Diagnosis Of Endometrial Cancer Research Articles

The association between endometrial cancer and subsequent diabetic retinopathy severity: A retrospective nationwide study.

The endometrial cancer is a disorder with elevated oxidative stress. The high oxidative stress resulting from hyperglycemia can lead to diabetic retinopathy (DR) development which is a complication of type 2 diabetes mellitus. Accordingly, we aim to evaluate the potential relationship between the endometrial cancer and following DR development. A retrospective cohort study was conducted using the National Health Insurance Research Database (NHIRD) of Taiwan. Individuals diagnosed with endometrial cancer were matched to the non-endometrial cancer patients in a 1:4 ratio. The major outcomes are the presence of DR, diabetic macular edema (DME) and proliferative diabetic retinopathy (PDR) according to diagnostic codes. Cox proportional hazard regression was used to show the adjusted hazard ratio (aHR) with 95% confidence interval (CI) of major outcomes between groups. There were 99 (2.3%), 20 (0.5%), and 14 (0.3%) cases with DR, DME and PDR in the endometrial cancer group, respectively. Another 303 (1.8%), 35 (0.2%), and 27 (0.2%) with DR, DME and PDR were observed in the control group, respectively. The endometrial cancer group revealed a significantly higher incidence of DR compared with the control group (aHR 1.51, 95% CI 1.20-1.90, P < 0.001). The cumulative probability of DR was also higher in the endometrial cancer group than in the control group (P < 0.001). The relationship between endometrial cancer and DR was significantly higher in patients aged over 70 years (P = 0.008). In addition, a higher incidence of DR was found during the first 5 years after the endometrial cancer diagnosis (P < 0.001). The endometrial cancer correlates to a higher incidence of subsequent DR, especially within first 5 years of endometrial cancer diagnosis.

Multiparametric ultrasound Diagnosis of Endometrial Cancer in the Preoperative Preparation of Menopausal Patients

Multiparametric ultrasound Diagnosis of Endometrial Cancer in the Preoperative Preparation of Menopausal Patients

Real-world treatment patterns and clinical outcomes from a retrospective chart review study of patients with recurrent or advanced endometrial cancer who progressed following prior systemic therapy in Europe

ObjectiveTo evaluate real-world treatment patterns and clinical outcomes in recurrent/advanced endometrial cancer patients who progressed following prior systemic therapy in clinical practice in Europe.DesignEndometrial Cancer Health Outcomes-Europe (ECHO-EU) is a...

Discovery of the potential biomarkers for early diagnosis of endometrial cancer via integrating metabolomics and transcriptomics

Endometrial cancer (EC) is one of the most common malignant tumors in women, and the increasing incidence and mortality pose a serious threat to the public health. Early diagnosis of EC could prolong the survival period and optimize the survivorship, greatly alleviating patients’ suffering and social medical pressure. In this study, we collected urine and serum samples from the recruited patients, analyzed the samples using LC-MS approach, and identified the differential metabolites through metabolomic analysis. Then, the differentially expressed genes were identified through the systematic transcriptomic analysis of EC-related dataset from Gene Expression Omnibus (GEO), followed by network profiling of metabolic-reaction-enzyme-gene. In this experiment, a total of 83 differential metabolites and 19 hub genes were discovered, of which 10 different metabolites and 3 hub genes were further evaluated as more potential biomarkers based on network analysis. According to the KEGG enrichment analysis, the potential biomarkers and gene-encoded proteins were found to be involved in the arginine and proline metabolism, histidine metabolism, and pyrimidine metabolism, which was of significance for the early diagnosis of EC. In particular, the combination of metabolites (histamine, 1-methylhistamine, and methylimidazole acetaldehyde) as well as the combination of RRM2, TYMS and TK1 exerted more accurate discrimination abilities between EC and healthy groups, providing more criteria for the early diagnosis of EC.

