Immunohistochemistry Slides Research Articles

The Impact of Pre-biopsy Corticosteroids Use on CD20 Staining Pattern in B-cell Lymphomas

Abstract Introduction/Objective Diffuse large B-cell lymphomas, the most common Non-Hodgkin’s lymphoma are heterogeneous in terms of varied clinical presentation. The pathological work up these lymphomas is usually initiated with a CD20/CD3 immunohistochemical panel. Due to the aggressive nature of these lymphomas, pre-diagnosis corticosteroids are necessitated in some cases. However, the corticosteroids treatment can significantly alter the antigen staining of the lymphoma delaying the pathological diagnosis and subsequent treatment. This study investigates how pre-biopsy corticosteroids administration affects CD20 staining in B-cell lymphoma cells along with CD3 and PAX5, aiming to provide insights to the practicing pathologist for prompter diagnosis in these challenging cases. Methods/Case Report 14 biopsy cases of B-cell lymphoma pretreated with corticosteroids were included in this study. Clinicopathological parameters including corticosteroids usage are collected. H&E and immunohistochemistry slides were reviewed to analyze CD20, CD3 and PAX5 staining patterns. Results (if a Case Study enter NA) Of 14 cases, 10 cases showed cytoplasmic and granular staining with CD20, with extracellular spilling instead of the typical membranous pattern. This change was more frequent with intravenous dexamethasone (7/9) compared to oral prednisone (3/5), high dose (80%) compared to moderate and low dose (67%), short-term corticosteroids usage (86%) compared to intermediate-term and long-term (57%) usage and shorter dosing interval (100% in Q6H). The impact of prebiopsy corticosteroids was seen more on lymph node (5/7) compared to bone marrow (3/5). This cytoplasmic granularity was also observed in CD3 in the background non-neoplastic T lymphocytes in 25% of the cases. Though nuclear stains such as PAX5, Ki67, MUM1 and BCL6 also showed granularity in a significant number of cases, it was limited to the nucleus. Conclusion Pre-biopsy corticosteroids leads to alteration in CD20 staining pattern of the lymphoma cells leading to cytoplasmic granularity with extracellular spillage, which causes diagnostic challenge. This effect varies according to the type, route, dose, and duration of corticosteroids usage.

Dual PD-L1/SOX10 Immunohistochemistry Combined With Digital Imaging Enhances Stratification Accuracy of Patients With Metastatic Melanoma.

Immune checkpoint inhibitor therapy has demonstrated an overall survival benefit in patients with advanced melanoma. Though the significance of programmed death-ligand 1 (PD-L1) expression on melanoma cells as a predictive biomarker of response remains inconclusive, some reports indicate that a PD-L1 expression of <1% of tumor cells may be associated with better outcomes with dual immunotherapy. Adequate patient selection for combination therapy is critical given the higher frequency of adverse effects compared with monotherapy. Immunohistochemical (IHC) PD-L1 interpretation in tumor cells is challenging when inflammatory cells are present and cutoffs are low. We studied 36 metastatic melanoma biopsies from Immune checkpoint inhibitor-naive patients, previously stained and scored for PD-L1 IHC using the tumor proportion score (TPS). Cases were classified into 3 groups: <1%, 1% to 5%, and >5%. After de-coverslipping, SRY-related HMG-box-10 (SOX10) IHC was performed on PD-L1 IHC slides with a red chromogen, and subsequently scanned and scored by ≥2 dermatopathologists. This assessment determined that 25% of cases (9/36) had a TPS ≥ 1%, in contrast to the single IHC assay (63.8%). The majority of the 1-5% group (11/13, 84.6%) underwent a change of category to <1% TPS. In the >5% group, 60% of cases (6/10) were downgraded to <1% and 1% to 5% (4 and 2 cases, respectively). Our study suggests that PD-L1 IHC evaluation could benefit from dual PD-L1/SOX10 IHC. Dual IHC is expected to decrease the interference caused by PD-L1 expression on inflammatory cells, and digital imaging proves useful for the preservation and analysis of stains. Refining PD-L1 evaluation in metastatic melanoma may improve clinical decisions between single and combination immunotherapy, with potentially profound consequences in response and quality of life.

Integrative analysis of H&E and IHC identifies prognostic immune subtypes in HPV related oropharyngeal cancer

BackgroundDeep learning techniques excel at identifying tumor-infiltrating lymphocytes (TILs) and immune phenotypes in hematoxylin and eosin (H&E)-stained slides. However, their ability to elucidate detailed functional characteristics of diverse cellular phenotypes within tumor immune microenvironment (TME) is limited. We aimed to enhance our understanding of cellular composition and functional characteristics across TME regions and improve patient stratification by integrating H&E with adjacent immunohistochemistry (IHC) images.MethodsA retrospective study was conducted on patients with Human Papillomavirus-positive oropharyngeal squamous cell carcinoma (OPSCC). Using paired H&E and IHC slides for 11 proteins, a deep learning pipeline was used to quantify tumor, stroma, and TILs in the TME. Patients were classified into immune inflamed (IN), immune excluded (IE), or immune desert (ID) phenotypes. By registering the IHC and H&E slides, we integrated IHC data to capture protein expression in the corresponding tumor regions. We further stratified patients into specific immune subtypes, such as IN, with increased or reduced CD8+ cells, based on the abundance of these proteins. This characterization provided functional insight into the H&E-based subtypes.ResultsAnalysis of 88 primary tumors and 70 involved lymph node tissue images reveals an improved prognosis in patients classified as IN in primary tumors with high CD8 and low CD163 expression (p = 0.007). Multivariate Cox regression analysis confirms a significantly better prognosis for these subtypes.ConclusionsIntegrating H&E and IHC data enhances the functional characterization of immune phenotypes of the TME with biological interpretability, and improves patient stratification in HPV( + ) OPSCC.

