Metabolic syndrome score as an indicator in a predictive nomogram for lymph node metastasis in endometrial cancer

Association Between Hepatic Steatosis Index and Endometrial Cancer Risk: A Cross-Sectional Study

Purpose

To investigate the relationship between hepatic steatosis index (HSI) and endometrial cancer (EC) and its diagnostic value for EC.

Patients and Methods

A total of 114 patients with pathologically diagnosed EC in Mindong Hospital, Ningde City, Fujian Province from 2016 to 2022 were retrospectively included as the EC group. A total of 175 patients with pathologically confirmed benign endometrial lesions (endometrial polyps and uterine submucosal fibroids) in the same hospital during the same period were selected as the control group. Non-parametric test were used to compare the differences in HSI and non-alcoholic fatty liver disease (NAFLD) between the two groups, and the diagnostic value of HSI and NAFLD levels on EC was analysed. The cut-off point of continuous variables was determined by receiver operating characteristic (ROC) curve analysis. Logistic regression analysis was used to calculate odds ratios (ORs).

Results

The results showed that compared with the control group, serum GGT, CA125, HDL-C and HSI were significantly increased in the EC group (P<0.05). 27.19% of the EC patients (31/114) and 12% of the control group (21/175) had NAFLD, and the difference between the two groups was statistically significant (P<0.05). The results of univariate logistic regression analysis showed that GGT, CA125, HDL-C, HSI and NAFLD were significantly correlated with the occurrence of EC (P<0.05). Further multivariate logistic regression analysis showed that CA125 and HSI elevation were independent risk factors for EC (P<0.05).

Conclusion

NAFLD is closely associated with EC, and elevated HSI is an independent risk factor for EC.

Immunohistochemistry as a reliable predictor of remission in patients with endometrial cancer: Establishment and validation of a machine learning model

Endometrial cancer (EC) is the most common gynecologic cancer. Unfortunately, its prognosis remains poor due to limited screening and treatment options. To address this issue, the present study evaluated the predictive value of four immunohistochemical (IHC) indicators for overall survival (OS) and recurrence-free survival (RFS) in patients with EC. A total of 834 patients diagnosed with EC were included at Peking University People's Hospital between January 2006 and December 2020. These patients were randomly divided into training and validation cohorts at a 2:1 ratio, collecting data on clinicopathological information and IHC indicators. A total of 92 combinations of algorithms were assessed using the Leave-One-Out Cross-Validation framework to identify the one with the highest C-index. To estimate the accuracy of the factors and four IHC indicators for predicting both OS and RFS, survival curves and receiver operating characteristic (ROC) curves were used. Independent predictors included estrogen receptor, progesterone receptor, body mass index, P53, FIGO stage, histology, grade, Ki67, ascites and lymph node metastasis. Both the training and validation cohorts exhibited excellent predictive performance for OS and RFS, as demonstrated by ROC curves at 1-year, 3-year and 5-year follow-ups. By introducing a model based solely on clinicopathological information as model 1 and adding four IHC indicators in model 2, a significant improvement was observed in the area under the curve (AUC) values across the entire sample. The AUC value for OS curves increased from 0.765 to 0.872, and the AUC for RFS curves rose from 0.791 to 0.882. Thus, the present study's model effectively predicts patients' probability of OS and RFS using these factors. This prediction capability can guide postoperative treatment plans and follow-up intervals, potentially enhancing long-term survival for patients with EC.

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.

Use of clinical variables for preoperative prediction of lymph node metastasis in endometrial cancer

OBJECTIVE

Endometrial cancer is the most common gynaecological cancer, and most patients are identified during early disease stages. Noninvasive evaluation of lymph node metastasis likely will improve the quality of clinical treatment, for example, by omitting unnecessary lymphadenectomy.

METHODS

The study population comprised 611 patients with endometrial cancer who underwent lymphadenectomy at four types of institutions, comprising seven hospitals in total. We systematically assessed the association of 18 preoperative clinical variables with postoperative lymph node metastasis. We then constructed statistical models for preoperative lymph node metastasis prediction and assessed their performance with a previously proposed system, in which the score was determined by counting the number of high-risk variables among the four predefined ones.

RESULTS

Of the preoperative 18 variables evaluated, 10 were significantly associated with postoperative lymph node metastasis. A logistic regression model achieved an area under the curve of 0.85 in predicting lymph node metastasis; this value is significantly higher than that from the previous system (area under the curve, 0.74). When we set the false-negative rate to ~1%, the new predictive model increased the rate of true negatives to 21%, compared with 6.8% from the previous one. We also provide a spreadsheet-based tool for further evaluation of its ability to predict lymph node metastasis in endometrial cancer.

CONCLUSIONS

Our new lymph node metastasis prediction method, which was based solely on preoperative clinical variables, performed significantly better than the previous method. Although additional evaluation is necessary for its clinical use, our noninvasive system may help improve the clinical treatment of endometrial cancer, complementing minimally invasive sentinel lymph node biopsy.

Nanocarrier-based targeting of metabolic pathways for endometrial cancer: Status and future perspectives

Cancer is the second-most lethal global disease, as per health reports, and is responsible for around 70% of deaths in low- and middle-income countries. Endometrial cancer is one of the emerging malignancies and has been predicted as a public health challenge for the future. Insulin resistance, obesity, and diabetes mellitus are the key metabolic factors that promote risks for the development of endometrial cancer. Various signaling pathways and associated genes are involved in the genesis of endometrial cancer, and any mutation or deletion in such related factors leads to the induction of endometrial cancer. The conventional way of drug delivery has been used for ages but is associated with poor management of cancer due to non-targeting of the endometrial cancer cells, low efficacy of the therapy, and toxicity issues as well. In this context, nanocarrier-based therapy for the management of endometrial cancer is an effective alternate choice that overcomes the problems associated with conventional therapy. In this review article, we highlighted the nanocarrier-based targeting of endometrial cancer, with a special focus on targeting various metabolic signaling pathways. Furthermore, the future perspectives of nanocarrier-based targeting of metabolic pathways in endometrial cancer were also underpinned. It is concluded that targeting metabolic signaling pathways in endometrial cancer via nanocarrier scaffolds is the future of pharmaceutical design for the significant management and treatment of endometrial cancer.