HER2Testing by Local, Central, and Reference Laboratories in Specimens From the North Central Cancer Treatment Group N9831 Intergroup Adjuvant Trial

Best practices for achieving consensus in HER2-low expression in breast cancer: current perspectives from practising pathologists

AIMS

Human epidermal growth factor receptor 2 (HER2) expression is an important biomarker in breast cancer (BC). Most BC cases categorised as HER2-negative (HER2-) express low levels of HER2 [immunohistochemistry (IHC) 1+ or IHC 2+/in-situ hybridisation not amplified (ISH-)] and represent a clinically relevant therapeutic category that is amenable to targeted therapy using a recently approved HER2-directed antibody-drug conjugate. A group of practising pathologists, with expertise in breast pathology and BC biomarker testing, outline best practices and guidance for achieving consensus in HER2 IHC scoring for BC.

METHODS AND RESULTS

The authors describe current knowledge and challenges of IHC testing and scoring of HER2-low expressing BC and provide best practices and guidance for accurate identification of BCs expressing low levels of HER2. These expert pathologists propose an algorithm for assessing HER2 expression with validated IHC assays and incorporate the 2023 American Society of Clinical Oncology and College of American Pathologist guideline update. The authors also provide guidance on when to seek consensus for HER2 IHC scoring, how to incorporate HER2-low into IHC reporting and present examples of HER2 IHC staining, including challenging cases.

CONCLUSIONS

Awareness of BC cases that are negative for HER protein overexpression/gene amplification and the related clinical relevance for targeted therapy highlight the importance of accurate HER2 IHC scoring for optimal treatment selection.

TBACkp: HER2 expression status classification network focusing on intrinsic subenvironmental characteristics of breast cancer liver metastases

The HER2 expression status in breast cancer liver metastases is a crucial indicator for the diagnosis, treatment, and prognosis assessment of patients. And typical diagnosis involves assessing the HER2 expression status through invasive procedures like biopsy. However, this method has certain drawbacks, such as being difficult in obtaining tissue samples and requiring long examination periods. To address these limitations, we propose an AI-aided diagnostic model. This model enables rapid diagnosis. It diagnoses a patient's HER2 expression status on the basis of preprocessed images, which is the region of the lesion extracted from a CT image rather than from an actual tissue sample. The algorithm of the model adopts a parallel structure, including a Branch Block and a Trunk Block. The Branch Block is responsible for extracting the gradient characteristics between the tumor sub-environments, and the Trunk Block is for fusing the characteristics extracted by the Branch Block. The Branch Block contains CNN with self-attention, which combines the advantages of CNN and self-attention to extract more meticulous and comprehensive image features. And the Trunk Block is so designed that it fuses the extracted image feature information without affecting the transmission of the original image features. The Conv-Attention is used to calculate the attention in the Trunk Block, which uses kernel dot product and is responsible for providing the weight for the self-attention in the process of using convolution induced deviation calculation. Combined with the structure of the model and the method used, we refer to this model as TBACkp. The dataset comprises the enhanced abdominal CT images of 151 patients with liver metastases from breast cancer, together with the corresponding HER2 expression levels for each patient. The experimental results are as follows: (AUC: 0.915, ACC: 0.854, specificity: 0.809, precision: 0.863, recall: 0.881, F1-score: 0.872). The results demonstrate that this method can accurately assess the HER2 expression status in patients when compared with other advanced deep learning model.

Hormone receptor conversion in metastatic breast cancer

Background/Objective

Hormone receptor (HR) status is one of the key factors in determining the treatment of breast cancer. Previous studies suggested that HR status may change in metastatic tissue. However, available studies focused mainly on primary biopsies and there are only few trials comparing HR status in the primary tumour and the metastasis using material from complete resection. The aim of the study was to determine the frequency of HR alterations in metastatic breast cancer.

Materials and methods

The study retrospectively examines a total of 50 patients who underwent brain, lung, or liver metastasectomy for metastatic breast cancer between January 2000 and January 2019.

Results

HR conversion was observed in a total of 30 cases (60.0%), while HER-2/neu (human epidermal growth factor receptor 2) discrepancy surprisingly occurred only in one case (2.0%). A change in immunophenotype occurred in 28% of cases. Triple-negativity was more frequent in brain metastases (p = 0.039).

Conclusions

We have confirmed that HR conversion between the primary tumour and its metastases occurs in a significant number of cases, which has important implications for further treatment decisions.

State of Cancer Control in South America: Challenges and Advancement Strategies

Cancer is a major public health problem in South America. The cancer mortality burden is increasing in the region due to its presentation at later stages, which is related to limited access to cancer care. This results in a noticeable inequity in provisions of cancer care including specialized screening programs, as well as cancer-related treatments such as personalized medicine, radiation therapy, palliative care, and survivorship services. Consequently, South America faces many challenges for cancer control, most of them deriving from a lack of funding and unequal distribution of resources and cancer services, affecting mostly the underserved populations in the region.

Machine learning-based model constructed from ultrasound radiomics and clinical features for predicting HER2 status in breast cancer patients with indeterminate (2+) immunohistochemical results

BACKGROUND

We aimed to predict human epidermal growth factor receptor 2 (HER2) 2+ status in patients with breast cancer by constructing and validating machine learning models utilizing ultrasound (US) radiomics and clinical features.

METHODS

We analyzed 203 breast cancer cases immunohistochemically determined as HER2 2+ and used fluorescence in situ hybridization (FISH) as the confirmation method. From each case, the study analyzed 840 extracted radiomics features and 11 clinicopathologic features. Cases were randomly split into training (n = 141) and validation sets (n = 62) at a 7:3 ratio. Univariate logistic regression analysis was first performed on the 11 clinicopathologic characteristics. The least absolute shrinkage and selection operator (LASSO) and decision tree (DT) techniques were employed for post-feature selection. Finally, 19 radiomics features were utilized in logistic regression (LR) and Naive Bayesian (NB) classifiers. Model performance was gauged using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity.

RESULTS

Our models exhibited notable diagnostic efficacy in differentiating HER2-positive from negative breast cancer cases. In the validation sets, the LR model outperformed the NB model with an AUC of 0.860 and accuracy of 83.8% compared to NB's AUC of 0.684 and accuracy of 79.0%. The LR model demonstrated higher sensitivity (92.3% vs. 46.2%) while the NB model had a better specificity (91.8% vs. 63.3%) in the validation set.

CONCLUSIONS

Machine learning models grounded on radiomics efficiently predicted IHC HER2 2+ status in breast cancer patients, suggesting potential enhancements in clinical decision-making for treatment and management.

Retrospective study to estimate the prevalence and describe the clinicopathological characteristics, treatments received, and outcomes of HER2-low breast cancer

BACKGROUND

Approximately 80% of all breast cancers (BCs) are currently categorized as human epidermal growth factor receptor 2 (HER2)-negative [immunohistochemistry (IHC) 0, 1+, or 2+/in situ hybridization (ISH) negative]; approximately 60% of BCs traditionally categorized as HER2-negative express low levels of HER2. HER2-low (IHC 1+ or IHC 2+/ISH-) status became clinically actionable with approval of trastuzumab deruxtecan to treat unresectable/metastatic HER2-low BC. Greater understanding of patients with HER2-low disease is urgently needed.

PATIENTS AND METHODS

This global, multicenter, retrospective study (NCT04807595) included tissue samples from patients with confirmed HER2-negative unresectable/metastatic BC [any hormone receptor (HR) status] diagnosed from 2014 to 2017. Pathologists rescored HER2 IHC-stained slides as HER2-low (IHC 1+ or IHC 2+/ISH-) or HER2 IHC 0 after training on low-end expression scoring using Ventana 4B5 and other assays at local laboratories (13 sites; 10 countries) blinded to historical scores. HER2-low prevalence and concordance between historical scores and rescores were assessed. Demographics, clinicopathological characteristics, treatments, and outcomes were examined.

