Diagnosis Of Endometrial Cancer Research Articles

Universal screening for Lynch syndrome in endometrial cancer diagnoses in Auckland, New Zealand: The initial experience.

Universal mismatch repair immunohistochemistry (MMR IHC) tumour testing in endometrial cancer (EC) for Lynch syndrome (LS) was introduced in Auckland, New Zealand, in January 2017. Identifying patients with LS allows them and their families to access risk reduction strategies. Universal MMR IHC testing aids in the molecular classification of EC and has prognostic and therapeutic implications. We aimed to determine the incidence of LS in women with EC in Auckland, New Zealand, following the introduction of MMR testing and the impact of universal screening on local genetic services. This is a retrospective clinicopathological evaluation of women with a new EC diagnosis referred to the Auckland Gynaecological Oncology Unit from 1/1/17 to 31/12/18. Patient data were extracted from the Gynaecological Oncology Unit database and electronic records, and analysed using descriptive statistics. During the study period, 409 patients were diagnosed with EC, with an over-representation of Pacific Islanders (32.5%). Of these, 82.6% underwent MMR IHC testing, 20% were MMR-deficient (MMRd), and 71% had somatic hypermethylation. The Pacific Islander population had a 64% (odds ratio 0.36, P = 0.005) reduction in the odds of having MMRd tumours compared with Europeans. Of the patients who underwent MMR IHC testing, 5.5% were referred to a genetic clinic for germline testing. LS was confirmed in eight patients (2.3%). LS was diagnosed in 2.3% of patients. There was an over-representation of Pacific Islanders in the EC group but not among those diagnosed with LS.

Latent relation shared learning for endometrial cancer diagnosis with incomplete multi-modality medical images

Latent relation shared learning for endometrial cancer diagnosis with incomplete multi-modality medical images

Redox-state-regulating enzymes have prognostic value in diabetic endometrial cancer patients: impact of statin use?

The incidence of endometrial cancer is increasing, and oxidative stress has been suggested to play a vital role in its carcinogenesis. Statins have an impact on the cellular redox-state. The aim of this study was to determine the effects of statin use on redox-state regulating enzymes in endometrial cancer in women with type 2 diabetes. This retrospective study consisted of 119 women with type 2 diabetes who were diagnosed with endometrial cancer at Oulu University Hospital in Finland between 2007 and 2014. There were 58 statin users and 61 non-users based on medication use at the time of endometrial cancer diagnosis. The expression of redox-state regulating proteins nuclear factor erythroid 2-related factor 2 (Nrf2) and Kelch-like ECH-associated protein 1 (Keap1) in the tumor samples was assessed immunohistochemically, and manganese superoxide dismutase (MnSOD) levels were measured both immunohistochemically and from serum samples. High MnSOD expression predicted better progression-free survival (PFS) in statin non-users in a univariate analysis (p=0.02). There was no statistical difference in overall survival (OS) or PFS between strong and weak expression of Nrf2 and Keap1. After adjusting for stage and statin use, the results were similar. Statin non-users with strong MnSOD expression had better PFS compared to statin users which proves that statins have impact on redox-state regulating enzymes. However, these findings are preliminary and require further research.

Label-Free Monitoring of Endometrial Cancer Progression Using Multiphoton Microscopy.

Endometrial cancer is the most common gynecological cancer in the developed world. However, the accuracy of current diagnostic methods is still unsatisfactory and time-consuming. Here, we presented an alternate approach to monitoring the progression of endometrial cancer via multiphoton microscopy imaging and analysis of collagen, which is often overlooked in current endometrial cancer diagnosis protocols but can offer a crucial signature in cancer biology. Multiphoton microscopy (MPM) based on the second-harmonic generation and two-photon excited fluorescence was introduced to visualize the microenvironment of endometrium in normal, hyperplasia without atypia, atypical hyperplasia, and endometrial cancer specimens. Furthermore, automatic image analysis based on the MPM image processing algorithm was used to quantify the differences in the collagen morphological features among them. MPM enables the visualization of the morphological details and alterations of the glands in the development process of endometrial cancer, including irregular changes in the structure of the gland, increased ratio of the gland to the interstitium, and atypical changes in the glandular epithelial cells. Moreover, the destructed basement membrane caused by gland proliferation and fusion is clearly shown in SHG images, which is a key feature for identifying endometrial cancer progression. Quantitative analysis reveals that the formation of endometrial cancer is accompanied by an increase in collagen fiber length and width, a progressive linearization and loosening of interstitial collagen, and a more random arrangement of interstitial collagen. Observation and quantitative analysis of interstitial collagen provide invaluable information in monitoring the progression of endometrial cancer. Label-free multiphoton imaging reported here has the potential to become an in situ histological tool for effective and accurate early diagnosis and detection of malignant lesions in endometrial cancer.

