Potential application of body fluids autofluorescence in the non-invasive diagnosis of endometrial cancer.

BACKGROUND: Endometrial carcinoma (EC) is the most common cancer of the female reproductive tract in developed countries. The prognosis and 5-year survival rates are closely tied to the stage diagnosis. Current routine diagnostic methods of EC are either lacking specificity or are uncomfortable, invasive and painful for the patient. As of now, the gold diagnostic standard is endometrial biopsy. Early and non-invasive diagnosis of EC requires the identification of new biomarkers of disease and a screening test applicable to routine laboratory diagnostics. The application of untargeted metabolomics combined with artificial intelligence and biostatistics tools has the potential to qualitatively and quantitatively represent the metabolome, but its introduction into routine diagnostics is currently unrealistic due to the financial, time and interpretation challenges. Fluorescence spectral analysis of body fluids utilizes autofluorescence of certain metabolites to define the composition of the metabolome under physiological conditions. PURPOSE: This review highlights the potential of fluorescence spectroscopy in the early detection of EC. Data obtained by three-dimensional fluorescence spectroscopy define the quantitative and qualitative composition of the complex fluorescent metabolome and are useful for identifying biochemical metabolic changes associated with endometrial carcinogenesis. Autofluorescence of biological fluids has the prospect of providing new molecular markers of EC. By integrating machine learning and artificial intelligence algorithms in the data analysis of the fluorescent metabolome, this technique has great potential to be implemented in routine laboratory diagnostics.

Histological assessment of endometrial polyps resected by hysteroscopy.

OBJECTIVE: This study aimed to analyze the clinical data and pathologic aspects of endometrial polyps (EMPs) excised completely during surgical hysteroscopy and assess the connection between premalignant and malignant EMPs. PATIENTS AND METHODS: This retrospective study includes 489 participants who underwent hysteroscopy due to endometrial polyps, and the clinical features and histological findings of the resected polyps analyzed. RESULTS: Participants with EMPs were divided into six groups according to histologic findings. The histologic finding of most cases was simple benign endometrial polyp [397 patients (81.2%)]. Malignant polyp was detected in 3 patients (0.6%). The histologic findings according to age, menopausal status, and menstrual bleeding patterns at the time of presentation to the outpatient clinic were compared; however, no significant difference was observed. 237 patients were observed to have menometrorrhagia, which was the most prevalent symptom reported. The distribution of polyp sizes observed at hysteroscopy according to histologic findings was compared, but no significant difference was observed. CONCLUSIONS: EMPs are often benign but can include premalignant or malignant tissue changes. Hysteroscopy is used for direct observation of the uterine cervix and resection of existing polyps, considering the increasing frequency of its use as a diagnostic and treatment tool.

A new perspective on Endometrial Carcinoma classification and management strategies in context of molecular subtypes.

Endometrial cancer is the most common gynecological cancer and the second most prevalent female malignancy in the developed world. It is typically diagnosed in postmenopausal women, presenting with the characteristic clinical symptom of uterine abnormal bleeding. In the past, only two histological types were considered. However, it has become increasingly evident that endometrial cancer is a clinically heterogeneous disease, and this heterogeneity is closely associated with the diversity of underlying molecular alterations. The Cancer Genome Atlas classification has significantly advanced the diagnosis, risk stratification, and management of endometrial cancer by categorizing it into four molecular subgroups, each characterized by distinct mutational burdens and copy number alterations.

New staging of endometrial carcinoma - FIGO 2023.

