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Recently, clinical trials have demonstrated promising efficacy for novel HER2-targeted therapies in HER2-low breast cancers, raising the prospect of including a HER2-low category (immunohistochemical [IHC] score of 1+, or 2+ with non-amplified in-situ hybridization [ISH]) in the HER2 evaluation of breast cancers. In order to better understand this newly-proposed HER2 category, we investigated the incidence, HER2 staining patterns, clinicopathologic features, and genomic profile of HER2-low breast cancers. HER2-stained slides of 281 consecutive breast cancers were re-reviewed and the clinicopathologic information, MammaPrint, and BluePrint results of these cases were retrospectively analyzed. HER2-low breast cancers were identified in 31% of cases and were more common in estrogen receptor (ER)-positive than ER-negative breast cancers (33.6% vs 15%, p = 0.017). HER2-low cancers were generally clinical stages I-II (79%), ER-positive (93.1%), had homogenous HER2 staining (59.2%), HER2 IHC score of 1+ (87.4%), ductal phenotype (81.6%), histologic grades of 1 or 2 (94.2%) and luminal molecular subtypes (94.3%). Three HER2-low patients received neoadjuvant chemotherapy and none of them achieved pathologic complete response. When compared to HER2-negative (IHC of 0+) and HER2-positive (IHC of 3+ or IHC of 2+ with amplified ISH) cancers, HER2-low breast cancers had significantly lower Ki-67 (p = 0.03 and p 0.01, respectively) and higher ER positivity (p = 0.01 and p = 0.03, respectively). HER2-low breast cancers were less likely to be basal molecular subtype when compared to HER2-negative cancers (p 0.01) and were less likely to have a HER2 molecular subtype when compared to HER2-positive cancers (p 0.01). When adjusted for ER status, there was no significant difference on all the examined variables between HER2-low and HER2-negative groups. Our study provides valuable baseline characteristics of HER2-low breast cancers deriving from consecutive, real-world cases with a consensus confirmation of HER2 status, and would help to increase our understanding of this newly-proposed HER2 category in breast cancers.

Magee Equations™ (ME) are multivariable models that can estimate oncotype DX® recurrence score. One of the equations, Magee Equation 3 (ME3) which utilizes only semi-quantitative receptor results has been shown to provide chemopredictive value in the neoadjuvant setting in a single institutional study. This multi-institutional study (seven institutions contributed cases) was undertaken to examine the validity of ME3 in predicting response to neoadjuvant chemotherapy in estrogen receptor positive, HER2-negative breast cancers. Stage IV cases were excluded. The primary endpoint was the pathologic complete response (pCR) rate in different categories of ME3 scores calculated based on receptor results in the pre-therapy core biopsy. A total of 166 cases met the inclusion criteria. The patient age ranged from 24 to 83 years (median 53 years). The average pre-therapy tumor size was 3.9 cm, and axillary lymph nodes were confirmed positive by pre-therapy core biopsy in 85 of 166 cases (51%). The pCR rate according to ME3 scores was 0% (0 of 64) in ME3 25 to 25 was significantly associated with shorter distant recurrence-free survival and showed a trend for shorter breast cancer-specific survival. The results of this multi-institutional study are similar to previously published data from a single institution (PMID: 28548119) and confirm the chemo-predictive value of ME3 in the neoadjuvant setting. In addition, ME3 may provide prognostic information in patients with residual disease which should be further evaluated.

Oncotype DX (Genomic Health, Redwood City, CA, USA, current list price $4,350.00) is a multigene quantitative reverse transcription-polymerase chain reaction-based assay that estimates the risk of distant recurrence and predicts chemotherapy benefit for patients with estrogen receptor (ER)-positive breast cancers. Studies have suggested that standard histologic variables can provide similar information. Klein and Dabbs et al have shown that Oncotype DX recurrence scores can be estimated by incorporating standard histologic variables into equations (Magee equations). Using a simple modification of the Magee equation, we predict the Oncotype DX recurrence score in an independent set of 283 cases. The Pearson correlation coefficient (r) for the Oncotype DX and average modified Magee recurrence scores was 0.6644 (n=283; P0.0001). 100% of cases with an average modified Magee recurrence score30 (n=8) or an average modified Magee recurrence score9 (with an available Ki-67, n=5) would have been correctly predicted to have a high or low Oncotype DX recurrence score, respectively. 86% (38/44) of cases with an average modified Magee recurrence score≤12, and 89% (34/38) of low grade tumors (NS6) with an ER and PR≥150, and a Ki-6710%, would have been correctly predicted to have a low Oncotype DX recurrence score. Using an algorithmic approach to eliminate high and low risk cases, between 5% and 23% of cases would potentially not have been sent by our institution for Oncotype DX testing, creating a potential cost savings between $56,550.00 and $282,750.00. The modified Magee recurrence score along with histologic criteria may be a cost-effective alternative to the Oncotype DX in risk stratifying certain breast cancer patients. The information needed is already generated by many pathology laboratories during the initial assessment of primary breast cancer, and the equations are free.