Accuracy of endometrial sampling in the diagnosis of endometrial cancer: a multicenter retrospective analysis of the JAGO-NOGGO

BackgroundAccurate preoperative molecular and histological risk stratification is essential for effective treatment planning in endometrial cancer. However, inconsistencies between pre- and postoperative tumor histology have been reported in previous studies. To address this issue and identify risk factors related to inaccurate histologic diagnosis after preoperative endometrial evaluation, we conducted this retrospective analysis.MethodsWe conducted a retrospective analysis involving 375 patients treated for primary endometrial cancer in five different gynaecological departments in Germany. Histological assessments of curettage and hysterectomy specimens were collected and evaluated.ResultsPreoperative histologic subtype was confirmed in 89.5% of cases and preoperative tumor grading in 75.2% of cases. Higher rates of histologic subtype variations (36.84%) were observed for non-endometrioid carcinomas. Non-endometrioid (OR 4.41) histology and high-grade (OR 8.37) carcinomas were identified as predictors of diverging histologic subtypes, while intermediate (OR 5.04) and high grading (OR 3.94) predicted diverging tumor grading.ConclusionWhen planning therapy for endometrial cancer, the limited accuracy of endometrial sampling, especially in case of non-endometrioid histology or high tumor grading, should be carefully considered.

Abstract 941: Patient-derived model systems of endometrial cancers for disease modeling and drug sensitivity testing

Abstract Background: Endometrial cancer (EC) is the most common gynecological cancer in the US, with increasing incidence and mortality rates. The survival rate lags behind four decades ago (81% vs 87%), underscoring the critical need for more effective treatment strategies. The heterogeneous nature of EC contributes to varied outcomes with current treatments. This project aims to establish reliable EC models for characterizing each individual tumor, distinguish optimal drug treatment, and determine specific drug effect mechanisms for personalized therapy. Methods: Freshly collected tumors were used for patient-derived xenograft models (PDXs) and patient-derived primary cancer cells (PDCs). Immunohistochemistry (IHC) staining was used to confirm the tumors grown in mice faithfully replicate the characteristics of patient tumor tissues. FDA-approved anticancer drugs were used to screen the optimal drugs to inhibit tumor cell proliferation and further utilized to inhibit tumor growth using PDXs. Results: We have collected 26 EC tumors and characterize them by DNA mutation and RNA-seq analysis. We implanted them in NSG mice, and 16 tumor samples have successfully grown in mice with a success rate of 61%. Most PDXs can be faithfully passaged to three generations. From the 16 PDXs, we created six novel PDCs. Using 2D and 3D spheroid cell culture, we screened 133 FDA-approved oncology drugs in the EC-PDC models. The drug screening results clearly highlighted several standout drugs, including CUDC-907 (a dual PI3K/HDAC inhibitor), two histone deacetylase (HDAC) inhibitors including romidepsin and panobinostat, four topoisomerase II (TOP II) inhibitors including mitoxantrone, daunorubicin, doxorubicin, and epirubicin, two proteasome inhibitors including carfilzomib and bortezomib, 2 DNA-directed RNA synthesis inhibitor dactinomycin and plicamycin, omacetaxine mepesuccinate (protein synthesis inhibitor), and valrubicin (DNA synthesis inhibitor). These drugs have demonstrated a significant capacity to inhibit tumor cell proliferation. Our pilot studies using single drugs, CUDC-907, romidepsin and mitoxantrone, achieved moderate drug effects. Combine mitoxantrone with romidepsin or CUDC-907 show surprisingly synergistic effects in multiple PDC models. The combination strategy will be tested in PDXs in the near future. Conclusion: Our unique PDXs and PDCs are excellent models for representing various characteristics of EC and testing novel therapeutics. This current study presents a promising direction for developing personalized therapy options for EC patients and provides a platform for further investigation of drug mechanisms and tumor development. Future studies will also involve etiology, such as chronic psychological stress, DNAm age and intratumoral microbiome. This information will help with endometrial cancer prevention, diagnosis, and prognosis. Citation Format: Tianyue Li, Xiaohao Huang, Riley Rosenmeyer, Samuel Robinson, Kazi Salsabil, Yiqin Xiong, Xiangbing Meng, Shujie Yang. Patient-derived model systems of endometrial cancers for disease modeling and drug sensitivity testing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 941.

Single-cell analysis reveals landscape of endometrial cancer response to estrogen and identification of early diagnostic markers.