Precision HER2: a comprehensive AI system for accurate and consistent evaluation of HER2 expression in invasive breast Cancer

BackgroundWith the development of novel anti-HER2 targeted drugs, such as ADCs, it has become increasingly important to accurately interpret HER2 expression in breast cancer. Previous studies have demonstrated high intra-observer and inter-observer variabilities in evaluating HER2 staining by human eyes. There exists a strong requirement to develop artificial intelligence (AI) systems to achieve high-precision HER2 expression scoring for better clinical therapy.MethodsIn the present study, we collected breast cancer tissue samples and stained consecutive sections with anti-Calponin and anti-HER2 antibodies. High-quality digital images were selected from immunohistochemical slides and interpreted as HER2 3+, 2+, 1+, and 0. AI models were trained and assessed using annotated training and testing sets. The AI model was trained to automatically identify ductal carcinoma in situ (DCIS) by Calponin staining and myoepithelial annotation and filter out DCIS components in HER2-stained slides using image-overlapping techniques. Furthermore, we organized two-phase validation studies. In phase one, pathologists interpreted 112 HER2 whole-slide images (WSIs) without AI assistance, whereas in phase two, pathologists read the same slides using the AI system after a washing period of 2 weeks.ResultsOur AI model greatly improved the accuracy of reading (0.902 vs. 0.710). The number of HER2 1 + patients misdiagnosed as HER2 0 was significantly reduced (32/279 vs. 65/279), and they benefitted from ADC drugs. In addition, the AI algorithm improved the intra-group consistency of HER2 readings by pathologists with different years of experience (intra-class correlation coefficient [ICC]: 0.872–0.926 vs. 0.818–0.908), with the improvement most pronounced among junior pathologists (0.885 vs. 0.818).ConclusionsWe proposed a high-precision AI system to identify and filter out DCIS components and automatically evaluate HER2 expression in invasive breast cancer.

Spatially fractionated GRID radiation potentiates immune-mediated tumor control

BackgroundTumor-immune interactions shape a developing tumor and its tumor immune microenvironment (TIME) resulting in either well-infiltrated, immunologically inflamed tumor beds, or immune deserts with low levels of infiltration. The pre-treatment immune make-up of the TIME is associated with treatment outcome; immunologically inflamed tumors generally exhibit better responses to radio- and immunotherapy than non-inflamed tumors. However, radiotherapy is known to induce opposing immunological consequences, resulting in both immunostimulatory and inhibitory responses. In fact, it is thought that the radiation-induced tumoricidal immune response is curtailed by subsequent applications of radiation. It is thus conceivable that spatially fractionated radiotherapy (SFRT), administered through GRID blocks (SFRT-GRID) or lattice radiotherapy to create areas of low or high dose exposure, may create protective reservoirs of the tumor immune microenvironment, thereby preserving anti-tumor immune responses that are pivotal for radiation success.MethodsWe have developed an agent-based model (ABM) of tumor-immune interactions to investigate the immunological consequences and clinical outcomes after 2Gy×35\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2\\,\ ext{Gy} \ imes 35$$\\end{document} whole tumor radiation therapy (WTRT) and SFRT-GRID. The ABM is conceptually calibrated such that untreated tumors escape immune surveillance and grow to clinical detection. Individual ABM simulations are initialized from four distinct multiplex immunohistochemistry (mIHC) slides, and immune related parameter rates are generated using Latin Hypercube Sampling.ResultsIn silico simulations suggest that radiation-induced cancer cell death alone is insufficient to clear a tumor with WTRT. However, explicit consideration of radiation-induced anti-tumor immunity synergizes with radiation cytotoxicity to eradicate tumors. Similarly, SFRT-GRID is successful with radiation-induced anti-tumor immunity, and, for some pre-treatment TIME compositions and modeling parameters, SFRT-GRID might be superior to WTRT in providing tumor control.ConclusionThis study demonstrates the pivotal role of the radiation-induced anti-tumor immunity. Prolonged fractionated treatment schedules may counteract early immune recruitment, which may be protected by SFRT-facilitated immune reservoirs. Different biological responses and treatment outcomes are observed based on pre-treatment TIME composition and model parameters. A rigorous analysis and model calibration for different tumor types and immune infiltration states is required before any conclusions can be drawn for clinical translation.

Impacts of gentamycin toxicity: nephroprotective role of guarana through different signaling pathways.

Gentamicin is a widely used aminoglycosidic antibiotic since its discovery. Like any other medication gentamicin causes unwanted side effects such as hepatotoxicity and nephrotoxicity. This study aims to examine the antioxidant effect of the guarana seed extract in protecting renal tissue. Forty male mice were divided into four groups (group one was control with free access to food and water, group two was treated orally with 300mg/kg of guarana seed extract daily, group three was injected intraperitoneally with 100mg/kg of gentamicin daily and the fourth group was co-treated with both 300mg/kg of guarana seed extract orally and injected intraperitoneally with 100mg/kg of gentamicin daily) for two weeks. Serum levels of urea, creatinine, AST, ALT, IL-1β and IL-6 have significantly elevated in the gentamicin treated group and those changes were not found in the guarana co-treated group. In gentamicin treated mice, a significant reduction was observed in two antioxidants SOD and GPX accompanied by downregulation of Ho-1 and Nrf2 while, that did not happen in the guarana seed extract co-treated group. Histopathology and immunohistochemistry slides show that the guarana seed extract prevents degenerative and necrotic events in tubular epithelial tissues caused by gentamicin toxicity. In conclusion, current data suggest that gentamicin can damage renal tissues when given at 100mg/kg/day, however, the guarana seed extract may be capable of preventing that event when cotreated with the gentamicin as a supplement.

A histology and immunochemistry study comparing open versus close and open-method endoscopic saphenous vein harvesting.

