Impact of the Updated Guidelines on Human Epidermal Growth Factor Receptor 2 (HER2) Testing in Breast Cancer

Impact of immunohistochemistry staining conditions on the incidence of human epidermal growth factor receptor 2 (HER2)-low breast cancer

We investigated frequencies of HER2-low breast cancer (BC) (immunohistochemistry [IHC] 1+ or 2+ without gene amplification) before and after IHC conditions were modified in order to understand the impact of IHC staining conditions on frequencies of HER2-low BC. Primary BC cases diagnosed at the Yeungnam University Hospital (YUH, n = 728) or Keimyung University Dongsan Hospital (KUDH, n = 290) in 2022 were reviewed, and data on HER2 status and IHC conditions were collected (cohort 1). Both institutions used the 4B5 antibody for HER2 IHC but had different staining protocols. After modifications of the IHC conditions at both institutions, primary BC cases (YUH, n = 324 and KUDH, n = 135) diagnosed from April to July 2023 (cohort 2) were reviewed to assess any changes in the frequency of HER2 status. In cohort 1, of the 728 cases diagnosed at YUH, 556 (76.4%) were HER2-zero, 76 (10.4%) were HER2-low, and 96 (13.2%) were HER2-positive, and of the 290 cases diagnosed at KUDH, 135 (46.6%) were HER2-zero, 82 (28.3%) were HER2-low, and 73 (25.2%) were HER2-positive. Modifications in HER2 IHC staining conditions dramatically increased the frequencies of HER2-low BC in cohort 2 (YUH 38.9% and KUDH 49.6%), but they did not result in significant changes in the HER2-positive rates (YUH 15.4% and KUDH 25.2%) compared to cohort 1. In conclusion, minor modifications in HER2 IHC staining conditions significantly affected the frequency of HER2-low BC but had little impact on the HER2-positivity rate. Each pathology laboratory should verify IHC conditions using control slides (including 1+) to enable the accurate identification of HER2-low BC.

Expression of BRCA1 by immunohistochemistry and its association with ER, PR, Her2neu status in infiltrative ductal carcinoma of breast

BACKGROUND

Breast cancer is a heterogeneous disease, which differs in its clinical behaviors and responses to treatment and outcome. The prognosis of breast cancer depends on histopathological parameters and molecular subtypes. Among more than 300 genes, which are involved in the pathogenesis of breast cancer tumor suppressor gene such as BRCA1 is known to play a significant role in hereditary cancers. However, its role in sporadic cases of infiltrating ductal carcinoma is yet to be established.

AIMS AND OBJECTIVES

To evaluate the expression of BRCA1 in infiltrative ductal carcinoma and to analyze the association of BRCA1 with histopathological parameters and estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor2 (Her2) neu expression.

MATERIALS AND METHODS

This was a laboratory-based exploratory study in which 56 patients with infiltrative ductal carcinoma who underwent radical mastectomy from October 2019 to July 2021 were included. Patients with chemotherapy and radiotherapy, trucut biopsies, and incomplete patient details were excluded. Immunostaining for BRCA1 was performed. Individual clinicopathological parameters were compared with the BRCA1 mutation. Statistical analysis was done using SPSS 22. A P value of < 0.05 was considered statistically significant.

RESULTS

Among 56 cases of IDC, 18 cases (32.1%) showed BRCA1 mutation. BRCA1 mutation was associated with postmenopausal age, larger tumor size, lower tumor grade, and higher tumor staging. When we analyzed the biomarkers with BRCA1 mutation, it showed a negative association with ER, PR, and Her2 neu and a high Ki67 proliferation index. No family history of breast carcinoma was seen in 34/56 patients where history was available.

CONCLUSION

Our study showed BRCA1 mutation in 32.1% and associated with postmenopausal age group, larger tumor size, and higher staging and negative hormonal status of breast carcinoma.