RESULTS

In rescored samples from 789 patients with HER2-negative unresectable/metastatic BC, the overall HER2-low prevalence was 67.2% (HR positive, 71.1%; HR negative, 52.8%). Concordance was moderate between historical and rescored HER2 statuses (81.3%; κ = 0.583); positive agreement was numerically higher for HER2-low (87.5%) than HER2 IHC 0 (69.9%). More than 30% of historical IHC 0 cases were rescored as HER2-low overall (all assays) and using Ventana 4B5. There were no notable differences between HER2-low and HER2 IHC 0 in patient characteristics, treatments received, or clinical outcomes.

CONCLUSIONS

Approximately two-thirds of patients with historically HER2-negative unresectable/metastatic BC may benefit from HER2-low-directed treatments. Our data suggest that HER2 reassessment in patients with historical IHC 0 scores may be considered to help optimize selection of patients for treatment. Further, accurate identification of patients with HER2-low BC may be achieved with standardized pathologist training.

A comparative study of gastric adenocarcinoma HER2 IHC phenotype and mass spectrometry-based quantification

Introduction

Gastric cancer is a highly heterogeneous malignant tumor of the digestive system. Anti-HER2 treatment can inhibit downstream signaling pathways and improve clinical treatment and outcomes in patients with HER2 protein overexpression. Currently, two standard methods for evaluating HER2 expression status are immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). However, these low-throughput assays often produce discordant or equivocal results.

Methods

In this study, we presented a new HER2 protein detection method based on mass spectrometry selected reaction monitoring (MS-SRM) and validated the method. We conducted a retrospective study on 118 formalin-fixed paraffin-embedded (FFPE) tissues from patients with advanced gastric adenocarcinoma in northern China, and we compared the MS-SRM results with those from IHC and correlated them with FISH.

Results

We established and validated the upper and lower detection limits (300-700 amol/μg) for abnormal HER2 protein expression in advanced gastric cancer. We also found that, among samples with mixed Lauren subtypes, those with a high level of HER2 expression had typical intestinal type features in pathology.

Discussion

This study demonstrated that the MS-SRM method can overcome the limitations and deficiencies of IHC, directly quantify the expression of HER2 protein in tumor cells and be used as a supplement to IHC. It has the potential to be used as a companion diagnosis for new drugs used to treat advanced gastric cancer. Large-scale clinical validation is required.

Frequency of HER2 protein overexpression and HER2 gene amplification in endometrial clear cell carcinoma

HER2 (ERBB2) overexpression and/or HER2 gene amplification has been well established in several tumors types and when present HER2 directed therapy may be to be efficacious. While recent findings suggests that HER2 overexpression and HER2 amplification are a relatively common in serous endometrial carcinoma, similar data regarding clear cell endometrial carcinoma (CCC) is difficult to interpret due to issues such as diagnostic criteria, sample type and HER2 interpretation criteria. Our goals were to study HER2 expression and HER2 copy number status in hysterectomy specimens from a large series of patients with pure CCC to determine the frequency of HER2 overexpression and HER2 amplification and evaluate applicability of current HER2 interpretation criteria. Pure CCC specimens derived from hysterectomy specimens from 26 patients were identified. All diagnoses were confirmed by two gynecologic pathologists. Immunohistochemistry for HER2 protein and fluorescence in situ hybridization (FISH) studies for HER2 were performed on whole-slide sections from all cases. Results were interpreted according to the 2018 ASO/CAP HER2 guidelines for breast cancer and International Society of Gynecologic Pathologists (ISGyP) HER2 guidelines for serous endometrial carcinoma. Additional testing was performed when indicated by the guidelines. HER2 expression by immunohistochemistry was 3+ in 4% and 0% of cases, and 2+ in 46% and 52% of cases, by 2018 ASCO/CAP and ISGyP criteria, respectively, while the remaining cases were negative. HER2 testing by FISH showed a positive result in 27% of tumors with 2018 ASCO/CAP guidelines, while 23% were positive with the ISGyP criteria. Our findings indicate that HER2 overexpression and HER2 amplification occur in a subset of CCC. Therefore, additional study into the potential benefit of HER2 targeted therapy in patients with CCC is warranted.

UK recommendations for HER2 assessment in breast cancer: an update

The last UK breast cancer (BC) human epidermal growth factor receptor 2 (HER2) testing guideline recommendations were published in 2015. Since then, new data and therapeutic strategies have emerged. The American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) published a focused update in 2018 that reclassified in situ hybridisation (ISH) Group 2 (immunohistochemistry (IHC) score 2+and HER2/chromosome enumeration probe 17 (CEP17) ratio ≥2.0 and HER2 copy number <4.0 signals/cell), as well as addressed other concerns raised by previous guidelines. The present article further refines UK guidelines, with specific attention to definitions of HER2 status focusing on eight key areas: (1) HER2 equivocal (IHC 2+) and assignment of the ASCO/CAP ISH group 2 tumours; (2) the definition of the group of BCs with low IHC scores for HER2 with emphasis on the distinction between IHC score 1+ (HER2-Low) from HER2 IHC score 0 (HER2 negative); (3) reporting cases showing HER2 heterogeneity; (4) HER2 testing in specific settings, including on cytological material; (5) repeat HER2 testing, (6) HER2 testing turnaround time targets; (7) the potential role of next generation sequencing and other diagnostic molecular assays for routine testing of HER2 status in BC and (8) use of image analysis to score HER2 IHC. The two tiered system of HER2 assessment remains unchanged, with first line IHC and then ISH limited to IHC equivocal cases (IHC score 2+) but emerging data on the relationship between IHC scores and levels of response to anti-HER2 therapy are considered. Here, we present the latest UK recommendations for HER2 status evaluation in BC, and where relevant, the differences from other published guidelines.

Refining the definition of HER2-low class in invasive breast cancer

BACKGROUND

Emerging evidence indicates that breast cancer (BC) patients whose tumours express HER2 protein without HER2 gene amplification (HER2-low), can benefit from antibody-drug conjugates (ADC). However, the current definition of HER2-low BC remains incomplete with low rates of concordance. This study aims to refine HER2-low definition with emphasis on distinguishing HER2 score 0 from score 1+ to identify patients who are eligible for ADC.

METHODS

A BC cohort (n = 363) with HER2 IHC scores 0, 1+ and 2+ (without HER2 gene amplification) and available HER2 mRNA was included. HER2 staining intensity, pattern and subcellular localisation were reassessed. Artificial neural network analysis was applied to cluster the cohort and to distinguish HER2 score 0 from 1+. Reproducibility and reliability of the refined criteria were tested.

RESULTS

HER2 IHC score 1+ was refined as membranous staining in invasive cells as either: (1) faint intensity in ≥ 20% of cells regardless the circumferential completeness, (2) weak complete staining in ≤ 10%, (3) weak incomplete staining in > 10% and (4) moderate incomplete staining in ≤ 10%. Based on this, 63% of the HER2-negative cases were reclassified as positive (HER2-low). The refined score showed perfect observer agreement compared to the moderate agreement in the original clinical scores. Similar results were generated when the refined score was applied on the independent BC cohorts. A proposal to refine the definition of other HER2 classes is presented.

CONCLUSION

This study refined the definition of HER2-low BC based on correlation with HER2 mRNA and distinguished between HER2 IHC score 1+ and score 0 tumours.

Loss of HER2 in breast cancer: biological mechanisms and technical pitfalls

Loss of HER2 in previously HER2-positive breast tumors is not rare, occurring in up to 50% of breast cancers; however, clinical research and practice underestimate this issue. Many studies have reported the loss of HER2 after neoadjuvant therapy and at metastatic relapse and identified clinicopathological variables more frequently associated with this event. Nevertheless, the biological mechanisms underlying HER2 loss are still poorly understood. HER2 downregulation, intratumoral heterogeneity, clonal selection, and true subtype switch have been suggested as potential causes of HER2 loss, but translational studies specifically investigating the biology behind HER2 loss are virtually absent. On the other side, technical pitfalls may justify HER2 loss in some of these samples. The best treatment strategy for patients with HER2 loss is currently unknown. Considering the prevalence of this phenomenon and its apparent correlation with worse outcomes, we believe that correlative studies specifically addressing HER2 loss are warranted.

