Unraveling Endometrial Cancer Survival Predictors Through Advanced Machine Learning Techniques.

This study explores endometrial cancer (EC) within the broader context of oncogynecology, focusing on 3,845 EC patients at the Almazov National Research Center. The research analyzes clinical data, employing machine learning techniques like random forest regression and decision tree analysis. Key findings include age-dependent impacts on EC outcomes, unexpected correlations between dietary habits and recurrence risk (e.g., higher risk for vegans), and intriguing associations like soft drink consumption influencing relapse. Despite limitations like a retrospective design and self-reported data, the study's extended eight-year follow-up and robust database enhance its credibility. The nuanced insights into EC risk factors, influenced by factors like physical activity and diet, open avenues for targeted diagnostics and prevention strategies, showcasing the potential of machine learning in predicting outcomes.

VOLTA: an enVironment-aware cOntrastive ceLl represenTation leArning for histopathology.

In clinical oncology, many diagnostic tasks rely on the identification of cells in histopathology images. While supervised machine learning techniques necessitate the need for labels, providing manual cell annotations is time-consuming. In this paper, we propose a self-supervised framework (enVironment-aware cOntrastive cell represenTation learning: VOLTA) for cell representation learning in histopathology images using a technique that accounts for the cell's mutual relationship with its environment. We subject our model to extensive experiments on data collected from multiple institutions comprising over 800,000 cells and six cancer types. To showcase the potential of our proposed framework, we apply VOLTA to ovarian and endometrial cancers and demonstrate that our cell representations can be utilized to identify the known histotypes of ovarian cancer and provide insights that link histopathology and molecular subtypes of endometrial cancer. Unlike supervised models, we provide a framework that can empower discoveries without any annotation data, even in situations where sample sizes are limited.

Glycometabolism and lipid metabolism related genes predict the prognosis of endometrial carcinoma and their effects on tumor cells.

BACKGROUND: Glycometabolism and lipid metabolism are critical in cancer metabolic reprogramming. The primary aim of this study was to develop a prognostic model incorporating glycometabolism and lipid metabolism-related genes (GLRGs) for accurate prognosis assessment in patients with endometrial carcinoma (EC). METHODS: Data on gene expression and clinical details were obtained from publicly accessible databases. GLRGs were obtained from the Genecards database. Through nonnegative matrix factorization (NMF) clustering, molecular groupings with various GLRG expression patterns were identified. LASSO Cox regression analysis was employed to create a prognostic model. Use rich algorithms such as GSEA, GSVA, xCELL ssGSEA, EPIC,CIBERSORT, MCPcounter, ESTIMATE, TIMER, TIDE, and Oncoppredict to analyze functional pathway characteristics of the forecast signal, immune status, anti-tumor therapy, etc. The expression was assessed using Western blot and quantitative real-time PCR techniques. A total of 113 algorithm combinations were combined to screen out the most significant GLRGs in the signature for in vitro experimental verification, such as colony formation, EdU cell proliferation, wound healing, apoptosis, and Transwell assays. RESULTS: A total of 714 GLRGs were found, and 227 of them were identified as prognostic-related genes. And ten GLRGs (AUP1, ESR1, ERLIN2, ASS1, OGDH, BCKDHB, SLC16A1, HK2, LPCAT1 and PGR-AS1) were identified to construct the prognostic model of patients with EC. Based on GLRGs, the risk model's prognosis and independent prognostic value were established. The signature of GLRGs exhibited a robust correlation with the infiltration of immune cells and the sensitivity to drugs. In cytological experiments, we selected HK2 as candidate gene to verify its value in the occurrence and development of EC. Western blot and qRT-PCR revealed that HK2 was substantially expressed in EC cells. According to in vitro experiments, HK2 knockdown can increase EC cell apoptosis while suppressing EC cell migration, invasion, and proliferation. CONCLUSION: The GLRGs signature constructed in this study demonstrated significant prognostic value for patients with endometrial carcinoma, thereby providing valuable guidance for treatment decisions.

Assessment of bidirectional relationships between hypothyroidism and endometrial cancer: a two-sample Mendelian randomization study.

