Automated imaging analysis of Ki-67 immunohistochemistry on whole slide images of cell blocks from pancreatic neuroendocrine neoplasms.

INTRODUCTION: Accurate grading of pancreatic neuroendocrine tumors (PanNETs) relies on the assessment of Ki-67 immunohistochemistry (IHC). While digital imaging analysis (DIA) has been employed for Ki-67 IHC assessment in surgical specimens, its applicability to cytologic specimens remains underexplored. This study aimed to evaluate an automated DIA for assessing Ki-67 IHC on PanNET cell blocks. MATERIALS AND METHODS: The study included 61 consecutive PanNETs and 5 pancreatic neuroendocrine carcinomas. Ki-67 IHC slides from cell blocks were digitally scanned into whole slide images using Philips IntelliSite Scanners and analyzed in batches using the Visiopharm Ki-67 App in a digital workflow. Ki-67 scores obtained through DIA were compared to pathologists' manual scores. RESULTS: The Pearson correlation coefficient of the percentage of Ki-67-stained nuclei between DIA reads and the originally reported reads was 0.9681. Concordance between DIA Ki-67 grades and pathologists' Ki-67 grades was observed in 92.4% (61/66) of cases with the calculated Cohen's Kappa coefficient of 0.862 (almost perfect agreement). Discordance between DIA and pathologists' consensus reads occurred in 5 PanNET cases which were upgraded from G1 to G2 by DIA due to contaminated Ki-67-stained inflammatory cells. CONCLUSIONS: DIA demonstrated excellent concordance with pathologists' assessments, with only minor grading discrepancies. However, the essential role of pathologists in confirming results is emphasized to enhance overall accuracy.

Artificial intelligence's impact on breast cancer pathology: a literature review.

This review discusses the profound impact of artificial intelligence (AI) on breast cancer (BC) diagnosis and management within the field of pathology. It examines the various applications of AI across diverse aspects of BC pathology, highlighting key findings from multiple studies. Integrating AI into routine pathology practice stands to improve diagnostic accuracy, thereby contributing to reducing avoidable errors. Additionally, AI has excelled in identifying invasive breast tumors and lymph node metastasis through its capacity to process large whole-slide images adeptly. Adaptive sampling techniques and powerful convolutional neural networks mark these achievements. The evaluation of hormonal status, which is imperative for BC treatment choices, has also been enhanced by AI quantitative analysis, aiding interobserver concordance and reliability. Breast cancer grading and mitotic count evaluation also benefit from AI intervention. AI-based frameworks effectively classify breast carcinomas, even for moderately graded cases that traditional methods struggle with. Moreover, AI-assisted mitotic figures quantification surpasses manual counting in precision and sensitivity, fostering improved prognosis. The assessment of tumor-infiltrating lymphocytes in triple-negative breast cancer using AI yields insights into patient survival prognosis. Furthermore, AI-powered predictions of neoadjuvant chemotherapy response demonstrate potential for streamlining treatment strategies. Addressing limitations, such as preanalytical variables, annotation demands, and differentiation challenges, is pivotal for realizing AI's full potential in BC pathology. Despite the existing hurdles, AI's multifaceted contributions to BC pathology hold great promise, providing enhanced accuracy, efficiency, and standardization. Continued research and innovation are crucial for overcoming obstacles and fully harnessing AI's transformative capabilities in breast cancer diagnosis and assessment.

Comparing Accuracy of Helicobacter pylori Identification Using Traditional Hematoxylin and Eosin-Stained Glass Slides With Digital Whole Slide Imaging.