The introduction of endoscopic saphenous vein harvesting (ESVH) has been reported to reduce wound pain and infection, compared with open saphenous vein harvesting (OSVH) techniques. There are still controversies regarding this technique. The aim of our study is to investigate the endothelial preservation of saphenous vein (SV) grafts harvested by different techniques. Further observations were made for harvesting and closure time, incision length and effect of pressure distension of the veins to the vein endothelium. Prospective observational study of sixty human saphenous vein grafts was performed to evaluate endothelial preservation by haematoxylin-eosin and Cluster of Differentiation 31 (CD 31) staining. Saphenous vein was harvested endoscopically either by closed CO2 (carbon dioxide) ESVH, open CO2 ESVH or OSVH harvesting technique. Demographic data and intra-operative data were collected. Two saphenous vein samples were collected from each patient to compare differences before and after distension of the veins. Both haematoxylin-eosin and immunohistochemistry slides were imaged by a high-resolution slide scanning system. Open CO2 ESVH group showed the highest number of endothelial detachments. Mean scoring of the immunohistochemistry method using the CD31 antibody was much lower in the open CO2 ESVH group (33.25% ± 28.71, P < 0.0003). This represents a more poorly preserved endothelial cells in the Open CO2 ESVH than the closed CO2 ESVH. Closure time and incision lengths were significantly shorter in both ESVH groups compared to the OSVH group. Significant low scores of immunohistochemistry for samples were seen in distended veins (39.0% ± 30.08, p = 0.004). The OSVH in random sample B, which represents the conduit that will be used, had a far better endothelium preservation and less endothelial detachment when compared to ESVH. We observed more endothelial detachment in the open CO2 ESVH group, due to lack of subcutaneous tissue separation, poor visualization and traction stress across the wall of the saphenous vein. The closed CO2 ESVH group had more endothelial cells preserved, but the OSVH group fared the best with the least number of endothelial cell detachment and a higher score of CD31 antibody. The online version contains supplementary material available at 10.1007/s12055-024-01752-3.

Tumor Budding: A Novel Prognostic Marker in Breast Carcinoma with Correlation of Histopathological and Immunohistochemical Parameters

Introduction Breast cancer is a highly heterogenous tumor with different subtypes showing varying prognosis. Tumor budding is an unfavorable histological feature of many epithelial cancers. The purpose of this study is to analyze the association between tumor bud density with various histological and immunohistochemical characteristics and to explore its prognostic role in breast carcinoma. Materials and Methods A retrospective analysis was performed on 100 patients of breast cancer diagnosed in our institute from January to December 2017. Hematoxylin and eosin (H&amp;E) stained slides from tumors and immunohistochemical slides were reviewed independently by two pathologists, and clinical data were acquired from computerized records. Patients on neoadjuvant chemotherapy were excluded from the study. Results The study comprised 100 patients of invasive breast carcinoma. The median age was 52 years, and 96% were invasive ductal carcinoma. The median follow-up was 34 months. High tumor bud density was substantially correlated with primary tumor staging (T3, T4; 73% [11/15] cases) and lymph node staging (N2, N3; 68% [13/19] cases) with p-values of 0.017 and 0.023, respectively. Systemic metastasis (85% [6/7] cases) was significantly associated with high tumor bud density (p =0.025) but lymphovascular invasion (LVI) and perineural invasion (PNI) were not significantly associated with tumor bud density (p = 0.762 and 0.862, respectively). Patients with N2 nodal stage had low event-free survival rate than N0/N1 nodal stage irrespective of tumor bud status. Grade 3 tumors with high tumor bud density had worse event-free survival than any other grades. There was no association of tumor bud density with tumor staging, necrosis, PNI, LVI, estrogen receptor (ER), progesterone receptor (PR) and Her2/neu, and event-free survival. Conclusion Strong relationships have been found between tumor bud density and poor prognostic variables such as primary tumor staging and lymph node staging. These results provide credence to the idea that tumor bud density can be an assessable prognostic feature that should be taken into account while reporting breast cancer cases. Tumor bud density evaluation has to be standardized nevertheless if it is to be widely adopted.

Uncommon Histopathological Subtypes and Variants of Cervical Carcinoma Diagnosed at a Tertiary Care Centre: A Case Series.

Introduction Cervical cancer ranks among the top gynaecological cancers worldwide. It is linked to lower socioeconomic status and high human papillomavirus (HPV) prevalence. This is a series of six cervical carcinoma cases analysed from 2021 to 2023 at our tertiary care centre to identify rare subtypes of cervical carcinoma. We document rare subtypes, which includeglassy cell carcinoma, small cell neuroendocrine carcinoma, papillary squamous-transitional variant,basaloid squamous cell carcinoma and serous carcinoma of the uterine cervix. Immunohistochemistry (IHC) was helpful in confirmation of the subtypes and in diagnosing HPV-associated cases. Materials and methods This case series comprises six cases, including raresubtypes and variants of cervical carcinomahistopathologically diagnosed by the Department of Pathology, Sri Ramachandra Institute of Higher Education and Research, Chennai, India, between 2021 and 2023. The demographic profile and patient details were obtained from the hospital information system and archival case files after obtaining informed consent from the patients. The H&E and relevant IHC slides along with histopathology reports of the included cases were analysed and studied. Results This series includes six cases of rare subtypes of cervical carcinoma, comprising glassy cell carcinoma, small cell neuroendocrine carcinoma, papillary squamous-transitional variant, basaloid squamous cell carcinoma (SCC), and serous carcinoma. Each subtype displays distinct clinicopathological features, emphasizing the need for specific diagnostic and treatment approaches, which are crucial in improving patient survival. Conclusion Six rare subtypes and variants of cervical carcinoma have been discussed in this case series, after correlating with histopathology reportsand clinical and radiological findings. Understanding the histopathological characteristics of these rarer subtypes is essential for accurate diagnosis and timely intervention. This series highlights the importance of comprehensive screening strategies, early diagnosis and awareness of rarer subtypes and variants of cervical carcinoma among healthcare professionals. These factors can tailor therapeutic options and improve patient outcomes.

Multimodal risk stratification of non-metastatic lung adenocarcinoma using AI on histology and immunohistochemistry slides.