Objective: Hypothyroidism, characterized by reduced thyroid hormone levels, and endometrial cancer, a prevalent gynecological malignancy, have been suggested to have a potential association in previous observational studies. However, the causal relationship between them remains uncertain. This study aimed to investigate the causal relationship between hypothyroidism and endometrial cancer using a bilateral Mendelian randomization approach. Methods: A bidirectional two-sample Mendelian randomization study was conducted using summary statistics from genome-wide association studies to identify genetic variants associated with hypothyroidism and endometrial cancer. The inverse variance weighting method was used as the main analysis, and sensitivity analyses were conducted to validate the MR results. Results: The results of our analysis did not support a causal effect of hypothyroidism (OR: 0.93, p=0.08) or autoimmune hypothyroidism (OR: 0.98, p=0.39) on endometrial cancer risk. In the reverse MR analysis, we did not find a significant causal effect of endometrial cancer on hypothyroidism (OR: 0.96, p=0.75) or autoimmune hypothyroidism (OR: 0.92, p=0.50). Based on subgroup analysis by pathological subtypes of endometrial cancer, the above findings were further substantiated (all p-value >0.05). Conclusions: Our Mendelian randomization analysis suggests a lack of causal association between hypothyroidism and endometrial cancer. To gain a deeper understanding of this association, it is essential to conduct large-scale randomized controlled trials in the future to validate our findings.

Precise lymph node biopsy for endometrial cancer confined to the uterus: Analysis of 43 clinical cases.

OBJECTIVE: To explore a precise association between tumor location and lymph node (LN) biopsy algorithm in uterine confined endometrial cancer (EC). MATERIALS AND METHODS: Patients with EC treated in the Department of Obstetrics and Gynecology, South Branch of Fujian Provincial Hospital were included in this observational retrospective study. Based on the procedure of treatment, patients were separated to stage I (2015.07-2019.09) and stage II (2019.09-2021.9). In each stage, patients were separated to high and low-risk group by the predicted results. Patients in the high-risk group received systematic lymphadenectomy in stage I and sentinel lymph node (SLN) dissection in stage II. The efficiency of lymph node metastasis (LNM) detection rates was compared between stage I and stage II cases. Precise lymph node biopsy algorithm was also constructed based on the outcomes of stage II. RESULTS: Overall, 43 patients, 28 in stage I and 15 in stage II, were included in the study. No recurrence or death cases had been found within follow-up terms. Based on the difference in the detection efficiency of LNM (p > 0.05), there was no difference between two stages. Thus, systematic lymphadenectomy and SLN biopsy provided similar success rates. The location of tumor site was also important for deciding whether pelvic or para-aortic SLN should be sampled for LNM. CONCLUSIONS: Precise SLN biopsy for EC confined to the uterus showed comparable LNM detection rate as systematic lymphadenectomy. EC location may be used to determine whether pelvic or para-aortic SLN sampling should be conducted for treatment.

Sociodemographic, clinical characteristics, and treatment patterns of endometrial cancer cases in Puerto Rico during the period 2009 to 2015: A retrospective study.

BACKGROUND: Over the past decades, the rising incidence rates of endometrial cancer have made it a significant public health concern for women worldwide. Treatment strategies for endometrial cancer vary based on several factors such as stage, histology, the patient's overall health, and preferences. However, limited amount of research on treatment patterns and potential correlations with sociodemographic characteristics among Hispanics is available. This study analyzes the treatment patterns for patients diagnosed with endometrial cancer in Puerto Rico. METHODS: A secondary database analysis was performed on endometrial cancer cases reported to the Puerto Rico Central Cancer Registry-Health Insurance Linkage Database from 2009 to 2015 (n = 2,488). The study population's sociodemographic and clinical characteristics were described, along with an overview of the therapy options provided to patients receiving care on the island. Logistic regression models were used to evaluate the association of sociodemographic/clinical characteristics with treatment patterns stratified by risk of recurrence. RESULTS: In our cohort, most patients were insured through Medicaid and had a median age of 60 years. Almost 90% of patients received surgery as the first course of treatment. Surgery alone was the most common treatment for low-risk patients (80.2%). High-risk patients were more likely to receive surgery with radiotherapy and chemotherapy (24.4%). Patients with Medicare insurance were five times (HR: 4.84; 95% CI: 2.45-9.58; p < 0.001) more likely to receive surgery when compared with patients insured with Medicaid. In contrast, those with private insurance were twice as likely to receive surgery (HR: 2.38; 95% CI: 1.40-4.04; p = 0.001) when compared to those with Medicaid. CONCLUSION: These findings provide insight into the treatment patterns for endometrial cancer in Puerto Rico and highlight the importance of considering factors such as disease risk when making treatment decisions. Addressing these gaps in treatment patterns can contribute to effective management of endometrial cancer.