Endometrial Thickness as Diagnostic Triage for Endometrial Cancer Among Black Individuals

Poor performance of the transvaginal ultrasonography triage strategy has been suggested as a contributor to racial disparity between Black individuals and White individuals in endometrial cancer (EC) stage at diagnosis in population-level simulation analyses. To examine the false-negative probability using ultrasonography-measured endometrial thickness (ET) thresholds as triage for EC diagnosis among Black individuals and assess whether known risk factors of EC modify ET triage performance. This retrospective diagnostic study of merged abstracted electronic health record data and secondary administrative data (January 1, 2014, to December 31, 2020) from the Guidelines for Transvaginal Ultrasound in the Detection of Early Endometrial Cancer sample assessed Black individuals who underwent hysterectomy in a 10-hospital academic-affiliated health care system and affiliated outpatient practices. Data analysis was performed from January 31, 2023, to November 30, 2023. Pelvic ultrasonography within 24 months before hysterectomy. Ultrasonography performed before hysterectomy as well as demographic and clinical data on symptom presentation, endometrial characterization, and final EC diagnosis were abstracted. Endometrial thickness thresholds were examined for accuracy in ruling out EC diagnosis by using sensitivity, specificity, and negative predictive value. False-negative probability was defined as 1 - sensitivity. Accuracy measures were stratified by risk factors for EC and by factors hypothesized to influence ET measurement quality. A total of 1494 individuals with a uterus (median [IQR] age, 46.1 [41.1-54.0] years) comprised the sample, and 210 had EC. Fibroids (1167 [78.1%]), vaginal bleeding (1067 [71.4%]), and pelvic pain (857 [57.4%]) were the most common presenting diagnoses within 30 days of ultrasonography. Applying the less than 5-mm ET threshold, there was an 11.4% probability that someone with EC would be classified as not having EC (n = 24). At the 4-mm (cumulative) threshold, the probability was 9.5%, and at 3 mm, it was 3.8%. False-negative probability at the 5-mm threshold was similar among EC risk factor groups: postmenopausal bleeding (12.4%; 95% CI, 7.8%-18.5%), body mass index greater than 40 (9.3%; 95% CI, 3.1%-20.3%); and age 50 years or older (12.8%; 95% CI, 8.4%-18.5%). False-negative probability was also similar among those with fibroids on ultrasonography (11.8%; 95% CI, 6.9%-18.4%) but higher in the setting of reported partial ET visibility (26.1%; 95% CI, 10.2%-48.4%) and pelvic pain (14.5%; 95% CI, 7.7%-23.9%). These findings suggest that the transvaginal ultrasonography triage strategy is not reliable among Black adults at risk for EC. In the presence of postmenopausal bleeding, tissue sampling is strongly recommended.

Risk Factors for Second Primary Cancer in a Prospective Cohort of Endometrial Cancer Survivors: an Alberta Endometrial Cancer Cohort Study.

We examined associations between modifiable and non-modifiable cancer-related risk factors measured at endometrial cancer diagnosis and during early survivorship (~3 years post-diagnosis) with second primary cancer (SPC) risk among 533 endometrial cancer survivors in the Alberta Endometrial Cancer Cohort using Fine and Gray sub-distribution hazard models. During a median follow-up of 16.7 years (interquartile range (IQR)=12.2-17.9), 89 (17%) participants developed a SPC with breast (29%), colorectal (13%) and lung (12%) cancers being the most common. Dietary glycemic load before endometrial cancer diagnosis (≥90.4 vs. <90.4 g/day: sub-hazard ratios (sHR)=1.71, 95% confidence intervals (CI)=1.09-2.69) as well as older age (≥60 vs. <60: sHR=2.48, 95% CI=1.34-4.62) and alcohol intake (≥2 drink/week vs. none: sHR=3.81, 95% CI=1.55-9.31) during early survivorship were associated with increased SPC risk. Additionally, reductions in alcohol consumption from prediagnosis to early survivorship significantly reduced SPC risk (sHR=0.34, 95% CI=0.14-0.82). With one-in-six survivors developing a SPC, further investigation of SPC risk factors and targeted surveillance options for high-risk survivors could improve long-term health outcomes in this population. Reductions in dietary glycemic load and alcohol intake from prediagnosis to early survivorship showed promising risk reductions for SPCs and could be important modifiable risk factors to target among endometrial cancer survivors.