e20083 Background: While immunohistochemistry (IHC) slides are commonly used to assess the presence of actionable biomarkers, the recent advances in artificial intelligence (AI) focus exclusively on hematoxylin and eosin (H&amp;E) slides. Nonetheless, many IHC slides, potentially rich in prognostic information, remain underexplored for risk stratification and outcome prediction. Our study aims to assess the complementarity of H&amp;E and IHC slides through the development of a multimodal prognostic AI model for lung adenocarcinoma patients. Methods: We collected 1 H&amp;E slide, 8 IHC slides (PD-L1, FOXP3, HELA2, CD3, CD4, CD8, CD163, KI67), and 2 double-stained slides (PDL1-CD163 and CD3-CD163) from 245 resected patients with lung adenocarcinoma at two different hospitals (median OS = 54.0 months [11.3 - 138.0]). Patients underwent various adjuvant treatments (chemotherapy n=92; immunotherapy n=4; other n=36; no treatment n=152). We cross-validated 11 AI models (one model per staining) to predict overall survival in these patients. We used Harell’s C-index and the 70-month cumulative AUC to evaluate the performance of our models. To assess their stratification power, each model’s predictions were split into high-risk and low-risk populations to compute a Hazard Ratio and a log-rank test p-value. Subsequently, a Cox proportional hazards model aggregated the predictions of the 11 models to compute a final risk score. We performed a grid search to find the combination of markers yielding the highest C-index. We calculated the hazard ratios to determine each biomarker's predictive value. Results: The H&amp;E model was the best unimodal model, with a C-index of 0.69 [0.67 - 0.71]. The best-performing multivariate model was obtained by combining the risk scores from univariate models in a Cox regression using H&amp;E, CD8, PD-L1, HELA2, and FOXP3 slides, reaching a C-index of 0.71 [0.69 - 0.73] (Table). We found that the predictions from H&amp;E (HR = 1.39; P = 0.03) and PD-L1 (HR = 1.17; P = 0.04) were significantly associated with survival. Conclusions: By significantly improving patient stratification with non-metastatic lung adenocarcinoma, our multivariate model proves that some IHC markers contain complementary proteomic information to H&amp;E slides. Consequently, this study paves the way for developing more comprehensive risk assessment tools from H&amp;E and IHC stainings. [Table: see text]

A digital pathology AI model to predict immune-oncology biomarker status and pembrolizumab response in a real-world cohort of patients with colorectal and breast cancer.

e13617 Background: Deep learning (DL) algorithms have garnered significant attention for prediction of biomarker status in digitized tissue slides. Here, we trained and validated a digital pathology algorithm to predict microsatellite instability (MSI)/mismatch repair deficiency (MMRd) in colorectal cancer (CRC) and PD-L1 status in breast cancer (BC) using a large real-world patient cohort. Methods: H&amp;E and immunohistochemistry (IHC) slides of CRC and BC from Caris Life Sciences (Phoenix, AZ) with known biomarker status were digitally scanned (CRC: N=27,494, 6.6% MSI-high by next-generation sequencing [NGS]; N=25,788, 6.4% MMRd by IHC; BC: N=16,069, 15.8% PD-L1+ by IHC). A transformer-based DL model (Wagner, Sophia J., et al., 2023) was trained to predict biomarker status, with 5-fold cross-validation. Accuracy, F1 score, area under the curve (AUC), and other metrics were calculated comparing the model to NGS/IHC “truth”. Risk stratification was performed on holdout datasets of pembrolizumab-treated CRC (N=422-454) and triple negative breast cancer (TNBC; N=513) pts. Post-treatment overall survival (OS) was calculated from start of pembrolizumab to last contact, per insurance claims data. Hazard ratios (HR) and 95% confidence intervals (CI) were calculated by Cox-Proportional hazards and compared between model and “truth”. Results: When applied to holdout datasets for biomarker prediction, the validated model achieved AUC of 0.78-0.95. In CRC and BC, performance was better among primary specimens than metastatic. For MSI-H/MMRd risk stratification in pembrolizumab-treated CRC, HR for OS were comparable between model and “truth” for primary and metastatic cohorts. When applied to the TNBC holdout dataset, the model performed better than “truth” for PD-L1 risk stratification in pembrolizumab-treated pts. Conclusions: A digital pathology DL model predicts biomarker status with high accuracy and is non-inferior to NGS/IHC for risk stratification of pembrolizumab-treated CRC and TNBC pts. These results support further investigation of AI algorithms developed from large datasets as possible rapid screening tools for biomarker detection in molecular testing programs. [Table: see text]

Fumarate Hydratase-Deficient Renal Cell Carcinoma—A Clinicopathological Study of a Series of 11 Cases

Abstract Introduction Fumarate hydratase (FH)-deficient renal cell carcinoma (RCC) is a rare, molecularly defined renal tumor with aggressive behavior. The diagnosis of these tumors is challenging because of varied morphology and limited access to molecular testing and immunohistochemistry (IHC) for FH and 2-succinocysteine. We aim to elucidate the histomorphology, clinical presentation, and follow-up of this tumor in this first series of cases of FH-deficient RCCs from India. Objectives This article aims to understand and elucidate the clinical presentation, pathologic findings, treatment options, and outcomes of FH-deficient RCC. Materials and Methods Diagnosed cases of FH-deficient RCC between January 2021 and January 2023 including clinical details were retrieved from the electronic medical record database. Histopathological and immunohistochemical slides were reviewed. Results Out of 11 cases of FH-deficient RCC, 36% had been referred with a diagnosis of type 2 papillary RCC. One patient presented with metastatic disease. All had mixed histologic patterns with the predominant pattern being papillary and showed FH loss on IHC. The classically described inclusion like nucleoli was present only focally in most cases. A subset of tumors had low-grade solid-nested morphology and these patients presented at an earlier stage (T2a). Two patients on multikinase inhibitors are alive with disease at 14 months' follow-up. Conclusion FH-deficient RCCs can have varied histologic patterns within the same tumor and show loss of FH expression by IHC. A subset has low grade morphology and tends to have a more indolent course. It is important to have a high index of suspicion for this diagnosis due to its varied histological appearance and aggressive behavior.

Clinicopathological characteristics of mucinous carcinoma of the breast.

Objective: To highlight clinicopathological differences between Pure Mucinous Carcinoma (PMC) and Mixed Mucinous Carcinoma (MMC) of the breast. Study Design: Descriptive Retrospective study. Setting: Private Lab in Faisalabad, Pakistan. Period: January 2017 to December 2022. Methods: FNAC smears diagnosed with Mucinous Carcinoma fulfilling the inclusion and exclusion criteria were carefully examined for features such as cellularity, extracellular mucin (ECM), nuclear pleomorphism, plasmacytoid cells, macrophages, and myxovascular fragments (MVFs). The diagnosis was confirmed by histopathology and were characterized in to PMC and MMC. Immunohistochemistry slides were evaluated according to established protocols. Statistical analysis was performed using SPSS (p &lt; 0.05). Results: The study analyzed 16 FNAC cytological samples with subsequent histopathological confirmation. These cases were derived from a pool of 712 female breast carcinoma cytology cases over a five-year duration. The predominant age group was 40 to 50 years, with the left breast and upper outer quadrant being the most common site. Distinct cytological characteristics, particularly the significant presence of extracellular mucin in PMC, were observed. Tumor grade and lymph node involvement emerged as crucial prognostic factors. MMC exhibited a high Ki-67 index, indicating increased cellular proliferation. Conclusion: Pure mucinous carcinomas (PMCs) are uncommon breast tumors with distinguished cytologic features. It is clinically and genetically distinct from mixed mucinous carcinoma (MMC) and other types of breast cancer. An important prognostic factor is lymph node involvement, and PMCs often have a low proliferation rate and a more favorable long-term prognosis. Therefore, the identification of PMC through FNAC holds significant diagnostic and clinical importance.