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.

FIGO 2023 endometrial staging: a leap of faith into the new "prognostic based' rather than "anatomical based" staging-too fast too furious??

BACKGROUND: In 2023 FIGO revised the endometrial cancer staging system after 13 years. There is a lacuna of data regarding the performance and practicality of the revised 2023 FIGO staging schema for endometrial cancer from Low Middle-Income Countries (LMIC). OBJECTIVE: To estimate the shift of stage and adjuvant management of endometrial cancer based on the FIGO 2023 system compared to the FIGO 2009 system and assess the predictive potential of the FIGO 2023 system. MATERIAL AND METHODS: A retrospective study was conducted from 1st January 2017 to 31st December 2022. All patients with endometrial cancer were staged according to the FIGO 2023 and FIGO 2009 staging system. Follow-up of patients was done to determine recurrence. RESULTS: A total of 152 patients were included. Aggressive histology was seen in 66 (45%) patients. Eighteen (11%) had subserosal involvement. Substantial LVSI was noted in 23 (15%) of patients. Twenty-four (47%) patients of FIGO 2009 Stage IA and 26 patients (63%) of FIGO 2009 Stage IB were upstaged. Eleven (50%) patients of FIGO 2009 Stage IIIA were down staged to IA3. Overall 23 patients (15%) had a shift of stage. Fifteen out of 152 patients (15%) would have had a possible risk stratification change which would imply 23 patients (15%) would have needed a more radical treatment. Molecular classification was done in 32 patients; however, only 2 patients could afford POLE testing. Kaplan-Meier curves showed significant PFS differences in FIGO 2009 Stage IB and Stage IIIA when restaged according to the FIGO 2023 system. CONCLUSION: The FIGO 2023 endometrial staging is a more robust prognosticator; however, the practicality of molecular classification in LMICs is still a distant dream.

Weibull parametric model for survival analysis in women with endometrial cancer using clinical and T2-weighted MRI radiomic features.

BACKGROUND: Semiparametric survival analysis such as the Cox proportional hazards (CPH) regression model is commonly employed in endometrial cancer (EC) study. Although this method does not need to know the baseline hazard function, it cannot estimate event time ratio (ETR) which measures relative increase or decrease in survival time. To estimate ETR, the Weibull parametric model needs to be applied. The objective of this study is to develop and evaluate the Weibull parametric model for EC patients' survival analysis. METHODS: Training (n = 411) and testing (n = 80) datasets from EC patients were retrospectively collected to investigate this problem. To determine the optimal CPH model from the training dataset, a bi-level model selection with minimax concave penalty was applied to select clinical and radiomic features which were obtained from T2-weighted MRI images. After the CPH model was built, model diagnostic was carried out to evaluate the proportional hazard assumption with Schoenfeld test. Survival data were fitted into a Weibull model and hazard ratio (HR) and ETR were calculated from the model. Brier score and time-dependent area under the receiver operating characteristic curve (AUC) were compared between CPH and Weibull models. Goodness of the fit was measured with Kolmogorov-Smirnov (KS) statistic. RESULTS: Although the proportional hazard assumption holds for fitting EC survival data, the linearity of the model assumption is suspicious as there are trends in the age and cancer grade predictors. The result also showed that there was a significant relation between the EC survival data and the Weibull distribution. Finally, it showed that Weibull model has a larger AUC value than CPH model in general, and it also has smaller Brier score value for EC survival prediction using both training and testing datasets, suggesting that it is more accurate to use the Weibull model for EC survival analysis. CONCLUSIONS: The Weibull parametric model for EC survival analysis allows simultaneous characterization of the treatment effect in terms of the hazard ratio and the event time ratio (ETR), which is likely to be better understood. This method can be extended to study progression free survival and disease specific survival. TRIAL REGISTRATION: ClinicalTrials.gov NCT03543215, https://clinicaltrials.gov/ , date of registration: 30th June 2017.

Predictive models for lymph node metastasis in endometrial cancer: A systematic review and bibliometric analysis.

