What is the added value of digital image analysis of HER2 immunohistochemistry in breast cancer in clinical practice? A study with multiple platforms

Fully Automated Artificial Intelligence Solution for Human Epidermal Growth Factor Receptor 2 Immunohistochemistry Scoring in Breast Cancer: A Multireader Study

PURPOSE

The proven efficacy of human epidermal growth factor receptor 2 (HER2) antibody-drug conjugate therapy for treating HER2-low breast cancers necessitates more accurate and reproducible HER2 immunohistochemistry (IHC) scoring. We aimed to validate performance and utility of a fully automated artificial intelligence (AI) solution for interpreting HER2 IHC in breast carcinoma.

MATERIALS AND METHODS

A two-arm multireader study of 120 HER2 IHC whole-slide images from four sites assessed HER2 scoring by four surgical pathologists without and with the aid of an AI HER2 solution. Both arms were compared with high-confidence ground truth (GT) established by agreement of at least four of five breast pathology subspecialists according to ASCO/College of American Pathologists (CAP) 2018/2023 guidelines.

RESULTS

The mean interobserver agreement among GT pathologists across all HER2 scores was 72.4% (N = 120). The AI solution demonstrated high accuracy for HER2 scoring, with 92.1% agreement on slides with high confidence GT (n = 92). The use of the AI tool led to improved performance by readers, interobserver agreement increased from 75.0% for digital manual read to 83.7% for AI-assisted review, and scoring accuracy improved from 85.3% to 88.0%. For the distinction of HER2 0 from 1+ cases (n = 58), pathologists supported by AI showed significantly higher interobserver agreement (69.8% without AI v 87.4% with AI) and accuracy (81.9% without AI v 88.8% with AI).

CONCLUSION

This study demonstrated utility of a fully automated AI solution to aid in scoring HER2 IHC accurately according to ASCO/CAP 2018/2023 guidelines. Pathologists supported by AI showed improvements in HER2 IHC scoring consistency and accuracy, especially for distinguishing HER2 0 from 1+ cases. This AI solution could be used by pathologists as a decision support tool for enhancing reproducibility and consistency of HER2 scoring and particularly for identifying HER2-low breast cancers.

Understanding the spectrum of HER2 status in breast cancer: From HER2-positive to ultra-low HER2

HER2 (human epidermal growth factor receptor 2) status in breast cancer spans a spectrum from HER2-positive to ultra-low HER2, each category influencing prognosis and treatment decisions differently. Approximately 20 % of breast cancers overexpress HER2, correlating with aggressive disease and poorer outcomes without targeted therapy. HER2 status is determined through immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH), guiding therapeutic strategies. HER2-positive breast cancer exhibits HER2 protein overexpression or gene amplification, benefiting from HER2-targeted therapies like trastuzumab and pertuzumab. In contrast, HER2-negative breast cancer lacks HER2 overexpression and amplification, treated based on hormone receptor status. HER2-low breast cancer represents a newly recognized category with low HER2 expression, potentially benefiting from evolving therapies. Ultra-low HER2 cancers, characterized by minimal expression without gene amplification, challenge conventional classifications and treatment paradigms. Their distinct molecular profiles and clinical behaviors suggest unique therapeutic approaches. Recent diagnostic guideline updates refine HER2 assessment, enhancing precision in identifying patients for targeted therapies. Challenges remain in accurately classifying HER2-low tumors and optimizing treatment efficacy, necessitating ongoing research and innovative diagnostic methods. Understanding the heterogeneity and evolving landscape of HER2 status in breast cancer is crucial for advancing personalized treatment strategies and improving patient outcomes.

