Circulating small extracellular vesicles microRNAs plus CA-125 for treatment stratification in advanced ovarian cancer.

BACKGROUND: No residual disease (R0 resection) after debulking surgery is the most critical independent prognostic factor for advanced ovarian cancer (AOC). There is an unmet clinical need for selecting primary or interval debulking surgery in AOC patients using existing prediction models. METHODS: RNA sequencing of circulating small extracellular vesicles (sEVs) was used to discover the differential expression microRNAs (DEMs) profile between any residual disease (R0, n = 17) and no residual disease (non-R0, n = 20) in AOC patients. We further analyzed plasma samples of AOC patients collected before surgery or neoadjuvant chemotherapy via TaqMan qRT-PCR. The combined risk model of residual disease was developed by logistic regression analysis based on the discovery-validation sets. RESULTS: Using a comprehensive plasma small extracellular vesicles (sEVs) microRNAs (miRNAs) profile in AOC, we identified and optimized a risk prediction model consisting of plasma sEVs-derived 4-miRNA and CA-125 with better performance in predicting R0 resection. Based on 360 clinical human samples, this model was constructed using least absolute shrinkage and selection operator (LASSO) and logistic regression analysis, and it has favorable calibration and discrimination ability (AUC:0.903; sensitivity:0.897; specificity:0.910; PPV:0.926; NPV:0.871). The quantitative evaluation of Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) suggested that the additional predictive power of the combined model was significantly improved contrasted with CA-125 or 4-miRNA alone (NRI = 0.471, IDI = 0.538, p < 0.001; NRI = 0.122, IDI = 0.185, p < 0.01). CONCLUSION: Overall, we established a reliable, non-invasive, and objective detection method composed of circulating tumor-derived sEVs 4-miRNA plus CA-125 to preoperatively anticipate the high-risk AOC patients of residual disease to optimize clinical therapy.

Chronic stress induces platinum and Niraparib resistance in mouse models of ovarian cancer.

Resistance to platinum and PARP inhibitors represents a major barrier to the long-term survival of ovarian cancer patients. We aim to explore the potential role of chronic stress in drug resistance in ovarian cancer. Leveraging four ovarian cancer with chronic stress (OCCS) mouse models, we explore the therapeutic efficacy of platinum, Niraparib, and Docetaxel treatment in vivo, and compare the efficacy of these anti-tumor drugs in vitro using cell viability assays. Comparing the transcriptional characteristics in RNA-Seq of OCCS mice with public databases, we analyze the molecular mechanism of chronic stress promoting drug resistance in ovarian cancer. We find that chronic stress is positively correlated with platinum-resistant recurrence in ovarian cancer patients. Chronic stress can induce platinum and Niraparib resistance of ovarian cancer, but it does not affect the therapeutic efficacy of Docetaxel treatment in vivo. And the platinum-resistant cell lines are not sensitive to these anti-tumor drugs, which is different from the result in vivo. Then, we identify several gene networks and their constituent genes that are most significantly associated with chronic stress and drug resistance in ovarian cancer, including the glycolysis pathway and DNA damage. This study develops Niraparib and platinum-resistant in vivo models, reflecting the ability of OCCS mice to reproduce different aspects of human ovarian cancer molecular mechanism, and provides a new theoretical basis for overcoming the double drug resistance of ovarian cancer.