Prognosis Of Endometrial Cancer Research Articles

Endometrial Cancer in Reproductive-Aged Females: Etiology and Pathogenesis.

Endometrial cancer is the most common gynecologic malignancy in developed countries, and the incidence is rising in premenopausal females. Type I EC is more common than Type II EC (80% vs. 20%) and is associated with a hyperestrogenic state. Estrogen unopposed by progesterone is considered to be the main driving factor in the pathogenesis of EC. Studies show that BMI > 30 kg/m2, prolonged duration of menses, nulliparity, presence of polycystic ovarian syndrome, and Lynch syndrome are the most common causes of EC in premenopausal women. Currently, there are no guidelines established to indicate premenopausal patients who should be screened. This review aims to synthesize current data on the etiology, risk factors, presentation, evaluation, and prognosis of endometrial cancer in this population.

Abstract CT008: A phase 2, two-stage study of mirvetuximab soravtansine (IMGN853) in combination with pembrolizumab in patients with microsatellite stable (MSS) recurrent or persistent endometrial cancer

Abstract Background & Objectives: Folate receptor-alpha (FRα) expression is associated with poor prognosis in endometrial cancer (EC). Mirvetuximab soravtansine (MIRV), an antibody drug conjugate (ADC) comprising a FRα-binding antibody, cleavable linker, and the tubulin-disrupting maytansinoid DM4, showed tolerability and single agent activity in a Phase 1 dose expansion study in FRα-positive advanced/recurrent EC (NCT01609556). In addition to target-mediated cytotoxicity, MIRV activates monocytes and promotes phagocytosis of tumor cells through Fc-FcγR interactions. We therefore hypothesized that MIRV would improve the low response to immune checkpoint inhibitors (ICI) in MSS/pMMR EC and conducted this two-stage, phase 2, single cohort study evaluating the activity of MIRV in combination with pembrolizumab in patients with recurrent/persistent EC (NCT03835819). Methods: Patients with advanced or recurrent MSS/pMMR, FRα positive (defined as ≥50% of tumor cells with ≥2+ staining on IHC by Ventana, Inc.) serous EC received MIRV 6 mg/kg AIBW and pembrolizumab 200 mg every 21 days until disease progression or unacceptable toxicity. Patients could have received 1-3 prior lines of therapy; prior ICI therapy was allowed. The co-primary endpoints were objective response rate (ORR) as measured by RECIST 1.1 and frequency of patients surviving progression-free for 6 months (PFS6). In the first stage of the study, 16 patients were enrolled; if there were ≥2 objective responses or ≥2 PFS6 responses, an additional 19 patients would be enrolled in Stage 2. If a total of 4 objective responses or 8 PFS6 events were achieved, the combination would be considered worthy of further study. Data: Among 130 patient tumors prescreened for FRα expression, the median FRα (% of tumor cells with ≥2+ staining) was 30% (IQR: 5-55) and 43 (33.1%) were FRα positive (PS 2+ ≥50%). As of data-cutoff in November 2023, a total of 16 patients had received study treatment with median follow-up of 4.7 months (IQR 2.9, 17.3). Of 16 treated patients, 6 patients (37.5%, 95% CI: 15.2-64.6%) achieved an objective response, including 1 patient achieving a confirmed CR and 5 patients achieving a PR [3 confirmed PR (18.8%) and 2 unconfirmed PR (12.5%)] (Fig. 1). An additional 31.3% (5/16) had stable disease and two patients were alive and progression free at 6 months. The most common TRAEs included AST elevation (50%), blurred vision (44%), fatigue (44%) and diarrhea (43%); grade 3 TRAEs occurred in 2 patients (12.5%). Ocular toxicities of any grade were reported in 56.3% of patients. Updated efficacy and safety data as well as ongoing correlative studies will be reported at the time of the meeting. Conclusions: In this investigator-initiated study, the combination of MIRV and pembrolizumab met the co-primary endpoint to be considered worthy of further study in FRα-positive recurrent MSS/pMMR serous EC. Investigations into subpopulations most likely to derive clinical benefit from this combination are ongoing. Citation Format: Rebecca L. Porter, Niya Xiong, Nabihah Tayob, Madeline Polak, Hannah Sawyer, Martin Hayes, Jeanette Gardner, Susana Campos, Neil Horowitz, Carolyn Krasner, Elizabeth K. Lee, Joyce F. Liu, Elizabeth H. Stover, Jennifer Veneris, Alexi A. Wright, Ursula A. Matulonis, Panagiotis Konstantinopoulos. A phase 2, two-stage study of mirvetuximab soravtansine (IMGN853) in combination with pembrolizumab in patients with microsatellite stable (MSS) recurrent or persistent endometrial cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr CT008.