Human epidermal growth factor receptor 2 (HER2) status in breast cancer: practice points and challenges

Human epidermal growth factor receptor 2 (HER2)-enriched breast cancer benefits significantly from anti-HER2 targeted therapies. This highlights the critical need for precise HER2 immunohistochemistry (IHC) interpretation serving as a triage tool for selecting patients for anti-HER2 regimens. Recently, the emerging eligibility of patients with HER2-low breast cancers for a novel HER2-targeted antibody-drug conjugate (T-DXd) adds challenges to HER2 IHC scoring interpretation, notably in the 0-1+ range, which shows high interobserver and interlaboratory staining platform variability. In this review, we navigate evolving challenges and suggest practical recommendations for HER2 IHC interpretation.

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.

The Performance and Clinical Applicability of HER2 Digital Image Analysis in Breast Cancer: A Systematic Review

This systematic review aims to address the research gap in the performance of computational algorithms for the digital image analysis of HER2 images in clinical settings. While numerous studies have explored various aspects of these algorithms, there is a lack of comprehensive evaluation regarding their effectiveness in real-world clinical applications. We conducted a search of the Web of Science and PubMed databases for studies published from 31 December 2013 to 30 June 2024, focusing on performance effectiveness and components such as dataset size, diversity and source, ground truth, annotation, and validation methods. The study was registered with PROSPERO (CRD42024525404). Key questions guiding this review include the following: How effective are current computational algorithms at detecting HER2 status in digital images? What are the common validation methods and dataset characteristics used in these studies? Is there standardization of algorithm evaluations of clinical applications that can improve the clinical utility and reliability of computational tools for HER2 detection in digital image analysis? We identified 6833 publications, with 25 meeting the inclusion criteria. The accuracy rate with clinical datasets varied from 84.19% to 97.9%. The highest accuracy was achieved on the publicly available Warwick dataset at 98.8% in synthesized datasets. Only 12% of studies used separate datasets for external validation; 64% of studies used a combination of accuracy, precision, recall, and F1 as a set of performance measures. Despite the high accuracy rates reported in these studies, there is a notable absence of direct evidence supporting their clinical application. To facilitate the integration of these technologies into clinical practice, there is an urgent need to address real-world challenges and overreliance on internal validation. Standardizing study designs on real clinical datasets can enhance the reliability and clinical applicability of computational algorithms in improving the detection of HER2 cancer.

Consensus Guidelines on Human Epidermal Growth Factor Receptor 2 (HER2)-Low Testing in Breast Cancer in Malaysia

Breast cancer is one of the most common cancers in Malaysia. Recently, a new nomenclature was introduced for breast cancers with human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) 1+, or 2+ with negative in situ hybridization (ISH), i.e., HER2-low breast cancer. In current clinical practice, these breast cancers are reported as HER2-negative. Clinical trials have shown that HER2-low breast cancer benefits from targeted therapy with anti-HER2 antibody-drug conjugates. Unfortunately, various challenges and obstacles are faced by local pathologists in HER2 testing, which may jeopardize the standard of care for patients with HER2-low breast cancer. This consensus guideline aims to elucidate standard practices pertaining to HER2 testing and HER2-low interpretation in Malaysia. Topics discussed among a panel of local experts include tissue sampling and handling, assay and antibody selection, result interpretation and reporting, and quality assurance. Practice recommendations made in this consensus guideline reflect current international guidelines and, where appropriate, adapted to the Malaysian landscape.

Novel approach to HER2 quantification using phosphor-integrated dots in human breast invasive cancer microarray

HER2 expression in breast cancer is evaluated to select patients for anti-HER2 therapy. With the advent of newly approved HER2-targeted drugs for low HER2 expression breast cancer, more solid evidence on the whole spectrum of HER2 expression is needed. In this study, we quantitatively assessed HER2 expression from the whole core by combining high-intensity phosphor-integrated dot (PID) immunostaining and whole slide imaging (WSI) analysis. Two types of staining were performed using a 170-core tissue microarray of invasive breast cancer. First, HER2 was stained by immunohistochemistry (IHC), and IHC scores were determined by two practicing pathologists according to the ASCO/CAP HER2 guideline. Second, HER2 was stained with PID, and tentative PID scores were determined by quantitative analysis. The results show that PID can numerically classify HER2 expression status into scores 3+, 2+, 1+, and 0. The HER2 value quantified by PID strongly correlated with the 3, 3'-diaminobenzidine (DAB) IHC score determined by pathologists (R2 = 0.93). PID IHC score 1+ cases included both DAB IHC score 1+ and 0 cases, and low HER2 expression cases appeared to be often evaluated as DAB IHC score 0. Therefore, digital image analysis by PID and WSI can help stratify HER2 IHC. It may also help classify low HER2 expression.

