A Novel Predictive Tool for Discriminating Endometriosis Associated Ovarian Cancer from Ovarian Endometrioma: The R2 Predictive Index

Overexpression of FOS enhances the malignant potential of eutopic endometrial stromal cells in patients with endometriosis‑associated ovarian cancer

Endometrial cysts of the ovary (EMC) may develop into endometriosis (EM)‑associated ovarian cancer over time (EAOC), but the pathogenesis of this disease has not been determined. In the present study, RNA sequencing was used to identify a feasible biomarker, and the molecular function of this biomarker in eutopic endometrial cells from EAOC and EMC patients was evaluated to explore the potential mechanism related to EAOC and orthotopic endometrial tissue. RNA sequencing was performed on 5 EAOC and 4 EMC tissue samples, and differential expression analysis was performed. To identify biomarkers, differentially expressed genes were subjected to protein‑protein interaction network design, Gene Ontology pathway enrichment, and Gene Set Enrichment Analysis pathway enrichment. The expression of FOS in the endometrium was detected via immunohistochemical staining. Lv‑FOS was utilized to upregulate FOS in human endometrial stromal cells (hEnSCs), and Cell Counting Kit‑8, colony formation and scratch assays were performed to assess cell viability, proliferation and migration, respectively. Western blotting was used to determine protein expression. In total, 249 genes, including FOS, were differentially expressed. Pathway enrichment analysis demonstrated that the MAPK, AP‑1, ERK and other signaling pathways were involved in the EMC‑to‑EAOC conversion. FOS upregulation in hEnSCs increased cell viability, proliferation and migration. Western blot results revealed that after FOS expression was inhibited, P21 expression was upregulated, and CDK4, Cyclin D1, p‑Stat3, MMP2 and MMP9 expression was downregulated. In conclusion, mitosis and the cell cycle were found to affect the progression of EMC to EAOC. The expression of FOS, a novel biomarker, was identified to enhance the malignant potential of eutopic endometrial stromal cells in patients with EM‑associated ovarian cancer.

A novel prognostic score of recurrence for endometrial cancer patients with staging surgery

BACKGROUND

Recently, there have been an increasing number of reports on the association between inflammatory markers and the prognosis of malignant tumors. However, the current inflammatory indicators have limited accuracy. We aimed to develop a new scoring system for predicting endometrial cancer recurrence using inflammatory markers, tumor markers, and histological diagnoses.

METHODS

Patients with primary, previously untreated, and suspected endometrial cancer who underwent surgery at the Nara Medical University Hospital between January 2007 and December 2020 were included and followed up until March 2024. Items were divided into positive and negative using scores based on cutoff values and placed into the new scoring system, the endometrial tumor-related (ETR) score.

RESULTS

We found that positive postoperative histological examination of lymph node metastasis and myometrial invasion, high levels of carcinoembryonic antigen and D-dimer in preoperative blood tests, and a large difference in preoperative and postoperative white blood cell counts were significantly associated with recurrence. The sensitivity and specificity of recurrence prediction using the ETR score were not inferior to those using the International Federation of Gynecology and Obstetrics staging system, which is considered the best prognostic factor for survival.

CONCLUSIONS

The ETR score is a significant prognostic marker of recurrence in patients who have undergone staging surgery, with complete surgical tumor removal.

Research progress on correlative prediction factors and prediction models of endometriosis associated ovarian carcinoma

BACKGROUND

Endometriosis is a common benign disease in women of childbearing age, with a malignant change rate of about 1%. Endometriosis associated ovarian cancer (EAOC), which usually occurs in the ovaries, is a serious threat to women's health. Early identification of high-risk groups of EMs malignant transformation is of great significance for the prevention and treatment of EAOC. However, there is still a lack of specific and sensitive prediction factors. In recent years, scholars at home and abroad have used traditional statistical methods and machine learning to explore EAOC related prediction factors and prediction models. This paper mainly reviews and evaluates the diagnosis and prediction model of EAOC.

METHODS

Studies were identified by searching the CNKI, PubMed and Web of Science Core Collection, (WOSCC) till 2023, Data which met the inclusion criteria of clinical studies were evaluated about the quality. This paper analyzes and summarizes the prediction factors and prediction models in the literature.

RESULTS

After screening, 7 relevant studies were finally obtained. Prediction factors included: age, menstruation, menopausal status, course of disease, infertility associated with endometriosis, history of single estrogen use during menopause, serological indexes: human epididymis protein 4, carbohydrate antigen 125(CA125), ovarian malignancy risk algorithm, indications for ultrasound examination: cyst shape, structure and blood flow signal, etc. Prediction models: Alignment diagram, Multivariate logistic regression model, Gail model, Gradient Boosting Decision Tree and Lasso-logistics regression.