Updates on breast biomarkers

Recent advancements in breast cancer treatment have ushered in a new era of precision medicine. Novel trials have led to the approval of a growing list of personalized therapies and corresponding biomarkers. These advancements have shifted the pathologist's practice into a leading role in the management breast cancer. Understanding the complex algorithms and diagnostic modalities used to assess predictive and prognostic biomarkers is central for quality oncology care. ER and HER2 subcategorize breast cancers into treatment groups under which different biomarkers and therapies are indicated, while they also serve as predictive biomarkers for specific targeted treatments. This review will cover the evolution and latest updates of the CAP/ASCO guidelines relevant to these two important biomarkers in breast cancer. Still evolving concepts such as HER2 heterogeneity, HER2 "low," and HER2-mutated cancers have the potential to continue to change HER2 testing in breast cancers. In addition to ER and HER2, biomarkers used in specific clinical scenarios will be covered. In early-stage ER-positive/HER2-negative disease, multi-gene expression panels (such as OncotypeDX) have emerged as the new standard biomarker when determining if chemotherapy should be added to endocrine therapy. In the more aggressive ER-negative/HER2-positive or triple negative early-stage breast cancers, response to neoadjuvant therapy has proved to be a useful biomarker to help determine if additional therapy should be added for patients with an incomplete response. Ki67 has also recently emerged as a marker that can be used to identify the highest risk ER-positive and HER2-negative cancers if considering adding a cell cycle inhibitor (abemaciclib) to endocrine therapy. Importantly, in the metastatic setting, numerous predictive biomarkers have emerged, including recommendations for germline BRCA mutation testing for all metastatic patients (to determine if PARP inhibitor therapy is an option) and other ER-/HER2-dependent biomarkers such as PD-L1 (for potential immunotherapy in triple negative patients) and PIK3CA mutation status (for potential PI3K inhibitor therapy in ER-positive metastatic patients). Other less common biomarkers of targeted therapy options (e.g., MSI/MMR, TMB, NTRK) as well as comprehensive genomic profiling to identify uncommon targets are also available in the metastatic setting to determine additional treatment options.

Nomogram for predicting axillary lymph node pathological response in node-positive breast cancer patients after neoadjuvant chemotherapy

Background:

Pathological complete response (pCR) of axillary lymph nodes (ALNs) is frequently achieved in patients with clinically node-positive breast cancer after neoadjuvant chemotherapy (NAC), and ALN status is an important prognostic factor for breast cancer patients. This study aims to develop a new predictive clinical model to assess the ALN pCR rate after NAC.

Methods:

This was a retrospective series of 467 patients who had biopsy-proven positive ALNs at diagnosis and underwent ALN dissection from 2007 to 2014 at the National Cancer Center/Cancer Hospital of the Chinese Academy of Medical Sciences. We analyzed the clinicopathologic features of the patients and developed a nomogram to predict the probability of ALN pCR. A multivariable logistic regression stepwise model was used to construct a nomogram to predict ALN pCR in node-positive patients. The adjusted area under the receiver operating characteristic curve (AUC) was calculated to quantify the ability to rank patients by risk. Internal validation was performed using the 50/50 hold-out validation method. The nomogram was externally validated with prospective cohorts of 167 patients from 2016 to 2018 at the Cancer Hospital of the Chinese Academy of Medical Sciences and 114 patients from 2018 to 2020 at Beijing Tiantan Hospital.

Results:

In this retrospective study, 115 (24.6%) patients achieved ALN pCR after NAC. Multivariate analysis showed that clinical tumor stage (Odds ratio [OR]: 0.321, 95% confidence interval [CI]: 0.121–0.856; P = 0.023); primary tumor response (OR: 0.189; 95% CI: 0.123–0.292; P < 0.001), and estrogen receptor status (OR: 0.530, 95% CI: 0.304–0.925; P = 0.025) were independent predictors of ALN pCR. The nomogram was constructed based on the result of multivariate analysis. In the internal validation of performance of nomogram, the AUCs for the training and test sets were 0.719 and 0.753, respectively. The nomogram was validated in external cohorts with AUCs of 0.720, which demonstrated good discriminatory power in these data sets.

Conclusion:

We developed a nomogram to predict the likelihood of axillary pCR in node-positive breast cancer patients after NAC. The predictive model performed well in multicenter prospective external validation. This practical tool could provide information to surgeons regarding whether to perform additional ALN dissection after NAC.

Trial registration:

ChiCTR.org.cn, ChiCTR1800014968.