Evaluation of the Immunohistochemical Scoring System of CDX2 Expression as a Prognostic Biomarker in Colon Cancer

Encoded by the CDX2 homeobox gene, the CDX2 protein assumes the role of a pivotal transcription factor localized within the nucleus of intestinal epithelial cells, orchestrating the delicate equilibrium of intestinal physiology while intricately guiding the precise development and differentiation of epithelial tissue. Emerging research has unveiled that positive immunohistochemical expression of this protein shows that the CDX2 gene exerts a potent suppressive impact on tumor advancement in colorectal cancer, impeding the proliferation and distant dissemination of tumor cells, while the inhibition or suppression of CDX2 frequently correlates with aggressive behavior in colorectal cancer. In this study, we conducted an immunohistochemical assessment of CDX2 expression on a cohort of 43 intraoperatively obtained tumor specimens from patients diagnosed with colon cancer at Colțea Clinical Hospital in Bucharest, between April 2019 and December 2023. Additionally, we shed light on the morphological diversity within colon tumors, uncovering varying differentiation grades within the same tumor, reflecting the variations in CDX2 expression as well as the genetic complexity underlying these tumors. Based on the findings, we developed an innovative immunohistochemical scoring system that addresses the heterogeneous nature of colon tumors. Comprehensive statistical analysis of CDX2 immunohistochemical expression unveiled significant correlations with known histopathological parameters such as tumor differentiation grades (p-value = 0.011) and tumor budding score (p-value = 0.002), providing intriguing insights into the complex involvement of the CDX2 gene in orchestrating tumor progression through modulation of differentiation processes, and highlighting its role in metastatic predisposition. The compelling correlation identified between CDX2 expression and conventional histopathological parameters emphasizes the prognostic significance of the CDX2 biomarker in colon cancer. Moreover, our novel immunohistochemical scoring system reveals a distinct subset of colon tumors exhibiting reserved prognostic outcomes, distinguished by their "mosaic" CDX2 expression pattern.

Kv 11.1 Expression Is Associated With Malignancy of Canine Mammary Gland Tumors

BACKGROUND/AIM

The expression level of the voltage-dependent potassium channel Kv 11.1 was shown to be associated with the clinicopathological features, aggressiveness, and prognosis of human breast cancer. Canine mammary gland tumor (cMGT) is the most common tumor type in intact female dogs; however, the significance of Kv 11.1 in cMGT is unknown. The aim of this study was to identify Kv 11.1 expression in 57 benign and malignant cMGT tissues from dogs and to investigate the correlation of Kv 11.1 expression with the clinicopathological parameters and prognosis of cMGT.

MATERIALS AND METHODS

A total of 57 samples were collected from cMGTs surgically resected at the Veterinary Medical Teaching Hospital, Seoul National University and subjected to immunohistochemistry assay using rabbit anti-Kv 11.1 polyclonal antibody. Immunohistochemical staining results were evaluated as the sum of intensity and percentage scores. The correlation between immunohistochemistry scores and clinicopathological parameters was investigated.

RESULTS

Immunohistochemical analysis revealed that Kv 11.1 immunoreactivity was higher in benign cMGTs than in malignant cMGTs. Kv 11.1 expression was significantly associated with tumor malignancy (p<0.001), tumor size (p<0.001), histological grade (p<0.05), and age at the time of mastectomy (p<0.05).