Optical biosensor based on weak value amplification for the high sensitivity detection of Pertuzumab in combination with Trastuzumab binding to the extracellular domain of HER2

A real-time optical phase sensing scheme based on weak value amplification was proposed to monitor the especially binding process of Pertuzumab combined with Trastuzumab on HER2 positive cells. From the wavelength shift of output spectrum, the phase difference between measuring and referential path related to the concentration of Pertuzumab as well as Trastuzumab could be calculated. With this approach, the limit of detection (LOD) of 5.54 × 10^-13 M for Pertuzumab assay was achieved. Besides, the kinetics signal of Pertuzumab in combination with Trastuzumab binding to HER2 was detected in real time. Experimental results demonstrated that both Trastuzumab and Pertuzumab can be captured by HER2, but the former was significantly superior to the latter in terms of the target number. Additionally, the binding speed was analyzed and demonstrated to be closely correlated with the initial concentration of the targeting agents.

Targeted Approaches to HER2-Low Breast Cancer: Current Practice and Future Directions

Simple Summary

HER2-low breast cancer (BC) accounts for more than half of breast cancer patients. Anti-HER2 therapy has been ineffective in HER2-low BC, for which palliative chemotherapy is the main treatment modality. The definitive efficacy of T-Dxd in HER2-low BC breaks previous treatment strategies, which will redefine HER2-low and thus reshape anti-HER2 therapy. This review summarizes detection technologies and novel agents for HER2-low BC, and explores their possible role in future clinics, to provide ideas for the diagnosis and treatment of HER2-low BC.

Abstract

HER2-low breast cancer (BC) has a poor prognosis, making the development of more suitable treatment an unmet clinical need. While chemotherapy is the main method of treatment for HER2-low BC, not all patients benefit from it. Antineoplastic therapy without chemotherapy has shown promise in clinical trials and is being explored further. As quantitative detection techniques become more advanced, they assist in better defining the expression level of HER2 and in guiding the development of targeted therapies, which include directly targeting HER2 receptors on the cell surface, targeting HER2-related intracellular signaling pathways and targeting the immune microenvironment. A new anti-HER2 antibody-drug conjugate called T-DM1 has been successfully tested and found to be highly effective in clinical trials. With this progress, it could eventually be transformed from a disease without a defined therapeutic target into a disease with a defined therapeutic molecular target. Furthermore, efforts are being made to compare the sequencing and combination of chemotherapy, endocrine therapy, and HER2-targeted therapy to improve prognosis to customize the subtype of HER2 low expression precision treatment regimens. In this review, we summarize the current and upcoming treatment strategies, to achieve accurate management of HER2-low BC.

Structure-preserving integrated analysis for risk stratification with application to cancer staging

To provide appropriate and practical level of health care, it is critical to group patients into relatively few strata that have distinct prognosis. Such grouping or stratification is typically based on well-established risk factors and clinical outcomes. A well-known example is the American Joint Committee on Cancer staging for cancer that uses tumor size, node involvement, and metastasis status. We consider a statistical method for such grouping based on individual patient data from multiple studies. The method encourages a common grouping structure as a basis for borrowing information, but acknowledges data heterogeneity including unbalanced data structures across multiple studies. We build on the "lasso-tree" method that is more versatile than the well-known classification and regression tree method in generating possible grouping patterns. In addition, the parametrization of the lasso-tree method makes it very natural to incorporate the underlying order information in the risk factors. In this article, we also strengthen the lasso-tree method by establishing its theoretical properties for which Lin and others (2013. Lasso tree for cancer staging with survival data. Biostatistics 14, 327-339) did not pursue. We evaluate our method in extensive simulation studies and an analysis of multiple breast cancer data sets.

A novel ensemble feature selection method for pixel-level segmentation of HER2 overexpression

Classifying histopathology images on a pixel-level requires sets of features able to capture the complex characteristics of the images, like the irregular cell morphology and the color heterogeneity on the tissue aspect. In this context, feature selection becomes a crucial step in the classification process such that it reduces model complexity and computational costs, avoids overfitting, and thereby it improves the model performance. In this study, we propose a new ensemble feature selection method by combining a set of base selectors, classifiers, and rank aggregation methods, aiming to determine from any initial set of handcrafted features, a smaller set of relevant color and texture pixel-level features, subsequently used for segmenting HER2 overexpression on a pixel-level, in breast cancer tissue images. We have been able to significantly reduce the set of initial features, using the proposed ensemble feature selection method. The best results are obtained using $$\chi ^2$$ χ 2 , Random Forest, and Runoff as the based selector, classifier, and aggregation method, respectively. The classification performance of the best model trained on the selected features set results in 0.939 recall, 0.866 specificity, 0.903 accuracy, 0.875 precision, and 0.906 F1-score.

Fine-Tuned DenseNet-169 for Breast Cancer Metastasis Prediction Using FastAI and 1-Cycle Policy

Lymph node metastasis in breast cancer may be accurately predicted using a DenseNet-169 model. However, the current system for identifying metastases in a lymph node is manual and tedious. A pathologist well-versed with the process of detection and characterization of lymph nodes goes through hours investigating histological slides. Furthermore, because of the massive size of most whole-slide images (WSI), it is wise to divide a slide into batches of small image patches and apply methods independently on each patch. The present work introduces a novel method for the automated diagnosis and detection of metastases from whole slide images using the Fast AI framework and the 1-cycle policy. Additionally, it compares this new approach to previous methods. The proposed model has surpassed other state-of-art methods with more than 97.4% accuracy. In addition, a mobile application is developed for prompt and quick response. It collects user information and models to diagnose metastases present in the early stages of cancer. These results indicate that the suggested model may assist general practitioners in accurately analyzing breast cancer situations, hence preventing future complications and mortality. With digital image processing, histopathologic interpretation and diagnostic accuracy have improved considerably.

A Novel Data Analytics-derived Metric (Nearest Cluster Distance) Is Easily Implemented in Routine Practice and Correctly Identifies Breast Cancer Cases for Quality Review

Background

Errors in breast cancer grading and predictive testing are clinically important and can be difficult to detect in routine practice. A quality metric able to identify a subset of breast cancer cases which are high yield on quality review would be of practical clinical benefit.

Methods

Data analytic techniques were used to generate consensus tumor signature centers from a dataset over 500 breast cancer cases from a single practice. Cases were assigned a novel metric, Nearest Cluster Distance, corresponding to their distances from the nearest tumor signature center. The subset of tumors exceeding a cutoff for this metric were flagged, and then reviewed and rescored in a blinded fashion together with matched controls. A simplified version of this metric was created using universally accessible methods.

Results

Flagged cases showed statistically significant movement toward consensus tumor signature centers compared with controls, consistent with identification of cases which could benefit from review and possible rescoring. The simplified metric performs identically.

Conclusion

This method can be readily applied in routine practice and is promising as a real time quality check for breast cancer diagnosis and reporting.

Blood Vessel Detection Algorithm for Tissue Engineering and Quantitative Histology

Immunohistochemistry for vascular network analysis plays a fundamental role in basic science, translational research and clinical practice. However, identifying vascularization in histological tissue images is time consuming and markedly depends on the operator’s experience. In this study, we present “blood vessel detection—BVD”, an automatic algorithm for quantitative analysis of blood vessels in immunohistochemical images. BVD is based on extraction and analysis of low-level image features and spatial filtering techniques, which do not require a training phase. BVD algorithm performance was comparatively evaluated on histological sections from three different in vivo experiments. Collectively, 173 independent images were analyzed, and the algorithm's results were compared to those obtained by human operators. The developed BVD algorithm proved to be a robust and versatile tool, being able to quantify number, area, and spatial distribution of blood vessels within all three considered histologic datasets. BVD is provided as an open-source application working on different operating systems. BVD is supported by a user-friendly graphical interface designed to facilitate large-scale analysis.

