Diagnosis and treatment of ovarian cancer are based on intraoperative pathology and debulking surgery. The development of a novel molecular tool is significant for rapid intraoperative pathologic diagnosis, which instructs the decision-making on excision surgery and effective chemotherapy. In this work, we represent a DNA aptamer named mApoc46, which is generated from cell-SELEX by targeting patient-derived primary serous ovarian cancer (pSOC) cells. An average dissociation constant (K d) was determined to be 0.15 ± 0.05 μM by flow cytometry. The mApoc46 aptamer displays a robust specificity to pSOC cells. Labeled with FAM, mApoc46 can selectively stain living pSOC cells in 30 min without staining commercial OC cell lines and cell lines associated with other cancers. Interestingly, FAM-mApoc46 displayed superb selectivity toward high-grade serous ovarian cancer (HG-SOC) tissues in frozen sections against low-grade SOC, ovarian borderline tumor, other nonepithelial ovarian tumors, and healthy ovarian tissue. These results lead to a potential application in the identification of OCs’ histological subtypes during operation. In the patient-derived tumor xenograft NCG mice model, Cy5-labeled mApoc46 was found to accumulate at the tumor area and served as an in vivo imaging probe. The mApoc46 probe shows a robust and stable performance to visualize SOC tumors in the body. Therefore, aptamer mApoc46 holds great potential in rapid intraoperative detection, pathological diagnosis, fluorescence image-guided cancer surgery, and targeted drug delivery and therapy.

What are the novel findings of this work?An objective definition for large niche was generated in this study based on the predictive performance of niche parameters for postmenstrual spotting. A large niche was defined as: niche depth ≥ 0.50 cm, residual myometrial thickness ≤ 0.21 cm or ratio of niche depth to adjacent myometrial thickness ≥ 0.56. What are the clinical implications of this work?This study has provided an objective evaluation for a large niche after Cesarean delivery.

Objective: To develop a risk prediction model to identify the high-risk individuals of large niche formation after cesarean section (CS). Design A retrospective study. Setting Women's health research in Anhui, China. Population: Women received CS between Jan 2012 to Jun 2017. Methods: Women were arranged to receive uterine scar examination by transvaginal ultrasonography, and those diagnosed with niche were divided into two groups according to whether they suffer from postmenstrual spotting. The cut-off values of depth, RMT (residual myometrium thickness), and depth/AMT (adjacent myometrium thickness) were chosen to define a large niche. Then, all participants were classified into three groups, including a control, a small niche, and a large niche group. The scores of each variable in the prediction model were calculated by dividing the minimum βcoefficient from the multivariate logistic analysis. Main outcome: Primary outcome was a prediction scoring model for large niche formation. Results: In total, 727 women were recruited in this study, and the large niche was defined as more than 0.50 cm in depth, less than 0.21 cm in RMT, more than 0.56 in depth/AMT. The large niche prediction model included eight variables of age at delivery, retroflexed uterine, meconium-stained amniotic fluid, history of CS, B-Lynch suture, operation duration, premature rupture of membranes and cervical dilatation more than 4 cm. The cut-off value of 5 in this score-based model presented sensitivity and specificity as 67.48% and 90.07% respectively. Conclusions: This score-based risk prediction model could present the risk of large niche formation of individuals after CS.