CONCLUSION

This study presents the first evidence of Kv 11.1 expression in cMGTs and indicates an inverse correlation between Kv 11.1 expression and tumor malignancy. Kv 11.1 expression can be used as a prognostic biomarker and a tool for the management of cMGTs.

Applications of Artificial Intelligence in Breast Pathology

CONTEXT.—

Increasing implementation of whole slide imaging together with digital workflow and advances in computing capacity enable the use of artificial intelligence (AI) in pathology, including breast pathology. Breast pathologists often face a significant workload, with diagnosis complexity, tedious repetitive tasks, and semiquantitative evaluation of biomarkers. Recent advances in developing AI algorithms have provided promising approaches to meet the demand in breast pathology.

OBJECTIVE.—

To provide an updated review of AI in breast pathology. We examined the success and challenges of current and potential AI applications in diagnosing and grading breast carcinomas and other pathologic changes, detecting lymph node metastasis, quantifying breast cancer biomarkers, predicting prognosis and therapy response, and predicting potential molecular changes.

DATA SOURCES.—

We obtained data and information by searching and reviewing literature on AI in breast pathology from PubMed and based our own experience.

CONCLUSIONS.—

With the increasing application in breast pathology, AI not only assists in pathology diagnosis to improve accuracy and reduce pathologists' workload, but also provides new information in predicting prognosis and therapy response.

HER2 Intratumoral Heterogeneity in Breast Cancer, an Evolving Concept

Amplification and/or overexpression of human epidermal growth factor receptor 2 (HER2) in breast cancer is associated with an adverse prognosis. The introduction of anti-HER2 targeted therapy has dramatically improved the clinical outcomes of patients with HER2-positive breast cancer. Unfortunately, a significant number of patients eventually relapse and develop distant metastasis. HER2 intratumoral heterogeneity (ITH) has been reported to be associated with poor prognosis in patients with anti-HER2 targeted therapies and was proposed to be a potential mechanism for anti-HER2 resistance. In this review, we described the current definition, common types of HER2 ITH in breast cancer, the challenge in interpretation of HER2 status in cases showing ITH and the clinical applications of anti-HER2 agents in breast cancer showing heterogeneous HER2 expression. Digital image analysis has emerged as an objective and reproducible scoring method and its role in the assessment of HER2 status with ITH remains to be demonstrated.

Pathological identification of HER2-low breast cancer: Tips, tricks, and troubleshooting for the optimal test

The introduction of novel anti-HER2 antibody-drug conjugates (ADC) for the treatment of HER2-low breast cancers has transformed the traditional dichotomy of HER2 status to an expanded spectrum. However, the identification of HER2-low (i.e., immunohistochemistry (IHC) score 1 + or IHC score 2+, without gene amplification) tumors is challenged by methodological and analytical variables that might influence the sensitivity and reproducibility of HER2 testing. To open all possible therapeutic opportunities for HER2-low breast cancer patients the implementation of more accurate and reproducible testing strategies is mandatory. Here, we provide an overview of the existing barriers that may trouble HER2-low identification in breast cancer and discuss practical solutions that could enhance HER-low assessment.

The Role of Artificial Intelligence in Accurate Interpretation of HER2 Immunohistochemical Scores 0 and 1+ in Breast Cancer