With advancements in the field of digital pathology, there has been a growing need to compare the diagnostic abilities of pathologists using digitized whole slide images against those when using traditional hematoxylin and eosin (H&E)-stained glass slides for primary diagnosis. One of the most common specimens received in pathology practices is an endoscopic gastric biopsy with a request to rule out Helicobacter pylori (H. pylori) infection. The current standard of care is the identification of the organisms on H&E-stained slides. Immunohistochemical or histochemical stains are used selectively. However, due to their small size (2-4 µm in length by 0.5-1 µm in width), visualization of the organisms can present a diagnostic challenge. The goal of the study was to compare the ability of pathologists to identify H. pylori on H&E slides using a digital platform against the gold standard of H&E glass slides using routine light microscopy. Diagnostic accuracy rates using glass slides vs digital slides were 81% vs 72% (P = .0142) based on H&E slides alone. When H. pylori immunohistochemical slides were provided, the diagnostic accuracy was significantly improved to comparable rates (96% glass vs 99% digital, P = 0.2199). Furthermore, differences in practice settings (academic/subspecialized vs community/general) and the duration of sign-out experience did not significantly impact the accuracy of detecting H. pylori on digital slides. We concluded that digital whole slide images, although amenable in different practice settings and teaching environments, does present some shortcomings in accuracy and precision, especially in certain circumstances and thus is not yet fully capable of completely replacing glass slide review for identification of H. pylori. We specifically recommend reviewing glass slides and/or performing ancillary stains, especially when there is a discrepancy between the degree of inflammation and the presence of microorganisms on digital images.

Computational pathology in the identification of HER2-low breast cancer: Opportunities and challenges.

For the past 2 decades, pathologists have been accustomed to reporting the HER2 status of breast cancer as either positive or negative, based on HER2 IHC. Today, however, there is a clinical imperative to employ a 3-tier approach to interpreting HER2 IHC that can also identify tumours categorised as HER2-low. Meeting this need for a finer degree of discrimination may be challenging, and in this article, we consider the potential for the integration of computational approaches to support pathologists in achieving accurate and reproducible HER2 IHC scoring as well as outlining some of the practicalities involved.

Digital cytology part 1: digital cytology implementation for practice: a concept paper with review and recommendations from the American Society of Cytopathology Digital Cytology Task Force.

Digital cytology and artificial intelligence (AI) are gaining greater adoption in the cytopathology laboratory. However, peer-reviewed real-world data and literature are lacking regarding the current clinical landscape. The American Society of Cytopathology in conjunction with the International Academy of Cytology and the Digital Pathology Association established a special task force comprising 20 members with expertise and/or interest in digital cytology. The aim of the group was to investigate the feasibility of incorporating digital cytology, specifically cytology whole slide scanning and AI applications, into the workflow of the laboratory. In turn, the impact on cytopathologists, cytologists (cytotechnologists), and cytology departments were also assessed. The task force reviewed existing literature on digital cytology, conducted a worldwide survey, and held a virtual roundtable discussion on digital cytology and AI with multiple industry corporate representatives. This white paper, presented in 2 parts, summarizes the current state of digital cytology and AI practice in global cytology practice. Part 1 of the white paper presented herein is a review and offers best practice recommendations for incorporating digital cytology into practice. Part 2 of the white paper provides a comprehensive review of AI in cytology practice along with best practice recommendations and legal considerations. Additionally, the results of a global survey regarding digital cytology are highlighted.

Digital cytology part 2: artificial intelligence in cytology: a concept paper with review and recommendations from the American Society of Cytopathology Digital Cytology Task Force.

Digital cytology and artificial intelligence (AI) are gaining greater adoption in the cytology laboratory. However, peer-reviewed real-world data and literature are lacking in regard to the current clinical landscape. The American Society of Cytopathology in conjunction with the International Academy of Cytology and the Digital Pathology Association established a special task force comprising 20 members with expertise and/or interest in digital cytology. The aim of the group was to investigate the feasibility of incorporating digital cytology, specifically cytology whole slide scanning and AI applications, into the workflow of the laboratory. In turn, the impact on cytopathologists, cytologists (cytotechnologists), and cytology departments were also assessed. The task force reviewed existing literature on digital cytology, conducted a worldwide survey, and held a virtual roundtable discussion on digital cytology and AI with multiple industry corporate representatives. This white paper, presented in 2 parts, summarizes the current state of digital cytology and AI practice in global cytology practice. Part 1 of the white paper is presented as a separate paper which details a review and best practice recommendations for incorporating digital cytology into practice. Part 2 of the white paper presented here provides a comprehensive review of AI in cytology practice along with best practice recommendations and legal considerations. Additionally, the cytology global survey results highlighting current AI practices by various laboratories, as well as current attitudes, are reported.