Colombian consensus for the molecular diagnosis of endometrial cancer

Objective: The Cancer Genome Atlas research program (TCGA) developed the molecular classification for endometrial cancer with prognostic and therapeutic utility, which was replaced by the ProMisE (Proactive Molecular Risk Classifier for Endometrial Cancer) classification by consensus and international guidelines due to its high cost. This article aims to present national recommendations from an expert consensus that allows unification and implementation of the molecular classification for women with endometrial cancer nationwide, with a rational use of resources and technology. Methods: Consensus of 36 experts in clinical oncology, oncological gynecology, pathology, and genetics, with clinical practice in the national territory. The leader group performed a literature review and structuring of questions rated 1 to 9 points. A modified nominal group technique was used. There was a face-to-face meeting with master presentations, deliberative dialogue, and Google Forms (Google LLC, Mountain View, CA, USA) questionnaire voting with analysis and discussion of responses. The non-consensual responses led to a second round of voting. The final manuscript was finally prepared and revised. Results: Seven recommendations were formulated integrating the panelist responses based on evidence, but adjusted to the Colombian context and reality. Recommendation 1. The molecular classification is recommended in all the endometrial cancers using the immunohistochemistry markers as subrogated results from the molecular profile initially proposed in the TCGA classification. Recommendation 2. The sequential test strategy is recommended, starting with the immunohistochemistry markers (p53, MLH1, MSH 2, MSH6, PMS2) simultaneously in all the patients, defining to request POLE (DNA polymerase epsilon) (if available) according to the risk classification based on the surgical piece. Recommendation 3. It is recommended, that the gynecologist oncologist should be the one to request the POLE (if available) according to the final pathology report. This test must be requested for all endometrial cancers stage I-II, except in low risk (stage IA low grade endometrioid histology without linfovascular invasion normal p53) and, stages III-IV without residual disease, without affecting the request of subrogated immunohistochemistry molecular markers upon histology. The consensus proposes that the POLE is requested after the immunohistochemistry and according to the categories in the risk classification established by the 2020 ESGO/ESTRO/ESP guidelines. Recommendation 4. It is recommended to perform immunohistochemistry for hormonal receptors for all women with endometrial cancer and the HER2 in patients with p53abn, simultaneously with the others immunohistochemistry markers. Recommendation 5. It is recommended to perform the immunohistochemistry markers (p53, MLH1, MSH2, MSH6 y PMS2) in an initial endometrial biopsy or curettage when the specimen is adequate and available. In case the initial immunohistochemistry is inconclusive, or there are histological discrepancies between the initial and definitive pathology, it is recommended to repeat the molecular profile in the surgical pathology. The immunohistochemistry markers must be reported in the pathology report according to the CAP (College of American Pathologists) recommendations, independently of the type of sample. Recommendation 6. It is recommended to perform MLH1 promoter methylation testing in patients who exhibit loss of expression of MLH1 in immunohistochemistry whether it is accompanied or not with loss of expression of PMS2. All the patients with deficient MMR (mismatch repair), should be sent for genetic counseling to rule out Lynch syndrome. Recommendation 7. It is recommended to consider the molecular classification in addition to the classical histopathological criteria when making adjuvant judgments, as incorporated by the classification of prognostic groups of the 2020 ESGO/ESTRO/ESP guidelines. Conclusions: It is necessary to implement the molecular classification of endometrial cancer in clinical practice in accordance to the Colombian context, due to its prognostic and probably predictive value. This will enable the characterization of the Colombian population in order to offer individualized guided treatments. This is an academic and nonregulatory document.

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

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

Differential Rapid Diagnosis of Endometrial Cancer and Its Benign Pathological Conditions Using Surface-Enhanced Raman Spectroscopy

Differential Rapid Diagnosis of Endometrial Cancer and Its Benign Pathological Conditions Using Surface-Enhanced Raman Spectroscopy

Integrating proteomics and explainable artificial intelligence: a comprehensive analysis of protein biomarkers for endometrial cancer diagnosis and prognosis.