Deep Learning-Enabled Technologies for Bioimage Analysis

Deep learning (DL) is a subfield of machine learning (ML), which has recently demonstrated its potency to significantly improve the quantification and classification workflows in biomedical and clinical applications. Among the end applications profoundly benefitting from DL, cellular morphology quantification is one of the pioneers. Here, we first briefly explain fundamental concepts in DL and then we review some of the emerging DL-enabled applications in cell morphology quantification in the fields of embryology, point-of-care ovulation testing, as a predictive tool for fetal heart pregnancy, cancer diagnostics via classification of cancer histology images, autosomal polycystic kidney disease, and chronic kidney diseases.

mRNA expression of specific HER ligands and their association with clinical outcome in patients with metastatic breast cancer treated with trastuzumab

Prognostic and predictive biomarkers are being studied for the diagnosis and treatment of breast cancer. The present study retrospectively assessed the mRNA expression of HER family receptor ligands and of other potential prognostic biomarkers and their association with time to progression (TTP), survival and clinicopathological characteristics in patients with metastatic breast cancer (MBC) treated with trastuzumab. A total of 145 tumour tissue samples were analysed. mRNA expression analysis of the transcripts of interest was performed and the association of these markers with selected clinicopathological parameters was examined. HER2 status was centrally re-evaluated. Only 67.6% of patients were truly HER2-positive according to the central HER2 re-evaluation. Heparin binding epidermal growth factor (EGF)-like growth factor, transforming growth factor β1 (TGFB1) and thyroid hormone receptor α (THRA) mRNA expression was higher in HER2-positive patients (P=0.026, P<0.001 and P<0.001). Insulin-like growth factor binding protein 4 was correlated with retinoic acid receptor α, TGFB1 and THRA (rho=0.45, rho=0.60 and rho=0.45). In HER2-positive patients, high neuregulin 1 and high betacellulin were unfavourable factors for TTP [hazard ratio (HR) = 1.78, P=0.040 and HR=2.00, P=0.043, respectively]. In patients with de novo MBC, high EGF expression was associated with a non-significant prolongation of TTP (HR=0.52, P=0.080) and significantly longer survival (HR=0.40, P=0.020). The present study examined clinical and biological implications of specific genes and it was concluded that their expression has an impact on the outcome of trastuzumab-treated patients with MBC.

Phenotype Discordance between Primary Tumor and Metastasis Impacts Metastasis Site and Outcome: Results of WSG-DETECT-PriMet

Introduction

Tumor biological factors of breast cancer (BC) such as hormone receptor (HR) status, HER2 status, and grade can differ in the metastatic cascade from primary to lymph node (LN) metastasis and to distant metastatic tissue. Systematic data regarding therapeutic consequences are yet limited.

Methods

We conducted a prospectively planned, retrospective cohort study comparing BC phenotype in tissue from primary tumors (PTs), locoregional LN metastases, and disease recurrence (DR). HR and HER2 as well as tumor grade in PTs and DR were obtained by a database search. No centralized biomarker testing was performed. The impact of changes in tumor biological factors on post-recurrence survival (PRS) and overall survival was analyzed.

Results

PriMet comprises 635 patients (LN tissue in 142 patients). Discrepancies for HR or HER2 status between PT and DR were observed in 18.7 and 21.6% of cases, respectively. For HR status, positivity of PT and negativity of DR was seen more often (13.2%) than vice versa (5.5%). For HER2 status, negativity of the primary and positivity of DR was seen more often (14.9%) than vice versa (6.7%). Discordance was more often observed between PT and LN metastasis compared to LN versus DR. However, numbers were small. Compared to concordant non-triple-negative (TN) disease, concordant TN disease showed significantly inferior PRS.

Conclusion

We demonstrate receptor discordance to occur relatively frequently between PT, LN metastasis, and DR and to impact patient prognosis. However, clinical consequences of receptor discordance need to be drawn with caution considering clinical aspects as well as tumor biology.

Detailed Reanalysis of 500 Breast Cancers With Equivocal HER2 Immunohistochemistry and Borderline ERBB2 Fluorescence In Situ Hybridization Results

OBJECTIVES

We investigated the impact of our laboratory's reflex testing process for resolving ERBB2 (HER2) status on breast cancer samples that require additional workup after fluorescence in situ hybridization (FISH), per guideline recommendations published in 2018 by the American Society of Clinical Oncology (ASCO) and the College of American Pathologists (CAP).

METHODS

In total, 500 breast cancer specimens with ERBB2 FISH results in groups 2 through 4 (all reported as immunohistochemistry [IHC] equivocal [2+] at external laboratories) were resubmitted for IHC testing in our laboratory. Per the ASCO/CAP guideline, FISH was rescored when internal IHC was also equivocal (2+), targeted to tumor areas demonstrating more intense IHC staining, if observed.

RESULTS

Reflex IHC/FISH testing changed the final reported ERBB2 status in 185 of 500 (37.0%) samples. Result changes included discordant IHC (n = 4 score 0, n = 132 score 1+, and n = 16 score 3+) and discordant FISH (n = 33). Numerical differences in FISH scores were comparable for targeted vs nontargeted FISH rescoring (P = .086 for ERBB2 copy number; P = .49 for ERBB2 ratio). Two cases showed larger differences in FISH scores, suggesting heterogeneity.

CONCLUSIONS

Retesting of breast cancer samples with equivocal IHC frequently changes IHC results, but targeted reanalysis of borderline FISH results rarely identifies significant differences in ERBB2 copy number or ratio.

Comparison of BSGI and MRI as Approaches to Evaluating Residual Tumor Status after Neoadjuvant Chemotherapy in Chinese Women with Breast Cancer

Background: The present retrospective study was designed to evaluate the relative diagnostic utility of breast-specific gamma imaging (BSGI) and breast magnetic resonance imaging (MRI) as means of evaluating female breast cancer patients in China. Methods: A total of 229 malignant breast cancer patients underwent ultrasound, mammography, BSGI, and MRI between January 2015 and December 2018 for initial tumor staging. Of these patients, 73 were subsequently treated via definitive breast surgery following neoadjuvant chemotherapy (NAC), of whom 17 exhibited a complete pathologic response (pCR) to NAC. Results: BSGI and MRI were associated with 76.8% (43/56) and 83.9% (47/56) sensitivity (BSGI vs. MRI, p = 0.341) values, respectively, as a means of detecting residual tumors following NAC, while both these approaches exhibited comparable specificity in this diagnostic context. The specificity of BSGI for detecting residual tumors following NAC was 70.6% (12/17), and that of MRI was 58.8% (10/17) (BSGI vs. MRI, p = 0.473). Conclusion: These results demonstrate that BSGI is a useful auxiliary approach to evaluating pCR to NAC treatment.

HER2 in situ hybridization test in breast cancer: quantifying margins of error and genetic heterogeneity

The aim of the present study was to evaluate the effect of counting increasing number of invasive cancer cells in the result of the HER2 in situ hybridization (ISH) test in breast cancer as well as to compare two different approaches of measuring genomic heterogeneity (single cell and population based). A cohort of 100 consecutive breast cancer cases (primary and metastatic) were evaluated for HER2 gene amplification with bright-field ISH. The evaluation of the samples included scoring 20 nuclei, in five different areas, measuring the margins of error for each case. Genomic heterogeneity (GH) was defined by the 2018 ASCO/CAP guideline as a discrete population of tumor cells with HER2 amplification. We also evaluated GH as single tumor cells with HER2 amplification. The stabilization of the coefficient of variation of HER2/CEP17 ratio requires about 60 invasive cancer cells. The average margin of error of HER2/CEP17 ratio and of HER2 copy number was 0.40 and 0.53, respectively, when counting 20 cells, decreasing to 0.20 and 0.26 when counting 100 cells. Population GH was observed in 1% of the cases, while single cell GH was observed in 27% of the cases, reaching its maximum value in cases near the thresholds of positivity. Therefore, margins of error in HER2 ISH test are high, and the minimal cell number recommended in current guidelines should be raised to at least 60 cells. Population GH is a rare event and single cell GH is maximal in cases near the thresholds.

Subtype switching in breast cancer brain metastases: a multicenter analysis

Background

Breast cancer (BC) brain metastases (BM) can have discordant hormonal or human epidermal growth factor receptor 2 (HER2) expression compared with corresponding primary tumors. This study aimed to describe incidence, predictors, and survival outcomes of discordant receptors and associated subtype switching in BM.

Methods

BCBM patients seen at 4 tertiary institutions who had undergone BM resection or biopsy were included. Surgical pathology reports were retrospectively assessed to determine discordance between the primary tumor and the BCBM. In discordant cases, expression in extracranial metastases was also assessed.