Unlocking Translational Potential: Conditionally Reprogrammed Cells in Advancing Breast Cancer Research.

Preclinical in vitro models play an important role in studying cancer cell biology and facilitating translational research, especially in the identification of drug targets and drug discovery studies. This is particularly relevant in breast cancer, where the global burden of disease is quite high based on prevalence and a relatively high rate of lethality. Predictive tools to select patients who will be responsive to invasive or morbid therapies (radiotherapy, chemotherapy, immunotherapy, and/or surgery) are relatively lacking. To be clinically relevant, a model must accurately replicate the biology and cellular heterogeneity of the primary tumor. Addressing these requirements and overcoming the limitations of most existing cancer cell lines, which are typically derived from a single clone, we have recently developed conditional reprogramming (CR) technology. The CR technology refers to a co-culture system of primary human normal or tumor cells with irradiated murine fibroblasts in the presence of a Rho-associated kinase inhibitor to allow the primary cells to acquire stem cell properties and the ability to proliferate indefinitely in vitro without any exogenous gene or viral transfection. This innovative approach fulfills many of these needs and offers an alternative that surpasses the deficiencies associated with traditional cancer cell lines. These CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and reproduce the genomic and histological characteristics of the parental tissue. Therefore, CR technology may be a clinically relevant model to test and predict drug sensitivity, conduct gene profile analysis and xenograft research, and undertake personalized medicine. This review discusses studies that have applied CR technology to conduct breast cancer research.

Comparison of four different displays for identification of select pathologic features extracted from whole slide images of surgical pathology cases.

BACKGROUND: The establishment of minimum standards for display selection for the whole slide image (WSI) interpretation has not been fully defined. Recently, pathologists have increasingly preferred using remote displays for clinical diagnostics. Our study aims to assess and compare the performance of three fixed work displays and one remote personal display in accurately identifying ten selected pathologic features integrated into WSIs. DESIGN: Hematoxylin and eosin-stained glass slides were digitized using Philips scanners. Seven practicing pathologists and three residents reviewed ninety WSIs to identify ten pathologic features using the LG, Dell, and Samsung and an optional consumer-grade display. Ten pathologic features included eosinophils, neutrophils, plasma cells, granulomas, necrosis, mucin, hemosiderin, crystals, nucleoli, and mitoses. RESULTS: The accuracy of the identification of ten features on different types of displays did not significantly differ among the three types of "fixed" workplace displays. The highest accuracy was observed for the identification of neutrophils, eosinophils, plasma cells, granuloma, and mucin. On the other hand, a lower accuracy was observed for the identification of crystals, mitoses, necrosis, hemosiderin, and nucleoli. Participant pathologists and residents preferred the use of larger displays (>30″) with a higher pixel count, resolution, and luminance. CONCLUSION: Most features can be identified using any display. However, certain features posed more challenges across the three fixed display types. Furthermore, the use of a remote personal consumer-grade display chosen according to the pathologists' preference showed similar feature identification accuracy. Several factors of display characteristics seemed to influence pathologists' display preferences such as the display size, color, contrast ratio, pixel count, and luminance calibration. This study supports the use of standard "unlocked" vendor-agnostic displays for clinical digital pathology workflow rather than purchasing "locked" and more expensive displays that are part of a digital pathology system.

Pancreaticobiliary Cytology Practice in 2021: Results of a College of American Pathologists Survey.