CONCLUSION

Related models were in good agreement with the actual situation, and have good sensitivity and specificity. The relevant prediction factors and prediction models were summarized to provide reference and new thinking for the research of prediction models in the field of EAOC, in order to develop standardized long-term management strategies for high-risk groups of EAOC and realize the advance of the diagnosis threshold of patients with EAOC.

Histologic Subtypes in Endometriosis-Associated Ovarian Cancer and Ovarian Cancer Arising in Endometriosis: A Systematic Review and Meta-Analysis

The definition of the association between ovarian cancer and endometriosis was first reported by Sampson in 1925. He identified the following criteria: (a) clear evidence of endometriosis in proximity to the tumour, (b) exclusion of a metastatic tumour to the ovary, (c) presence of tissue resembling endometrial stroma surrounding epithelial glands. The naming of these cancers is "endometriosis-associated ovarian cancer" (EAOC). Scott proposed an additional stringent criterion: evidence of histological transition from endometriosis to cancer is to define "ovarian cancer arising in endometriosis" (OCAE). The aim of this systematic review is to analyse the distribution of different ovarian cancer histotypes in EAOC and OCAE to understand their similarities and differences. A total of 31 studies were included. Four studies added data for both EAOC and OCAE. Twenty-three studies were selected for EAOC, with a total of 800 patients, and 12 studies were selected for OCAE, with a total of 375 patients. The results show no significant differences in the distribution of histotypes in the two populations analysed. Clear cell carcinoma (CCC) and endometrioid carcinoma (EC) were the most common subtypes and were less frequent in EAOC compared to OCAE; the odd ratios were 0.58 (0.26-1.29) and 0.65 (0.33-1.26) respectively, although the difference was not statistically significant. The other histotypes were present in small proportions. This analysis shows that the histological profiles of EAOC and OCAE are similar, suggesting a similar aetiopathological mechanism, which requires further research to investigate whether EAOC and OCAE may be in the same way but at different points of the process to malignancy or have different pathways of progression to malignancy.

Malignancy in Abdominal Wall Endometriosis: Is There a Way to Avoid It? A Systematic Review

Background: Malignant-associated abdominal wall endometriosis (AWE) is a rare pathology, likely to occur in 1% of scar endometriosis. The objectives of this study were to update the evidence on tumor degeneration arising from AWE to notify about the clinical characteristics, the different treatments offered to patients and their outcomes. Methods: A comprehensive systematic review of the literature was conducted. PubMed, Embase and Cochrane Library databases were used. Prospero (ID number: CRD42024505274). Results: Out of the 152 studies identified, 63 were included, which involved 73 patients. The main signs and symptoms were a palpable abdominal mass (85.2%) and cyclic pelvic pain (60.6%). The size of the mass varied between 3 and 25 cm. Mean time interval from the first operation to onset of malignant transformation was 20 years. Most common cancerous histological types were clear cell and endometrioid subtypes. Most widely accepted treatment is the surgical resection of local lesions with wide margins combined with adjuvant chemotherapy. The prognosis for endometriosis-associated malignancy in abdominal wall scars is poor, with a five-year survival rate of around 40%. High rates of relapse have been reported. Conclusions: Endometrial implants in the abdominal wall should be considered as preventable complications of gynecological surgeries. Special attention should be paid to women with a history of cesarean section or uterine surgery.

New insights about endometriosis-associated ovarian cancer: pathogenesis, risk factors, prediction and diagnosis and treatment

Previous studies have shown that the risk of malignant transformation of endometriosis in premenopausal women is approximately 1%, significantly impacting the overall well-being and quality of life of affected women. Presently, the diagnostic gold standard for endometriosis-associated ovarian cancer (EAOC) continues to be invasive laparoscopy followed by histological examination. However, the application of this technique is limited due to its high cost, highlighting the importance of identifying a non-invasive diagnostic approach. Therefore, there is a critical need to explore non-invasive diagnostic methods to improve diagnostic precision and optimize clinical outcomes for patients. This review presents a comprehensive survey of the current progress in comprehending the pathogenesis of malignant transformation in endometriosis. Furthermore, it examines the most recent research discoveries concerning the diagnosis of EAOC and emphasizes potential targets for therapeutic intervention. The ultimate objective is to improve prevention, early detection, precise diagnosis, and treatment approaches, thereby optimizing the clinical outcomes for patients.