Results

In BM from 219 patients, prevalence of any discordance was 36.3%; receptor-specific discordance was 16.7% for estrogen, 25.2% for progesterone, and 10.4% for HER2. Because estrogen and progesterone were considered together for hormonal status, 50 (22.8%) patients switched subtype as a result; 20 of these switches were HER2 based. Baseline subtype predicted switching, which occurred in up to 37.5% of primary HR+ patients. Moreover, 14.8% of initially HER2-negative patients gained HER2 in the BM. Most (63.6%) discordant patients with extracranial metastases also had discordance between BM and extracranial subtype. Loss of receptor expression was generally associated with worse survival, which appeared to be driven by estrogen loss (hazard ratio = 1.80, P = 0.03). Patients gaining HER2 status (n = 8) showed a nonsignificant tendency toward improved survival (hazard ratio = 0.64, P = 0.17).

Conclusions

In this multicenter study, we report incidence and predictors of subtype switching, the risk of which varies considerably by baseline subtype. Switches can have clinical implications for prognosis and treatment choice.

Systematic review and meta-analysis of breast cancer brain metastasis and primary tumor receptor expression discordance

Background

Change in hormone receptor (estrogen [ER] and progesterone [PR]) and/or human epidermal growth factor receptor type 2 (HER2) status during the evolutionary course of metastatic breast cancer and the effect of tumor classification subtype switching remain understudied and underappreciated in brain metastasis patients.

Methods

Using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, a systematic review of series published prior to April 2020 obtained from the Medline database of biopsied or resected breast cancer brain metastasis (BCBM) was performed. Weighted random effects models were used to calculate pooled estimates.

Results

15 full-text articles were included with receptor expression analyses on 1373 patients who underwent biopsy or resection of at least one intracranial lesion to compare to the primary tumor. Primary tumor receptor expression immunophenotypes were 45.0% ER+, 41.0% ER−, 31.0% PR+, 51.0% PR−, 35% HER2+, and 47.0% HER2−. Corresponding BCBM immunophenotypes were 19.0% ER+, 31.0% ER−, 13.0% PR+, 40.0% PR−, 21.0% HER2+, and 26.0% HER2−. On primary/BCBM comparison, 540 patients (42.6%) exhibited discordance in any receptor with 17.0% (95% CI: 13.0%–23.0%) discordant on ER, 23.0% (95% CI: 18.0%–30.0%) discordant on PR, and 12.0% (95% CI: 8.0%–16.0%) discordant on HER2 status. The most common receptor conversions found in BCBM were ER loss 11.0% (95% CI: 8.0%–16.0%), PR loss 15.0% (95% CI: 11.0%–21.0%), and HER2 gain 9.0% (95% CI: 7.0%–11.0%).

Conclusions

BCBM exhibits significant receptor expression discordance in comparison to primary tumors in approximately 40% of patients. Classification patterns need to be analyzed to determine factors predictive of BCBM/primary tumor discordance. Overall, tumor subtype switching and its effect on clinical management remains underappreciated.

Molecular intrinsic versus clinical subtyping in breast cancer: A comprehensive review

Breast cancer is a heterogeneous disease manifesting diversity at the molecular, histological and clinical level. The development of breast cancer classification was centered on informing clinical decisions. The current approach to the classification of breast cancer, which categorizes this disease into clinical subtypes based on the detection of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and proliferation marker Ki67, is not ideal. This is manifested as a heterogeneity of therapeutic responses and outcomes within the clinical subtypes. The newer classification model, based on gene expression profiling (intrinsic subtyping) informs about transcriptional responses downstream from IHC single markers, revealing deeper appreciation for the disease heterogeneity and capturing tumor biology in a more comprehensive way than an expression of a single protein or gene alone. While accumulating evidences suggest that intrinsic subtypes provide clinically relevant information beyond clinical surrogates, it is imperative to establish whether the current conventional immunohistochemistry-based clinical subtyping approach could be improved by gene expression profiling and if this approach has a potential to translate into clinical practice.

MRI-Based Radiomic Signature as a Prognostic Biomarker for HER2-Positive Invasive Breast Cancer Treated with NAC

Purpose

To identify MRI-based radiomics signature (Rad-score) as a biomarker of risk stratification for disease-free survival (DFS) in patients with HER2-positive invasive breast cancer treated with trastuzumab-based neoadjuvant chemotherapy (NAC) and establish a radiomics-clinicoradiologic-based nomogram that combines Rad-score, MRI findings, and clinicopathological variables for DFS estimation.

Patients and Methods

A total of 127 patients were divided into a training set and testing set according to the ratio of 7:3. Radiomic features were extracted from multiphase CE-MRI (CE_m). Rad-score was calculated using the LASSO (least absolute shrinkage and selection operator) regression analysis. The cutoff point of Rad-score to divide the patients into high- and low-risk groups was determined by receiver operating characteristic curve analysis. A Kaplan–Meier survival curves and the Log rank test were used to investigate the association of the Rad-score with DFS. Univariate and multivariate Cox proportional hazards model were used to determine the association of Rad-score, MRI features, and clinicopathological variables with DFS. A radiomics-clinicoradiologic-based nomogram combining the Rad-score, MRI features, and clinicopathological findings was plotted to validate the radiomic signatures for DFS estimation.

Results

The Rad-score stratified patients into high- and low-risk groups for DFS in the training set (P<0.0001) and was validated in the testing set (P=0.002). The radiomics-clinicoradiologic-based nomogram estimated DFS (training set: C-index=0.974, 95% confidence interval (CI)=0.954–0.994; testing set: C-index=0.917, 95% CI=0.842–0.991) better than the clinicoradiologic-based nomogram (training set: C-index=0.855, 95% CI=0.739–0.971; testing set: C-index=0.831, 95% CI=0.643–0.999).

Conclusion

The Rad-score is an independent biomarker for the estimation of DFS in invasive HER2-positive breast cancer with NAC and the radiomics-clinicoradiologic-based nomogram improved individualized DFS estimation.

Deep computational pathology in breast cancer

Deep Learning (DL) algorithms are a set of techniques that exploit large and/or complex real-world datasets for cross-domain and cross-discipline prediction and classification tasks. DL architectures excel in computer vision tasks, and in particular image processing and interpretation. This has prompted a wave of disruptingly innovative applications in medical imaging, where DL strategies have the potential to vastly outperform human experts. This is particularly relevant in the context of histopathology, where whole slide imaging (WSI) of stained tissue in conjuction with DL algorithms for their interpretation, selection and cancer staging are beginning to play an ever increasing role in supporting human operators in visual assessments. This has the potential to reduce everyday workload as well as to increase precision and reproducibility across observers, centers, staining techniques and even pathologies. In this paper we introduce the most common DL architectures used in image analysis, with a focus on histopathological image analysis in general and in breast histology in particular. We briefly review how, state-of-art DL architectures compare to human performance on across a number of critical tasks such as mitotic count, tubules analysis and nuclear pleomorphism analysis. Also, the development of DL algorithms specialized to pathology images have been enormously fueled by a number of world-wide challenges based on large, multicentric image databases which are now publicly available. In turn, this has allowed most recent efforts to shift more and more towards semi-supervised learning methods, which provide greater flexibility and applicability. We also review all major repositories of manually labelled pathology images in breast cancer and provide an in-depth discussion of the challenges specific to training DL architectures to interpret WSI data, as well as a review of the state-of-the-art methods for interpretation of images generated from immunohistochemical analysis of breast lesions. We finally discuss the future challenges and opportunities which the adoption of DL paradigms is most likely to pose in the field of pathology for breast cancer detection, diagnosis, staging and prognosis. This review is intended as a comprehensive stepping stone into the field of modern computational pathology for a transdisciplinary readership across technical and medical disciplines.