Abstract PO2-07-05: Deep learning model for automated quantification of HER2 expression in invasive breast cancers from immunohistochemical whole slide images

Abstract Introduction Human epidermal growth factor receptor 2 (HER2) protein overexpression and/or HER2 gene amplification is found in about 20% of invasive breast cancers. Considering the results of the DESTINY-Breast trials confirming the remarkable efficacy of anti-HER2 antibody drug-conjugate (T-Dxd) in both HER2-overexpressed and HER2-low tumors, it is necessary to identify not only HER2 (immunohistochemistry (IHC) score 3+) overexpressing tumors, but also HER2-low tumors. The latter category, defined as IHC1+ or IHC2+ but non-amplified, has proven to be challenging even for experienced pathologists, with high inter-observer variability. Here, we validate the performance of a deep learning (DL) model at: 1) predicting the IHC score from IHC histological features and 2) identifying HER2-low tumors with high sensitivity. Methods 675 HER2 stained IHC slides from primary breast cancer patients were selected based on pathology reports across three different cohorts (KCL_GSTT_1 n=369; Cypath_Breast n=214; KCL_GSTT_2 n=92). The slides were digitized and reviewed by expert breast pathologists. Specifically, Cypath_Breast and KCL_GSTT_2 were each annotated by one expert pathologist, while KCL_GSTT_1 was annotated by 5 expert pathologists with the ground truth defined as a majority vote between the 5 annotators. Cypath_Breast was assigned as the “discovery” set; while KCL_GSTT_1 and KCL_GSTT_2 were used as two independent validation cohorts. The model was specifically trained to extract features from IHC tiles to ensure they would capture both the staining intensity and the staining location on the cells (membrane, cytoplasmic or nuclei). The one-vs-one (OVO) and one-vs-rest (OVR) AUC as well as sensitivity and specificity to HER2-low and positive tumors were used as metrics to assess the performance of our model. An expert pathologist reviewed the most predictive regions of HER2 expression. Results After review by expert pathologists, 59 slides from KCL_GSTT_1 were removed either because of folded tissue, blurriness or because there was too little tissue. The IHC scores (0/1+/2+/3+) for the 3 cohorts were distributed as follows; Cypath_Breast: 42/120/36/16; KCL_GSTT_1: 120/90/52/48; KCL_GSTT_2: 54/22/15/1. For KCL_GSTT_1, the average agreement between the 5 expert pathologists amounted to a Cohen’s Kappa score of 0.63. Following training on Cypath_Breast, the performance of the model are presented in An ablation study proved that a feature extractor trained on IHC tiles outperformed an in-house extractor solely trained on H&amp;E tiles (OVO AUC 0.95 vs 0.93 on KCL_GSTT_1; DeLong p&amp;lt; 0.001). Specifically, the model performed best at distinguishing HER2-negative (HER2 IHC 0) from HER2-low and HER2-positive tumors with a sensitivity (0 vs 1+/2+/3+) of 0.95 [0.93 - 0.98] and a specificity (0 vs 1+/2+/3+) of 0.78 [0.72 - 0.84] on KCL_GSTT_1. We observed the same tendency on KCL_GSTT_2 with a sensitivity (0 vs 1+/2+/3+) of 0.97 [0.91 - 1.00] and a specificity of 0.91 [0.83 - 0.98]. More importantly, the DL model reached a Cohen’s Kappa score of 0.72 [0.67 - 0.77] with the ground truth on KCL_GSTT_1, surpassing the average agreement Kappa score between expert pathologists (0.63). The most predictive regions showed cytoplasmic staining in tumor regions. Conclusion Our model provides a path towards a fully automated workflow for identifying up to 95% of breast cancer patients who could potentially benefit from anti-HER2 targeted therapies. Additionally, we show the utility of AI-based tools to minimize discrepancies among pathologists and assist in the diagnostic patient pathway. Table 1: Results of external validation on KCL_GSTT_1 and KCL_GSTT_2 &amp;lt;grpahic&amp;gt; Cohorts OVO AUC OVR AUC IHC 0 OVR AUC IHC 1+ OVR AUC IHC 2+ OVR AUC IHC 3+ KCL_GSTT_1 0.95 0.95 0.80 0.91 0.99 [0.93 - 0.96] [0.94 - 0.95] [0.79 - 0.82] [0.90 - 0.92] [0.99 - 1.00] KCL_GSTT_2 0.92 0.97 0.78 0.84 N/A [0.90 - 0.93] [0.96 - 0.98] [0.76 - 0.81] [0.80 - 0.88] Citation Format: Pierre-Antoine Bannier, Loïc Herpin, Rémy Dubois, Lydwine Van Praet, Charles Maussion, Ellen Amonoo, Anca Mera, Jasmine Timbres, Cheryl Gillett, Elinor Sawyer, Patrycja Gazinska, Piotr Ziolkowski, Roberto Salgado, Sheeba Irshad. Deep learning model for automated quantification of HER2 expression in invasive breast cancers from immunohistochemical whole slide images [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-07-05.