Advances in research on autophagy mechanisms in resistance to endometrial cancer treatment.

Administering medication is a crucial strategy in improving the prognosis for advanced endometrial cancer. However, the rise of drug resistance often leads to the resurgence of cancer or less-than-ideal treatment outcomes. Prior studies have shown that autophagy plays a dual role in the development and progression of endometrial cancer, closely associated with drug resistance. As a result, concentrating on autophagy and its combination with medical treatments might be a novel approach to improve the prognosis for endometrial cancer. This study explores the impact of autophagy on drug resistance in endometrial cancer, investigates its core mechanisms, and scrutinizes relevant treatments aimed at autophagy, aiming to illuminate the issue of treatment resistance in advanced endometrial cancer.

Abstract 7563: Efficacy of JPI-547, novel dual PARP inhibitor, in endometrial cancer cell line

Abstract Objectives: PARP inhibitor is effective in treating DNA repair deficiency endometrial cancer. Endometrial cancer (EC) is one of the most common gynecological cancers in developed countries and its incidence is increasing, and the prognosis of patients with early stage and low-risk EC is very good, but the prognosis of progressive and recurrent EC is poor. Novel PARP inhibitor JPI-547 is a PARP and tankyrase dual inhibitor, and in cancer cells, tankyrase inhibitor plays an important role in DNA repair, telomere maintenance, and cell survival. This experiment was conducted to determine whether the reactivity of the PTEN mutant EEC was increased by using the Novel PARP inhibitor. Method: Human endometrioid endometrial cancer cell lines, Hec-1A, Hec-1B and Ishikawa were obtained. Cell viability assay for the drugs Olaparib and JPI-547 were assessed. Colonies consisting of at least 50 cells were counted. The number of dead cells was counted in five different areas of the hemocytometer, and the experiment was performed three times. The percentage of dead cells was analyzed compared to the untreated group. We confirmed the efficacy by siRNA transfection and immunofluorescence. Result: When treated with Olaparib, there was no change in cell viability in the rest of the cells except for Ishikawa cells, which are PTEN mutations. It decreased by 35.4% in Ishikawa cells, whereas when treated with JPI-547, all cell lines Hec-1A, Hec-1B, and Ishikawa cell viability decreased by 28%, 34.3%, and 48.7%, respectively. PTEN knock-down reduced cell visibility by 28% when treated with olaparib, whereas when treated with JPI-547, Hec-1A (siCont) and Hec-1A (siPTEN) decreased by 26% and 42%, respectively, in all cells regardless of whether PTEN knock-down is present. When treated with Olaparib, dead cells were identified only in PTEN knock-down cells, increasing by 22%. When treated with JPI-547, dead cells increased by 25.5% and 33% in all cells of Hec-1A (siCont) and Hec-1A (siPTEN), respectively. It was confirmed that JPI-547 can reduce cell viability regardless of the formation of Rad51 according to PTEN. Conclusion: JPI-547, a novel PARP inhibitor, showed good efficacy in PTEN mutation and PTEN-wild-type EEC cell lines than in conventional PARP inhibitor. The effect of reducing survival of ECC cell line with JPI-547 was confirmed with or without PTEN mutation. Further evaluation and in vivo experiments are needed to prove the efficacy of JPI-547 in EC. Citation Format: Shin-Wha Lee, So-Hyun Nam, Su-Bin Park. Efficacy of JPI-547, novel dual PARP inhibitor, in endometrial cancer cell line [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 7563.

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.

Whether surgical procedure can improve the prognosis of endometrial cancer arising in adenomyosis (EC-AIA)? A systematic review and meta-analysis.