Progress and Future Trends in PET/CT and PET/MRI Molecular Imaging Approaches for Breast Cancer

Breast cancer is a major disease with high morbidity and mortality in women worldwide. Increased use of imaging biomarkers has been shown to add more information with clinical utility in the detection and evaluation of breast cancer. To date, numerous studies related to PET-based imaging in breast cancer have been published. Here, we review available studies on the clinical utility of different PET-based molecular imaging methods in breast cancer diagnosis, staging, distant-metastasis detection, therapeutic and prognostic prediction, and evaluation of therapeutic responses. For primary breast cancer, PET/MRI performed similarly to MRI but better than PET/CT. PET/CT and PET/MRI both have higher sensitivity than MRI in the detection of axillary and extra-axillary nodal metastases. For distant metastases, PET/CT has better performance in the detection of lung metastasis, while PET/MRI performs better in the liver and bone. Additionally, PET/CT is superior in terms of monitoring local recurrence. The progress in novel radiotracers and PET radiomics presents opportunities to reclassify tumors by combining their fine anatomical features with molecular characteristics and develop a beneficial pathway from bench to bedside to predict the treatment response and prognosis of breast cancer. However, further investigation is still needed before application of these modalities in clinical practice. In conclusion, PET-based imaging is not suitable for early-stage breast cancer, but it adds value in identifying regional nodal disease and distant metastases as an adjuvant to standard diagnostic imaging. Recent advances in imaging techniques would further widen the comprehensive and convergent applications of PET approaches in the clinical management of breast cancer.

Intense basolateral membrane staining indicates HER2 positivity in invasive micropapillary breast carcinoma

Invasive micropapillary carcinoma is characterized by the inside-out growth of tumor clusters and displays incomplete membrane immunostaining of HER2. According to the 2018 American Society of Clinical Oncology and the College of American Pathologists (ASCO/CAP) HER2-testing recommendation, moderate to intense but incomplete staining could be scored as immunohistochemical 2+. Furthermore, the criteria of immunohistochemical 3+ for this staining pattern are not mentioned. One hundred and forty-seven cases of invasive micropapillary carcinoma with moderate-to-intense HER2 immunostaining were enrolled. Invasive micropapillary carcinoma components of all cases were scored as immunohistochemical 2+ based on the 2018 ASCO/CAP recommendation. The invasive micropapillary carcinoma component varied from 10% to 100% (mean, 80%). Invasive micropapillary carcinoma components of all 147 tumors exhibited reversed polarity and incomplete basolateral HER2 membrane staining. One hundred and seventeen of the tumors (80%, 117/147) had moderate staining, and 38 (32%, 38/117) showed HER2 gene amplification by fluorescence in-situ hybridization. HER2 gene was amplified in all the remaining 30 tumors (20%, 30/147) that exhibited intense basolateral membrane staining. Besides, average HER2 signals per cell and ratio of HER2/CEP17 were significantly higher in the intense-staining tumors compared with the moderate-staining tumors (p < 0.0001). Follow-up data were available for 140 patients. None of the patients were died. The follow-up time ranged from 1 month to 99 months (median, 57 months). Thirteen (9%, 13/140) patients exhibited disease progression (recurrence or metastasis). HER2 gene amplification was correlated inversely with estrogen receptor (p = 0.000) and progesterone receptor (p = 0.000) expression, and positively with histological grade (p = 0.003) and disease progression (p = 0.000). Invasive micropapillary carcinoma with intense clear linear basolateral membrane immunostaining indicates HER2 positivity, even if the staining is incomplete. They should be classified as immunohistochemical 3+ rather than immunohistochemical 2+, which would avoid further fluorescence in-situ hybridization-testing procedure and greatly save the related time, labor, and financial costs. Ultimately, ensure all patients with HER2 gene amplification obtain effective targeted therapy in time.

Estrogen Receptor, Progesterone Receptor, and Human Epidermal Growth Factor Receptor-2 Testing in Breast Cancer: Assessing the Value of Repeated Centralized Testing in Excision Specimens

At some tertiary breast care centers, where many patients are referred from other institutions, it is routine to repeat testing for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2/neu) in excision specimens if these tests were performed on the preceding biopsy at the referring facility. The goal of this study is to assess the value of this practice. We documented results from ER, PR, and HER2 testing in 541 consecutive invasive breast cancers excised over a 2.5-year period and analyzed the subset (n=153) for which testing was performed on the excision specimen solely due to the fact that testing on the preceding biopsy was performed at an outside institution. The rates and directions of biopsy-to-excision change were as follows: ER [1.3% (2/153), 100% from (+) to (-)]; PR [4% (6/153), 83% from (+) to (-)]; HER2/neu assessed by immunohistochemistry [21% (29/137)]; HER2/neu assessed by fluorescence in situ hybridization [3.3% (2/61); 50% from amplified to nonamplified and 50% vice versa]. There were no ER(-) and PR(-) biopsy cases that became ER and/or PR(+) in the excision. By coordinate analysis for the hormone receptors [ie, ER and/or PR(+) being indicative of "hormone receptor" (HR) positivity], there were no cases that changed from HR(+) in the biopsy to HR(-) in the excision (or vice versa), which suggests that repeat testing for ER and PR in this setting is of limited value. In an analysis that incorporated both immunohistochemistry and in situ fluorescence hybridization results, there were 2 cases with a clinically significant biopsy-to-excision change in HER2/neu status in which that change was detected primarily because the excision was retested. These findings provide baseline data for formulating policies on whether repeat testing should routinely be performed in the described scenario.

Comparison of Dako HercepTest and Ventana PATHWAY Anti-HER2 (4B5) Tests and Their Correlation With Fluorescent In Situ Hybridization in Breast Carcinoma

OBJECTIVES

We compared the performance of two Food and Drug Administration-approved HER2 immunohistochemistry (IHC) tests: HercepTest (Dako) and PATHWAY anti-HER2 (4B5) (Ventana).

MATERIALS AND METHODS

In total, 180 invasive breast carcinomas previously tested by both HercepTest and fluorescent in situ hybridization (FISH) were retested with 4B5. Three pathologists scored the HER2 IHC using the 2013 American Society of Clinical Oncology/College of American Pathologists guidelines. The HER2 IHC results were correlated with FISH.

RESULTS

Among 135 equivocal cases by HercepTest, 100 (74.1%) were negative by 4B5. Among 45 positive HercepTest cases 9 (20%) were equivocal by 4B5. Among 135 equivocal HercepTest results, 100 (74.1%) were nonamplified, 18 (13.3%) equivocal, and 17 (12.6%) amplified by FISH. Among the 45 positive results with HercepTest, 2 (4.5%) were nonamplified and 1 (2.2%) was equivocal by FISH. All 37 positive and 3 negative by 4B5 cases were amplified by FISH. The absolute interobserver agreement was high for both tests (Fleiss kappa=0.838 for HercepTest and 0.771 for 4B5).

CONCLUSIONS

PATHWAY anti-HER2 (4B5) significantly reduced the number of equivocal results that require additional testing. Although HercepTest was positive in a small number of HER2 nonamplified cases, 4B5 failed to detect 3 cases that were interpreted as positive by FISH, all with nonclassic or low levels of amplification.

Applying the New Guidelines of HER2 Testing in Breast Cancer

PURPOSE OF REVIEW

The human epidermal growth factor receptor 2 (HER2) is an important prognostic and predictive biomarker in the breast cancer. The American Society of Clinical Oncology/College of American Pathology (ASCO/CAP) has published HER2 testing guidelines in breast cancer. We herein reviewed the HER2 testing guidelines in breast cancer with a focus on the application of the current guidelines.

RECENT FINDINGS

The continual investigation of HER2 testing in breast cancer has resulted in updates in the HER2 testing guidelines. The current guidelines focus on the uncommon clinical scenarios and emphasize the coordination between immunohistochemistry and in situ hybridization results, in an effort to improve clarity and accuracy. The ASCO/CAP guidelines provide valuable recommendations to ensure the accurate evaluation of HER2 status in breast cancer patients through standardization. Additional studies, particularly those with long-term outcome data are still needed to validate the guideline recommendations, especially the uncommon cases.