The new human epidermal growth factor receptor (HER)2-targeting antibody-drug conjugate offers the opportunity to treat patients with HER2-low breast cancer. Distinguishing HER2 immunohistochemical (IHC) scores of 0 and 1+ is not only critical but also challenging owing to HER2 heterogeneity and variability of observers. In this study, we aimed to increase the interpretation accuracy and consistency of HER2 IHC 0 and 1+ evaluation through assistance from an artificial intelligence (AI) algorithm. In addition, we examined the value of our AI algorithm in evaluating HER2 IHC scores in tumors with heterogeneity. AI-assisted interpretation consisted of AI algorithms and an augmenting reality module with a microscope. Fifteen pathologists (5 junior, 5 midlevel, and 5 senior) participated in this multi-institutional 2-round ring study that included 246 infiltrating duct carcinoma cases that were not otherwise specified. In round 1, pathologists analyzed 246 HER2 IHC slides by microscope without AI assistance. After a 2-week washout period, the pathologists read the same slides with AI algorithm assistance and rendered the definitive results by adjusting to the AI algorithm. The accuracy of interpretation accuracy with AI assistance (0.93 vs 0.80), thereby the evaluation precision of HER2 0 and the recall of HER2 1+. In addition, the AI algorithm improved the total consistency (intraclass correlation coefficient = 0.542-0.812), especially in HER2 1+ cases. In cases with heterogeneity, accuracy improved significantly (0.68 to 0.89) and to a similar level as in cases without heterogeneity (accuracy, 0.97). Both accuracy and consistency improved more for junior pathologists than those for the midlevel and senior pathologists. To the best of our knowledge, this is the first study to show that the accuracy and consistency of HER2 IHC 0 and 1+ evaluation and the accuracy of HER2 IHC evaluation in breast cancers with heterogeneity can be significantly improved using AI-assisted interpretation.

Digital image analysis and assisted reading of the HER2 score display reduced concordance: pitfalls in the categorisation of HER2-low breast cancer

AIMS

Digital image analysis (DIA) is used increasingly as an assisting tool to evaluate biomarkers, including human epidermal growth factor receptor 2 (HER2) in invasive breast cancer (BC). DIA can assist pathologists in HER2 evaluation by presenting quantitative information about the HER2 staining in APP assisted reading (AR). Concurrently, the HER2-low category (HER2-1+/2+ without HER2 gene amplification) has gained prominence due to newly developed antibody-drug conjugates. However, major inter- and intraobserver variability have been observed for the entity. The present quality assurance study investigated the concordance between DIA and AR in clinical use, especially concerning the HER2-low category.

METHODS AND RESULTS

HER2 immunohistochemistry (IHC) in 761 tumours from 727 patients was evaluated in tissue microarray (TMA) cores by DIA (Visiopharm HER2-CONNECT) and AR. Overall concordance between HER2-scores were 73% (n = 552, weighted-κ: 0.66), and 88% (n = 669, weighted-κ: 0.70), when combining HER2-0/1+. A total of 205 scores were discordant by one category, while four were discordant by two categories. A heterogeneous HER2 pattern was relatively common in the discordant cases and a pitfall in the categorisation of HER2-low BC. AR more commonly reassigned a lower HER2 score (from HER2-1+ to HER2-0) within the HER2-low subgroup (n = 624) compared with DIA.

CONCLUSION

DIA and AR display moderate agreement with heterogeneous and aberrant staining, representing a source of discordance and a pitfall in the evaluation of HER2.

Determining HER2 Status by Artificial Intelligence: An Investigation of Primary, Metastatic, and HER2 Low Breast Tumors

The expression of human epidermal growth factor receptor 2 (HER2) protein or gene transcripts is critical for therapeutic decision making in breast cancer. We examined the performance of a digitalized and artificial intelligence (AI)-assisted workflow for HER2 status determination in accordance with the American Society of Clinical Oncology (ASCO)/College of Pathologists (CAP) guidelines. Our preliminary cohort consisted of 495 primary breast carcinomas, and our study cohort included 67 primary breast carcinomas and 30 metastatic deposits, which were evaluated for HER2 status by immunohistochemistry (IHC) and in situ hybridization (ISH). Three practicing breast pathologists independently assessed and scored slides, building the ground truth. Following a washout period, pathologists were provided with the results of the AI digital image analysis (DIA) and asked to reassess the slides. Both rounds of assessment from the pathologists were compared to the AI results and ground truth for each slide. We observed an overall HER2 positivity rate of 15% in our study cohort. Moderate agreement (Cohen's κ 0.59) was observed between the ground truth and AI on IHC, with most discrepancies occurring between 0 and 1+ scores. Inter-observer agreement amongst pathologists was substantial (Fleiss´ κ 0.77) and pathologists' agreement with AI scores was 80.6%. Substantial agreement of the AI with the ground truth (Cohen´s κ 0.80) was detected on ISH-stained slides, and the accuracy of AI was similar for the primary and metastatic tumors. We demonstrated the feasibility of a combined HER2 IHC and ISH AI workflow, with a Cohen's κ of 0.94 when assessed in accordance with the ASCO/CAP recommendations.

