Are micro-RNA 21 and 143 indicative as prognostic biomarkers in dedifferentiated endometrial adenocarcinoma?

AIM: Dedifferentiated endometrial adenocarcinoma (DEAC) is a rare, aggressive subtype, accounting for 2% of all endometrial cancers. Poor survival in DEAC prompts the need for effective treatment modalities through better prognostic classification. MicroRNAs (miRNA) have essential roles in tumor angiogenesis, which might enable their use as novel biomarkers. In this study, we aimed to reveal the relationship between the expression of miRNA-21 and miRNA-143, which are associated with angiogenesis, and the prognosis of DEAC. METHOD: The study included six cases diagnosed with DEAC. The expression levels of miRNA-21 and miRNA-143 were detected by quantitative real-time PCR. Microvascular density (MVD) was measured by CD34 staining. All data and effects on survival were compared for statistical significance. RESULTS: Six cases diagnosed with DEAC were included in the study. The percentage of undifferentiated components ranged from 50 to 90%. The second component of differentiated carcinoma was detected as endometrioid (3/5 grade I, 1/5 grade II, 1/5 grade III) in five cases and serous in one case. The mean MVD was 27 (range 17-44, SD 9.4). In three cases, miRNA-21 expression was down-regulated in neoplastic areas compared to non-neoplastic areas. On the contrary, it was found to be up-regulated in the remaining three cases. MiRNA-143 expression decreased in four cases and increased in two cases. CONCLUSIONS: Based on these findings, we found a significant irregular expression of miRNA-21 in DEACs. As in other cancers, angiogenesis is significantly associated with survival in DEACs. This study provides initial data for revealing possible implications of miRNAs as prognostic indicators in DEAC.

Construction and validation of a clinical risk model based on machine learning for screening characteristic factors of lymphovascular space invasion in endometrial cancer.

This study aimed to identify factors that affect lymphovascular space invasion (LVSI) in endometrial cancer (EC) using machine learning technology, and to build a clinical risk assessment model based on these factors. Samples were collected from May 2017 to March 2022, including 312 EC patients who received treatment at Xuzhou Medical University Affiliated Hospital of Lianyungang. Of these, 219 cases were collected for the training group and 93 for the validation group. Clinical data and laboratory indicators were analyzed. Logistic regression and least absolute shrinkage and selection operator (LASSO) regression were used to analyze risk factors and construct risk models. The LVSI and non-LVSI groups showed statistical significance in clinical data and laboratory indicators (P < 0.05). Multivariable logistic regression analysis identified independent risk factors for LVSI in EC, which were myometrial infiltration depth, cervical stromal invasion, lymphocyte count (LYM), monocyte count (MONO), albumin (ALB), and fibrinogen (FIB) (P < 0.05). LASSO regression identified 19 key feature factors for model construction. In the training and validation groups, the risk scores for the logistic and LASSO models were significantly higher in the LVSI group compared with that in the non-LVSI group (P < 0.001). The model was built based on machine learning and can effectively predict LVSI in EC and enhance preoperative decision-making. The reliability of the model was demonstrated by the significant difference in risk scores between LVSI and non-LVSI patients in both the training and validation groups.

[Application of PRAME immunohistochemistry in the differential diagnosis of primary endometrial and endocervical adenocarcinomas].

Objective: To investigate the diagnostic value of preferentially expressed antigen in melanoma (PRAME) immunohistochemical staining in differential diagnosis of primary endometrial and endocervical adenocarcinomas. Methods: Eighty-seven cases of endometrial adenocarcinoma and sixty-three cases of cervical adenocarcinoma were collected from May 2018 to November 2023 in the Department of Pathology, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School and all the cases were subject to PRAME immunohistochemical staining. The difference of PRAME expression between endometrial and endocervical adenocarcinomas was analyzed. Results: In 87 cases of endometrial adenocarcinoma, patients' age ranged from 35 to 71 years (average 59 years, median 59 years); in 63 cases of cervical adenocarcinoma patients' age ranged from 28 to 80 years (average 49 years, median 47 years). Seventy-eight cases (78/87, 89.7%) of endometrial adenocarcinoma; 2 cases (2/63, 3.2%) of cervical adenocarcinoma showed positive PRAME staining, and both cases of cervical adenocarcinoma were clear cell carcinoma. The sensitivity and specificity of PRAME in distinguishing between endometrial and cervical adenocarcinoma in the cohort were 89.7% and 96.8%, while those in differentiating non-clear cell carcinoma of the uterus from that of the cervix reached up to 91% and 100%, respectively. Conclusions: Immunohistochemical staining for PRAME demonstrates statistically significant differences between endometrial and cervical carcinomas, making it a useful auxiliary diagnostic marker for differentiating cervical and endometrial adenocarcinoma, especially non-clear cell carcinoma.

circRNAs in Endometrial Cancer-A Promising Biomarker: State of the Art.

Endometrial cancer (EC) is one of the most common malignant tumors among women in the 21st century, whose mortality rate is increasing every year. Currently, the diagnosis of EC is possible only after a biopsy. However, it is necessary to find a new biomarker that will help in both the diagnosis and treatment of EC in a non-invasive way. Circular RNAs (circRNAs) are small, covalently closed spherical and stable long non-coding RNAs (lncRNAs) molecules, which are abundant in both body fluids and human tissues and are expressed in various ways. Considering the new molecular classification of EC, many studies have appeared, describing new insights into the functions and mechanisms of circRNAs in EC. In this review article, we focused on the problem of EC and the molecular aspects of its division, as well as the biogenesis, functions, and diagnostic and clinical significance of circRNAs in EC.