Derivation and validation of a nomogram based on clinical characteristics to diagnose endometriosis associated ovarian cancer preoperatively

PURPOSE

The preoperative diagnosis of endometriosis associated ovarian cancer (EAOC) remains challenging for lack of effective diagnostic biomarker. We aimed to study clinical characteristics and develop a nomogram for diagnosing EAOC before surgery.

METHODS

A total of 87 patients with EAOC and 348 patients with ovarian endometrioma (OEM) were enrolled in our study. Least absolute shrinkage and selection operator (LASSO) regression and Logistic regression were utilized to select variables and construct the prediction model. The performance of the model was assessed using receiver operating characteristic (ROC) analyses and calibration plots, while decision curve analyses (DCAs) were conducted to assess clinical value. Bootstrap resampling was used to evaluated the stability of the model in the derivation set.

RESULTS

The EAOC patients were older compared to the OEM patients (46.41 ± 9.62 vs. 36.49 ± 8.09 year, P < 0.001) and proportion of postmenopausal women was higher in EAOC group than in the OEM group (34.5 vs. 1.5%, P < 0.001). Our prediction model, which included age at diagnosis, tumor size, cancer antigen (CA) 19-9 and risk of ovarian malignancy algorithm (ROMA), demonstrated an area under the curve (AUC) of 0.858 (95% confidence interval (CI): 0.795-0.920) in the derivation set (N = 304) and an AUC of 0.870 (95% CI: 0.779-0.961) in the validation set (N = 131). The model fitted both the derivation (Hosmer-Lemeshow test (HL) chi-square = 12.600, P = 0.247) and the validation (HL chi-square = 8.210, P = 0.608) sets well.

CONCLUSION

Compared to patients with OEM, those with EAOC exhibited distinct clinical characteristics. Our four-variable prediction model demonstrated excellent performance in both the derivation and validation sets, suggesting its potential to assist with preoperative diagnosis of EAOC.

Clinicopathological characteristics, molecular features and novel diagnostic strategies for the detection of malignant transformation of endometriosis (Review)

Endometriosis is a benign gynecological disease that affects women of reproductive age. Although malignant transformation of endometriosis is rare, physicians must be aware of this due to the high incidence of clear cell carcinoma of the ovary (CCC) in Japan. The most prevalent histological subtype of ovarian cancer is CCC (~70%) followed by endometrioid carcinoma (30%). The present review discusses the clinicopathological and molecular features of endometriosis-associated ovarian cancer (EAOC) as well as prospects for novel diagnostic strategies. Papers published between 2000 and 2022 in the PubMed and Google Scholar databases were included. Contents of the endometriotic cyst fluid may be involved in carcinogenesis, although the underlying mechanisms are largely unknown. Some studies have proposed a possible mechanism wherein excessive hemoglobin, heme and iron could cause an imbalance in intracellular redox homeostasis in endometriotic cells. Combined with DNA damage and mutations, the imbalances may induce the development of EAOC. Endometriotic cells evolve to adapt to the prolonged unfavorable oxidative microenvironmental stress. On the other hand, macrophages enhance the antioxidative defense mechanism and protect endometriotic cells against oxidative damage through intercellular crosstalk and signaling pathways. Therefore, changes in redox signaling, energy metabolism and the tumor immune microenvironment could be the key elements in the malignant transformation of certain endometriotic cell clones. Additionally, non-invasive bioimaging (i.e., magnetic resonance relaxometry) and biomarkers (i.e., tissue factor pathway inhibitor 2) may be promising tools for early-stage detection of the disease. In conclusion, the present review summarizes the latest advancements in research on the biological characteristics and early diagnosis of malignant transformation of endometriosis.

The Endometriotic Neoplasm Algorithm for Risk Assessment (e-NARA) Index Sheds Light on the Discrimination of Endometriosis-Associated Ovarian Cancer from Ovarian Endometrioma

BACKGROUND

Magnetic resonance (MR) relaxometry provides a noninvasive tool to discriminate endometriosis-associated ovarian cancer (EAOC) from ovarian endometrioma (OE) with high accuracy. However, this method has a limitation in discriminating malignancy in clinical use because the R2 value depends on the device manufacturer and repeated imaging is unrealistic. The current study aimed to reassess the diagnostic accuracy of MR relaxometry and investigate a more powerful tool to distinguish EAOC from OE.

METHODS

This retrospective study was conducted at our institution from December, 2012, to May, 2022. A total of 150 patients were included in this study. Patients with benign ovarian tumors (n = 108) mainly received laparoscopic surgery, and cases with suspected malignancy (n = 42) underwent laparotomy. Information from a chart review of the patients' medical records was collected.