Quantitative Image Analysis as an Adjunct to Manual Scoring of ER, PgR, and HER2 in Invasive Breast Carcinoma

OBJECTIVES

Biomarker expression evaluation for estrogen receptor (ER), progesterone receptor (PgR), and human epidermal growth factor receptor 2 (HER2) is an essential prognostic and predictive parameter for breast cancer and critical for guiding hormonal and neoadjuvant therapy. This study compared quantitative image analysis (QIA) with pathologists' scoring for ER, PgR, and HER2.

METHODS

A retrospective analysis was undertaken of 1,367 invasive breast carcinomas, including all histopathology subtypes, for which ER, PgR, and HER2 were analyzed by manual scoring and QIA. The resulting scores were compared, and in a subset of HER2 cases (n = 373, 26%), scores were correlated with available fluorescence in situ hybridization (FISH) results.

RESULTS

Concordance between QIA and manual scores for ER, PgR, and HER2 was 93%, 96%, and 90%, respectively. Discordant cases had low positive scores (1%-10%) for ER (n = 33), were due to nonrepresentative region selection (eg, ductal carcinoma in situ) or tumor heterogeneity for PgR (n = 43), and were of one-step difference (negative to equivocal, equivocal to positive, or vice versa) for HER2 (n = 90). Among HER2 cases where FISH results were available, only four (1.0%) showed discordant QIA and FISH results.

CONCLUSIONS

QIA is a computer-aided diagnostic support tool for pathologists. It significantly improves ER, PgR, and HER2 scoring standardization. QIA demonstrated excellent concordance with pathologists' scores. To avoid pitfalls, pathologist oversight of representative region selection is recommended.

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.

Quantitative Image Analysis for Tissue Biomarker Use: A White Paper From the Digital Pathology Association

Tissue biomarkers have been of increasing utility for scientific research, diagnosing disease, and treatment response prediction. There has been a steady shift away from qualitative assessment toward providing more quantitative scores for these biomarkers. The application of quantitative image analysis has thus become an indispensable tool for in-depth tissue biomarker interrogation in these contexts. This white paper reviews current technologies being employed for quantitative image analysis, their application and pitfalls, regulatory framework demands, and guidelines established for promoting their safe adoption in clinical practice.

Can AI-assisted microscope facilitate breast HER2 interpretation? A multi-institutional ring study

The level of human epidermal growth factor receptor-2 (HER2) protein and gene expression in breast cancer is an essential factor in judging the prognosis of breast cancer patients. Several investigations have shown high intraobserver and interobserver variability in the evaluation of HER2 staining by visual examination. In this study, we aim to propose an artificial intelligence (AI)-assisted microscope to improve the HER2 assessment accuracy and reliability. Our AI-assisted microscope was equipped with a conventional microscope with a cell-level classification-based HER2 scoring algorithm and an augmented reality module to enable pathologists to obtain AI results in real time. We organized a three-round ring study of 50 infiltrating duct carcinoma not otherwise specified (NOS) cases without neoadjuvant treatment, and recruited 33 pathologists from 6 hospitals. In the first ring study (RS1), the pathologists read 50 HER2 whole-slide images (WSIs) through an online system. After a 2-week washout period, they read the HER2 slides using a conventional microscope in RS2. After another 2-week washout period, the pathologists used our AI microscope for assisted interpretation in RS3. The consistency and accuracy of HER2 assessment by the AI-assisted microscope were significantly improved (p < 0.001) over those obtained using a conventional microscope and online WSI. Specifically, our AI-assisted microscope improved the precision of immunohistochemistry (IHC) 3 + and 2 + scoring while ensuring the recall of fluorescent in situ hybridization (FISH)-positive results in IHC 2 + . Also, the average acceptance rate of AI for all pathologists was 0.90, demonstrating that the pathologists agreed with most AI scoring results.