AIM: To review the changes in the new version of the FIGO 2023 staging system for endometrial cancer. METHODS AND RESULTS: The new FIGO 2023 endometrial cancer staging system provides key updates for the diagnosis and treatment of endometrial cancer. An important step in diagnosis is molecular classification, which allows more accurate risk stratification for recurrence and the identification of targeted therapies. The new staging system, based on the recommendations of the international societies ESGO, ESTRO and ESP, incorporates not only the description of the pathological and anatomical extent of the disease, but also the histopathological characteristics of the tumour, including the histological type and the presence of lymphovascular space invasion. In addition, the staging system uses molecular testing to classify endometrial cancers into four prognostic groups: POLEmut, MMRd, NSMP and p53abn. Each group has its own specific characteristics and prognosis. The most significant changes have occurred in stages I and II, in which the sub-staging better reflects the biological behaviour of the tumour. This update increases the accuracy of prognosis and improves individualized treatment options for patients with endometrial cancer. CONCLUSION: The updated FIGO staging of endometrial cancer for 2023 incorporates different histologic types, tumour features, and molecular classifications to better reflect the current improved understanding of the complex nature of several endometrial cancer types and their underlying bio logic behaviour. The aim of the new endometrial cancer staging system is to better define stages with similar prognosis, allowing for more precise indication of individualised adjuvant radiation or systemic treatment, including the use of immunotherapy.

Endometrial Cancer Detection by DNA Methylation Analysis in Cervical Papanicolaou Brush Samples.

Background: Endometrial cancer (EC) is the leading gynecological cancer worldwide, yet current EC screening approaches are not satisfying. The purpose of this retrospective study was to evaluate the feasibility and capability of DNA methylation analysis in cervical Papanicolaou (Pap) brush samples for EC detection. Methods: We used quantitative methylation-sensitive PCR (qMS-PCR) to determine the methylation status of candidate genes in EC tissue samples, as well as cervical Pap brushes. The ability of RASSF1A and HIST1H4F to serve as diagnostic markers for EC was then examined in cervical Pap brush samples from women with endometrial lesions of varying degrees of severity. Results: Methylated RASSF1A and HIST1H4F were found in EC tissues. Further, methylation of the two genes was also observed in cervical Pap smear samples from EC patients. Methylation levels of RASSF1A and HIST1H4F increased as endometrial lesions progressed, and cervical Pap brush samples from women affected by EC exhibited significantly higher levels of methylated RASSF1A and HIST1H4F compared to noncancerous controls (P < .001). Receiver operating characteristic (ROC) curves and area under the curve (AUC) analyses revealed RASSF1A and HIST1H4F methylation with a combined AUC of 0.938 and 0.951 for EC/pre-EC detection in cervical Pap brush samples, respectively. Conclusion: These findings demonstrate that DNA methylation analysis in cervical Pap brush samples may be helpful for EC detection, broadening the scope of the commonly used cytological screening. Our proof-of-concept study provides new insights into the field of clinical EC diagnosis.

Applications of Data Characteristic AI-Assisted Raman Spectroscopy in Pathological Classification.

Raman spectroscopy has been widely used for label-free biomolecular analysis of cells and tissues for pathological diagnosis in vitro and in vivo. AI technology facilitates disease diagnosis based on Raman spectroscopy, including machine learning (PCA and SVM), manifold learning (UMAP), and deep learning (ResNet and AlexNet). However, it is not clear how to optimize the appropriate AI classification model for different types of Raman spectral data. Here, we selected five representative Raman spectral data sets, including endometrial carcinoma, hepatoma extracellular vesicles, bacteria, melanoma cell, diabetic skin, with different characteristics regarding sample size, spectral data size, Raman shift range, tissue sites, Kullback-Leibler (KL) divergence, and significant Raman shifts (i.e., wavenumbers with significant differences between groups), to explore the performance of different AI models (e.g., PCA-SVM, SVM, UMAP-SVM, ResNet or AlexNet). For data set of large spectral data size, Resnet performed better than PCA-SVM and UMAP. By building data characteristic-assisted AI classification model, we optimized the network parameters (e.g., principal components, activation function, and loss function) of AI model based on data size and KL divergence etc. The accuracy improved from 85.1 to 94.6% for endometrial carcinoma grading, from 77.1 to 90.7% for hepatoma extracellular vesicles detection, from 89.3 to 99.7% for melanoma cell detection, from 88.1 to 97.9% for bacterial identification, from 53.7 to 85.5% for diabetic skin screening, and mean time expense of 5 s.

Endogenous estrogen metabolites as oxidative stress mediators and endometrial cancer biomarkers.