Re-evaluation of HER2 status in 606 breast cancers-gene protein assay on tissue microarrays versus routine pathological assessment

Human epidermal growth factor receptor 2 (HER2) status in breast cancer is routinely determined through immunohistochemistry (IHC) and/or in situ hybridisation (ISH) performed on whole tissue sections (WS). The purpose was to evaluate whether a gene protein assay (GPA) combining IHC with ISH, performed on breast cancer tissue microarray (TMA), is suitable for large-scale retrospective HER2 status evaluation. TMAs from 606 tumours from a Swedish population-based cohort (2005-2012) were stained with GPA. GPA IHC on TMA yielded weaker staining than IHC on WS during routine pathological assessment (86.0% agreement). However, final HER2 status agreement between GPA on TMA and WS based on both IHC and ISH was 97.7%. Only 14 tumours were discordant and one tumour with IHC score 1+ on both TMA and WS was HER2 amplified on TMA. In conclusion, GPA on TMA is suitable for large-scale retrospective evaluation of HER2 status.

Learning Where to See: A Novel Attention Model for Automated Immunohistochemical Scoring

Estimating over-amplification of human epidermal growth factor receptor 2 (HER2) on invasive breast cancer is regarded as a significant predictive and prognostic marker. We propose a novel deep reinforcement learning (DRL)-based model that treats immunohistochemical (IHC) scoring of HER2 as a sequential learning task. For a given image tile sampled from multi-resolution giga-pixel whole slide image (WSI), the model learns to sequentially identify some of the diagnostically relevant regions of interest (ROIs) by following a parameterized policy. The selected ROIs are processed by recurrent and residual convolution networks to learn the discriminative features for different HER2 scores and predict the next location, without requiring to process all the sub-image patches of a given tile for predicting the HER2 score, mimicking the histopathologist who would not usually analyze every part of the slide at the highest magnification. The proposed model incorporates a task-specific regularization term and inhibition of return mechanism to prevent the model from revisiting the previously attended locations. We evaluated our model on two IHC datasets: a publicly available dataset from the HER2 scoring challenge contest and another dataset consisting of WSIs of gastroenteropancreatic neuroendocrine tumor sections stained with Glo1 marker. We demonstrate that the proposed model outperforms other methods based on state-of-the-art deep convolutional networks. To the best of our knowledge, this is the first study using DRL for IHC scoring and could potentially lead to wider use of DRL in the domain of computational pathology reducing the computational burden of the analysis of large multi-gigapixel histology images.

High Fidelity of Breast Biomarker Metrics: A 10-Year Experience in a Single, Large Academic Institution

PURPOSE

Recommendations for standardization of breast biomarkers including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 (HER2) led to the creation of American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guidelines to provide continuous guidance. Included in these recommendations is the "ongoing assay assessment procedures." We report these biomarker metrics as there is a dearth of published information on this topic.

MATERIALS AND METHODS

ER, PR, and HER2 positivity rates of all newly diagnosed, recurrent, and metastatic invasive breast cancers on core biopsies, and repeated testing on resection specimen by immunohistochemistry (IHC) and/or fluorescence in situ hybridization (FISH) were collected from April 1, 2008 to December 31, 2017.

RESULTS

The positivity rates of ER, PR, and HER2 over almost 10 years of monitoring showed high fidelity. Total ER-positive rate was 83.6% (81.4% to 86.8%), ER+/PR+ was 71.7% (68.6% to 75.5%), ER+/PR- was 17.6% (11.0% to 15.0%), ER-/PR- was 16.0% (13.5% to 18.2%), and ER-/PR+ was 0.6% (0.2% to 1.0%). The HER2-positive rate was 13.7% (10.2% to 17.4%) including 9.9% (7.3% to 11.9%) by IHC and 3.8% (1.9% to 5.9%) by FISH reflexed from IHC 2+ results. FISH amplification rate of HER2 IHC 2+ cases was 11.0% (5.8% to 19.2%). Annual quality-assurance check for HER2 IHC/FISH percent positive and percent negative agreement (as defined by Food and Drug Administration) was 96% to 100%.

CONCLUSIONS

This longitudinal active assessment of 9564 breast biomarker cases shows the achievement of high fidelity of breast biomarker results when following the ASCO/CAP guidelines. Continuous monitoring of breast biomarkers may minimize assay analytical drift and assure quality clinically relevant results.

Targeted therapeutic options and future perspectives for HER2-positive breast cancer

Over the past 2 decades, there has been an extraordinary progress in the regimens developed for the treatment of human epidermal growth factor receptor 2 (HER2)-positive breast cancer. Trastuzumab, pertuzumab, lapatinib, and ado-trastuzumab emtansine (T-DM1) are commonly recommended anti-HER2 target agents by the U.S. Food and Drug Administration. This review summarizes the most significant and updated research on clinical scenarios related to HER2-positive breast cancer management in order to revise the guidelines of everyday clinical practices. In this article, we present the data on anti-HER2 clinical research of neoadjuvant, adjuvant, and metastatic studies from the past 2 decades. We also highlight some of the promising strategies that should be critically considered. Lastly, this review lists some of the ongoing clinical trials, findings of which may soon be available.

Receptor Conversion in Distant Breast Cancer Metastases: A Systematic Review and Meta-analysis

Background

In metastatic breast cancer, hormone and/or human epidermal growth factor receptor 2 (HER2)-targeted therapy decision-making is still largely based on tissue characteristics of the primary tumor. However, a change of estrogen receptor alpha (ERα), progesterone receptor (PR), and HER2 status in distant metastases has frequently been reported. The actual incidence of this phenomenon has been debated.

Methods

We performed a meta-analysis including 39 studies assessing receptor conversion from primary breast tumors to paired distant breast cancer metastases. We noted the direction of change (positive to negative or vice versa) and performed subgroup analyses for different thresholds for positivity, the type of test used to assess HER2 receptor status, and metastasis location-specific differences (two-sided tests).

Results

Overall, the incidence of receptor conversion varied largely between studies. For ERα, PR, and HER2, we found that random effects pooled positive to negative conversion percentages of 22.5% (95% confidence interval [CI] = 16.4% to 30.0%), 49.4% (95% CI = 40.5% to 58.2%), and 21.3% (95% CI = 14.3% to 30.5%), respectively. Negative to positive conversion percentages were 21.5% (95% CI = 18.1% to 25.5%), 15.9% (95% CI = 11.3% to 22.0%), and 9.5% (95% CI = 7.4% to 12.1%). Furthermore, ERα discordance was statistically significantly higher in the central nervous system and bone compared with liver metastases (20.8%, 95% CI = 15.0% to 28.0%, and 29.3%, 95% CI = 13.0% to 53.5%, vs 14.3%, 95% CI = 11.3% to 18.1, P = .008 and P < .001, respectively), and PR discordance was higher in bone (42.7%, 95% CI = 35.1% to 50.6%, P < .001) and liver metastases (47.0%, 95% CI = 41.0% to 53.0%, P < .001) compared with central nervous system metastases (23.3%, 95% CI = 16.0% to 32.6%).

Conclusions

Receptor conversion for ERα, PR, and HER2 occurs frequently in the course of disease progression in breast cancer. Large prospective studies assessing the impact of receptor conversion on treatment efficacy and survival are needed. Meanwhile, reassessing receptor status in metastases is strongly encouraged.

Comparison of Dual-ISH (DISH) With Fluorescence In Situ Hybridization (FISH) and Correlation With Immunohistochemical Findings for HER2/Neu Status in Breast Carcinoma

INTRODUCTION

The most widely used methods for determination of HER2/neu status in breast carcinoma are immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). Both techniques are associated with technical and interpretive difficulties. Alternative methods exist including quantitative PCR and the newly developed chromogenic dual in situ hybridization (DISH).

METHODS

We evaluated HER2 DISH as an alternative to FISH and report our findings from 101 cases. In addition, we correlated HER2 DISH and FISH results with HercepTest and 4B5 immunohistochemistry.

RESULTS

Eight cases failed FISH analysis and none failed DISH analysis. A 95% (88/93) concordance was found between DISH and FISH for all cases in the series. When only 2+ IHC cases were evaluated, the concordance was 94% for DISH and FISH. Using the 2013 ASCO/CAP recommendations, none of the tested cases were equivocal by FISH or DISH despite 66% of cases being 2+ by HercepTest and 32% by the 4B5 antibody.

COMMENT

Our study, which utilizes a majority of IHC equivocal cases, demonstrates that HER2 FISH and DISH are concordant methodologies. HER2 DISH is therefore an acceptable alternative to FISH.