Abstract PO5-24-07: HER2 EXPRESSION HETEROGENEITY PATTERN IN INVASIVE BREAST CARCINOMAS: FREQUENCY, DISTRIBUTION AND RELATION TO MORPHOLOGICAL VARIABLES

Abstract Human epidermal growth factor receptor 2 (HER2), a critical contributor to breast cancer development, is found to be amplified and overexpressed in approximately 15-20% of cases, making it a significant factor in carcinogenesis. This scenario was targeted by anti-HER2 drugs approved by several regulatory agencies in the past 15 years. Recently, novel anti-HER2 antibody-drug conjugates (ADCs) were approved to metastatic breast cancer with some HER2 expression albeit not due to amplification of the gene. Despite being classified as HER2 negative, most of these tumors exhibit detectable amounts of HER2 protein, reinforcing the challenging task of HER2 expression evaluation. In this scenario, it is very important to evaluate the spectrum of HER2 expression within a tumor due to its heterogeneity. We designed a retrospective linear study to reanalyze all HER2 immunohistochemical core biopsy slides of patients with primary invasive breast carcinomas (IBC) diagnosed and treated at São Paulo Federal University Hospital between 2019 and 2023. Pathological variables (histological subtype, histological grading, and hormonal receptors expression) were collected in pathology reports. Only patients with available slides and blocks were enrolled. HER2 slides were evaluated by three observers in consensus to access ASCO-CAP 2018 guidelines HER2 expression; presence or absence of HER2 expression heterogeneity; pattern of heterogeneity; frequency of the primary and secondary HER2 score in heterogeneous cases; and frequency of HER2 score in cases with homogeneous expression. Statistical analyses were performed with Chi-Square and Mann–Whitney U test using SSPS (26.0) program. 353 cases were included in this study. 104 (29,5%) were under 50 years and 249 (70,5%) over 50 years. 54,1% cases were left sided and 45,9% right sided. IBC of no special type comprehended 324 cases (91,8%) and invasive lobular carcinomas (ILC) were represented by 26 cases (7,4%); less than 1% of the cases were rare subtypes. Overall, HER2 results was negative in 296 (83,9%) cases and positive in 42 (11,9%) cases; HER2 2+ accounted by 15 cases (4,2%). Out of the negative cases, 235 (79.4%) were classified as 0+ and 61 (20.6%) were classified as 1+. Homogenous HER2 expression was observed in 287 cases (81,3%) with predominance of 0+ expression (80,8% - 232 cases), followed by 1+ (9,4% - 27 cases). ITH was present in 66 cases (18,7%), in which the subtyping was represented by 39 scattered (59,1%), 25 clustered (37,9%) and 2 mosaic (3%). The most prevalent score in this group was 1+ (51,5% - 34 cases), followed by 3+ (25,8% - 17 cases); the secondary score was predominantly categorized as 0+ (58,3%), followed by 1+ (20%) and 2+ (20%); only one case showed as 3+ expression. In the ILC group, 24 cases (92,3%) exhibited homogeneous HER2 expression, with predominant 0+ score (75% - 18 cases), while 2 cases (7,7%) showed heterogeneous expression. Out of the cases with heterogeneous HER2 expression, one exhibited a clustered heterogeneity pattern, with a primary HER2 score of 1+ and a secondary score of 0+. The other case displayed a scattered heterogeneity pattern, with a primary HER2 score of 3+ and a secondary score of 2+. There was a statistically significant association between HER2 expression heterogeneity and histologic grade (p = 0.005), and a marginal association with estrogen (p = 0.060) and progesterone (p = 0.060) expression. Tumor size wasn’t associated with heterogeneity (p = 0,071). We conclude that heterogeneity is prevalent in HER2 expression, especially in IBC, and should be addressed in pathology reports, especially in the ADCs scenario. Citation Format: Angela Flavia Waitzberg, Lucas de Figueiredo Barbosa, Adilson Monteiro dos Santos Filho, Ana Luiza da Cruz, Lisandra Gonzalez Porta Nova, Karla Calaça Kabbach Prigenzi. HER2 EXPRESSION HETEROGENEITY PATTERN IN INVASIVE BREAST CARCINOMAS: FREQUENCY, DISTRIBUTION AND RELATION TO MORPHOLOGICAL VARIABLES [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-24-07.

Abstract PO4-15-11: HER2 STATUS AND TUMOR HETEROGENEITY IN INVASIVE BREAST CARCINOMAS: CLINICAL PATHOLOGICAL IMPACT

Abstract Human epidermal growth factor receptor 2 (HER2) is a major player in breast carcinogenesis with a range of 15-20% of cases harboring gene amplification and overexpression turning the tumor eligible to over eight anti-HER2 drugs in the past 15 years. Recently, novel anti-HER2 antibody-drug conjugates (ADCs) treatment was recently approved to metastatic breast cancer bearing some HER2 expression albeit not due to gene amplification. Immunohistochemically classified, by ASCO-CAP Guidelines (2018), as 1+ cases were enrolled in clinical trials and benefited by the addition of ADCs to chemotherapy. Despite being classified as HER2 negative, most tumors exhibit detectable levels of HER2 protein, reinforcing the importance of HER2 expression evaluation. HER-2 intratumoral heterogeneity (ITH) is reported in up to 40% of breast cancers and is defined as the coexistence of subpopulations of tumor cells with different HER2 gene or protein expression. In this scenario, it becomes very important to evaluate the spectrum of HER-2 expression in correlation with pathological factors as ITH is associated with poor prognosis and anti-HER2 resistance. We designed a retrospective linear study to reanalyze all HER2 immunohistochemical core biopsy slides of patients with primary invasive breast carcinomas (IBC) diagnosed and treated at São Paulo Federal University Hospital between 2019 and 2023. Clinical variables (age, laterality, tumor size by ultrasound imaging, BI-RADS) were collected from clinical files. HER2 slides were reviewed by three observers and reported regarding status by ASCO-CAP 2018 guidelines, HER2 heterogeneity and patterns. Statistical analyses were performed with Chi-Square test of independence, Fisher's exact test and Mann–Whitney U test using IBM® SPSS® Statistics (26.0) software. 353 cases were included; the mean age of the patients at the time of diagnosis was 58 years old. 191 cases (54,1%) were left sided and 162 cases (45,9%) were right sided. Regarding BI-RADS report, the major category was 4 (140 cases), followed by 5 (119 cases). Out of the 164 patients who underwent clinical follow-up at our institute, 14 deaths were reported. Concerning pathological features, IBC of no special type was the prevalent histological subtype with 304 cases (86,1%), followed by invasive lobular carcinoma, with 26 cases (7,4%). 296 cases (83,9%) were HER2 negative and 42 (11,9%) were HER2 positive; 15 cases were HER2 2+ (4,2%). Amongst negative cases, 235 were HER2 0+ and 61 were HER2 1+. Considering ITH, 287 cases (81,3%) were HER2 homogenous with 0+ score as the most prevalent, presenting with 232 cases (80%). 66 cases (18,7%) had ITH, with 1+ as the most prevalent primary score, with 34 cases (51,5%), followed by 3+, with 17 cases (25,8%). Not only HER2 positive carcinomas, but also the presence of heterogeneity in HER2 expression was associated with death outcome (p=0,003 and p=0,001, respectively). Also, HER2 positive IBC had larger tumor size compared to HER2 negative carcinomas (mean size of 25,6 mm x 31,3 mm, respectively; p=0,012); HER2 heterogeneity showed no statistical significance when associated with tumor size (p=0,165). We conclude that ITH is prevalent in HER2 expression and should be addressed in pathology reports since it may play an additional role in tumor progression and drug response, especially in the ADCs scenario. Citation Format: Karla Calaça Kabbach Prigenzi, Lisandra Gonzalez Porta Nova, Adilson Monteiro dos Santos Filho, Ana Luiza da Cruz, Lucas de Figueiredo Barbosa, Angela Flavia Waitzberg. HER2 STATUS AND TUMOR HETEROGENEITY IN INVASIVE BREAST CARCINOMAS: CLINICAL PATHOLOGICAL IMPACT [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-15-11.