BACKGROUND: Endometrial cancer is the most common gynecologic malignancy found in developed countries. Because therapy can be curative at first, early detection and diagnosis are crucial for successful treatment. Early diagnosis allows patients to avoid radical therapies and offers conservative management options. There are currently no proven biomarkers that predict the risk of disease occurrence, enable early identification or support prognostic evaluation. Consequently, there is increasing interest in discovering sensitive and specific biomarkers for the detection of endometrial cancer using noninvasive approaches. CONTENT: Hormonal imbalance caused by unopposed estrogen affects the expression of genes involved in cell proliferation and apoptosis, which can lead to uncontrolled cell growth and carcinogenesis. In addition, due to their ability to cause oxidative stress, estradiol metabolites have both carcinogenic and anticarcinogenic properties. Catechol estrogens are converted to reactive quinones, resulting in oxidative DNA damage that can initiate the carcinogenic process. The molecular anticancer mechanisms are still not fully understood, but it has been established that some estradiol metabolites generate reactive oxygen species and reactive nitrogen species, resulting in nitro-oxidative stress that causes cancer cell cycle arrest or cell death. Therefore, identifying biomarkers that reflect this hormonal imbalance and the presence of endometrial cancer in minimally invasive or noninvasive samples such as blood or urine could significantly improve early detection and treatment outcomes.

Factors associated with interobserver variation amongst pathologists in the diagnosis of endometrial hyperplasia: A systematic review.

OBJECTIVE: Reproducible diagnoses of endometrial hyperplasia (EH) remains challenging and has potential implications for patient management. This systematic review aimed to identify pathologist-specific factors associated with interobserver variation in the diagnosis and reporting of EH. METHODS: Three electronic databases, namely MEDLINE, Embase and Web of Science, were searched from 1st January 2000 to 25th March 2023, using relevant key words and subject headings. Eligible studies reported on pathologist-specific factors or working practices influencing interobserver variation in the diagnosis of EH, using either the World Health Organisation (WHO) 2014 or 2020 classification or the endometrioid intraepithelial neoplasia (EIN) classification system. Quality assessment was undertaken using the QUADAS-2 tool, and findings were narratively synthesised. RESULTS: Eight studies were identified. Interobserver variation was shown to be significant even amongst specialist gynaecological pathologists in most studies. Few studies investigated pathologist-specific characteristics, but pathologists were shown to have different diagnostic styles, with some more likely to under-diagnose and others likely to over-diagnose EH. Some novel working practices were identified, such as grading the "degree" of nuclear atypia and the incorporation of objective methods of diagnosis such as semi-automated quantitative image analysis/deep learning models. CONCLUSIONS: This review highlighted the impact of pathologist-specific factors and working practices in the accurate diagnosis of EH, although few studies have been conducted. Further research is warranted in the development of more objective criteria that could improve reproducibility in EH diagnostic reporting, as well as determining the applicability of novel methods such as grading the degree of nuclear atypia in clinical settings.

Biomarker characterization in endometrial cancer in Europe: first survey data analysis from 69 pathological academic and hospital labs.

Introduction: Endometrial carcinoma (EC) is the commonest gynecological cancer affecting women in Western populations. To predict patient risk, the 2020 edition of the World Health Organization (WHO) Classification of Tumors of the Female Genital Tract stressed the importance of integrated histo-molecular classification of the disease. This survey analysis poses attention on the most frequently used immunohistochemical and molecular markers adopted in daily categorization of ECs in European laboratories. Methods: We analyzed data collected through questionnaires administered to 40 Italian, 20 Spanish, 3 Swiss and 6 United Kingdom (UK) laboratories. We collected information regarding daily practice in EC evaluation, specifically concerning mismatch repair status (MMR) and microsatellite instability (MSI). Summary and descriptive statistical analyses were carried out to evaluate the current practice of each laboratory. Results: The results show that MMR status is mainly evaluated by using immunohistochemistry (IHC) on most EC samples. The most frequent approach for the analysis of MMR status is IHC of four proteins (PMS2, MSH6, MSH2, MLH1). MSI analysis by molecular methods is uncommon but useful as a supplemental tool in specific conditions. MLH1 promoter hypermethylation and BRAF V600 mutations analysis are performed in case of negative expression of MLH1/PMS2. Other markers (mainly p53 followed by POLE and PTEN) are investigated in particular in Spain and Switzerland in a consistent number of cases. Conclusion: Guidelines consultation and standardization of laboratory procedures are efficient means for EC prognostic risk stratification and improving the quality of care.