Endometrial cancer arising in adenomyosis (EC-AIA) is frequently detected accidentally following a general hysterectomy for adenomyosis. Whether supplemental lymphadenectomy in patients with EC-AIA can improve the survival outcome remains inconclusive. Herein, the authors summarized the data of patients with EC-AIA and further explored the impact of lymphadenectomy on the prognosis of these patients. Five electronic databases, namely MEDLINE, Web of Science, PubMed, Embase, and the Cochrane Library were employed for searching articles from inception to May 2023. In total, 38 eligible studies enrolling 56 patients were included. Of these, 44 patients had a traceable prognosis. Kaplan-Meier curves demonstrated that patients who had undergone lymphadenectomy had a better progression-free survival (PFS) compared with those who had not undergone lymphadenectomy ( P =0.016), but there was no difference in overall survival. Univariable ( P =0.025, HR=0.25, 95% CI=0.08-0.84) and multivariable ( P =0.042, HR=0.13, 95% CI=0.020-0.930) Cox regression analyses revealed that lymphadenectomy was an independent protective factor for PFS. For patients diagnosed with EC-AIA following hysterectomy for benign disease, further supplementary lymphadenectomy is recommended to improve PFS.

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.

Exploring prognostic microbiota markers in patients with endometrial carcinoma: Intratumoral insights

Endometrial cancer, a leading gynecological malignancy, is profoundly influenced by the uterine microbiota, a key factor in disease prognosis and treatment. Our study underscores the distinct microbial compositions in endometrial cancer compared to adjacent non-cancerous tissues, revealing a dominant presence of p_Actinobacteria in cancerous tissues as opposed to p_Firmicutes in surrounding areas. Through comprehensive analysis, we identified 485 unique microorganisms in cancer tissues, 26 of which correlate with patient prognosis. Employing univariate Cox regression and LASSO regression analyses, we devised a microbial risk scoring model, effectively stratifying patients into high and low-risk categories, thereby providing predictive insights into their overall survival. We further developed a nomogram that incorporates the microbial risk score along with age, grade, and clinical stage, significantly enhancing the accuracy of our clinical prediction model for endometrial cancer. Moreover, our study delves into the differential immune landscapes of high-risk and low-risk patients. The low-risk group displayed a higher prevalence of activated B cells and increased T cell co-stimulation, indicative of a robust immune response. Conversely, high-risk patients showed elevated tumor immune dysfunction and exclusion scores, suggesting less favorable outcomes in immunotherapy. Notably, the efficacy of IPS-CTLA4 and PD1/PD-L1/PD-L2 blockers was substantially higher in the low-risk group, pointing to a more responsive immunotherapeutic approach. In summary, our research elucidates the unique microbial patterns in endometrial cancer and adjacent tissues, and establishes both a microbial risk score model and a clinical prediction nomogram. These findings highlight the potential of uterine microbiota as a biomarker for customizing treatment strategies, enabling precise interventions for high-risk patients while preventing overtreatment in low-risk cases. This study emphasizes the microbiota's role in tailoring immunotherapy, offering a novel perspective in the treatment and prognosis of endometrial cancer. Significantly, our study's expansive sample analysis from the TCGA-UCEC cohort, employing linear discriminant analysis effect size methodology, not only validates but also enhances our understanding of the microbiota's role in endometrial cancer, paving the way for novel diagnostic and therapeutic approaches in its management.

Mismatch repair gene MSH6 correlates with the prognosis, immune status and immune checkpoint inhibitors response of endometrial cancer.

Many patients treated with immune checkpoint inhibitors (ICIs) developed primary or secondary drug resistance for unknown reasons. This study investigates whether mismatch repair (MMR) genes are responsible for this therapeutic restriction. We obtained the transcriptional, clinical and single nucleotide polymorphism data for endometrial cancer (EC) from The Cancer Genome Atlas and the immunophenoscore data of EC from The Cancer Immunome Atlas, then analyzed in R to evaluate the relationship between MMR genes and clinicopathological features, prognosis, immune infiltration, immune checkpoint expression and responsiveness to ICIs in EC. We used differentially expressed genes in the MSH6 high and low expression groups to conduct GO and KEGG analyses to explore the impact of MSH6 on the biological functions of EC. Finally, we verified the bioinformatics results with in vitro experiments. Our analyses showed that compared with the high MSH6 expression group, the low MSH6 expression group had better survival outcomes and less aggressive clinicopathological features. In the multivariate Cox analysis, MSH6 was the only independent risk factor that could predict the prognosis of EC. Besides, the low MSH6 expression group also had a higher immune score, more active immune infiltration and higher immune checkpoint expression, resulting in better responsiveness to ICIs treatment, consistent with the enrichment of GO terms and KEGG pathways related to immune response in this group. Meanwhile, the GO and KEGG enrichment results of the MSH6 high expression group were associated with cell cycle, DNA damage repair and tumorigenesis. To exclude the influence of MSH6 mutations, we performed the previous analyses on the MSH6 wild-type tumor samples and obtained consistent results. In vitro experiments also confirmed that after knocking down MSH6 in endometrial cancer cells, their proliferation, migration and invasion abilities were weakened, while the expression levels of PD-L1 and PD-L2 were elevated. In comparison, overexpression of MSH6 showed an opposite trend. Reduced MSH6 expression could serve as a potential biomarker for predicting better prognosis, active immune status, higher immune checkpoint expression level and better responsiveness to ICIs treatment in EC. MSH6 may become a potential target for treating solid tumors.