CONTEXT.­: The College of American Pathologists (CAP) surveys provide national benchmarks of pathology practice. OBJECTIVE.­: To investigate pancreaticobiliary cytology practice in domestic and international laboratories in 2021. DESIGN.­: We analyzed data from the CAP Pancreaticobiliary Cytology Practice Supplemental Questionnaire that was distributed to laboratories participating in the 2021 CAP Nongynecologic Cytopathology Education Program. RESULTS.­: Ninety-three percent (567 of 612) of respondent laboratories routinely evaluated pancreaticobiliary cytology specimens. Biliary brushing (85%) was the most common pancreaticobiliary cytology specimen evaluated, followed by pancreatic fine-needle aspiration (79%). The most used sampling methods reported by 235 laboratories were 22-gauge needle for fine-needle aspiration (62%) and SharkCore needle for fine-needle biopsy (27%). Cell block was the most used slide preparation method (76%), followed by liquid-based cytology (59%) for pancreatic cystic lesions. Up to 95% (303 of 320) of laboratories performed rapid on-site evaluation (ROSE) on pancreatic solid lesions, while 56% (180 of 320) performed ROSE for cystic lesions. Thirty-six percent (193 of 530) of laboratories used the Papanicolaou Society of Cytopathology System for Reporting Pancreaticobiliary Cytology in 2021. Among all institution types, significant differences in specimen volume, specimen type, ROSE practice, and case sign-out were identified. Additionally, significant differences in specimen type, slide preparation, and ROSE practice were found. CONCLUSIONS.­: This is the first survey from the CAP to investigate pancreaticobiliary cytology practice. The findings reveal significant differences among institution types and between domestic and international laboratories. These data provide a baseline for future studies in a variety of practice settings.

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.

Triple-negative Breast Carcinoma With Apocrine and Histiocytoid Features: A Clinicopathologic and Molecular Study of 18 Cases.

Triple-negative breast cancer (TNBC) is a heterogenous group of tumors. Most TNBCs are high-grade aggressive tumors, but a minority of TNBCs are not high grade, with relatively indolent behavior and specific morphologic and molecular features. We performed a clinicopathologic and molecular assessment of 18 non-high-grade TNBCs with apocrine and/or histiocytoid features. All were grade I or II with low Ki-67 (≤20%). Thirteen (72%) showed apocrine features, and 5 (28%) showed histiocytoid and lobular features. In all, 17/18 expressed the androgen receptor, and 13/13 expressed gross cystic disease fluid protein 15. Four (22.2%) patients were treated with neoadjuvant chemotherapy, but none achieved a pathologic complete response. In all, 2/18 patients (11%) had lymph node metastasis at the time of surgery. None of the cases had a recurrence or disease-specific death, with an average follow-up time of 38 months. Thirteen cases were profiled by targeted capture-based next-generation DNA sequencing. Genomic alterations (GAs) were most significant for PI3K-PKB/Akt pathway (69%) genes, including PIK3R1 (23%), PIK3CA (38%), and PTEN (23%), and RTK-RAS pathway (62%) including FGFR4 (46%) and ERBB2 (15%). TP53 GA was seen in only 31% of patients. Our findings support those on high-grade TNBCs with apocrine and/or histiocytoid features as a clinicopathologic and genetically distinct subgroup of TNBC. They can be defined by features including tubule formation, rare mitosis, low Ki-67 (≤20%), triple-negative status, expression of androgen receptor and/or gross cystic disease fluid protein 15, and GA in the PI3K-PKB/Akt and/or RTK-RAS pathway. These tumors are not sensitive to chemotherapy but have favorable clinical behavior. Tumor subtype definitions are the first step to implementing future trial designs to select these patients.

SOX17 is a highly sensitive and specific marker for metastatic ovarian and endometrial carcinomas in cytology cell block specimens.