Single-cell analysis reveals landscape of endometrial cancer response to estrogen and identification of early diagnostic markers.

BACKGROUND: The development of endometrial cancer (EC) is closely related to the abnormal activation of the estrogen signaling pathway. Effective diagnostic markers are important for the early detection and treatment of EC. METHOD: We downloaded single-cell RNA sequencing (scRNA-seq) and spatial transcriptome (ST) data of EC from public databases. Enrichment scores were calculated for EC cell subpopulations using the "AddModuleScore" function and the AUCell package, respectively. Six predictive models were constructed, including logistic regression (LR), Gaussian naive Bayes (GaussianNB), k-nearest neighbor (KNN), support vector machine (SVM), extreme gradient boosting (XGB), and neural network (NK). Subsequently, receiver-operating characteristics with areas under the curves (AUCs) were used to assess the robustness of the predictive model. RESULT: We classified EC cell coaggregation into six cell clusters, of which the epithelial, fibroblast and endothelial cell clusters had higher estrogen signaling pathway activity. We founded the epithelial cell subtype Epi cluster1, the fibroblast cell subtype Fib cluster3, and the endothelial cell subtype Endo cluster3 all showed early activation levels of estrogen response. Based on EC cell subtypes, estrogen-responsive early genes, and genes encoding Stage I and para-cancer differentially expressed proteins in EC patients, a total of 24 early diagnostic markers were identified. The AUCs values of all six classifiers were higher than 0.95, which indicates that the early diagnostic markers we screened have superior robustness across different classification algorithms. CONCLUSION: Our study elucidates the potential biological mechanism of EC response to estrogen at single-cell resolution, which provides a new direction for early diagnosis of EC.

Detection of endometrial cancer in cervico-vaginal fluid and blood plasma: leveraging proteomics and machine learning for biomarker discovery.

BACKGROUND: The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma. METHODS: Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony. FINDINGS: A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively. INTERPRETATION: Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted. FUNDING: Cancer Research UK, Blood Cancer UK, National Institute for Health Research.

Discovery of the potential biomarkers for early diagnosis of endometrial cancer via integrating metabolomics and transcriptomics.

Endometrial cancer (EC) is one of the most common malignant tumors in women, and the increasing incidence and mortality pose a serious threat to the public health. Early diagnosis of EC could prolong the survival period and optimize the survivorship, greatly alleviating patients' suffering and social medical pressure. In this study, we collected urine and serum samples from the recruited patients, analyzed the samples using LC-MS approach, and identified the differential metabolites through metabolomic analysis. Then, the differentially expressed genes were identified through the systematic transcriptomic analysis of EC-related dataset from Gene Expression Omnibus (GEO), followed by network profiling of metabolic-reaction-enzyme-gene. In this experiment, a total of 83 differential metabolites and 19 hub genes were discovered, of which 10 different metabolites and 3 hub genes were further evaluated as more potential biomarkers based on network analysis. According to the KEGG enrichment analysis, the potential biomarkers and gene-encoded proteins were found to be involved in the arginine and proline metabolism, histidine metabolism, and pyrimidine metabolism, which was of significance for the early diagnosis of EC. In particular, the combination of metabolites (histamine, 1-methylhistamine, and methylimidazole acetaldehyde) as well as the combination of RRM2, TYMS and TK1 exerted more accurate discrimination abilities between EC and healthy groups, providing more criteria for the early diagnosis of EC.

Endometrial stromal tumors: A clinico-histomorphological spectrum of endometrial stromal tumors with review of literature.