Identification ATP5F1D as a Biomarker Linked to Diagnosis, Prognosis, and Immune Infiltration in Endometrial Cancer Based on Data-Independent Acquisition (DIA) Analysis.

In developed countries, endometrial cancer (EC) is the most prevalent gynecological cancer. ATP5F1D is a subunit of ATP synthase, as well as an important component of the mitochondrial electron transport chain (ETC). ETC plays a compelling role in carcinogenesis. To date, little is known about the role of ATP5F1D in EC. We undertook data-independent acquisition mass spectrometry (DIA-MS) of 20 EC patients, comprising 10 high-grade and 10 low-grade cancer tissues. Biological functions of differentially expressed genes (DEGs) were analyzed by GO and KEGG. The expression level, clinicopathological features, diagnostic potency, prognostic value, RNA modifications, immune characteristics, and therapy response of ATP5F1D were investigated. In total, 77 DEGs were acquired by DIA analysis, which were closely related to regulating immune response and metabolic pathways. Among the five genes (NDUFB8, SLC26A2, RAF1, ATP5F1D, and GSTM5) involving in reactive oxygen species pathway, ATP5F1D showed the most significant differential expression (2.903-fold change). We found ATP5F1D had a high diagnostic value and was associated with a favorable prognosis in EC patients. After analyzing the RNA modifications of ATP5F1D, revealing a negative regulation between them. Additionally, ATP5F1D was closely related to tumor immune infiltration. Our results suggested T-cell dysfunction and TAM-M2 polarization might be the important mechanisms of ATP5F1D to facilitate tumor immune escape. Noticeably, EC patients with ATP5F1D-high expression had better immune treatment responses and were more sensitive to chemotherapy drugs. ATP5F1D can be used as a biomarker for diagnosis, prognosis, and immune infiltration of EC, and offers a crucial reference for personalized treatment of EC patients.

A single-institution retrospective exploratory analysis on the effectiveness and safety of lenvatinib plus pembrolizumab for advanced endometrial cancer: insights from ProMisE molecular classification system.

The Proactive Molecular Risk Classifier for Endometrial Cancer has identified four risk groups for the prognosis of endometrial cancer. Lenvatinib plus pembrolizumab was recently approved as a second-line treatment for unresectable endometrial cancer, but reports in clinical practice are lacking. The relationship between the efficacy of lenvatinib/pembrolizumab and Proactive Molecular Risk Classifier for Endometrial Cancer classification is unclear. This single-centre retrospective study included patients who underwent lenvatinib/pembrolizumab therapy at Iwate Medical University Hospital between January 2022 and March 2023. Formalin-fixed paraffin-embedded specimens obtained from patients before treatment were collected and classified into the mismatch repair-deficient, p53 abnormal and no specific molecular profile subtypes using immunohistochemistry. The response rate, progression-free survival and adverse events were evaluated using electronic medical records. The study was approved by the hospital's ethics committee (approval number: MH2022-093). This study enrolled 20 patients, who underwent a median follow-up of 17.8months (95% confidence interval: 16.6-18.9). The best overall response rate was 60.0% (36.1-80.9), and the median progression-free survival was 11.6months (2.9-20.3). The median progression-free survival in the p53 abnormal group (n =9) was 3.4months (3.0-3.8); however, progression-free survival did not reach the median (P<0.001) in the mismatch repair-deficient/no specific molecular profile group (n=11). Symptomatic immune-related adverse events (except hypothyroidism) occurred in 4/20 (25.0%) patients, and partial responses were observed in all cases. No treatment-related deaths occurred. The p53abn group in the Proactive Molecular Risk Classifier for Endometrial Cancer classification has a poor prognosis even after treatment with lenvatinib/pembrolizumab.

