Endometrial Tumor Classification by Histomorphology and Biomarkers in the Nurses' Health Study

The vasculogenic mimicry, CD146+ and CD105+ microvessel density in the prognosis of endometrioid endometrial adenocarcinoma: a single-centre immunohistochemical study

The microvessel compartment is crucial in the tumour microenvironment of endometrioid adenocarcinoma (EA). This study investigated the role of vasculogenic mimicry (VM), CD146, and CD105 microvessel density in the clinical prognosis of EA. A total of 188 EA cases were analyzed, with VM channels and microvessels detected using PAS/CD31, CD146, and CD105 staining. Mann-Whitney and Fisher exact tests were used to compare the study groups according to the evaluated criteria. ROC analysis included determination of the confidence interval (CI) and area under the ROC curve. The Mantel-Cox test was used to analyze progression-free survival. Multivariate Cox proportional hazard analysis was performed using stepwise regression. Results showed that VM channels and CD146 and CD105 microvessels were significantly higher (p < 0.0001) in cases with unfavourable prognosis. Univariate survival analysis highlighted the significant role of these factors in progression-free survival, while multivariate Cox analysis identified VM and CD146+ vessels as predictive factors. This study demonstrates, for the first time, that VM, CD146, and CD105-positive vessels are involved in EA prognosis, suggesting their potential as independent prognostic indicators and targets for antiangiogenic therapy. However, these findings require further validation through large-scale studies.

Impact of artificial intelligence on the diagnosis, treatment and prognosis of endometrial cancer

Endometrial cancer is one of the most prevalent tumours in females and holds an 83% survival rate within 5 years of diagnosis. Hypoestrogenism is a major risk factor for the development of endometrial carcinoma (EC) therefore two major types are derived, type 1 being oestrogen-dependent and type 2 being oestrogen independent. Surgery, chemotherapeutic drugs, and radiation therapy are only a few of the treatment options for EC. Treatment of gynaecologic malignancies greatly depends on diagnosis or prognostic prediction. Diagnostic imaging data and clinical course prediction are the two core pillars of artificial intelligence (AI) applications. One of the most popular imaging techniques for spotting preoperative endometrial cancer is MRI, although this technique can only produce qualitative data. When used to classify patients, AI improves the effectiveness of visual feature extraction. In general, AI has the potential to enhance the precision and effectiveness of endometrial cancer diagnosis and therapy. This review aims to highlight the current status of applications of AI in endometrial cancer and provide a comprehensive understanding of how recent advancements in AI have assisted clinicians in making better diagnosis and improving prognosis of endometrial cancer. Still, additional study is required to comprehend its strengths and limits fully.

Keratinization in atypical glandular cell clusters as a cytological clue to endometrioid carcinoma on cervical cytology

INTRODUCTION

Specific diagnosis of endometrial carcinomas on cervical cytology is difficult with few useful cytomorphological clues reported. This study reviews a cohort of cervical cytology to investigate the presence of keratinization in atypical glandular cells (AGC), an undescribed cytomorphological clue for identifying endometrial endometrioid carcinomas on cervical cytology.

METHODS

Cervical cytology slides from patients with a histologic diagnosis of endometrial endometrioid carcinoma were reviewed for the presence of keratinization associated with AGCs. Corresponding histology slides were reviewed for tumour grading and degree of squamous differentiation.

RESULTS

In total, 42 cases of cervical cytology specimens from 41 patients were retrieved, including 7 (16.7%) with keratinization associated with AGCs seen and 35 (83.3%) without. Comparison of histologic grading did not demonstrate an association with the presence of keratinization on cytology (p = 0.565). Corresponding histology slides were available for 37 cases. Cytologic and histologic keratinization were associated statistically (p = 0.002). Frank keratinization was seen on histologic slides of five cases, with four also showing cytologic keratinization. Area of squamous differentiation, including squamous morule formation, did not correlate with keratinization on cytologic preparation (p = 0.185).

CONCLUSION

Histologic and cytologic keratinization are observed in endometrioid endometrial carcinomas. Such is reflected in cervical cytology by the presence of orangeophilic, rigid and acellular fragments within or associated with AGC clusters. Keratinization, when identified with AGCs, should be regarded as a cytologic clue suggestive of an endometroid carcinoma of endometrial origin.