BACKGROUND: Endometrial stromal tumors (ESTs) are rare subset of mesenchymal uterine neoplasms. There are heterogeneous morphological, immunohistochemical, and genetic features. Approximately 50% of ESTs occur in perimenopausal women. In 2020, WHO sub-categorized ESTs into four groups: endometrial stromal nodule (ESN), low-grade endometrial stromal sarcoma (LGESS), high-grade endometrial stromal sarcoma (HGESS), and undifferentiated uterine sarcoma (UUS). OBJECTIVE: To review the morphological spectrum of endometrial stromal tumors. METHOD: This retrospective study reviewed the histomorphological features of 15 endometrial stromal tumors with respect to atypia, necrosis, mitosis, collagen bands, whorling around vessels, myometrial invasion, and inflammatory cells. Immunohistochemistry markers (CD10, SMA, and ER) along with special stains (Masson's trichrome, toluidine blue) were also studied. RESULTS: The age of the patients ranged from 32 to 60 years. Three patients were postmenopausal. The most common presenting symptom was vaginal bleeding. Five patients were operated with a clinical diagnosis of uterine fibroid. One patient presented with prolapse with no other complaint. All the 15 patients had total abdominal hysterectomy and salpingo-oophorectomy. One case showed necrosis, eight cases showed collagen bands, all the 15 cases showed whorling around vessels, one case showed vascular emboli, and seven cases showed inflammatory cells. In low-grade cases, one case showed focal atypia and one case showed focal coagulative necrosis indicating infarction. Thirteen cases were LGESS, and one case of ESN and HGESS. All cases were positive for ER and CD10. CONCLUSION: Endometrial stromal tumors demonstrate extensive permeation of the myometrium as irregular islands with frequent vascular invasion, whorling around vessels, collagen bands, and inflammatory cells. All these features should be observed thoroughly on microscopy by pathologists to clearly differentiate the low-grade and high-grade endometrial stromal tumors, and to understand the overlapping gray areas morphologically as it affects the prognosis of the patient.

Accuracy of endometrial sampling in the diagnosis of endometrial cancer: a multicenter retrospective analysis of the JAGO-NOGGO.

BACKGROUND: Accurate preoperative molecular and histological risk stratification is essential for effective treatment planning in endometrial cancer. However, inconsistencies between pre- and postoperative tumor histology have been reported in previous studies. To address this issue and identify risk factors related to inaccurate histologic diagnosis after preoperative endometrial evaluation, we conducted this retrospective analysis. METHODS: We conducted a retrospective analysis involving 375 patients treated for primary endometrial cancer in five different gynaecological departments in Germany. Histological assessments of curettage and hysterectomy specimens were collected and evaluated. RESULTS: Preoperative histologic subtype was confirmed in 89.5% of cases and preoperative tumor grading in 75.2% of cases. Higher rates of histologic subtype variations (36.84%) were observed for non-endometrioid carcinomas. Non-endometrioid (OR 4.41) histology and high-grade (OR 8.37) carcinomas were identified as predictors of diverging histologic subtypes, while intermediate (OR 5.04) and high grading (OR 3.94) predicted diverging tumor grading. CONCLUSION: When planning therapy for endometrial cancer, the limited accuracy of endometrial sampling, especially in case of non-endometrioid histology or high tumor grading, should be carefully considered.

Psychometric validation of the Functional Assessment of Cancer Therapy-Endometrial among endometrial cancer patients.