Discordance Between Immunohistochemistry and In Situ Hybridization to Detect HER2 Overexpression/Gene Amplification in Breast Cancer in the Modern Age: A Single Institution Experience and Pooled Literature Review Study

BACKGROUND

Human epidermal growth factor 2 (HER2) amplification and/or overexpression occurs in 12% to 25% of breast cancers. Accurate detection of HER2 is critical in predicting response to HER2-targeted therapy. Both immunohistochemistry (IHC) and in situ hybridization (ISH) are FDA-approved methods for detecting HER2 status because its protein overexpression is largely attributable to gene amplification. However, variable discordant results between IHC and ISH have been reported.

METHODS

We determined the frequency of HER2 IHC/ISH discordance in these patients and also performed a pooled literature review analysis.

RESULTS

Of the 1125 consecutive primary or metastatic breast cancers with HER2 IHC and ISH performed simultaneously between 2015 and 2020, 84.6% had an unequivocal HER2 status. Discordance was found in 30 cases from 26 patients, including 13 IHC^-/ISH⁺ and 17 IHC⁺/ISH^-, representing 1.6% and 11.9% of IHC^- and IHC⁺ cases, respectively. Review of the literature between 2001 and 2020 identified 46 relevant studies, with a total of 43,468 cases with IHC and ISH performed. The IHC^-/ISH+ and IHC⁺/ISH^- discordances were seen in all antibody clones and ISH methods used. The IHC⁺/ISH^- discordance was significantly higher than IHC^-/ISH⁺ (13.8% vs. 3%, P < .0001). The overall discordance constituted 4% of all cases and 5.4% of those with an unequivocal IHC status. Significantly lower incongruities for both IHC^-/ISH⁺ and IHC⁺/ISH^- were found in those published after 2018. The discordances probably reflect altered biology of HER2 oncogene/oncoprotein. Routinely performing both IHC and ISH may uncover such cases to prevent denial of potentially beneficial targeted therapy.

A Validation Study of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry Digital Imaging Analysis and its Correlation with Human Epidermal Growth Factor Receptor 2 Fluorescence In situ Hybridization Results in Breast Carcinoma

Background:

The Visiopharm human epidermal growth factor receptor 2 (HER2) digital imaging analysis (DIA) algorithm assesses digitized HER2 immunohistochemistry (IHC) by measuring cell membrane connectivity. We aimed to validate this algorithm for clinical use by comparing with pathologists’ scoring and correlating with HER2 fluorescence in situ hybridization (FISH) results.

Materials and Methods:

The study cohort consisted of 612 consecutive invasive breast carcinoma specimens including 395 biopsies and 217 resections. HER2 IHC slides were scanned using Philips IntelliSite Scanners, and the digital images were analyzed using Visiopharm HER2-CONNECT App to obtain the connectivity values (0–1) and scores (0, 1+, 2+, and 3+). HER2 DIA scores were compared with Pathologists’ manual scores, and HER2 connectivity values were correlated with HER2 FISH results.

Results:

The concordance between HER2 DIA scores and pathologists’ scores was 87.3% (534/612). All discordant cases (n = 78) were only one-step discordant (negative to equivocal, equivocal to positive, or vice versa). Five cases (0.8%) showed discordant HER2 IHC DIA and HER2 FISH results, but all these cases had relatively low HER2 copy numbers (between 4 and 6). HER2 IHC connectivity showed significantly better correlation with HER2 copy number than HER2/CEP17 ratio.