BACKGROUND: Lymph node metastasis is associated with a poorer prognosis in endometrial cancer. OBJECTIVE: The objective was to synthesize and critically appraise existing predictive models for lymph node metastasis risk stratification in endometrial cancer. DESIGN: This study is a systematic review. DATA SOURCES AND METHODS: We searched the Web of Science for articles reporting models predicting lymph node metastasis in endometrial cancer, with a systematic review and bibliometric analysis conducted based upon which. Risk of bias was assessed by the Prediction model Risk Of BiAS assessment Tool (PROBAST). RESULTS: A total of 64 articles were included in the systematic review, published between 2010 and 2023. The most common articles were "development only." Traditional clinicopathological parameters remained the mainstream in models, for example, serum tumor marker, myometrial invasion and tumor grade. Also, models based upon gene-signatures, radiomics and digital histopathological images exhibited an acceptable self-reported performance. The most frequently validated models were the Mayo criteria, which reached a negative predictive value of 97.1%-98.2%. Substantial variability and inconsistency were observed through PROBAST, indicating significant between-study heterogeneity. A further bibliometric analysis revealed a relatively weak link between authors and organizations on models predicting lymph node metastasis in endometrial cancer. CONCLUSION: A number of predictive models for lymph node metastasis in endometrial cancer have been developed. Although some exhibited promising performance as they demonstrated adequate to good discrimination, few models can currently be recommended for clinical practice due to lack of independent validation, high risk of bias and low consistency in measured predictors. Collaborations between authors, organizations and countries were weak. Model updating, external validation and collaborative research are urgently needed. REGISTRATION: None.

Introduction to predictive models for lymph node metastasis in endometrial cancerLymph node metastasis of endometrial cancer is associated with a poor prognosis. There are currently many predictive models. We summarized and evaluated them in this article.

Association between immune cells and endometrial cancer: A bidirectional Mendelian randomization study.

BACKGROUND: The prognostic significance of tumor-infiltrating immune cells in endometrial cancer is a subject of ongoing debate. Recent evidence increasingly suggests that these immune cells and cytokines, abundant in endometrial cancer tissues, play a pivotal role in stimulating the body inherent anti-tumor immune responses. METHODS: Leveraging publicly accessible genetic data, we conducted an exhaustive 2-sample Mendelian randomization (MR) study. This study aimed to explore the causal links between 731 immunophenotypes and the risk of endometrial cancer. We thoroughly assessed the robustness, heterogeneity, and potential horizontal pleiotropy of our findings through extensive sensitivity analyses. RESULTS: Our study identified 36 immunophenotypes associated with endometrial cancer risk. Specific immunophenotypes, such as the percentage of Naive-mature B-cells in lymphocytes (OR = 0.917, 95% CI = 0.863-0.974, P = .005), and HLA DR expression on CD14-CD16 + monocytes (OR = 0.952, 95% CI = 0.911-0.996, P = .032), exhibited a negative correlation with endometrial cancer. Conversely, CD127 expression on CD45RA + CD4 + in Treg cells (OR = 1.042, 95% CI = 1.000-1.085, P = .049), and CM CD4+%T in T cell maturation stages (OR = 1.074, 95% CI = 1.012-1.140, P = .018) showed a positive correlation. Reverse MR analysis linked endometrial cancer to 4 immunophenotypes, including a positive correlation with CD127-CD8br %T cell of Treg (OR = 1.172, 95% CI = 1.080-1.270, P = .0001), and negative correlations with 3 others, including CM CD4+%T cell (OR = 0.905, 95% CI = 0.832-0.984, P = .019). CONCLUSION SUBSECTIONS: Our findings underscore a significant causal relationship between immunophenotypes and endometrial cancer in bidirectional MR analyses. Notably, the CM CD4+%T immunophenotype emerged as potentially crucial in endometrial cancer development.

The Deep Proteomics Approach Identified Extracellular Vesicular Proteins Correlated to Extracellular Matrix in Type One and Two Endometrial Cancer.

Among gynecological cancers, endometrial cancer is the most common in developed countries. Extracellular vesicles (EVs) are cell-derived membrane-surrounded vesicles that contain proteins involved in immune response and apoptosis. A deep proteomic approach can help to identify dysregulated extracellular matrix (ECM) proteins in EVs correlated to key pathways for tumor development. In this study, we used a proteomics approach correlating the two acquisitions-data-dependent acquisition (DDA) and data-independent acquisition (DIA)-on EVs from the conditioned medium of four cell lines identifying 428 ECM proteins. After protein quantification and statistical analysis, we found significant changes in the abundance (p < 0.05) of 67 proteins. Our bioinformatic analysis identified 26 pathways associated with the ECM. Western blotting analysis on 13 patients with type 1 and type 2 EC and 13 endometrial samples confirmed an altered abundance of MMP2. Our proteomics analysis identified the dysregulated ECM proteins involved in cancer growth. Our data can open the path to other studies for understanding the interaction among cancer cells and the rearrangement of the ECM.

