Prognostic values of molecular subtypes and SWI/SNF protein expression in de-differentiated/undifferentiated endometrial carcinoma.

Aims: Classification and risk stratification of endometrial carcinoma (EC) has transitioned from histopathological features to molecular classification, e.g. the ProMisE classifier, identifying four prognostic subtypes: POLE mutant (POLEmut) with almost no recurrence or disease-specific death events, mismatch repair deficient (MMRd) and no specific molecular profile (NSMP), with intermediate outcome and p53 abnormal (p53abn) with poor outcomes.

Serum CA125 levels in the context of ProMisE molecular classification provides pre-operative prognostic information that can direct endometrial cancer management.

Objective: Previous research suggests serum CA125 reflects extra-uterine disease in patients with endometrial carcinoma (EC). Our objective was to determine if CA125 can identify patients with extra-uterine and/or nodal metastases, the association of this biomarker with EC molecular subtype, and to explore an optimal cutoff in this context.

Methods: We assessed the association of CA125 levels with clinicopathologic and outcomes data on a cohort of 1107 molecularly classified EC.

Papillary and ductal patterns of mesonephric-like adenocarcinomas are often overlooked: a retrospective revaluation of over 1000 endometrial carcinomas.

Aims: Mesonephric-like adenocarcinoma (MLA) of the endometrium is often a diagnostic challenge, due to its morphological resemblance to other more common Müllerian neoplasms. This study aimed to retrospectively identify overlooked MLA in a large endometrial carcinoma cohort, using a combination of immunohistochemistry (IHC), morphology and KRAS sequencing.

Methods And Results: IHC was conducted on 1094 endometrial carcinomas, identifying 16 potential MLA cases based on GATA3+ and/or TTF1+ and ER- staining patterns, which subsequently underwent detailed histological review, KRAS sequencing and ProMisE molecular classification.

Hormonal biomarkers remain prognostically relevant within the molecular subgroups in endometrial cancer.

Objective: The prognostic relevance of hormonal biomarkers in endometrial cancer (EC) has been well-established. A refined three-tiered risk model for estrogen receptor (ER)/progesterone receptor (PR) expression was shown to improve prognostication. This has not been evaluated in relation to the molecular subgroups.

Assessing the impact of deep-learning assistance on the histopathological diagnosis of serous tubal intraepithelial carcinoma (STIC) in fallopian tubes.

In recent years, it has become clear that artificial intelligence (AI) models can achieve high accuracy in specific pathology-related tasks. An example is our deep-learning model, designed to automatically detect serous tubal intraepithelial carcinoma (STIC), the precursor lesion to high-grade serous ovarian carcinoma, found in the fallopian tube. However, the standalone performance of a model is insufficient to determine its value in the diagnostic setting.