The Impact of Partial Weak Staining in Normal Breast Epithelium on the Reliability of Immunohistochemistry Results in HercepTest-positive Breast Cancer

INTRODUCTION

Although normal epithelial cells do not show human epidermal growth factor receptor-2 (HER2) gene amplification and should lack membrane staining by HER2 immunohistochemistry (IHC), HER2 staining in benign breast epithelium is occasionally encountered. The significance of this occurrence has not yet been adequately studied, and its associated American Society of Clinical Oncology/College of American Pathologists recommendations are vague. Our objective is to assess the correlation between HER2 IHC 3+ breast cancer cases with normal epithelium staining (NES) and their corresponding fluorescence in situ hybridization (FISH) results, and to suggest recommendations for interpretation.

MATERIALS AND METHODS

A total of 154 breast cancer cases with HER2 IHC 3+ were reviewed. NES, along with other clinicopathologic characteristics, were recorded. NES was scored as present or absent. All study cases were sent for FISH testing. All cases, and particularly those that showed false positivity for IHC (positive IHC, negative FISH) were examined for NES.

RESULTS

Of the 154 cases, 146 cases were FISH-positive (94.8%) and 2 failed FISH testing (1.3%). Conversely, 22% (34/154) of the cases showed NES for HER2. Of these 34 cases, 23 (67%) were FISH-amplified, 9 (26%) were FISH not amplified, and 2 failed FISH testing. Notably, all of the false-positive (FISH-negative) breast cancer cases showed some degree of positivity in normal breast epithelium.

CONCLUSIONS

Our findings, though descriptive, show a very strong association between NES and false-positive HER2 IHC. This confirms the need to carefully evaluate IHC-positive breast cancers for NES, and to have a low threshold for confirmatory testing by FISH.

Robust identification of molecular phenotypes using semi-supervised learning

BACKGROUND

Modern molecular profiling techniques are yielding vast amounts of data from patient samples that could be utilized with machine learning methods to provide important biological insights and improvements in patient outcomes. Unsupervised methods have been successfully used to identify molecularly-defined disease subtypes. However, these approaches do not take advantage of potential additional clinical outcome information. Supervised methods can be implemented when training classes are apparent (e.g., responders or non-responders to treatment). However, training classes can be difficult to define when assessing relative benefit of one therapy over another using gold standard clinical endpoints, since it is often not clear how much benefit each individual patient receives.

RESULTS

We introduce an iterative approach to binary classification tasks based on the simultaneous refinement of training class labels and classifiers towards self-consistency. As training labels are refined during the process, the method is well suited to cases where training class definitions are not obvious or noisy. Clinical data, including time-to-event endpoints, can be incorporated into the approach to enable the iterative refinement to identify molecular phenotypes associated with a particular clinical variable. Using synthetic data, we show how this approach can be used to increase the accuracy of identification of outcome-related phenotypes and their associated molecular attributes. Further, we demonstrate that the advantages of the method persist in real world genomic datasets, allowing the reliable identification of molecular phenotypes and estimation of their association with outcome that generalizes to validation datasets. We show that at convergence of the iterative refinement, there is a consistent incorporation of the molecular data into the classifier yielding the molecular phenotype and that this allows a robust identification of associated attributes and the underlying biological processes.

CONCLUSIONS

The consistent incorporation of the structure of the molecular data into the classifier helps to minimize overfitting and facilitates not only good generalization of classification and molecular phenotypes, but also reliable identification of biologically relevant features and elucidation of underlying biological processes.

The FDA-Approved Breast Cancer HER2 Evaluation Kit (HercepTest; Dako) May Miss Some HER2-Positive Breast Cancers

OBJECTIVES

Accurate evaluation of human epidermal growth factor receptor 2 (HER2) in breast cancer is critical.

METHODS

HER2 fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) tests were performed on 52 cases using a US Food and Drug Administration (FDA)-approved kit (HercepTest, FDA kit) and a laboratory-developed test (LDT) with the HercepTest antibody and a Leica Bond automated stainer.

RESULTS

By FISH, 22 were HER2 positive, 29 were negative, and one was equivocal. Of the 22 HER2 FISH-positive cases, five were negative by the FDA kit and none by LDT. The five discrepant cases were retested using the same FDA kit in another Clinical Laboratory Improvement Amendments-certified laboratory, and all five cases were still negative. None of the 29 HER2 FISH-negative cases were positive by the FDA kit or LDT. The overall IHC-FISH concordance rate was 90.4% for the FDA kit and 100% for the LDT.

CONCLUSIONS

The FDA kit may miss some HER2-positive cases. The LDT has a higher sensitivity and a higher concordance rate with FISH results.

HER2 testing in gastric cancer diagnosis: insights on variables influencing HER2-positivity from a large, multicenter, observational study in Germany

HER2 testing in metastatic gastric or gastroesophageal junction cancer (mGC/mGEJC) is standard practice. Variations in HER2-positivity rates suggest factors affecting test quality; however, the influence of patient-, tumor-, and laboratory-related factors on HER2-positivity rates remains unknown. This observational, prospective study collected routine HER2 testing data from 50 pathology centers in Germany (January 2013-December 2015). For each sample, HER2 status, primary tumor location, method of sample retrieval, and other patient- and tumor-related parameters were recorded. A model for predicting the probability of HER2-positivity was developed using stepwise multiple logistic regression to identify influencing factors. Documented positivity rates and corresponding predicted HER2-positivity probabilities were compared to identify institutes with deviations in HER2-positivity. Data from 2761 mGC/mGEJC routine diagnostic specimens included 2033 with HER2 test results (1554 mGC, 479 mGEJC); overall HER2-positivity rates across centers were 19.8% and 30.5%, respectively. HER2-positivity correlated most with Lauren classification, then HER2 testing rate, primary tumor location, sample type, and testing method (all p < 0.05). Three institutes had model-predicted HER2-positivity rates outside the 95% confidence interval of their documented rate, which could not be explained by sample and center characteristics. Results demonstrated the high quality of routine HER2 testing in the mGC/mGEJC cohort analyzed. This is the first study investigating parameters impacting on HER2-positivity rates in mGC/mGEJC in routine practice and suggests that assessment of HER2 testing quality should consider primary tumor location, testing method and rate, and tumor characteristics. Accurate identification of patients with HER2-positive mGC/mGEJC is essential for appropriate use of HER2-targeted therapies.

Hormone- and HER2-receptor assessment in 33,046 breast cancer patients: a nationwide comparison of positivity rates between pathology laboratories in the Netherlands

Purpose

Patient management of invasive breast cancer (IBC) is to a large extent based on hormone- and HER2-receptor assessment. High-quality, reliable receptor assessment is of key importance as false results may lead to under- or overtreatment of patients. Surveillance of case-mix adjusted positivity rates has been suggested as a tool to identify laboratories with insufficient testing assays, as this covers the whole process of receptor assessment and enables laboratories to benchmark their positivity rates against other laboratories. We studied laboratory-specific variation in hormone- and HER2 positivity rates of 33,046 breast cancer patients using real-life nationwide data.

Methods

All synoptic pathology reports of IBC resection-specimens, obtained between 2013 and 2016, were retrieved from the nationwide Dutch pathology registry (PALGA). Absolute and case-mix adjusted receptor positivity rates were compared to the mean national proportion and presented in funnel plots in separate analyses for estrogen (ER), progesterone (PR) and HER2. Case-mix adjustment was performed by multivariable logistic regression.

Results

33,794 IBC lesions from 33,046 patients of 39 pathology laboratories were included. After case-mix adjustment, mean positivity rates were 87.2% for ER (range 80.4–94.3), 71.3% for PR (62.5–77.5%), and 9.9% for HER2 (5.5–12.7%). Overall, 14 (35.9%), 17 (43.6%) and 11 (28.2%) laboratories showed positivity rates outside the 95% confidence interval for ER, PR and HER2, respectively.

Conclusion

This nationwide study shows that absolute variation in hormone- and HER2-receptor positivity rates between Dutch pathology laboratories is limited. Yet, the considerable number of outlying laboratories shows that there is still need for improvement. Continuous monitoring and benchmarking of positivity rates may help to realize this.