Analysis of CDO1, PITX2, and CDH13 Gene Methylation in Early Endometrial Cancer for Prediction of Medical Treatment Outcomes.

An observational cohort study of patients diagnosed with endometrial cancer (EC) stage IA G1, or atypical endometrial hyperplasia (AEH), undergoing organ-preserving treatment, was conducted. OBJECTIVE OF THE STUDY: To determine CDO1, PITX2, and CDH13 gene methylation levels in early endometrial cancer and atypical hyperplasia specimens obtained before organ-preserving treatment in the patients with adequate response and with insufficient response to hormonal treatment. MATERIALS AND METHODS: A total of 41 endometrial specimens obtained during diagnostic uterine curettage in women with EC (n = 28) and AEH (n = 13), willing to preserve reproductive function, were studied; 18 specimens of uterine cancer IA stage G1 from peri- and early postmenopausal women (comparison group) were included in the study. The control group included 18 endometrial specimens from healthy women obtained by diagnostic curettage for missed abortion and/or intrauterine adhesions. Methylation levels were analyzed using the modified MS-HRM method. RESULTS: All 13 women with AEH had a complete response (CR) to medical treatment. In the group undergoing organ-preserving treatment for uterine cancer IA stage G1 (n = 28), 14 patients had a complete response (EC CR group) and 14 did not (EC non-CR group). It was found that all groups had statistically significant differences in CDO1 gene methylation levels compared to the control group (p < 0.001) except for the EC CR group (p = 0.21). The p-value for the difference between EC CR and EC non-CR groups was <0.001. The differences in PITX2 gene methylation levels between the control and study groups were also significantly different (p < 0.001), except for the AEH group (p = 0.21). For the difference between EC CR and EC non-CR groups, the p-value was 0.43. For CDH13 gene methylation levels, statistically significant differences were found between the control and EC non-CR groups (p < 0.001), and the control and EC comparison groups (p = 0.005). When comparing the EC CR group with EC non-CR group, the p-value for this gene was <0.001. The simultaneous assessment of CDO1 and CDH13 genes methylation allowed for an accurate distinction between EC CR and EC non-CR groups (AUC = 0.96). CONCLUSION: The assessment of CDO1 and CDH13 gene methylation in endometrial specimens from patients with endometrial cancer (IA stage G1), scheduled for medical treatment, can predict the treatment outcome.

Validating the 2023 FIGO staging system: A nomogram for endometrioid endometrial cancer and adenocarcinoma.

BACKGROUND: To find the factors impacting overall survival (OS) prognosis in patients with endometrioid endometrial carcinoma (EEC) and adenocarcinoma and to establish a nomogram model to validate the 2023 International Federation of Obstetrics and Gynecology (FIGO) staging system for endometrial cancer. METHODS: Data were obtained from the Surveillance, Epidemiology, and End Results (SEER) training cohort. An independent validation cohort was obtained from the First Affiliated Hospital of Anhui Medical University between 2008 and 2023. Cox regression analysis identified independent prognostic factors for OS in EEC and adenocarcinoma patients. A nomogram predicting OS was developed and validated utilizing the C-index, calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). The relationship between the tumor grade and prognosis of EEC and adenocarcinoma was quantified using net reclassification improvement (NRI), propensity score matching (PSM), and Kaplan-Meier curves. RESULTS: Cox regression analysis identified age, race, marital status, tumor grade, tumor stage, tumor size, and chemotherapy as independent prognostic factors for OS. A nomogram for predicting OS was developed based on these factors. The C-indexes for the OS nomogram was 0.743 and 0.720 for the SEER training set and external validation set, respectively. The area under the ROC (AUC) for the OS nomogram was 0.755, 0.757, and 0.741 for the SEER data subsets and 0.844, 0.719, and 0.743 for the external validation subsets. Calibration plots showed high concordance between the nomogram-predicted and observed OS. DCA also demonstrated the clinical utility of the OS nomogram. NRI, PSM, and survival analyses revealed that tumor grade was the most important histopathological factor for EEC and adenocarcinoma prognosis. CONCLUSION: Seven independent prognostic variables for the OS of patients with EEC and adenocarcinoma were identified. The established OS nomogram has good predictive ability and clinical utility and validates the 2023 endometrial cancer FIGO staging system.