Abnormal p53 expression is associated with poor outcomes in grade I or II, stage I, endometrioid carcinoma: a retrospective single-institute study.

The Cancer Genome Atlas study revealed an association between copy-number high (p53 abnormal) genetic mutation and poor prognosis in endometrial cancer in 2013. This retrospective study investigated outcomes in patients with abnormal p53 expression and stage I, low-grade endometrial endometrioid carcinoma (EEC). We enrolled women with stage I, grade 1 or 2 EEC who received comprehensive staging and adjuvant therapy between January 2019 and December 2022 at MacKay Memorial Hospital, Taipei, Taiwan. Pathologists interpreted immunohistochemistry stains of cancerous tissues to detect p53 mutation. We compared recurrence, survival, progression-free survival, and overall survival between p53 abnormal and p53 normal groups. Of the 115 patients included, 26 had pathologically confirmed abnormal p53 expression. Of these 26 patients, five (19.2%) experienced recurrence, and two died due to disease progression. By contrast, no patients in the normal p53 group experienced disease recurrence or died due to disease progression. Significant intergroup differences were discovered in recurrent disease status (19.4% vs. 0%, p<0.001), mortality (7.7% vs. 0%, p<0.001), and progression-free survival (p<0.001). The overall survival (p=0.055) also showed powerful worse trend. For patients with stage I, low-grade EEC, abnormal p53 expression may be used as an indicator of poor prognosis. Therefore, we suggest considering aggressive adjuvant therapies for these patients.

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

Lymph node metastasis is associated with a poorer prognosis in endometrial cancer. The objective was to synthesize and critically appraise existing predictive models for lymph node metastasis risk stratification in endometrial cancer. This study is a systematic review. 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). 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. 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. None.

The Role of Lymphovascular Space Invasion and Cytology in the Prognosis of Endometrial Cancer.

Lymphovascular space invasion (LVSI) and cytology are both independent and strong prognostic factors in endometrial cancer. This study aims to highlight the impact of LVSI and cytology positivity on prognosis, in addition to molecular classification. A retrospective review was conducted on the records of 223 patients with endometrial cancer diagnosed between January 2011 and January 2021. The inclusion criteria stipulated that the patients were diagnosed with endometrial cancer by endometrial biopsy and were operated in the clinic. The exclusion criteria included sarcoma in the postoperative pathology report results or synchronous tumor. Staging was performed according to the Fédération internationale de gynécologie et d'obstétrique (FIGO) 2009 criteria. Cytology (using 50 cc saline) was obtained upon entry into the peritoneal cavity. In 20 patients, saline was not used due to the presence of ascites in the abdomen. The Kaplan-Meier method was employed to evaluate overall survival and progression-free survival. Survival rates were compared in terms of cytology and LVSI. After analyzing the postoperative pathology results, it was found that the mean tumor size was 4.03 ± 2.3 cm. The most common histological type was endometrioid carcinoma, with stage IA being the most common stage. Out of 223 patients with endometrial cancer, the overall survival rate was 82.4%, and the progression-free survival rate was 88.3%. For patients negative for LVSI, the progression-free survival rate was 93%, while for LVSI-positive patients, it was 77.3% (p < 0.001). Additionally, the progression-free survival rate for patients negative for cytology was 90.4%, whereas for cytology-positive patients, it was 77.1% (p < 0.05). In our study, we observed that LVSI positivity and cytology positivity also reduced the overall survival rate. We aimed to highlight that, in addition to molecular classification, cytology positivity and LVSI positivity are still highly significant and independent factors in prognosis.

Nutritional index in relation to prognosis of endometrial cancer.