BACKGROUND: SOX17 (SRY-box transcription factor 17) was recently identified as a highly sensitive and specific marker for ovarian and endometrial carcinomas in surgical specimens. In this study, validation of the utility of SOX17 immunohistochemistry (IHC) in diagnosing metastatic gynecologic carcinomas in cytology specimens was sought. METHODS: The study cohort included 84 cases of metastatic carcinomas that included 29 metastatic gynecologic carcinomas (24 ovarian high-grade serous carcinomas, two endometrial serous carcinomas, one low-grade serous carcinoma, one ovarian clear cell carcinoma, and one endometrial endometrioid carcinoma) and 55 cases of metastatic nongynecologic carcinomas (10 clear cell renal cell carcinomas, 10 papillary thyroid carcinomas, 11 gastrointestinal adenocarcinomas, 10 breast carcinomas, 10 lung adenocarcinomas, and four urothelial carcinomas). Cytology specimen types included peritoneal fluid (n = 44), pleural fluid (n = 25), and fine-needle aspiration (n = 15). SOX17 IHC was performed on the cell block sections. The intensity of staining and percent positivity of the tumor cells were evaluated. RESULTS: SOX17 was highly expressed in all tested metastatic gynecologic carcinomas with diffuse and strong nuclear expression (29 of 29; 100%). SOX17 was negative in other metastatic nongynecologic carcinomas (54 of 55; 98.18%) except for one papillary thyroid carcinoma that showed low positivity (<10%). CONCLUSIONS: SOX17 is a highly sensitive (100%) and specific (98.2%) marker for the differential diagnosis of metastatic gynecologic carcinomas in cytology specimens. Therefore, SOX17 IHC should be included in the workup of differential diagnosis of metastatic gynecologic carcinomas in cytology specimens.

Artificial Intelligence-Aided Diagnosis of Breast Cancer Lymph Node Metastasis on Histologic Slides in a Digital Workflow.

Identifying lymph node (LN) metastasis in invasive breast carcinoma can be tedious and time-consuming. We investigated an artificial intelligence (AI) algorithm to detect LN metastasis by screening hematoxylin and eosin (H&E) slides in a clinical digital workflow. The study included 2 sentinel LN (SLN) cohorts (a validation cohort with 234 SLNs and a consensus cohort with 102 SLNs) and 1 nonsentinel LN cohort (258 LNs enriched with lobular carcinoma and postneoadjuvant therapy cases). All H&E slides were scanned into whole slide images in a clinical digital workflow, and whole slide images were automatically batch-analyzed using the Visiopharm Integrator System (VIS) metastasis AI algorithm. For the SLN validation cohort, the VIS metastasis AI algorithm detected all 46 metastases, including 19 macrometastases, 26 micrometastases, and 1 with isolated tumor cells with a sensitivity of 100%, specificity of 41.5%, positive predictive value of 29.5%, and negative predictive value (NPV) of 100%. The false positivity was caused by histiocytes (52.7%), crushed lymphocytes (18.2%), and others (29.1%), which were readily recognized during pathologists' reviews. For the SLN consensus cohort, 3 pathologists examined all VIS AI annotated H&E slides and cytokeratin immunohistochemistry slides with similar average concordance rates (99% for both modalities). However, the average time consumed by pathologists using VIS AI annotated slides was significantly less than using immunohistochemistry slides (0.6 vs 1.0 minutes, P = .0377). For the nonsentinel LN cohort, the AI algorithm detected all 81 metastases, including 23 from lobular carcinoma and 31 from postneoadjuvant chemotherapy cases, with a sensitivity of 100%, specificity of 78.5%, positive predictive value of 68.1%, and NPV of 100%. The VIS AI algorithm showed perfect sensitivity and NPV in detecting LN metastasis and less time consumed, suggesting its potential utility as a screening modality in routine clinical digital pathology workflow to improve efficiency.

The thioredoxin system determines CHK1 inhibitor sensitivity via redox-mediated regulation of ribonucleotide reductase activity.