Endometrial cancer, which is the most common gynaecological cancer in women after breast, colorectal and lung cancer, can be diagnosed at an early stage. The first aim of this study is to classify age, tumor grade, myometrial invasion and tumor size, which play an important role in the diagnosis and prognosis of endometrial cancer, with machine learning methods combined with explainable artificial intelligence. 20 endometrial cancer patients proteomic data obtained from tumor biopsies taken from different regions of EC tissue were used. The data obtained were then classified according to age, tumor size, tumor grade and myometrial invasion. Then, by using three different machine learning methods, explainable artificial intelligence was applied to the model that best classifies these groups and possible protein biomarkers that can be used in endometrial prognosis were evaluated. The optimal model for age classification was XGBoost with AUC (98.8%), for tumor grade classification was XGBoost with AUC (98.6%), for myometrial invasion classification was LightGBM with AUC (95.1%), and finally for tumor size classification was XGBoost with AUC (94.8%). By combining the optimal models and the SHAP approach, possible protein biomarkers and their expressions were obtained for classification. Finally, EWRS1 protein was found to be common in three groups (age, myometrial invasion, tumor size). This article's findings indicate that models have been developed that can accurately classify factors including age, tumor grade, and myometrial invasion all of which are critical for determining the prognosis of endometrial cancer as well as potential protein biomarkers associated with these factors. Furthermore, we were able to provide an analysis of how the quantities of the proteins suggested as biomarkers varied throughout the classes by combining the SHAP values with these ideal models.

Assessment of sociodemographic factors in timely endometrial cancer diagnosis following an abnormal transvaginal ultrasound performed for postmenopausal bleeding.

Assessment of sociodemographic factors in timely endometrial cancer diagnosis following an abnormal transvaginal ultrasound performed for postmenopausal bleeding.

Evaluating the Efficacy and Accuracy of AI-Assisted Diagnostic Techniques in Endometrial Carcinoma: A Systematic Review.

Diagnosing endometrial carcinoma correctly is essential for appropriate treatment, as it is a major health risk.As machine learning (ML) and artificial intelligence (AI) have grown in popularity, so has interest in their potential to improve cancer diagnosis accuracy.In the context of endometrial cancer, this study attempts to examine the efficacy as well as the accuracy of AI-assisted diagnostic approaches. Additionally, it aims to methodically evaluate the contribution of AI and ML techniques to the improvement of endometrial cancer diagnosis. Following PRISMA guidelines, we performed a thorough search of numerous databases, including Medline via Ovid, PubMed, Scopus, Web of Science, and Google Scholar. Ten years were searched, encompassing both basic and advanced research. Peer-reviewed papers and original research studies that explicitly looked at the application of AI/ML in endometrial cancer diagnosis were the main targets of the well-defined selection criteria. Using the Critical Appraisal Skills Programme (CASP) methodology, two independent researchers conducted a thorough screening process and quality assessment of included studies. The review found a notable inclination towards the effective use of AI in endometrial carcinoma diagnostics, namely in the identification and categorization of endometrial cancer.Artificial intelligence models, particularly Convolutional Neural Networks (CNNs) and deep learning algorithms have shown remarkable precision in detecting endometrial cancer. They frequently achieve or even exceed the diagnostic proficiency of human specialists.The use of artificial intelligence in medical diagnostics signifies revolutionary progress in the field of oncology.AI-assisted diagnostic tools have demonstrated the potential to improve the precision and effectiveness of cancer diagnosis, namely in cases of endometrial carcinoma.This innovation not only enhances the quality of patient care but also indicates a transition towards more individualized and efficient treatment approaches in the field of oncology. The advancement of AI technology is expected to play a crucial role in medical diagnostics, particularly in the field of cancer detection and treatment, perhaps leading to a significant transformation in the approach to these areas.

Clinical Correlations between Serological Markers and Endometrial Cancer.