The development of endometrial cancer (EC) is closely related to the abnormal activation of the estrogen signaling pathway. Effective diagnostic markers are important for the early detection and treatment of EC. We downloaded single-cell RNA sequencing (scRNA-seq) and spatial transcriptome (ST) data of EC from public databases. Enrichment scores were calculated for EC cell subpopulations using the "AddModuleScore" function and the AUCell package, respectively. Six predictive models were constructed, including logistic regression (LR), Gaussian naive Bayes (GaussianNB), k-nearest neighbor (KNN), support vector machine (SVM), extreme gradient boosting (XGB), and neural network (NK). Subsequently, receiver-operating characteristics with areas under the curves (AUCs) were used to assess the robustness of the predictive model. We classified EC cell coaggregation into six cell clusters, of which the epithelial, fibroblast and endothelial cell clusters had higher estrogen signaling pathway activity. We founded the epithelial cell subtype Epi cluster1, the fibroblast cell subtype Fib cluster3, and the endothelial cell subtype Endo cluster3 all showed early activation levels of estrogen response. Based on EC cell subtypes, estrogen-responsive early genes, and genes encoding Stage I and para-cancer differentially expressed proteins in EC patients, a total of 24 early diagnostic markers were identified. The AUCs values of all six classifiers were higher than 0.95, which indicates that the early diagnostic markers we screened have superior robustness across different classification algorithms. Our study elucidates the potential biological mechanism of EC response to estrogen at single-cell resolution, which provides a new direction for early diagnosis of EC.

Association of tet methylcytosine dioxygenase 2 and 5-hydroxymethylcytosine in endometrioid adenocarcinoma and its clinical significance

BackgroundAberrant DNA methylation is a vital molecular alteration commonly detected in type I endometrial cancers (EC), and tet methylcytosine dioxygenase 2 (TET2) and 5-hydroxymethylcytosine (5hmC) play significant roles in DNA demethylation. However, little is known about the function and correlation of TET2 and 5hmC co-expressed in EC. This study intended to investigate the clinical significance of TET2 and 5hmC in EC.MethodsThe levels of TET2 and 5hmC were detected in 326 endometrial tissues by immumohistochemistry, and the correlation of their level was detected by Pearson analysis. The association between the levels of TET2 and 5hmC and clinicopathologic characteristics was analyzed. Prognostic value of TET2 and 5hmC was explored by Kaplan–Meier analysis. The Cox proportional hazard regression model was used for univariate and multivariate analyses.ResultsBased on the analysis results, TET2 protein level was positively correlated with 5hmC level in EC tissues (r = 0.801, P < 0.001). TET2+5hmC+ (high TET2 and high 5hmC) association was significantly associated with well differentiation, myometrial invasion, negative lymph node metastasis, and tumor stage in EC. Association of TET2 and 5hmC was confirmed as a prognostic factor (HR = 2.843, 95%CI = 1.226–3.605, P = 0.007) for EC patients, and EC patients with TET2−5hmC− level had poor overall survival.ConclusionsIn summary, the association of TET2 and 5hmC was downregulated in EC tissues, and may be a potential poor prognostic indicator for EC patients. Combined detection of TET2 and 5hmC may be valuable for the diagnosis and prognosis of EC.

Accuracy of Frozen Section Biopsy in the Diagnosis of Endometrial Cancer: A Systematic Review and Meta-Analysis.

The early and accurate diagnosis of endometrial cancer is of paramount importance for the survival of these patients. The aim of this study was to systematically appraise the available data regarding the accuracy of frozen section biopsy in diagnosing endometrial cancer. A thorough literature search was performed in PubMed/Medline, Scopus and the Cochrane Central Register of Controlled Trials databases from inception up to January 2023, with the use of specific, relevant key terms. A quality evaluation for each study was performed with the QUADAS-2 tool, whereas a bivariate random-effect model was performed to generate a summary receiver-operated curve. Heterogeneity was evaluated with Cochrane Q and Higgins' I2 statistics. Subgroup analyses were performed for studies focused on atypical hyperplasia and those focused on endometrial cancer. The search yielded 47 studies, involving 7790 patients with endometrial cancer. Among them, only 11 could be included in the quantitative analysis. QUADAS-2 evaluation resulted in rather high quality among the included studies. Quantitative synthesis resulted in a pooled sensitivity of 0.863 and pooled specificity of 0.916. The AUC was 0.948, the Q statistic was 10.488 (10 df, p = 0.399) and Higgins' I2 (4.655%) reported no significant heterogeneity. Subgroup analyses based on the diagnosis revealed a pooled sensitivity 0.886, specificity 0.862 and AUC 0.934 for endometrial cancer versus a sensitivity of 0.816, specificity of 0.962 and AUC 0.939 for atypical hyperplasia. Frozen section appears as a valid and reliable diagnostic tool for endometrial cancer. Its reliability seems to be even higher for the diagnosis of atypical hyperplasia. Therefore, this method may be considered in clinical practice and in settings with appropriate resources.