OBJECTIVE: To evaluate a psychometric validation of the endometrial cancer subscales (EnCS) in the Functional Assessment of Cancer Therapy-Endometrial (FACT-EN) among patients with endometrial cancer. METHODS: This cross-sectional study was conducted at a tertiary university-based hospital in South Korea between April and October 2022. Participants completed a survey questionnaire that included the FACT-EN. Exploratory and confirmatory factor analyses (EFA, CFA) and the reliability were measured using the intraclass correlation coefficient (ICC) under a two-way mixed model. Pearson's correlations were used to evaluate the validity. We also tested known-group validity. RESULTS: In total, 240 patients with endometrial cancer participated in the survey. In EFA, we found EnCS included four domains. In CFA, four-factor solution model was good: CFI = 0.659; SRMR = 0.066, and RMSEA = 0.073. The mean (SD) of total score of FACT-EN was 122.84 (23.58). The floor and ceiling effects were 0.4% and 0.4%, respectively. Cronbach's α coefficients for the five scales of the EnCS ranged from 0.78 to 0.91. The ICC of EnCS was 0.76. The convergent and discriminant validity of EnCS was acceptable. In the group analysis, older age and lower ECOG performance scores were associated with higher EnCS scores. The stomach and vaginal domains in EnCS were higher in patients who had completed treatment for more than 1 year compared to those who were still undergoing treatment. CONCLUSIONS: FACT-EN has demonstrated its validity as an assessment tool with significant implications for capturing various symptoms in patients with endometrial cancer.

Enhanced Diagnostic Efficiency of Endometrial Carcinogenesis and Progression in Women with Abnormal Uterine Bleeding through Peripheral Blood Cytokine Testing: A Multicenter Retrospective Cohort Study.

Objective: This study aimed to evaluate the role of plasma cytokine detection in endometrial cancer screening and tumor progression assessment in patients with abnormal uterine bleeding. Methods: In this multicenter retrospective cohort study of 287 patients with abnormal uterine bleeding, comprehensive clinical information and laboratory assessments, including cytokines, routine blood tests, and tumor markers, were performed. Associations between the clinical indicators and endometrial carcinogenesis/progression were evaluated. The independent risk factors for endometrial cancer and endometrial cancer with deep myometrial invasion were analyzed using multivariate binary logistic regression. Additionally, a diagnostic model was used to evaluate the predictive efficacy of these identified risk factors. Results: In patients with abnormal uterine bleeding, low IL-4 and high IL-8 levels were independent risk factors for endometrial cancer (p < 0.05). Combining IL-4, IL-8, CA125, and menopausal status improved the accuracy of assessing endometrial cancer risk. The area under curve of the model is 0.816. High IL-6 and IL-8 levels were independent risk factors for deep myometrial invasion in patients with endometrial cancer (p < 0.05). Similarly, combining IL-6, IL-8, and Monocyte counts enhanced the accuracy of assessing endometrial cancer risk with deep myometrial invasion. The area under curve of the model is 0.753. Conclusions: Cytokines such as IL-4, IL-8, and IL-6 can serve as markers for monitoring endometrial cancer and its progression in women with abnormal uterine bleeding.

Endometrial cytological findings for a mesonephric-like endometrial adenocarcinoma: A case report.

A mesonephric-like endometrial adenocarcinoma (ML-EAC) is very rare and has a worse prognosis than other endometrial carcinomas. We describe an ML-EAC and report our endometrial cytological findings. A 76-year-old woman presented with irregular genital bleeding and a uterine mass. Endometrial cytology revealed atypical cylindrical or spindle-shaped cells in the form of small aggregates or solitary cells. The cell aggregates exhibited irregularly stacked papillary structures, small glandular structures, and fenestrated structures. The atypical cells had a nucleus with fine-granular chromatin and a granular cytoplasm, and nuclear grooves and intranuclear pseudo-inclusions were present. Hyaline globules were observed in the glandular lumens and in the background. The presumptive histological type was an adenocarcinoma, but the cytological features were different from those of an endometrioid carcinoma. A histological examination of the endometrial biopsy revealed an adenocarcinoma, and a simple hysterectomy was performed. A grayish-white elevated mass measuring 90 mm × 70 mm × 40 mm was observed on the uterine corpus in the hysterectomy specimen. Histologically, the tumor proliferated as complex tubular structures containing eosinophilic colloid-like materials and trabecular structures. The tumor cells were diffuse and positive for GATA-3 and partially positive for thyroid transcription factor-1. Estrogen and progesterone receptors were negative. An ML-EAC was diagnosed. The tumor was invasive and extended beyond one-half of the muscle layer with a high degree of vascular invasion. In conclusion, we need to focus on the various shapes of the cell aggregate, nuclear grooves, and intranuclear pseudo-inclusions of tumor cells to distinguish an ML-EAC from other endometrial carcinomas in endometrial cytology.