Checkpoint kinase 1 (CHK1) is critical for cell survival under replication stress (RS). CHK1 inhibitors (CHK1i's) in combination with chemotherapy have shown promising results in preclinical studies but minimal efficacy with substantial toxicity in clinical trials. To explore novel combinational strategies that can overcome these limitations, we performed an unbiased high-throughput screen in a non-small cell lung cancer (NSCLC) cell line and identified thioredoxin1 (Trx1), a major component of the mammalian antioxidant-system, as a novel determinant of CHK1i sensitivity. We established a role for redox recycling of RRM1, the larger subunit of ribonucleotide reductase (RNR), and a depletion of the deoxynucleotide pool in this Trx1-mediated CHK1i sensitivity. Further, the TrxR1 inhibitor auronafin, an anti-rheumatoid arthritis drug, shows a synergistic interaction with CHK1i via interruption of the deoxynucleotide pool. Together, these findings identify a new pharmacological combination to treat NSCLC that relies on a redox regulatory link between the Trx system and mammalian RNR activity.

HPV genotyping of cervical histologic specimens of 61, 422 patients from the largest women hospital in China.

Objectives: We investigated HPV genotypes in a large cohort of patients with definitive cervical histologic diagnosis. Methods: HPV testing was performed by real-time PCR assay, including 18 high-risk HPV (hrHPV) and 3 low-risk HPV (lrHPV). Totally 61,422 patients with documented HPV genotyping results within 6 months before cervical histologic diagnoses were included. Results: HrHPV positive rate was 55.1% among all tested cases with the highest in adenosquamous carcinoma (94.1%), followed by squamous cell carcinoma (SCC) (93.7%), cervical intraepithelial neoplasia 2/3 (CIN2/3) (92.8%). HrHPV positive rates were significantly higher in high-grade squamous lesions than in those in glandular lesions. HPV16 was the most common genotype followed by HPV52 and HPV58 in CIN2/3. The most frequent hrHPV genotype in adenocarcinoma in situ (AIS) was HPV18, followed by HPV16, HPV45 and HPV52. In SCC cases, HPV16 was the most common type followed by HPV58, HPV52, HPV18 and HPV33. However, HPV18 showed significantly higher prevalence in adenocarcinoma and adenosquamous carcinoma than in that in SCC. Theoretically, the protective rates of 2/4-valent and 9-valent vaccine were 69.1% and 85.8% for cervical cancers. Conclusions: The prevalence of HPV genotypes in Chinese population was different from that in Western population. Some hrHPV types were identified in cervical precancerous lesions and cancers, which are not included in current HPV vaccines. These data provide baseline knowledge for future HPV vaccine development.

Low-grade adenosquamous carcinoma of the breast: a clinical, morphological and immunohistochemical analysis of 25 patients.

AIMS: Due to its rarity and non-specific clinical and pathological features, low-grade adenosquamous carcinoma (LGASC) of the breast continues to pose diagnostic challenges. Unlike other triple-negative breast carcinomas, LGASC tends to have an indolent clinical behaviour. It is essential to recognise this lesion for accurate diagnosis and appropriate management. METHODS AND RESULTS: Twenty-five cases of LGASC were identified in our archives and collaborating institutes. Cases of LGASC with dominant coexisting other type carcinomas were excluded. We studied the clinical presentation, morphological features, patterns of the commonly used immunohistochemical stains and follow-up. In our cohort, LGASC was commonly located at the outer aspect of the breast and associated with intraductal papilloma. The morphology of LGASC is characterised by infiltrating small glands and nests with variable squamous differentiation. We also found cuffing desmoplastic (fibrolamellar) stromal change in 75% of patients and peripheral lymphocytic aggregates in 87.5% of patients. P63 and smooth muscle myosin (SMM) were the most common myoepithelial markers used to assist in diagnosis. P63 often stained peripheral tumour cells surrounding invasive glands (circumferential staining in 80% of the cases), mimicking myoepithelial cells. It also stained the small nests with squamous differentiation. However, SMM was negative in 63% of the cases. The vast majority of our cases were triple-negative; only a few had focal and weak expressions of ER and PR. One patient who did not have excision developed lymph node metastasis. Most patients underwent excision or mastectomy with negative margins as surgical treatment; there were no recurrences or metastases in these patients with clinical follow-ups up to 108 months. CONCLUSIONS: LGASC has some unique, although not entirely specific, morphological features and immunohistochemical staining patterns. Fibrolamellar stromal change, peripheral lymphocytic aggregates and variable staining of p63 and SMM are valuable features to facilitate the diagnosis.

