Aberrant DNA methylation and histone modification are associated with an increased risk of reproductive disorders such as endometriosis. However, a cause-effect relationship between epigenetic mechanisms and endometriosis development has not been fully determined. This review provides current information based on oxidative stress in epigenetic modification in endometriosis. This article reviews the English-language literature on epigenetics, DNA methylation, histone modification, and oxidative stress associated with endometriosis in an effort to identify epigenetic modification that causes a predisposition to endometriosis. Oxidative stress, secondary to the influx of hemoglobin, heme, and iron during retrograde menstruation, is involved in the expression of CpG demethylases, ten-eleven translocation, and jumonji (JMJ). Ten-eleven translocation and JMJ recognize a wide range of endogenous DNA methyltransferases (DNMTs). The increased expression levels of DNMTs may be involved in the subsequent downregulation of the decidualization-related genes. This review supports the hypothesis that there are at least 2 distinct phases of epigenetic modification in endometriosis: the initial wave of iron-induced oxidative stress would be followed by the second big wave of epigenetic modulation of endometriosis susceptibility genes. We summarize the recent advances in our understanding of the underlying epigenetic mechanisms focusing on oxidative stress in endometriosis.
Tissue factor pathway inhibitor 2 (TFPI2) is a serodiagnostic marker for epithelial ovarian cancer (EOC) and is the primary inhibitor of the extrinsic coagulation pathway. The present study assessed the diagnostic performance of TFPI2 for detecting venous thromboembolism (VTE) in patients with EOC and positive D-dimer results (>1.0 µg/ml). First, the clinical data of 81 patients with EOC admitted to Nara Medical University Hospital between January 2008 and December 2015 were collected. Also, 25 patients with VTE and 56 patients without VTE were included. Receiver-operating characteristic (ROC) curve analyses were performed to determine the diagnostic efficacy of TFPI2 in discriminating patients with VTE from those without VTE. Serum TFPI2 levels in patients with VTE were significantly higher than in non-VTE patients (median, 472.2 vs. 279.1 pg/ml, P<0.001). Using the Youden index, the optimal cutoff value for the TFPI2 level was set at 398.9 pg/ml. Furthermore, the sensitivity, specificity, positive predictive value and negative predictive value of TFPI2 for diagnosing VTE were 64.0, 80.4, 59.3 and 83.3%, respectively. Additionally, 80.4% of patients with TFPI2 levels <398.9 pg/ml were VTE-negative. ROC analysis demonstrated that the area under the curve for TFPI2 was 0.729 (95% confidence interval, 0.614-0.844). Conclusively, TFPI2 may distinguish patients with VTE from those without VTE among patients with EOC and positive D-dimer results.
<b><i>Objectives:</i></b> Patients with asymptomatic venous thromboembolism (VTE) are associated with an increased risk of pulmonary thromboembolism events. However, due to low specificity and high false-positive rates, D-dimer testing cannot be used alone to diagnose VTE. Tissue factor pathway inhibitor 2 (TFPI2), a new serodiagnostic marker for ovarian cancer, plays a role in blood coagulation system regulation. We hypothesized that combining D-dimer and TFPI2 would improve its utility in diagnosing VTE. This study aimed to look into the clinical utility of serum D-dimer and TFPI2 levels in detecting asymptomatic VTE in patients with epithelial ovarian cancer (EOC). <b><i>Design:</i></b> From January 2008 to December 2015, researchers at Nara Medical University Hospital’s Department of Gynecology conducted a single-center retrospective study. The receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic value of preoperative D-dimer, TFPI2, and D-dimer combined with TFPI2 in distinguishing VTE patients from those who did not have VTE. <b><i>Participants:</i></b> This study included 122 patients with EOC who met the inclusion and exclusion criteria out of 223 admitted to the hospital with EOC. The patients were divided into two groups: VTE (<i>n</i> = 25) and non-VTE (<i>n</i> = 97). <b><i>Results:</i></b> There were significant differences in D-dimer, TFPI2, and CA125 levels and residual tumor between the VTE and non-VTE groups. The D-dimer level was found to be significantly related to age, body mass index, VTE, massive ascites, residual tumor, histology, and Federation of Gynecology and Obstetrics stage, whereas the TFPI2 level was only related to VTE. Multivariate analysis revealed that D-dimer (the optimal cutoff value, 3.5 μg/mL) and TFPI2 (the optimal cutoff value, 400 pg/mL) are independent risk factors for preoperative VTE. ROC analysis revealed that the area under the curve was 0.8266 for D-dimer, 0.7963 for TFPI2, and 0.8495 for the combination of D-dimer and TFPI2. When compared to the D-dimer test alone, the combination of D-dimer and TFPI2 had higher specificity (77.3–96.9%) and positive predictive value (48.8–81.2%) for the diagnosis of VTE. <b><i>Limitations:</i></b> This is a single-center retrospective study. <b><i>Conclusion:</i></b> The combination of D-dimer and TFPI2 may be useful to safely exclude VTE and select patients at high risk of VTE.
Background: Magnetic resonance (MR) relaxometry provides a noninvasive tool to discriminate between ovarian endometrioma (OE) and endometriosis-associated ovarian cancer (EAOC), with a sensitivity and specificity of 86% and 94%, respectively. MRI models that can measure R2 values are limited, and the R2 values differ between MRI models. This study aims to extract the factors contributing to the R2 value, and to make a formula for estimating the R2 values, and to assess whether the R2 predictive index calculated by the formula could discriminate EAOC from OE. Methods: This retrospective study was conducted at our institution from November 2012 to February 2019. A total of 247 patients were included in this study. Patients with benign ovarian tumors mainly received laparoscopic surgery, and the patients suspected of having malignant tumors underwent laparotomy. Information from a chart review of the patients’ medical records was collected. Results: In the investigative cohort, among potential factors correlated with the R2 value, multiple regression analyses revealed that tumor diameter and CEA could predict the R2 value. In the validation cohort, multivariate analysis confirmed that age, CRP, and the R2 predictive index were the independent factors. Conclusions: The R2 predictive index is useful and valuable to the detection of the malignant transformation of endometrioma.
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.
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