Evaluation of Lineage/Site-specific Nuclear Immunohistochemical Markers SATB2, Cyclin D1, SALL4, and BCOR in High-grade Endometrial Carcinomas

Poorly differentiated malignant neoplasms involving the gynecologic tract routinely include a poorly differentiated endometrial carcinoma (EC) in the differential diagnosis. Some nuclear lineage/site-specific immunohistochemical markers are utilized in this diagnostic setting including SATB2, cyclin D1, SALL4, and BCOR, but their specificity and use in small samples are not clear across the spectrum of ECs. Cases of undifferentiated/dedifferentiated endometrial carcinomas (UEC/DDEC), clear cell carcinoma (CCC), uterine serous carcinoma (USC), FIGO grade 3 endometrial endometrioid carcinoma (EEC), and uterine carcinosarcoma (UCS) were identified and diagnoses confirmed. Whole-section immunohistochemical stains for SATB2, cyclin D1, SALL4, BCOR, and PAX8 were performed. A total of 113 cases were utilized: 15 CCC, 26 EEC, 19 UCS, 22 USC, and 31 UEC/DDEC. Cases were distributed across both low (49%) and high (51%) FIGO clinical stages. SATB2 was expressed by UCS (8/19, 42%), EEC (10/26, 38%), UEC/DDEC (11/30, 37%), and USC (6/22, 27%). Cyclin D1 was expressed by EEC (24/26, 92%), USC (17/22, 77%), UEC/DDEC (15/20 EEC component, 75%; 22/30 UEC, 73%), UCS (10/16 carcinoma, 63%; 11/19 sarcoma, 58%), and CCC (8/15, 53%). SALL4 was expressed most frequently by UEC/DDEC (12/30, 40%), but also USC (7/22, 32%), EEC (5/26, 19%), and UCS (4/16 carcinoma, 25%; 3/19 sarcoma, 16%). BCOR was expressed at low levels in 2 USC, 2 UEC/DDEC, and 2 UCS. PAX8 was generally positive but showed lower expression in UEC/DDEC (17/30, 57%) and in the sarcomatous portions of UCS (6/19, 32%). SATB2, cyclin D1, SALL4, and BCOR stain variable numbers of poorly-differentiated EC and must be carefully interpreted within morphologic and clinical context.

Diagnostic accuracy of HNF1β, Napsin A and P504S/Alpha-Methylacyl-CoA Racemase (AMACR) as markers of endometrial clear cell carcinoma

Endometrial clear cell carcinoma (CCC) shows morphological overlap with endometrioid and serous carcinoma. We aimed to assess the accuracy of immunohistochemical diagnostic markers of CCC, i.e. HNF1β, Napsin A and P504S/Alpha-Methylacyl-CoA Racemase (AMACR). A systematic review and meta-analysis was conducted by searching 4 electronic databases from their inception to April 2022 for all studies assessing HNF1β, Napsin A and/or AMACR in endometrial CCC vs endometrioid/serous carcinomas. Diagnostic accuracy was assessed as sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-), diagnostic odds ratio (DOR) and area under the curve (AUC) on sROC curves. Eleven studies were included. HNF1β positivity (any expression) showed sensitivity= 0.78; specificity= 0.81; LR+ =2.46; LR-= 0.38; DOR= 5.96; AUC= 0.79. Diffuse HNF1β expression showed sensitivity= 0.53; specificity= 0.95; LR+ =9.68; LR-= 0.51; DOR= 18.02; AUC= 0.40. Napsin A positivity (any expression) showed sensitivity= 0.76; specificity= 0.97; LR+ =18.79; LR-= 0.27; DOR= 73.31; AUC= 0.81. Diffuse Napsin A expression showed sensitivity= 0.52; specificity= 0.99; LR+ =14.50; LR-= 0.55; DOR= 24.93; AUC= 0.98. AMACR positivity (any expression) showed sensitivity= 0.76; specificity= 0.86; LR+ =4.86; LR-= 0.30; DOR= 13.56; AUC was not assessable due to the presence of only 2 studies. In conclusion, HNF1β, Napsin A and AMACR show moderate accuracy in identifying endometrial CCC. Considering only a diffuse expression of these markers as positive leads to high specificity but low sensitivity. In particular, Napsin A appears as the most specific marker of endometrial CCC.