Background: Endometrial cancer is associated with changes in blood cell counts and with high levels of inflammatory markers, thus reflecting the tumor's impact on various biological processes and suggesting their potential as biomarkers for endometrial cancer diagnosis, prognosis, and treatment response. The neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and monocyte-to-lymphocyte ratio in peripheral blood sampled preoperatively from patients have been reported to be independently associated with the prognosis of different types of malignancies. Objectives: This study aimed to compare several blood markers-red blood cells, white blood cells, platelet parameters, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, C-reactive protein, and fibrinogen-in patients with benign or malignant endometrial tumors. Material and methods: Our retrospective study included 670 patients (192 diagnosed with endometrial cancer and 478 with endometrial hyperplasia), and we compared the serological parameters discussed above with those sampled the day before surgery. Results: Analysis of complete blood count indices revealed no significant differences in red blood cell or total white blood cell parameters between the endometrial cancer group and the endometrial hyperplasia group. However, a distinct pattern emerged in the white blood cell differential. The endometrial cancer group showed a statistically significant decrease in lymphocyte count compared with the endometrial hyperplasia group. In contrast, the endometrial cancer group showed significantly higher mean platelet counts and increased mean platelet volume compared with controls. Furthermore, the endometrial cancer group demonstrated a marked inflammatory response, as evidenced by significantly elevated levels of C-reactive protein, fibrinogen, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and monocyte-to-lymphocyte ratio compared with the endometrial hyperplasia group. Conclusions: The current research revealed statistically significant differences in multiple serological biomarkers between the two groups. These findings support the initial hypothesis regarding the potential utility of these biomarkers in endometrial cancer diagnosis, prognosis, and treatment response, highlighting the existence of biomarkers affordable for analysis under any health system, regardless of the country's level of development.

Polycystic ovary syndrome and endometrial cancer risk: results from a nationwide cohort study.

Most previous studies have found an elevated risk of endometrial cancer among women with polycystic ovary syndrome (PCOS). However, these have highly varying methods for ascertainment of PCOS diagnoses and have limitations such as few exposed women and short follow-up. In this cohort study, we investigated the association between PCOS and endometrial cancer among women born in Denmark between January 1, 1940, and December 31, 1993 (N=1,719,121). Data in this study, including PCOS and endometrial cancer diagnoses and covariates, were derived from nationwide registers. We used cox proportional hazard regression models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). A total of 7862 endometrial cancer cases were identified during 23.7 years of follow-up (inter quartile range 37.7-61.9). We found an increased risk of endometrial cancer among women with PCOS compared with women without PCOS (HR: 3.02, 95% CI; 2.03-4.49). The risk was increased for premenopausal women (HR5.82, 95% CI: 3.64-9.30) whereas no marked association was seen for postmenopausal women. However, for postmenopausal women, results were limited by few cases and young age at end of follow-up. Mounting evidence of an increased risk for endometrial cancer among women with PCOS reinforces the need for prevention and early detection.

Stage II endometrial cancer: The diagnostic power of hysteroscopic excisional biopsy and MRI in the pre-operative cervical stroma assessment

Introduction/backgroundStage II Endometrial cancer (EC) accounts only for 12% of cases. Recent evidences redraw the weight of radicality in this stage as it would seem to have no impact on survival outcomes claiming for radicality when free surgical margins are not ensured to be achieved by simple hysterectomy. Thus, an accurate pre-operative evaluation might be crucial. This study aims to estimate the diagnostic power of Hysteroscopic excisional biopsy (HEB) of cervical stroma alone and combined with Magnetic resonance imaging (MRI) to predict the stage and concealed parametrial invasion in patients with preoperative stage II EC. MethodologyFrom January 2019 to November 2023, all patients evaluated at the Department of Gynaecology Oncology of Humanitas, Istituto Clinico Catanese, Catania, Italy, with a diagnosis of EC and evidence of cervical stromal diffusion on preoperative MRI and/or office hysteroscopy evaluation, considered suitable for laparoscopic modified type B hysterectomy, were consecutively included in the study. These underwent endometrial and cervical hysteroscopy excisional biopsy (HEB) for histological evaluation before definitive surgery. The data obtained were compared with the definitive histological examination (reference standard). ResultsSixteen patients met the including/excluding criteria and were considered into the study. Stage II endometrial cancer were confirmed in 3 cases (18.7%). We reported 2 (12,5%) parametrial involvement (IIIB), 4 (25%) cases of lymph nodes metastasis (IIIc), 7 (43,7%) cases of I stage. MRI had a sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy (95% CIs) of 71%, 44%, 50%, 66% and 56.2 % respectively.HEB showed sensitivity, specificity, PPV, NPV and accuracy (95 % CI) of 85 %, 89 %, 85 %, 88 % and 87 % respectively. Comparing HEB + MRI to HEB alone, no statistical differences were noted in all fields. Considering parametrial invasion, MRI had better sensitivity but there were no statistical differences to HEB in other fields, showing both a worthy NPV. ConclusionHEB was accurate in all fields for cervical stroma assessment and had a fine NPV to exclude massive cervical involvement up to parametrial. Considering the new FIGO staging a preoperative molecular and histological evaluation of the cervical stroma may be useful. Operative hysteroscopy seems to be a feasible and accurate method for this purpose.

