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Background: To develop the preoperative prediction of ovarian lesions using regression-based statistics analyses and machine learning methods based on multiple serological biomarkers in China. Methods: 1137 patients with ovarian lesions in Zhujiang Hospital and 518 patients in others hospital in China were randomly assigned to training, test and external validation cohorts. Five machine learning classifiers, including Random Forest (RF), Extreme Gradient Boosting (XGB), Support Vector Classifier (SVC), K-nearest Neighbor (KN), Multi-Layer Perceptron (MLP) and the Lasso-Logistics prediction model (LLRM) were used to derive diagnostic information from 23 predictors. Results: The RF model had a high diagnostic value (AUC = 0.968) in predicting benign and malignant ovarian disease. Age and MLR were also potential diagnostic indicators for predicting ovarian disease except tumor indicators. The RF model well distinguished borderline ovarian tumors (AUC = 0.742). The RFM had a high predictive power to identify ovarian serous adenocarcinoma (AUC = 0.943) and ovarian endometriosis cysts (AUC = 0.914). Conclusions: The RF models can effectively predict adnexal lesions, promising to be adjuncts to the preoperative prediction of ovarian cancer.
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To investigate the efficacy and safety of laparoscopic internal iliac artery temporary occlusion and uterine repair combined with hysteroscopic aspiration in type III cesarean scar pregnancy. 135 cases of cesarean scar pregnancy in Guangzhou Women and Children's Hospital from November 2017 to November 2020 were collected and 32 cases of type III patients were retrospectively analyzed. They were divided into internal iliac artery temporary occlusion (IIATO) group (21 cases), and bilateral uterine artery embolization (UAE) group (11 cases). The general condition, intraoperative bleeding, postoperative complications, and prognosis of the two groups were analyzed. In the IIATO group, the bilateral internal iliac arteries were temporarily blocked with No. 10 silk thread under laparoscopy. The scar pregnancy clearance and repair of the scar were performed after incision. Subsequently, we performed hysteroscopic aspiration. After the operation, the internal iliac artery ligation thread was removed. In the UAE group, the patients were treated with bilateral uterine artery embolization. Laparoscopic uterine scar repair and hysteroscopy aspiration were performed within 24 hours after embolization. There was no significant difference in age, times of pregnancy, times of cesarean section and gestational weeks between the two groups (P>0.05). No significant differences were observed in the diameter of gestational sac or gestational mass and serum human chorionic gonadotropin (ß-hCG) level between the two groups before operation (P>0.05). The operations were successfully completed in 32 patients, and intraoperative blood loss was 67.14±32.78 ml and 71.35±31.56 ml, respectively (P<0.05). The length of hospital stay was 5.14±0.32 day and 4.97±0.21 day, respectively. No peri-procedural bleeding occurred and no secondary surgeries were required. Laparoscopic internal iliac artery temporary occlusion and uterine repair combined with hysteroscopic aspiration is an effective and safe treatment for type III cesarean scar pregnancy, with less postoperative complications and better protection of fertility function for patients.
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Metabolic dysregulation in the tumor microenvironment has significant impact on immune infiltration and immune responses. However, interaction between immunity and metabolism in the ovarian microenvironment requires further exploration. We constructed an immunometabolism gene set and ovarian cancer cohort from The Cancer Genome Atlas (TCGA) and classified these into three immunometabolism subtypes. We explored the relationships between immune infiltration and metabolic reprogramming. Additionally, we built risk score and nomogram as prognostic signatures. Three distinctive immunometabolism subtypes were identified with therapeutic and prognostic implications. Subtype 1, the "immune suppressive-glycan metabolism subtype," featured high levels of immunosuppressive cell infiltration and glycan metabolism activation; Subtype 2, the "immune inflamed-amino acid metabolism subtype," showed abundant adaptive immune cell infiltration and amino acid metabolism activation; Subtype 3, the "immune desert-endocrine subtype," was characterized by low immune cell infiltration and upregulation of hormone biosynthesis. Furthermore, we found that epinephrine biosynthesis displayed a significantly negative correlation with MHC molecules, which may result in defective antigen presentation. We proposed immunometabolism subtypes with prognostic implications and provided new perspectives for the ovarian cancer microenvironment.