Delineating genotype and parent-of-origin effect on the phenotype in MSH6-associated Lynch syndrome.

BACKGROUND: This study investigates the potential influence of genotype and parent-of-origin effects (POE) on the clinical manifestations of Lynch syndrome (LS) within families carrying (likely) disease-causing MSH6 germline variants. PATIENTS AND METHODS: A cohort of 1615 MSH6 variant carriers (310 LS families) was analyzed. Participants were categorized based on RNA expression and parental inheritance of the variant. Hazard ratios (HRs) were calculated using weighted Cox regression, considering external information to address ascertainment bias. The findings were cross-validated using the Prospective Lynch Syndrome Database (PLSD) for endometrial cancer (EC). RESULTS: No significant association was observed between genotype and colorectal cancer (CRC) risk (HR = 1.06, 95% confidence interval [CI]: 0.77-1.46). Patients lacking expected RNA expression exhibited a reduced risk of EC (Reference Cohort 1: HR = 0.68, 95% CI: 0.43-1.03; Reference Cohort 2: HR = 0.63, 95% CI: 0.46-0.87). However, these results could not be confirmed in the PLSD. Moreover, no association was found between POE and CRC risk (HR = 0.78, 95% CI: 0.52-1.17) or EC risk (Reference Cohort 1: HR = 0.93, 95% CI: 0.65-1.33; Reference Cohort 2: HR = 0.8, 95% CI: 0.64-1.19). DISCUSSION AND CONCLUSION: No evidence of POE was detected in MSH6 families. While RNA expression may be linked to varying risks of EC, further investigation is required to explore this observation.

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 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.

Palmitic Acid Exerts Anti-Tumorigenic Activities by Modulating Cellular Stress and Lipid Droplet Formation in Endometrial Cancer.

Epidemiological and clinical evidence have extensively documented the role of obesity in the development of endometrial cancer. However, the effect of fatty acids on cell growth in endometrial cancer has not been widely studied. Here, we reported that palmitic acid significantly inhibited cell proliferation of endometrial cancer cells and primary cultures of endometrial cancer and reduced tumor growth in a transgenic mouse model of endometrial cancer, in parallel with increased cellular stress and apoptosis and decreased cellular adhesion and invasion. Inhibition of cellular stress by N-acetyl-L-cysteine effectively reversed the effects of palmitic acid on cell proliferation, apoptosis, and invasive capacity in endometrial cancer cells. Palmitic acid increased the intracellular formation of lipid droplets in a time- and dose-dependent manner. Depletion of lipid droplets by blocking DGAT1 and DGAT2 effectively increased the ability of palmitic acid to inhibit cell proliferation and induce cleaved caspase 3 activity. Collectively, this study provides new insight into the effect of palmitic acid on cell proliferation and invasion and the formation of lipid droplets that may have potential clinical relevance in the treatment of obesity-driven endometrial cancer.

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.

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.

Killer Function of Circulating Neutrophils in Relation to Cytokines in Uterine Myoma and Endometrial Cancer.

The study presents the killer functions of circulating neutrophils: myeloperoxidase activity, the ability to generate ROS, phagocytic activity, receptor status, NETosis, as well as the level of cytokines IL-2, IL-4, IL-6, IL-17A, and IL-18, granulocyte CSF, monocyte chemotactic protein 1, and neutrophil elastase in the serum of patients with uterine myoma and endometrial cancer (FIGO stages I-III). The phagocytic ability of neutrophils in uterine myoma was influenced by serum levels of granulocyte CSF and IL-2 in 54% of the total variance. The degranulation ability of neutrophils in endometrial cancer was determined by circulating IL-18 in 50% of the total variance. In uterine myoma, 66% of the total variance in neutrophil myeloperoxidase activity was explained by a model dependent on blood levels of IL-17A, IL-6, and IL-4. The risk of endometrial cancer increases when elevated levels of monocyte chemotactic protein 1 in circulating neutrophils are associated with reduced ability to capture particles via extracellular traps (96% probability).

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.

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.

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.

Tailoring postoperative management through sentinel lymph node biopsy in low- and intermediate-risk endometrial cancer - the SENTRY clinical trial.