Differential levels of circulating RNAs prior to endometrial cancer diagnosis.

Endometrial cancer (EC) is one of the most common female cancers and there is currently no routine screening strategy for early detection. An altered abundance of circulating microRNAs (miRNAs) and other RNA classes have the potential as early cancer biomarkers. We analyzed circulating RNA levels using small RNA sequencing, targeting RNAs in the size range of 17-47 nucleotides, in EC patients with samples collected prior to diagnosis compared to cancer-free controls. The analysis included 316 cases with samples collected 1-11 years prior to EC diagnosis, and 316 matched controls, both from the Janus Serum Bank cohort in Norway. We identified differentially abundant (DA) miRNAs, isomiRs, and small nuclear RNAs between EC cases and controls. The top EC DA miRNAs were miR-155-5p, miR-200b-3p, miR-589-5p, miR-151a-5p, miR-543, miR-485-5p, miR-625-p, and miR-671-3p. miR-200b-3p was previously reported to be among one of the top miRNAs with higher abundance in EC cases. We observed 47, 41, and 32 DA miRNAs for EC interacting with BMI, smoking status, and physical activity, respectively, including two miRNAs (miR-223-3p and miR-29b-3p) interacting with all three factors. The circulating RNAs are altered and show temporal dynamics prior to EC diagnosis. Notably, DA miRNAs for EC had the lowest q-value 4.39-6.66 years before diagnosis. Enrichment analysis of miRNAs showed that signaling pathways Fc epsilon RI, prolactin, toll-like receptor, and VEGF had the strongest associations.

The usefulness of p16 and COX-2 expression on the prediction of progression to endometrial cancer.

Endometrial cancer (EC) is the most commonly diagnosed gynecological cancer. Endometrial hyperplasia (EH) is a more common diagnosis than EC. Endometrial hyperplasia is found in approximately 1.5% of all women presenting with abnormal bleeding. Endometrial hyperplasia progresses to EC, and especially, cancer risk increases in cases with atypical hyperplasia. p16, one of the tumor suppressor proteins involved in the cell cycle, and COX-2, one of the key enzymes of prostaglandin synthesis, are important markers for the diagnosis of both EH and EC. There is lack of consensus in the classification, diagnosis and treatment of EH. The subject of changes in the cell cycle in the progression of endometrial pathologies may help to identify and prevent these affected pathways in the treatment stage. The aim of this study is to investigate the expression of p16 and COX-2 during the development of EC from EH. We investigated COX-2 and P16 expressions in patients with proliferative endometrium, complex/simple endometrial hyperplasia and endometrioid adenocarcinoma. p16 expression increased in EH and EC (p<0.001). COX-2 expression was increased in endometrial cancer compared to other groups, but this increase was not found to be statistically significant. Although p16 and COX-2 expression were increased in patients with advanced grade/stage, lymphovascular invasion, and >50% of myometrial invasion, this increase was not statistically significant. More detailed studies are needed to investigate the prognostic significance of the COX-2 molecule. COX-2 might be a potential biomarker for the prognosis of endometrial cancer and a potential therapeutic target for EC treatment. Also, it might be used to prevent the progression of precursor lesions to invasive EC.

Multiparametric magnetic resonance imaging-based assessment of the effect of adenomyosis on determining the depth of myometrial invasion in endometrial cancer.