Conclusions:

HER2 IHC DIA demonstrates excellent concordance with pathologists’ scores and accurately discriminates between HER2 FISH positive and negative cases. HER2 IHC connectivity has better correlation with HER2 copy number than HER2/CEP17 ratio, suggesting HER2 copy number may be more important in predicting HER2 protein expression, and response to anti-HER2-targeted therapy.

Quantitative digital imaging analysis of HER2 immunohistochemistry predicts the response to anti-HER2 neoadjuvant chemotherapy in HER2-positive breast carcinoma

PURPOSE

Patients with HER2-positive breast cancer commonly receive anti-HER2 neoadjuvant chemotherapy and pathologic complete response (pCR) can be achieved in up to half of the patients. HER2 protein expression detected by immunohistochemistry (IHC) can be quantified using digital imaging analysis (DIA) as a value of membranous connectivity. We aimed to investigate the association HER2 IHC DIA quantitative results with response to anti-HER2 neoadjuvant chemotherapy.

METHODS

Digitized HER2 IHC whole slide images were analyzed using Visiopharm HER2-CONNECT to obtain quantitative HER2 membranous connectivity from a cohort of 153 HER2+ invasive breast carcinoma cases treated with anti-HER2 neoadjuvant chemotherapy (NAC). HER2 connectivity and other factors including age, histologic grade, ER, PR, and HER2 fluorescence in situ hybridization (FISH) were analyzed for association with the response to anti-HER2 NAC.

RESULTS

Eighty-three cases (54.2%) had pCR, while 70 (45.8%) showed residual tumor. Younger age, negative ER/PR, higher HER2 DIA connectivity, higher HER2 FISH ratio and copy number were significantly associated with pCR in univariate analysis. Multivariate analysis demonstrated only age, HER2 DIA connectivity, PR negativity, and HER2 copy number was significantly associated with pCR, whereas HER2 DIA connectivity had the strongest association.

CONCLUSIONS

HER2 IHC DIA connectivity is the most important factor predicting pCR to anti-HER2 neoadjuvant chemotherapy in patients with HER2-positive breast cancer.

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.

What is the added value of digital image analysis of HER2 immunohistochemistry in breast cancer in clinical practice? A study with multiple platforms

AIMS

We aimed to compare digital image analysis (DIA) of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) in breast cancer by two platforms: (i) to validate DIA against standard diagnostics; and (ii) to evaluate the added value of DIA in clinical practice.

METHODS AND RESULTS

HER2 IHC and in-situ hybridisation (ISH) were performed on 152 consecutive invasive breast carcinomas. IHC scores were determined with DIA using two independent platforms. Manual scoring was performed by two independent observers. HER2 status was considered positive in 3+ and ISH-positive 2+ cases. HER2 status using DIA was compared to HER2 status with standard diagnostics (manual scoring with ISH in 2+ cases). Interplatform agreement of IHC scores was 'moderate' (linear weighted κ = 0.58), agreement between manual scoring and platform A was 'moderate' (κ = 0.60) and between manual scoring and platform B 'almost perfect' (κ = 0.85). Compared to manual scoring, DIA resulted in a reduction of 2+ cases from 17.1 to 1.3% with platform A and from 17.1 to 15.8% with platform B. However, compared to standard diagnostics, there were three false-negative cases with DIA using platform A [81.3% sensitivity, 100% specificity, 100% positive predictive value (PPV), 97.8% negative predictive value (NPV)]. Sensitivity, specificity, PPV and NPV were 100% with DIA using platform B.

CONCLUSIONS

DIA of HER2 IHC is a valid tool in determining HER2 status in breast carcinoma. Algorithms in different platforms can behave differently, and optimal calibration is essential. In clinical practice, DIA offers an objective alternative to manual scoring, but a reduction in 2+ cases could result in loss of sensitivity.