BACKGROUND: While total hysterectomy and bilateral salpingo-oophorectomy without lymph node staging are standard for low- and intermediate-risk endometrial cancer, certain histopathologic factors revealed after surgery can necessitate additional interventions. Our study assessed the influence of sentinel lymph node biopsy on postoperative decision-making. MATERIALS AND METHODS: In the SENTRY trial (July 2021 - February 2023), we enrolled patients with International Federation of Gynaecology and Obstetrics (FIGO) stage IA-IB low-grade endometrioid endometrial cancer. Laparoscopic sentinel lymph node mapping using indocyanine green was performed alongside total hysterectomy with bilateral salpingo-oophorectomy. Subsequent management changes based on sentinel lymph node biopsy results were evaluated. The trial was registered at ClinicalTrials.gov (NCT04972682). RESULTS: Of the 100 enrolled participants, a bilateral detection rate of 91% was observed with a median detection time of 10 min (interquartile range 8-13 min). Sentinel lymph node metastases were found in 8% (N = 8) of participants. Postoperative FIGO staging increased in 15% (N = 15) and decreased in 5% (N = 5) of patients. Sentinel lymph node biopsy results altered the adjuvant treatment plan for 20% (N = 20): external beam radiotherapy was omitted in 12% (N = 12) while 6% (N = 6) had external beam radiotherapy +/- systemic chemotherapy added due to sentinel lymph node metastases. In 2% (N = 2), the external beam radiotherapy field was expanded with the paraaortic region. No intraoperative complications were reported and no 30-day major morbidity and mortality occurred. Throughout a median follow-up of 14 (95% CI 12-15 months, neither patient-reported lymphedema nor pelvic recurrence surfaced in the cohort. CONCLUSIONS: Sentinel lymph node biopsy using indocyanine green is a safe procedure and allows tailoring adjuvant therapy in presumed low- and intermediate-risk endometrial cancer. It assists in avoiding external beam radiotherapy overtreatment and introducing additional modalities when necessary.

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.

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.

Sesamolin serves as an MYH14 inhibitor to sensitize endometrial cancer to chemotherapy and endocrine therapy via suppressing MYH9/GSK3ß/ß-catenin signaling.

BACKGROUND: Endometrial cancer (EC) is one of the most common gynecological cancers. Herein, we aimed to define the role of specific myosin family members in EC because this protein family is involved in the progression of various cancers. METHODS: Bioinformatics analyses were performed to reveal EC patients' prognosis-associated genes in patients with EC. Furthermore, colony formation, immunofluorescence, cell counting kit 8, wound healing, and transwell assays as well as coimmunoprecipitation, cycloheximide chase, luciferase reporter, and cellular thermal shift assays were performed to functionally and mechanistically analyze human EC samples, cell lines, and a mouse model, respectively. RESULTS: Machine learning techniques identified MYH14, a member of the myosin family, as the prognosis-associated gene in patients with EC. Furthermore, bioinformatics analyses based on public databases showed that MYH14 was associated with EC chemoresistance. Moreover, immunohistochemistry validated MYH14 upregulation in EC cases compared with that in normal controls and confirmed that MYH14 was an independent and unfavorable prognostic indicator of EC. MYH14 impaired cell sensitivity to carboplatin, paclitaxel, and progesterone, and increased cell proliferation and metastasis in EC. The mechanistic study showed that MYH14 interacted with MYH9 and impaired GSK3ß-mediated ß-catenin ubiquitination and degradation, thus facilitating the Wnt/ß-catenin signaling pathway and epithelial-mesenchymal transition. Sesamolin, a natural compound extracted from Sesamum indicum (L.), directly targeted MYH14 and attenuated EC progression. Additionally, the compound disrupted the interplay between MYH14 and MYH9 and repressed MYH9-regulated Wnt/ß-catenin signaling. The in vivo study further verified sesamolin as a therapeutic drug without side effects. CONCLUSIONS: Herein, we identified that EC prognosis-associated MYH14 was independently responsible for poor overall survival time of patients, and it augmented EC progression by activating Wnt/ß-catenin signaling. Targeting MYH14 by sesamolin, a cytotoxicity-based approach, can be applied synergistically with chemotherapy and endocrine therapy to eventually mitigate EC development. This study emphasizes MYH14 as a potential target and sesamolin as a valuable natural drug for EC 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.

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.