.8%) were HER2-low by IHC and HER2-positive by RP-qPCR. Conclusions.— Our findings indicate a strong agreement between mRNA expression quantified by RT-qPCR and HER2 IHC scores, although there was a substantial proportion of discordant HER2 results between both methods owing to overestimation of HER2 expression by MammaTyper compared to IHC. Future large-scale trials should determine which technique is best associated with clinical outcome.
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