Objective: Evaluate the prognostic value of the prognostic nutritional index (PNI) in patients with endometrial cancer (EC). Method: Laboratory and clinicopathological data from 370 patients who were diagnosed with EC between January 2010 and December 2021 were reviewed. The PNI was analyzed for correlations with recurrence and survival. The receiver operating characteristic curves were generated for the PNI. Optimal cut-off values were determined as the points at which the Youden index (sensitivity + specificity - 1) was maximal. Based on the results of the ROC curve analysis, the patients were grouped into high and low PNI groups. Differences in the clinicopathological characteristics between patients with high and low PNI were compared between the two groups. The effects of the prognostic factors were analyzed using univariate and multivariate Cox proportional hazards model. Results: The optimal cutoff value of the PNI was 52.74 for DFS (area under the curve: 0.817; 95% CI: 0.738-0.858, p <0.001). Significantly more patients in the low PNI group experienced recurrence (30.6% vs. 5.2%, p <0.001) and cancer-related death (17.8% vs. 2.8%, p <0.001). In multivariate analysis, PNI were independent prognostic factors for both DFS and overall survival OS. Conclusion: Low PNI was significantly associated with worse clinical outcomes in patients with EC. Our findings demonstrate that the PNI may be clinically reliable and useful as a prognostic marker for patients with EC. Further large-scale prospective studies are needed to confirm our findings.

Artificial Intelligence and Radiomics for Endometrial Cancer MRI: Exploring the Whats, Whys and Hows.

Endometrial cancer (EC) is intricately linked to obesity and diabetes, which are widespread risk factors. Medical imaging, especially magnetic resonance imaging (MRI), plays a major role in EC assessment, particularly for disease staging. However, the diagnostic performance of MRI exhibits variability in the detection of clinically relevant prognostic factors (e.g., deep myometrial invasion and metastatic lymph nodes assessment). To address these challenges and enhance the value of MRI, radiomics and artificial intelligence (AI) algorithms emerge as promising tools with a potential to impact EC risk assessment, treatment planning, and prognosis prediction. These advanced post-processing techniques allow us to quantitatively analyse medical images, providing novel insights into cancer characteristics beyond conventional qualitative image evaluation. However, despite the growing interest and research efforts, the integration of radiomics and AI to EC management is still far from clinical practice and represents a possible perspective rather than an actual reality. This review focuses on the state of radiomics and AI in EC MRI, emphasizing risk stratification and prognostic factor prediction, aiming to illuminate potential advancements and address existing challenges in the field.

Preoperative Imaging Evaluation of Endometrial Cancer in FIGO 2023.

The staging of endometrial cancer is based on the International Federation of Gynecology and Obstetrics (FIGO) staging system according to the examination of surgical specimens, and has revised in 2023, 14 years after its last revision in 2009. Molecular and histological classification has incorporated to new FIGO system reflecting the biological behavior and prognosis of endometrial cancer. Nonetheless, the basic role of imaging modalities including ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography, as a preoperative assessment of the tumor extension and also the evaluation points in CT and MRI imaging are not changed, other than several point of local tumor extension. In the field of radiology, it has also undergone remarkable advancement through the rapid progress of computational technology. The application of deep learning reconstruction techniques contributes the benefits of shorter acquisition time or higher quality. Radiomics, which extract various quantitative features from the images, is also expected to have the potential for the quantitative prediction of risk factors such as histological types and lymphovascular space invasion, which is newly included in the new FIGO system. This article reviews the preoperative imaging diagnosis in new FIGO system and recent advances in imaging analysis and their clinical contributions in endometrial cancer. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 3.

Exploring the significance of tumor volume in endometrial cancer: Clinical pathological features, prognosis, and adjuvant therapies.

To assist clinicians in formulating treatment strategies for endometrial cancer (EC), this retrospective study explores the relationship between tumor volume and clinical pathological features, as well as prognosis, in patients undergoing staging surgery. Preoperative pelvic MRI examinations were conducted on 234 histologically confirmed EC patients. The ITK-SNAP software was employed to manually delineate the region of interest in the MRI images and calculate the tumor volume (MRI-TV). The analysis focused on investigating the relationship between MRI-TV and the clinical pathological features and prognosis of EC patients. Larger MRI-TV was found to be associated with various adverse prognostic factors (G3, deep myometrial invasion, cervical stromal invasion, lymphovascular space invasion, lymph node metastasis, advanced international federation of gynecology and obstetrics staging, and receipt of adjuvant therapy). The receiver operating characteristic curve indicated that MRI-TV ≥ 8 cm3 predicted deep myometrial invasion, and MRI-TV ≥ 12 cm3 predicted lymph node metastasis. Penalized spline (P-spline) regression analysis identified 14 cm3 of MRI-TV as the optimal prognostic cutoff value. MRI-TV ≥ 14 cm3 was an independent prognostic factor for overall survival and disease-free survival. For patients with MRI-TV ≥ 14 cm3, the disease-free survival rate with adjuvant therapy was superior to that of the sole staging surgery group. This study demonstrates a significant correlation between MRI-TV and clinical pathological features and prognosis in EC. For patients with MRI-TV ≥ 14 cm3, staging surgery followed by adjuvant therapy was superior to sole staging surgery.