Surface-Enhanced Raman Spectroscopy-Based Detection of EMT-Related Targets in Endometrial Cancer: Potential for Diagnosis and Prognostic Prediction.

Epithelial-mesenchymal transformation (EMT) is one of the important mechanisms of malignancy in endometrial cancer, and detection of EMT targets is a key challenge to explore the mechanism of endometrial carcinoma (EC) malignancy and discover novel therapeutic targets. This study attempts to use surface-enhanced Raman spectroscopy (SERS), a highly sensitive, ultrafast, and highly specific analytical technology, to rapidly detect microRNA-200a-3p and ZEB1 in endometrial cancer cell lines. The silver nanoparticles were decorated with iodine and calcium ions, can capture the SERS fingerprints of microRNA-200a-3p and ZEB1 protein, and effectively avoid the interference of impurity signals. At the same time, the method has high sensitivity for the detection of the above EMT targets, and the lowest detection limits for microRNA-200a-3p and ZEB1 are 4.5 pmol/mL and 10 ng/mL, respectively. At the lowest detection concentration, the method still has high stability. In addition, principal component analysis can not only identify microRNA-200a-3p and ZEB1 protein from a variety of EMT-associated microRNA and proteins but also identify them in the total RNA and total protein of endometrial cancer cell lines and normal endometrial epithelial cell lines. This study modified silver nanoparticles with iodine and calcium ions and for the first time captured the fingerprints of EMT-related targets microRNA-200a-3p and ZEB1 at the same time without label, and the method has high sensitivity and stability. This SERS-based method has immense potential for elucidating the molecular mechanisms of EMT-related EC, as well as identifying biomarkers for malignant degree and prognosis prediction.

Assessment of the localization of chondroitin sulfate in various types of endometrial carcinoma.

INTRODUCTION: This study aimed to assess the localization of chondroitin sulfate (CS), a primary extracellular matrix component, in the stromal region of endometrial carcinoma (EC). METHODS: Immunostaining was performed on 26 endometrial endometrioid carcinoma (EEC) samples of different grades and 10 endometrial serous carcinoma (ESC) samples to evaluate CS localization. This was further confirmed by Alcian Blue (AB) staining as well. RESULTS: In the G1-EEC samples, CS showed reactivity with fibrovascular stroma, supporting closely packed glandular crowding and papillary structures. As the grade increased, the original interstitial structure was re-established, and the localization of CS in the perigulandular region decreased. In the ESC samples, the thick fibrous strands supporting the papillary architecture showed reactivity with CS; however, the delicate stromal region branching into the narrow region showed poor reactivity. The AB staining results showed similar characteristics to the immunostaining ones. CONCLUSIONS: The characteristic localization of CS in various EC types was elucidated. The present study provides new information on endometrial stromal assessment.

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.

Diagnostic and therapeutic challenges in a recurrent endometrial carcinoma in lung, 15 years after primary treatment.

Endometrial carcinoma (EC) is the sixth most common cancer in females. Most ECs are detected in stage 1 and have a 5-year survival rate of more than 90%. Recurrence rates are highest within 5 years after treatment and are exceptionally rare after 10 years. Here, we describe a woman in her late 70s with endometrial cancer who was treated in 2008 and was diagnosed with a relapse in her left lung in 2023. Due to her advanced age and comorbidities, she was deemed inoperable. However, she received sequential chemotherapy and radiotherapy with a good partial response. She has now been started on hormonal therapy with an alternate megestrol and tamoxifen regime. There is a lack of follow-up imaging guidelines to detect late relapse, a dilemma in preferred treatment sequencing at relapse and an enigma in selecting chemotherapy or hormonal therapy.

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.

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.

Prognostic value of pretreatment systemic immune-inflammation index in patients with endometrial cancer: a meta-analysis.

Background: The present work focused on evaluating the systemic immune-inflammation index (SII) for its role in predicting endometrial cancer (EC) patient prognosis by meta-analysis. Methods: SII's role in predicting the prognosis of EC patients was analyzed by calculating combined hazard ratios (HRs) and 95% CIs. Results: As revealed by combined analysis, an increased SII predicted poor overall survival (HR = 2.01; 95% CI = 1.58-2.57; p < 0.001) as well as inferior progression-free survival (HR = 1.87; 95% CI = 1.36-2.58; p < 0.001) of EC. Conclusion: An increased SII score significantly predicted poor overall survival and progression-free survival in subjects with EC. The SII is suitable for predicting short- and long-term prognoses of patients with EC.

[Box: see text].

Prognostic role of C-reactive protein in patients with endometrial cancer: a meta-analysis.

Background: The present meta-analysis aimed to explore the association between C-reactive protein (CRP) levels and the prognosis of patients with endometrial cancer (EC). Methods: The effect of CRP level on predicting overall survival (OS) and disease-free survival (DFS) in patients with EC was evaluated according to pooled hazard ratios (HRs) and corresponding 95% CIs. Results: High CRP levels were not significantly correlated with OS (HR: 1.32 [95% CI: 0.99-1.77]; p = 0.060) or DFS (HR: 1.05 [95% CI: 0.88-1.25]; p = 0.597) in patients with EC. Conclusion: CRP levels did not significantly predict OS or DFS in patients with EC. However, according to subgroup analyses, higher CRP levels were significantly associated with poor OS in Asian patients with EC.

[Box: see text].

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.

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.

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.

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.