Integrative Analysis of Multi-Omic Data for the Characteristics of Endometrial Cancer.

Endometrial cancer (EC) is a frequently diagnosed gynecologic cancer. Identifying reliable prognostic genes for predicting EC onset is crucial for reducing patient morbidity and mortality. Here, a comprehensive strategy with transcriptomic and proteomic data was performed to measure EC's characteristics. Based on the publicly available RNA-seq data, death-associated protein kinase 3, recombination signal-binding protein for the immunoglobulin kappa J region, and myosin light chain 9 were screened out as potential biomarkers that affect the EC patients' prognosis. A linear model was further constructed by multivariate Cox regression for the prediction of the risk of being malignant. From further integrative analysis, exosomes were found to have a highly enriched role that might participate in EC occurrence. The findings were validated by qRT-polymerase chain reaction (PCR) and western blotting. Collectively, we constructed a prognostic-gene-based model for EC prediction and found that exosomes participate in EC incidents, revealing significantly promising support for the diagnosis of EC.

Recent Advances in Endometrial Cancer Prevention, Early Diagnosis and Treatment.

Endometrial cancer is the sixth commonest cancer in women worldwide, with over 417,000 diagnoses in 2020. The disease incidence has increased by 132% over the last 30 years and is set to continue to rise in response to an ageing population and increasing global rates of obesity and diabetes. A greater understanding of the mechanisms driving endometrial carcinogenesis has led to the identification of potential strategies for primary disease prevention, although prospective evaluation of their efficacy within clinical trials is still awaited. The early diagnosis of endometrial cancer is associated with improved survival, but has historically relied on invasive endometrial sampling. New, minimally invasive tests using protein and DNA biomarkers and cytology have the potential to transform diagnostic pathways and to allow for the surveillance of high-risk populations. The molecular classification of endometrial cancers has been shown to not only have a prognostic impact, but also to have therapeutic value and is increasingly used to guide adjuvant treatment decisions. Advanced and recurrent disease management has also been revolutionised by increasing the use of debulking surgery and targeted treatments, particularly immunotherapy. This review summarises the recent advances in the prevention, diagnosis and treatment of endometrial cancer and seeks to identify areas for future research.

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

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

Abstract IA007: The WID-qEC test for simple and accurate endometrial cancer detection