Incidence, Clinicopathologic Features, HER2 Fluorescence In Situ Hybridization Profile, and Oncotype DX Results of Human Epidermal Growth Factor Receptor 2-Low Breast Cancers: Experience From a Single Academic Center.

Human epidermal growth factor receptor 2 (HER2)-low breast cancer, defined by an immunohistochemical (IHC) score of 1+ or 2+ with negative in situ hybridization, is emerging as a predictive marker for the use of the antibody-drug conjugate. To understand how this category differs from HER2-zero cases, we investigated clinicopathological characteristics and HER2 fluorescence in situ hybridization results in a large cohort of 1309 continuous HER2-negative invasive breast carcinomas from 2018 to 2021 evaluated by the Food and Drug Administration-approved HER2 IHC test. Additionally, we compared Oncotype DX recurrence scores and HER2 mRNA expression between HER-low and HER2-zero cases in a separate cohort of 438 estrogen receptor-positive (ER+) early-stage breast carcinoma cases from 2014 to 2016. Based on the cohort from 2018 to 2021, the incidence of HER2-low breast cancers was approximately 54%. HER2-low cases had less frequent grade 3 morphology, less frequent triple-negative results, ER and progesterone receptor negativity, and a higher mean HER2 copy number and HER2/CEP17 ratio than HER2-zero cases (P < .0001). Among ER+ cases, HER2-low cases showed significantly less frequent Nottingham grade 3 tumors. In the cohort from 2014 to 2016, HER2-low cases showed significantly higher ER+ percentages, fewer progesterone receptor-negative cases, lower Oncotype DX recurrence scores, and higher HER2 mRNA expression scores than HER2-zero cases. In summary, this is the first study, to our knowledge, using a large cohort of continuous cases evaluated by the Food and Drug Administration-approved HER2 IHC companion diagnostic test for HER2-low expression and HER2 fluorescence in situ hybridization profile in a real-world setting. Although HER2-low cases showed a higher HER2 copy number, ratio, and mRNA level than HER2-zero cases statistically, such small differences are unlikely to be biologically or clinically meaningful. However, our study suggests that HER2-low/ER+ early-stage breast carcinoma may represent a less aggressive group of breast carcinoma, given its association with a lower Nottingham grade and Oncotype DX recurrence score.

HER2 Gene Protein Assay: A Robust Tool for Evaluating HER2 Status and Intratumoral Heterogeneity in Endometrial Cancers.

OBJECTIVES: Human epidermal growth factor receptor 2 (HER2) status in endometrial cancer is usually determined by immunohistochemistry and/or in situ hybridization. We employed a novel HER2 gene protein assay (GPA) to simultaneously assesses HER2 gene amplification and protein expression in high-grade endometrial cancers. METHODS: We performed GPA in 180 endometrial cancers, including 106 serous carcinomas, 34 carcinosarcomas, and 40 mixed epithelial carcinomas. HER2 status was determined using the 2018 HER2 guidelines for breast carcinoma, and HER2 intratumoral heterogeneity (ITH) was examined. Clinicopathologic characteristics were collected and correlated with HER2 status. RESULTS: HER2 positivity was noted in 32% of serous carcinomas, significantly higher than in carcinosarcomas (5.9%) and mixed carcinomas (12.5%). HER2 ITH was detected in 32% of serous carcinomas, significantly greater than in carcinosarcomas (8.8%) and mixed carcinomas (10%). Patients with carcinosarcoma had a significantly lower overall survival than patients with serous or mixed epithelial carcinoma, but HER2 status caused no difference in survival in patients with serous carcinoma. CONCLUSIONS: HER2 GPA can be used to accurately determine HER2 status in endometrial cancers and is a highly valuable tool for identifying HER2 heterogeneity.