RESULTS

A multiple regression analysis revealed that the age, the tumor diameter, and the R2 value were independent malignant predicting factors. The endometriotic neoplasm algorithm for risk assessment (e-NARA) index provided high accuracy (sensitivity, 85.7%; specificity, 87.0%) to discriminate EAOC from OE.

CONCLUSIONS

The e-NARA index is a reliable tool to assess the probability of malignant transformation of endometrioma.

The Comparison of Three Predictive Indexes to Discriminate Malignant Ovarian Tumors from Benign Ovarian Endometrioma: The Characteristics and Efficacy

This study aimed to evaluate the prediction efficacy of malignant transformation of ovarian endometrioma (OE) using the Copenhagen Index (CPH-I), the risk of ovarian malignancy algorithm (ROMA), and the R2 predictive index. This retrospective study was conducted at the Department of Gynecology, Nara Medical University Hospital, from January 2008 to July 2021. A total of 171 patients were included in the study. In the current study, cases were divided into three cohorts: pre-menopausal, post-menopausal, and a combined cohort. Patients with benign ovarian tumor mainly received laparoscopic surgery, and patients with suspected malignant tumors underwent laparotomy. Information from a review chart of the patients’ medical records was collected. In the combined cohort, a multivariate analysis confirmed that the ROMA index, the R2 predictive index, and tumor laterality were extracted as independent factors for predicting malignant tumors (hazard ratio (HR): 222.14, 95% confidence interval (CI): 22.27−2215.50, p < 0.001; HR: 9.80, 95% CI: 2.90−33.13, p < 0.001; HR: 0.15, 95% CI: 0.03−0.75, p = 0.021, respectively). In the pre-menopausal cohort, a multivariate analysis confirmed that the CPH index and the R2 predictive index were extracted as independent factors for predicting malignant tumors (HR: 6.45, 95% CI: 1.47−28.22, p = 0.013; HR: 31.19, 95% CI: 8.48−114.74, p < 0.001, respectively). Moreover, the R2 predictive index was only extracted as an independent factor for predicting borderline tumors (HR: 45.00, 95% CI: 7.43−272.52, p < 0.001) in the combined cohort. In pre-menopausal cases or borderline cases, the R2 predictive index is useful; while, in post-menopausal cases, the ROMA index is better than the other indexes.

Challenges in Diagnosis and Prevention of Iatrogenic Endometriosis as a Long-Term Surgical Complication after C-Section

Endometriosis is a gynecological condition caused by the development of endometrial tissue outside the uterine cavity. Naturally, it commonly occurs at locations such as the ovaries and pelvic peritoneum. However, ectopic endometrial tissue may be discovered outside of the typical sites, suggesting the possibility of iatrogenic seeding after gynecological operations. Based on this hypothesis, we developed a study aiming to establish the root cause of atypical implantation of endometrial foci, as the main end point, and to determine diagnostic features and risk factors for this condition, as a secondary target. The research followed a retrospective design, including a total of 126 patients with endometriosis who met the inclusion criteria. A group of 71 patients with a history of c-section was compared with a control group of patients with endometriosis and no history of c-section. Endometriosis that developed inside or in close proximity to surgical incisions of asymptomatic patients before surgical intervention was defined as iatrogenic endometriosis. Compared with patients who did not have a c-section, the c-section group had significantly more minimally invasive pelvic procedures and multiple adhesions and endometriosis foci at intraoperative look (52.1% vs. 34.5%, respectively 52.1% vs. 29.1%). The most common location for endometriosis lesions in patients with prior c-section was the abdominal wall (42.2% vs. 5.4%), although the size of foci was significantly smaller by size and weight (32.2 mm vs. 34.8 mm, respectively 48.6 g vs. 53.1 g). The abdominal wall endometriosis was significantly associated with minimally invasive pelvic procedures (correlation coefficient = 0.469, p-value = 0.001) and c-section (correlation coefficient = 0.523, p-value = 0.001). A multivariate regression analysis identified prior c-section as an independent risk factor for abdominal wall endometriosis (OR = 1.85, p-value < 0.001). We advocate for strict protocols to be implemented and followed during c-section and minimally invasive procedures involving the pelvic region to ensure minimum spillage of endometrial cells. Further research should be developed to determine the method of abdominal and surgical site irrigation that can significantly reduce the risk of implantation of viable endometrial cells. Understanding all details of iatrogenic endometriosis will lead to the development of non-invasive disease diagnosis and minimally invasive procedures that have the potential to reduce postoperative complications.