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.

Synchronous Well-Differentiated Papillary Mesothelioma and Endometrioid Adenocarcinoma Arising From Endometriosis.

Well-differentiated papillary mesothelioma (WDPM) is a rare mesothelial tumor of uncertain malignant potential. We present a unique case of a woman with synchronous WDPM and well-differentiated endometrioid adenocarcinoma (EA) arising from extraovarian endometriosis. A 56-year-old postmenopausal woman presented with a several-month history of right lower quadrant abdominal pain. She had a history of supracervical hysterectomy and bilateral salpingo-oophorectomy secondary to endometriosis. Imaging reported a mass in the right lower quadrant originating from the distal ileum. At laparotomy, the patient underwent a right colectomy with resection of the terminal ileum and excision of a solitary peritoneal nodule. Pathology was consistent with a diagnosis of well-differentiated EA (arising from extraovarian endometriosis) and WDPM. Further treatment consisted of complete surgical staging/debulking and adjuvant chemotherapy directed toward metastatic well-differentiated EA. Surgeons should be familiar with WDPM as a potential finding in women of reproductive age undergoing abdominal surgery for any indication.

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.

Neuroendocrine carcinoma of the endometrium: a retrospective analysis of data from a single center.

BACKGROUND: Neuroendocrine carcinoma (NEC) originating from the endometrium is rare, and there is limited knowledge regarding its diagnosis and optimal management. In this study, we present our experience with 11 patients with endometrial NEC, aiming to provide guidance for clinical practice. METHODS: We retrospectively collected the clinical, pathological, and treatment data of 11 patients with endometrial NEC who were treated at the First Affiliated Hospital of Zhengzhou University from January 2011 to July 2023. The clinicopathological characteristics, treatment and prognosis of these patients were analyzed. RESULTS: The median age of the patients was 55.0 (39.0-64.0) years, and the median tumor size was 40.0 (33.0-60.0) mm. Irregular vaginal bleeding was the most common symptom observed in 10 out of 11 patients, while metabolic syndrome occurred in only 2 out of 11 patients. Six out of the 11 patients were diagnosed at an early stage. Among the patients, 6 were diagnosed with endometrial NECs, while the remaining patients had a combination of endometrial NEC and other non-NEC endometrial carcinomas. All patients underwent surgery, except for one who received only chemotherapy due to multiple metastases. After surgery, adjuvant chemotherapy was administered to 5 patients, chemotherapy combined with radiotherapy was given to 3 patients, and 2 patients did not receive any adjuvant therapy. A total of 10 patients completed the follow-up, with a median follow-up time of 51.0 (14.3-81.0) months. Unfortunately, 2 patients died from the disease. CONCLUSION: NECs originating from the endometrium might not be affected by metabolic disorders. Preoperative diagnosis of these tumors was challenging. The primary approach for managing endometrial NEC can be multimodal treatment centered around surgery.

Exploring the Role of the MUTYH Gene in Breast, Ovarian and Endometrial Cancer.

BACKGROUND: MUTYH germline monoallelic variants have been detected in a number of patients affected by breast/ovarian cancer or endometrial cancer, suggesting a potential susceptibility role, though their significance remains elusive since the disease mechanism is normally recessive. Hence, the aim of this research was to explore the hypothesis that a second hit could have arisen in the other allele in the tumor tissue. METHODS: we used Sanger sequencing and immunohistochemistry to search for a second MUTYH variant in the tumoral DNA and to assess protein expression, respectively. RESULTS: we detected one variant of unknown significance, one variant with conflicting interpretation of pathogenicity and three benign/likely benign variants; the MUTYH protein was not detected in the tumor tissue of half of the patients, and in others, its expression was reduced. CONCLUSIONS: our results fail to demonstrate that germinal monoallelic MUTYH variants increase cancer risk through a LOH (loss of heterozygosity) mechanism in the somatic tissue; however, the absence or partial loss of the MUTYH protein in many tumors suggests its dysregulation regardless of MUTYH genetic status.