Abstract Endometrial cancer incidence has been rising over the past ten years. Delays in diagnosis reduce survival and necessitate more aggressive treatment. We developed the WID-qEC test, a PCR-based test that evaluates DNA methylation in gene regions of GYPC and ZSCAN12, using 726 cervico-vaginal samples from women with and without endometrial cancer. So far, the WID-qEC test has been validated in an additional 1388 women in various settings, including a case/control study utilizing self-samples and a nested case/control set from a screening cohort including samples taken up to 3 years prior to endometrial cancer diagnosis. In a recent prospective observational study (the EPI-SURE study), the primary aim was to compare the performance of conventional index imaging tests (i.e., sonography) with the WID-qEC test for endometrial cancer detection. We invited all women aged ≥ 45 years with abnormal uterine bleeding attending a tertiary gynecological diagnostic referral center in the UK between June and November 2022 to participate. A cervicovaginal sample for the WID-qEC test was obtained prior to the current diagnostic pathway, and the test was performed blinded to the clinical outcome. Patients were followed until diagnostic resolution or until June 12, 2023. Four hundred of the eligible 474 women consented to study participation; one patient withdrew. Based on 603 index imaging tests (i.e., sonography), 186 (46.6%) women were recommended for a reference histology test (i.e., biopsy+/-hysteroscopy). Twelve cancers were diagnosed. 198 reference histology test procedures detected nine cancers and missed two; one further cancer was directly diagnosed at hysterectomy without a prior reference test. Endometrial thickness assessment from an ultrasound scan was possible in 379 (95.0%) of the 399 women and a pre-specified cut-off of ≥ 4.5mm had sensitivity, specificity, positive (PPV) and negative (NPV) predictive values of 90.9% (95% CI: 62.3-98.4), 79.1% (95% CI: 74.5-82.9), 11.8% (95% CI: 6.5-20.3) and 99.6% (95% CI: 98.0-99.9), respectively. Using a cut-off of &amp;gt; 3mm, the specificity was 45.8% (95% CI: 40.7–51.0) without a change in sensitivity. The WID-qEC test was possible in 390 (97.7%) of the 399 patients with 90.9% sensitivity (95% CI: 62.3-98.4), 92.1% specificity (95% CI: 88.9-94.4), a PPV of 25.6% (95% CI:14.6-41.1) and a NPV of 99.7% (95% CI: 98.3-99.9) when the pre-specified threshold (WID-qEC sumPMR ≥ 0.03) was applied. When a higher threshold was applied (WID-qEC sumPMR ≥ 0.3) the specificity increased to 97.3% (95% CI: 95.1-98.5) without a change in sensitivity. The WID-qEC test delivers fast results and shows improved performance compared with a combination of imaging index tests. Triage of women with abnormal uterine bleeding using the WID-qEC test could reduce the number of women requiring histological assessments for identification of potential malignancy and, specifically, reduce the false positive rate by up to 95% (from 52.6% based on the endometrial thickness of &amp;gt; 3mm to 2.6% based on a WID-qEC sumPMR ≥ 0.3). Citation Format: Martin Widschwendter, Iona Evans, Daniel Reisel, Allison Jones, Alba Bajrami, Simrit Nijjar, Sarah A Solangon, Rupali Arora, Elisa Redl, Lena Schreiberhuber, Isma Ishaq-Parveen, Julia Rothärmel, Chiara Herzog, Davor Jurkovic. The WID-qEC test for simple and accurate endometrial cancer detection [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr IA007.

Analysis of clinical data of different endometrial pathological types in perimenopausal women with abnormal uterine bleeding.

Early detection and diagnosis are important for improving the therapeutic effect and quality of life in patients with endometrial cancer (EC). This study aimed to analyze the clinical data of different endometrial pathological types in perimenopausal women with abnormal uterine bleeding (AUB) in order to provide evidence for the prevention and early diagnosis of EC. A total of 462 perimenopausal women with AUB were enrolled in this prospective observational study. Endometrial biopsy was performed in patients with suspected endometrial lesions. According to the pathological examination results, the patients were divided into endometrial polyp group (EP) (n = 71), endometrial hyperplasia without atypia group (EH) (n = 59), atypical endometrial hyperplasia (AEH) (n = 36), and EC group (n = 27). The history risk factors and ultrasonic imaging characteristics of endometrium among the four groups were compared. Twenty-seven women were diagnosed with EC (5.84%). The prevalence rate of AEH and EC in the group of 51- to 55-year-old women was significantly higher than that in the groups of 40- to 45-year-old women and of 46- to 50-year-old women (P < 0.05). The age, body mass index, and history of diabetes gradually increased with the development of endometrial pathological types. In addition, the correlation index of endometrial blood flow increased gradually, and the proportion of uneven endometrial echo, unclear endometrial-myometrial junction (EMJ), and ovarian cyst also increased gradually. However, no statistically significant difference was found when comparing endometrial thickness (ET) and endometrial volume (EV) among endometrial pathological groups (P > 0.05). The ET, EV, endometrial vascularization index, endometrial flow index, and vascularization flow index in the ovarian cyst group were significantly higher (P < 0.05), and the proportion of uneven endometrium echo and unclear EMJ were significantly higher compared with that in the non-ovarian cyst group (P < 0.05). The most common cause of perimenopausal women with AUB was benign endometrial lesions. However, women aged 51-55 years old with endometrial high risk factors and ovarian cyst should be alert to AEH and EC. Endometrial biopsy needs to be performed to determine endometrial malignancy in necessity.

Diagnosis and management of endometrial hyperplasia: A UK national audit of adherence to national guidance 2012-2020.