Abstract PO3-15-07: False-negative results of hyperexpression of HER2 receptor in breast cancer at a public tertiary hospital in Brazil

Abstract Introduction: Breast cancer (BC) is the second leading cause of cancer death in women worldwide. One of the major advances in BC management was its molecular classification, especially regarding the Human Epidermal growth factor Receptor 2 (HER2). HER2 positive tumors are at greater risk of visceral metastasis and are associated with worse survival rates. Thus, the use of specific drugs to target this pathway is essential and false-negative have a high impact on patient care. HER2 status is usually accessed using immunohistochemistry (IHC), but false-negatives results occur. When IHC results are inconclusive, in-situ hybridization (ISH) testing is necessary. Objective: to determine if there is variability between the positivity rates between laboratories that performed the ISH, according to the IHQ, and to evaluate if there are false-negative results and possible prognostic impact. Methods: retrospective, observational study in a public hospital in the city of Curitiba (Brazil), followed by cross-sectional analysis of histological samples. All cases of BC that underwent HER2 assessment by IHC and ISH between January 2008 and December 2018 were included. Participants classified as HER2 negative by IHC and patients whose medical records were not available were excluded. A new analysis of all IHC slides and of cases with negative ISH was performed. Results: We identified 205 people with an average age of 53.52 (± 11.89) years. Most cases were classified as clinical stage I and II (68.3%), and the most prevalent histological features were Invasive Ductal Carcinoma (82.4%) and luminal molecular subtype (49.8%). Initial ISH testing was performed by four laboratories. There was a significant difference in HER2 positivity rates between these laboratories, even after individual reanalysis of all IHC slides. Of the 114 cases with negative ISH, it was possible to obtain histological material in 82 of them to perform a new standardized ISH. The false-negative rate for HER2 in this 82 patients was 41.46%, with 10 cases out of 24 for positive IHC (3+) and 22 out of 58 for inconclusive IHC (2+). In this paper, false-negative results did not impact in survival, most likely to differences between groups. Conclusion: our work showed different rates of positivity for HER2 among laboratories that performed confirmatory test with ISH. The performance of a second standardized ISH proved that the difference between the laboratories was due to false-negative results. There was no difference in recurrence and cancer-specific survival in this false-negative sample. Keywords: breast cancer. Biomarkers. Health technology assessment. HER2 receptor. DIfferences between laboratories reagarding HER2 false negatives –insert figrue image– Citation Format: Bruno Batista, Sergio Ioshii, Sergio Padilha, Jacqueline Nabhen, Tayza Ostroski, Caroline Batista. False-negative results of hyperexpression of HER2 receptor in breast cancer at a public tertiary hospital in Brazil [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-15-07.

Abstract PO4-26-08: Prevalence of HER2-low and IHC &amp;gt;0 to &amp;lt; 1+ in breast cancer and its concordance between historical and rescored results: a multi-center, retrospective study in China