Development and validation of a nomogram for predicting overall survival in patients with early-onset endometrial cancer

BackgroundThis study aimed to investigate the differences in the clinicopathological characteristics of younger and older patients with endometrial cancer (EC) and develop a nomogram to assess the prognosis of early onset EC in terms of overall survival.MethodsPatients diagnosed with EC from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015 were selected. Clinicopathological characteristics were compared between younger and older patients, and survival analysis was performed for both groups. Prognostic factors affecting overall survival in young patients with EC were identified using Cox regression. A nomogram was created and internal validation was performed using the consistency index, decision curve analysis, receiver operating characteristic curves, and calibration curves. External validation used data from 70 patients with early onset EC. Finally, Kaplan-Meier curves were plotted to compare survival outcomes across the risk subgroups.ResultsA total of 1042 young patients and 12,991 older patients were included in this study. Younger patients were divided into training (732) and validation (310) cohorts in a 7:3 ratio. Cox regression analysis identified age, tumorsize, grade, FIGO stage(International Federation of Gynecology and Obstetrics) and surgery as independent risk factors for overall survival, and a nomogram was constructed based on these factors. Internal and external validations demonstrated the good predictive power of the nomogram. In particular, the C-index for the overall survival nomogram was 0.832 [95% confidence interval (0.797–0.844)] in the training cohort and 0.839 (0.810–0.868) in the internal validation cohort. The differences in the Kaplan-Meier curves between the different risk subgroups were statistically significant.ConclusionsIn this study, a nomogram for predicting overall survival of patients with early onset endometrial cancer based on the SEER database was developed to help assess the prognosis of patients and guide clinical treatment.

The identification of a PTEN-associated gene signature for the prediction of prognosis and planning of therapeutic strategy in endometrial cancer.

Endometrial cancer (EC) is one of the most common malignancies among women. To improve the prognosis and treatment of EC, finding out a phosphatase and tensin homolog deleted on chromosome 10 (PTEN)-associated prognostic signature would be beneficial. EC clinical data, genetic mutation data, and transcriptome data were downloaded from The Cancer Genome Atlas (TCGA) database. To clarify the specific PTEN-associated signature, cox regression analyses were performed. The clinical value of the selected signature on the overall survival (OS) and the secretoglobin family 2A member 1 (SCGB2A1)-independent analysis, immune and functional analysis were investigated respectively. Five hundred and fourteen EC samples were screened and PTEN mutation occupied 57%. Enrichment analysis indicated that mutant-type PTEN was enriched for pathways related to the upregulated human T-cell leukemia virus-1 (HTLV-1) infection and estrogen signaling pathway. SCGB2A1 was identified by cox regression analysis. Immune analysis exhibited significant immune infiltration with higher expression of T cells, B cells, and macrophage groups. Immune-checkpoint transcripts CD274 molecule (CD274), and cytotoxic T-lymphocyte associated protein 4 (CTLA4), hepatitis A virus cellular receptor 2 (HAVCR2), lymphocyte activation gene 3 (LAG3), programmed cell death 1 (PDCD1), PDCD1 ligand 2 (PDCD1LG2), T cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibition motif domains (TIGIT), and sialic acid binding immunoglobulin like lectin 15 (SIGLEC15) were discovered statistically different. In addition, the low-SCGB2A1 group had worse OS than the high-SCGB2A1 group. SCGB2A1 showed significant area under the curve (AUC) values in a time-dependent receiver operating characteristic (ROC) analysis. Prevalence of microsatellite instability (MSI) was detected and SCGB2A1 showed a negative correlation with EC. Immune checkpoint blockade (ICB) response indicated a worse immune response in the low-SCGB2A1 group. The distribution of one-class linear regression (OCLR) scores reflected the negative correlation between messenger RNA expression-based stemness index (mRNAsi) and prognostic gene expression. Furthermore, several SCGB2A1-related signaling pathways in EC were identified. SCGB2A1 is a prognostic immunometabolic signature for patients with EC, which may help improve the prognosis and therapeutic effect.