Accurate preoperative diagnosis of endometrial cancer (EC) with deep myometrial invasion (DMI) is critical to deciding whether to perform lymphadenectomy. However, the presence of adenomyosis makes distinguishing DMI from superficial myometrial invasion (SMI) on magnetic resonance imaging (MRI) challenging. We aimed to evaluate the accuracy of multiparametric MRI (mpMRI) in diagnosing DMI in EC coexisting with adenomyosis (EC-A) compared with EC without coexisting adenomyosis and to evaluate the effect of different adenomyosis subtypes on myometrial invasion (MI) depth in EC. Patients with histologically confirmed International Federation of Gynecology and Obstetrics (FIGO) stage I EC who underwent preoperative MRI were consecutively included in this 2-center retrospective study. Institution 1 was searched from January 2017 to November 2022 and institution 2 was searched from June 2017 to March 2021. Patients were divided into 2 groups: group A, patients with EC-A; group B, EC patients without coexisting adenomyosis, matched 1:2 according to age ±5 years and tumor grade. A senior radiologist assessed the MRI adenomyosis classification in group A. Then, 2 radiologists (R1/R2) independently interpreted T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), T1-weighted contrast-enhanced (T1CE), and a combination of all images (mpMRI) respectively, and then assessed MI depth. Accuracy, sensitivity, specificity, and the areas under the receiver operating curve (AUC) were calculated. The chi-square test was used to compare the accuracy of diagnosing DMI. Interobserver agreement was evaluated using the Kappa test. A total of 70 cases in group A and 140 cases in group B were included. The accuracy, sensitivity, and specificity of consensus were 94.3% [95% confidence interval (CI): 88.9-99.7%] vs. 92.1% (95% CI: 87.7-96.6%), 60.0% (95% CI: 17-92.7%) vs. 86.7% (95% CI: 68.4-95.6%), and 96.9% (95% CI: 88.4-95.5%) vs. 93.6% (95% CI: 86.8-97.2%) (group A vs. group B, respectively). There was no significant difference in the diagnostic accuracy of DMI on each sequence between the groups (Reviewer 1/Reviewer 2): PT2WI=0.14/0.17, PDWI=0.50/0.33, PT1CE=0.90/0.18, PmpMRI=0.50/0.37. The AUC for T2WI, DWI, T1CE, and mpMRI (Reviewer 1/Reviewer 2), respectively, were 0.54 (95% CI: 0.42-0.66)/0.78 (95% CI: 0.67-0.87), 0.63 (95% CI: 0.50-0.74)/0.77 (95% CI: 0.65-0.86), 0.69 (95% CI: 0.57-0.80)/0.79 (95% CI: 0.68-0.88), and 0.91 (95% CI: 0.82-0.97)/0.89 (95% CI: 0.79-0.95) (group A) and 0.83 (95% CI: 0.76-0.89)/0.85 (95% CI: 0.78-0.90), 0.83 (95% CI: 0.76-0.89)/0.86 (95% CI: 0.79-0.91), 0.88 (95% CI: 0.82-0.93)/0.86 (95% CI: 0.80-0.92), and 0.91 (95% CI: 0.85-0.95)/0.87 (95% CI: 0.80-0.92) (group B). Interobserver agreement was highest with mpMRI [κ=0.387/0.695 (case/control)]. The consensus results of MRI categorization of adenomyosis revealed no significant difference in the accuracy of diagnosing DMI by adenomyosis subtype (Pspatial relationship>0.99, Paffected area=0.52, Paffected pattern=0.58, Paffected size>0.99). The presence of adenomyosis or adenomyosis subtype had no significant effect on the interpretation of the depth of MI. T1CE can increase the contrast between adenomyosis and cancer foci; therefore, the information provided by T1CE should be valued.

High-Grade Endometrial Cancer: Molecular Subtypes, Current Challenges, and Treatment Options.

Although many recent advancements have been made in women's health, perhaps one of the most neglected areas of research is the diagnosis and treatment of high-grade endometrial cancer (EnCa). The molecular classification of EnCa in concert with histology was a major step forward. The integration of profiling for mismatch repair deficiency and Human Epidermal Growth Factor 2 (HER2) overexpression, can further inform treatment options, especially for drug resistant recurrent disease. Recent early phase trials suggest that regardless of subtype, combination therapy with agents that have distinct mechanisms of action is a fruitful approach to the treatment of high-grade EnCa. Unfortunately, although the importance of diagnosis and treatment of high-grade EnCa is well recognized, it is understudied compared to other gynecologic and breast cancers. There remains a tremendous need to couple molecular profiling and biomarker development with promising treatment options to inform new treatment strategies with higher efficacy and safety for all who suffer from high-grade recurrent EnCa.

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.