Abstract Background: With Trastuzumab deruxtecan (T-DXd) changing the anti-HER2 treatment paradigm, HER2-low (defined as IHC2+/ISH- and IHC1+) breast cancer patients have emerged as a new targetable population. The lower threshold for HER2 expression that can benefit from HER2-directed antibody-drug conjugates (ADCs) is still being investigated, such as HER2 immunohistochemistry (IHC) &amp;gt;0 to &amp;lt; 1+ (defined as IHC 0 with incomplete and faint staining in ≤10% of tumor cells) in the DESTINY-Breast06 trial. Accurate determination of HER2 scores has become a critical topic in clinical discussions, given its clinical relevance to HER2-directed treatment strategies. Hence, we conduct this study (HER2-PATH, NCT05203458) to evaluate the distribution of HER2 status including HER2 IHC &amp;gt;0 to &amp;lt; 1+ in Chinese patients with breast cancer. Concordance between rescored and historical results was also analyzed. Methods: A retrospective study was conducted in breast cancer patients who underwent surgery at 10 sites in China between July 2021 and July 2022. Archived HER2 IHC slides from these patients were subjected to rescoring by a review committee comprising two readers and one adjudicator. The two readers independently evaluated each slide blinded to the historical scores. If their results matched, the recorded outcome was considered final. In cases of disagreement, the adjudicator made the final judgment. All slides were stained using Ventana 4B5 and scored following the ASCO/CAP 2018 guidelines, including the addition of the IHC &amp;gt;0&amp;lt; 1+ as defined in the DESTINY-Breast06 trial. The prevalence of the rescored HER2 status was calculated, and the concordance between the historical and rescored HER2 status was assessed using the Cohen's Kappa coefficient. Results: A total of 2868 patients were included in the analysis. The rescored results categorized 682 (23.8%) patients as HER2 IHC 0, 871 (30.4%) patients as IHC 1+, 800 (27.9%) patients as IHC 2+, and 515 (18.0%) patients as IHC 3+. The rates of HER2-positive, HER2-low, and HER2 IHC 0 (including HER2 null and HER2 IHC &amp;gt;0 to &amp;lt; 1+) were 21.8%, 54.3% and 23.9%, respectively. Notably, the prevalence of HER2-low was numerically higher in the HR-positive subgroup compared to the HR-negative subgroup (60.2% vs 30.6%). Furthermore, the prevalence of HER2 IHC &amp;gt;0 to &amp;lt; 1+ and HER2 null was 10.6% and 13.2% among all patients, respectively. Among the HR-positive subgroup, the prevalence of HER2 IHC &amp;gt;0 to &amp;lt; 1+ was 10.9%, while the rate was 9.1% among the HR-negative subgroup. Overall, there was an 83.1% concordance between the historical and rescored results for HER2 IHC scores. The concordance rate for IHC 1+ was numerically lower (74.5%) compared to IHC 0 (85.2%), IHC 2+ (81.4%), and IHC 3+ (98.6%). However, considering that 12.0% of IHC 1+ patients turned into IHC 2+ with limited impact on HER2-low diagnosis, the concordance rate for HER2-low remained as 91.6%. Conclusion: HER2-low prevalence in Chinese breast cancer patients was found to be consistent with global data, while additional 10.6% of patients were identified as HER2 IHC &amp;gt;0 to &amp;lt; 1+, which is currently being investigated in a randomized controlled trial comparing T-DXd with SoC. To our knowledge, this is the first study to report the prevalence of HER2-low, including HER2 IHC &amp;gt;0 to &amp;lt; 1+, in the Chinese breast cancer population based on rescored results. The concordance of HER2-low between the historical and rescored results was 91.6%, indicating that most cases could be reproducibly classified. Table: Rescored HER2 Expression Level Citation Format: Hong Lv, Junqiu Yue, Qingfu Zhang, Fangping Xu, Jianming Li, Lingfei Kong, Peng Gao, Guanjun Zhang, Haifeng Yang, Xiu Nie, Wen-Tao Yang. Prevalence of HER2-low and IHC &amp;gt;0 to &amp;lt; 1+ in breast cancer and its concordance between historical and rescored results: a multi-center, retrospective study in China [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-26-08.

Abstract PO4-26-09: The Advantage of Artificial-Intelligence in HER2 IHC 0 and 1+ Scoring in Breast Cancer

Abstract Background: Trastuzumab deruxtecan has substantially changed the treatment of HER2-low breast cancer, emphasizing the need for accurate differentiation between HER2 immunohistochemistry (IHC) scores of 0 and 1+. However, the current accuracy of HER2 IHC 0 and 1+ scoring in real-world is inadequate. Artificial intelligence (AI) has emerged as a potential solution to improve interpretation accuracy. We developed an AI algorithm based on whole slide images (WSI) to quantitatively assess HER2 expression and its role in interpreting HER2 IHC scores of 0 and 1+. Methods: Our three-phase AI analysis framework involved segmenting tumor areas (excluding ductal carcinoma in situ), detecting and classifying tumor cells based on membrane staining patterns, and grading HER2 IHC scores according to the 2018 ASCO/CAP HER2 guideline. The AI tool was trained using 6012 patches annotated by experienced pathologists. Performance evaluation was conducted using a test dataset comprising 265 slides. A total of 141 HER2 IHC slides (27 IHC 0 and 114 IHC 1+) from patients diagnosed with invasive breast cancer at Fudan University Shanghai Cancer Center in 2021 were included. Two pretrained expert pathologists independently rescored the HER2 slides, followed by analysis using the AI tool. All inconsistent cases were also reviewed by a third senior pathologist. Interobserver agreement between the pathologists and concordance between the pathologists and the AI interpretation results were assessed. We also explored potential ranges where HER2 interpretation by pathologists exhibited inconsistency or inaccuracy. Results: The HER2 AI algorithm showed high performance in interpreting all levels of HER2 expression, with an overall kappa value of 0.85. For HER2 IHC 0 and 1+ cases, the AI model demonstrated high sensitivities (0.839 and 0.914) and specificities (0.983 and 0.890) (Table 1). After the rescoring process, 51 cases were reclassified as IHC 0 and 90 cases as IHC 1+. The overall agreement rate between the historical and re-scoring results was 73.05% (103/141). The agreement rate between the AI and re-scoring results was 91.49% (129/141) (Table 2), indicating comparable interpretation capabilities between the AI model and well-trained pathologists. The interobserver agreement between the two pathologists was 83.69% (118/141), with agreement rates of 88.23% (45/51) for IHC 0 and 81.11% (73/90) for IHC 1+. Analyzing the inconsistent cases (n=12) between IHC 0 and IHC 1+, we examined the percentage of weak and incomplete expression provided by the AI. In 9 out of 12 cases, the AI provided the same results as the third senior pathologist, suggesting that AI could assist in interpretation within this range. We identified a range of 2.83% to 24.98% as a "grey-zone," where even well-trained pathologists provided inconsistent results. Conclusion: Our study demonstrates the excellent performance of an AI-based tool for scoring HER2 IHC 0 and 1+. The AI model exhibits comparable capabilities to well-trained pathologists in interpreting HER2 expression. Additionally, we identified a "grey-zone" among pathologists, highlighting the limitations of manual subjective interpretation. AI assistance within this zone may help mitigate subjective variations. Table 1. Correlation between pathologist read and AI read of HER2 immunohistochemistry. Table 2. Correlation between pathologist rescoring and AI read of HER2 immunohistochemistry. Citation Format: Ming Li, Hong Lv, Yizhi Zhao, Chenglu Zhu, Hansheng Li, Mingzhen Lin, Wen-Tao Yang. The Advantage of Artificial-Intelligence in HER2 IHC 0 and 1+ Scoring in Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-26-09.

Establishing guidelines for sentinel lymph node ultrastaging in endometrial cancer

BackgroundMany sentinel lymph node (SLN) ultrastaging protocols for endometrial cancer exist, but there is no consensus method.ObjectiveThis study aims to develop guidelines for size criteria in SLN evaluation for endometrial...