Atypical glandular cells in Pap tests: cytology-histology correlation and risk assessment with human papillopmavirus (HPV) testing.

INTRODUCTION: Atypical glandular cells (AGC) represent less than 1% of Pap test cases and include a variety of lesions in both the cervix and endometrium. The study aimed to investigate the cytology-histology correlation in AGC patients and to evaluate the clinical utility of hrHPV testing in this diagnostic context. MATERIALS AND METHODS: We identified 491 atypical glandular cells (AGC) cases in our quality analysis (QA) database of 336,064 Pap tests interpreted between March 1, 2013 and July 12, 2016. Of these, 251 cases had follow-up biopsies with hrHPV tests in 148 cases. RESULTS: The most common histologic diagnosis associated with AGC was normal/benign or low-grade lesions, comprising 55% of cervical biopsies and 24% of endometrial biopsies. High-grade lesions were identified in 21% of follow-up biopsies. In patients with AGC cytology, a positive hrHPV test significantly increased the likelihood of cervical HSIL or above lesions on biopsy by 26.4 times (OR = 26.4, 95% CI: 5.8-119.4, P < 0.0001). A positive genotyping result for HPV 16 dramatically increased the likelihood of cervical HSIL or above lesions on biopsy (OR = 84, 95% CI: 12.0-590.5, P < 0.0001). The HPV test had a negative predictive value of 97% (CI: 85%-100%). CONCLUSIONS: Our study confirms that AGC is a significant diagnosis with an overall risk for high-grade cervical or endometrial lesions as high as 21%. hrHPV testing with genotyping is an effective tool for identifying high-risk individuals within the AGC population, with excellent positive and negative predictive values. This approach is valuable for clinical risk stratification and differential diagnosis in patients with AGC cytology.

Establishing guidelines for sentinel lymph node ultrastaging in endometrial cancer.

BACKGROUND: Many sentinel lymph node (SLN) ultrastaging protocols for endometrial cancer exist, but there is no consensus method. OBJECTIVE: This study aims to develop guidelines for size criteria in SLN evaluation for endometrial cancer, to determine whether a single cytokeratin AE1:AE3 immunohistochemical slide provides sufficient data for diagnosis, and to compare cost efficiency between current and limited ultrastaging protocols at a large tertiary care institution. METHODS: Our current SLN ultrastaging protocol consists of cutting two adjacent paraffin block sections at two levels (L1 and L2), 50 µm apart, with two slides at each level stained with hematoxylin and eosin and cytokeratin AE1:AE3 immunohistochemistry. We retrospectively reviewed digitized L1 and L2 slides of all positive ultrastaged SLNs from patients treated for endometrial cancer between January 2013 and January 2020. SLN diagnosis was defined by measuring the largest cluster of contiguous tumor cells in a single cross section: macrometastasis (>2.0 mm), micrometastasis (>0.2 to ≤2.0 mm or >200 cells), or isolated tumor cells (≤0.2 mm or ≤200 cells). Concordance between L1 and L2 results was evaluated. Cost efficiency between current (two immunohistochemical slides per block) and proposed limited (one immunohistochemical slide per block) protocols was compared. RESULTS: Digitized slides of 147 positive SLNs from 109 patients were reviewed; 4.1% of SLNs were reclassified based on refined size criteria. Complete concordance between L1 and L2 interpretations was seen in 91.8% of SLNs. A false-negative rate of 0%-0.9% in detecting micrometastasis and macrometastasis using a limited protocol was observed. Estimated charge-level savings of a limited protocol were 50% per patient. CONCLUSION: High diagnostic accuracy in SLN interpretation may be achieved using a limited ultrastaging protocol of one immunohistochemical slide per block and linear measurement of the largest cluster of contiguous tumor cells. Implementation of the proposed limited ultrastaging protocol may result in laboratory cost savings with minimal impact on health outcomes.