Endometrial hyperplasia (EH) is a precusor lesion for endometrial cancer (EC), the commonest gynaecological malignancy in high-income countries. EH is a proliferation of glandular tissue, classified as either non-atypical endometrial hyperplasia (NEH) or, if the cytological features are abnormal, atypical endometrial hyperplasia (AEH). The clinical significance of AEH is that patients face both a high risk of having occult EC and a high risk of progression to EC if untreated. Recommendations on the care of women with EH were introduced by United Kingdom-wide guidance (Green-top Guide No. 67, 2016). National adherence to guidance is unknown. We aimed to describe the care of patients with EH; to compare the patterns of care for those with EH with national guidance to identify opportunities for quality improvement; and to compare patterns of care prior to and following the introduction of national guidance to understand its impact. In this UK-wide patient-level clinical audit, we included 3,307 women who received a new histological diagnosis of EH through a gynaecology service between 1 January 2012 and 30 June 2020. We described first-line management, management at 2 years, and surgical characteristics prior to and following national guidance for EH using proportions and 95% confidence intervals (CIs) and compared process measures between time periods using multilevel Poisson regression. Of the 3,307 patients, 1,570 had NEH and 1,511 had AEH between 2012 and 2019. An additional 85 patients had NEH and 141 had AEH during 2020. Prior to national guidance, 9% (95% CI [6%, 15%]) received no initial treatment for NEH compared with 3% (95% CI [1%, 5%]) post-guidance; 31% (95% CI [26%, 36%]) and 48% (95% CI [43% 53%]) received an intrauterine progestogen, respectively, in the same periods. The predominant management of women with AEH did not differ, with 68% (95% CI [61%, 74%]) and 67% (95 CI [63%, 71%]) receiving first-line hysterectomy, respectively. By 2 years, follow-up to histological regression without hysterectomy increased from 38% (95% CI [33%, 43%]) to 52% (95% CI [47%, 58%]) for those with NEH (rate ratio (RR) 1.38, 95% CI [1.18, 1.63] p < 0.001). We observed an increase in the use of total laparoscopic hysterectomy among those with AEH (RR 1.26, 95% CI [1.04, 1.52]). In the later period, 37% (95% CI [29%, 44%]) of women initially diagnosed with AEH who underwent a first-line hysterectomy, received an upgraded diagnosis of EC. Study limitations included retrospective data collection from routine clinical documentation and the inability to comprehensively understand the shared decision-making process where care differed from guidance. The care of patients with EH has changed in accordance with national guidance. More women received first-line medical management of NEH and were followed up to histological regression. The follow-up of those with AEH who do not undergo hysterectomy must be improved, given their very high risk of coexistent cancer and high risk of developing cancer.

A new methodology to reveal potential nucleic acid modifications associated with the risk of endometrial cancer through dispersive solid-phase extraction coupled with UHPLC-QE-Orbitrap-MS/MS and HPLC-UV.

Nucleic acid modifications have attracted increasing attention in recent years since they have been found to be related to a number of diseases including cancer. Previous studies have shown that the early development of endometrial cancer (EC) is often accompanied by changes in methylation levels of related genes, and the expression of related proteins that regulate reactive oxygen species (ROS) shows significant differences in EC cells and tissues. However, it has not been reported whether nucleic acid modifications related to methylation or ROS can serve as biomarkers for EC. Accurate quantification of these nucleic acid modifications still has challenges because their amounts in urine are very low and the interferences in urine are complicated. In this study, a novel dispersive solid-phase extraction (DSPE) method based on chitosan-carbon nanotube-Al2O3 (CS-CNT-Al2O3) has been established for the analysis of 5-hydroxymethyluracil (5mU), 5-methyl-2'-deoxycytidine (5-mdC), 5-hydroxymethyl-2'-deoxycytidine (5-hmdC), 5-formyl-2'-deoxycytidine (5-fdC), and 8-hydroxy-2'-deoxyguanosine (8-OHdG) in EC patient urine samples coupled with UHPLC-QE-Orbitrap-MS/MS and HPLC-UV. Firstly, the synthesis of the CS-CNT-Al2O3 nanocomposite was conducted by a sono-coprecipitation method and was characterized by scanning electron microscope (SEM), energy dispersive spectrometer (EDS), and Fourier transform infrared (FTIR). Under the optimal extraction conditions of DSPE, we successfully quantified 5mU, 5-mdC, 5-hmdC, 5-fdC, and 8-OHdG in urine samples from 37 EC patients and 39 healthy controls. The results showed that there were significant differences in the levels of 5-mdC, 5-hmdC, 5-fdC, and 8-OHdG in EC patients compared to the healthy control group. The receiver operator characteristic (ROC) curve analysis was carried out to evaluate the potential of 5-mdC, 5-hmdC, 5-fdC, and 8-OHdG to distinguish EC patients from healthy volunteers. The area under the curve (AUC) for 5-mdC, 5-hmdC, 5-fdC, and 8-OHdG was 0.7412, 0.667, 0.8438, and 0.7981, respectively. It indicated that 5-mdC, 5-hmdC, 5-fdC, and 8-OHdG had certain potential in distinguishing between EC patients and healthy volunteers and they could act as potential non-invasive biomarkers for early diagnosis of EC. Moreover, the present study would stimulate investigations of the effects of nucleic acid modifications on the initiation and progression of EC.

Developing a Nomogram for Prioritizing Hysteroscopy in Endometrial Cancer Diagnosis: A Case-Control Study.

(1) Background: The pandemic led to significant healthcare disruptions, resulting in postponed surgeries and extended waiting times for non-urgent treatments, including hysteroscopies essential for diagnosing endometrial cancer. This study aims to formulate a risk stratification model to enhance the prioritization of hysteroscopy procedures in Brazil; (2) Methods: A case-control study was conducted at Vila Santa Catarina Hospital in São Paulo, analyzing the medical records of 2103 women who underwent hysteroscopy between March 2019 and March 2022. We used bivariate analysis and multivariate linear regression to identify risk factors associated with endometrial cancer and formulate a nomogram; (3) Results: The findings revealed a 5.5% incidence of pre-invasive and invasive endometrial disease in the study population, with an average waiting time of 120 days for hysteroscopy procedures. The main risk factors identified were hypertension, diabetes, postmenopausal bleeding, and obesity; (4) Conclusions: This research highlights the urgent need for efficient prioritization of hysteroscopy procedures in the wake of the pandemic. The developed nomogram is an innovative tool for identifying patients at higher risk of endometrial cancer, thus facilitating timely diagnosis and treatment and improving overall patient outcomes in a strained healthcare system.

Identification and validation of serum metabolite biomarkers for endometrial cancer diagnosis

Endometrial cancer (EC) stands as the most prevalent gynecological tumor in women worldwide. Notably, differentiation diagnosis of abnormity detected by ultrasound findings (e.g., thickened endometrium or mass in the uterine cavity) is essential and remains challenging in clinical practice. Herein, we identified a metabolic biomarker panel for differentiation diagnosis of EC using machine learning of high-performance serum metabolic fingerprints (SMFs) and validated the biological function. We first recorded the high-performance SMFs of 191 EC and 204 Non-EC subjects via particle-enhanced laser desorption/ionization mass spectrometry (PELDI-MS). Then, we achieved an area-under-the-curve (AUC) of 0.957–0.968 for EC diagnosis through machine learning of high-performance SMFs, outperforming the clinical biomarker of cancer antigen 125 (CA-125, AUC of 0.610–0.684, p < 0.05). Finally, we identified a metabolic biomarker panel of glutamine, glucose, and cholesterol linoleate with an AUC of 0.901–0.902 and validated the biological function in vitro. Therefore, our work would facilitate the development of novel diagnostic biomarkers for EC in clinics.

Racioethnic Disparities in Endometrial Cancer Outcomes.

Black women are twice as likely to die from endometrial cancer (EC) compared with white women. This represents one of the worst racioethnic disparities amongst all cancers globally. Compared with white women, black women are more likely to be diagnosed with advanced EC, have more barriers to accessing care and experience increased delays in obtaining an EC diagnosis and commencing treatment. Histological and molecular differences place black women at higher risk of being diagnosed with more aggressive EC subtypes that carry less favourable outcomes. Furthermore, EC diagnostic pathways are less reliable in black women, and black women are less likely to receive evidence-based treatment for EC. This racioethnic disparity in EC outcomes exists both in the UK and US, despite differences in healthcare systems. This review methodically describes the key factors along the patient journey that contribute to the disparity in black women and proposes multifaceted approaches to lessen these gaps.

Role of endometrial sampling to differentiate between advanced endometrial versus ovarian malignancy: retrospective cohort study

ObjectiveDistinguishing between advanced stage endometrial and ovarian cancer at diagnosis can be challenging, especially when patients do not present with abnormal uterine bleeding. Given emerging systemic therapies specific for ovarian...