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.

Integrated analysis of the M2 macrophage-related signature associated with prognosis in ovarian cancer.

Background: M2 macrophages play an important role in cancer development. However, the underlying biological fator affecting M2 macrophages infiltration in ovarian cancer (OV) has not been elucidated. Methods: R software v 4.0.0 was used for all the analysis. The expression profile and clinical information of OV patients enrolled in this study were all downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Results: The CIBERSORT algorithm was used to quantify the M2 macrophage infiltration in OV tissue, which was found a risk factor for patients survival. Based on the limma package, a total of 196 DEGs were identified between OV patients with high and low M2 macrophage infiltration, which were defined as M2 macrophages related genes. Finally, the genes PTGFR, LILRA2 and KCNA1 were identified for prognosis model construction, which showed a great prediction efficiency in both training and validation cohorts (Training cohort, 1-year AUC = 0.661, 3-year AUC = 0.682, 8-year AUC = 0.846; Validation cohort, 1-year AUC = 0.642, 3-year AUC = 0.716, 5-year AUC = 0.741). Clinical correlation showed that the riskscore was associated with the worse clinical features. Pathway enrichment analysis showed that in high risk patients, the pathway of epithelial-mesenchymal transition (EMT), TNF-α signaling via NFKB, IL2/STAT5 signaling, apical junction, inflammatory response, KRAS signaling, myogenesis were activated. Moreover, we found that the PTGFR, LILRA2 and KCNA1 were all positively correlated with M2 macrophage infiltration and PTGFR was significantly associated with the pathway of autophagy regulation. Moreover, we found that the low risk patients might be more sensitive to cisplatin, while high risk patient might be more sensitive to axitinib, bexarotene, bortezomib, nilotinib, pazopanib. Conclusions: In this study, we identified the genes associated with M2 macrophage infiltration and developed a model that could effectively predict the prognosis of OV patients.

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.

A phase II study of apatinib in patients with recurrent epithelial ovarian cancer.

OBJECTIVE: Antiangiogenic treatments have been implicated to play a major role in epithelial ovarian cancer (EOC). Apatinib, a novel oral antiangiogenic agent targeting vascular endothelial growth factor receptor (VEGFR2), is currently being studied in different tumor types and is already used in gastric adenocarcinoma. This study was performed to assess the efficacy and safety of apatinib in patients with recurrent, pretreated EOC. PATIENTS AND METHODS: Patients with recurrent, platinum-resistant, pre-treated EOC who failed available standard chemotherapy were enrolled. Apatinib was administered as 500mg daily. Primary objective is the overall response rate (ORR) according to MASS criteria. Secondary objectives are progression free survival (PFS), overall survival (OS), disease control rate (DCR), safety and tolerability. The treatment duration is until disease progression or intolerability of apatinib. RESULTS: 29 eligible patients were enrolled in this multicenter, open-label, single arm study and received apatinib for a median of 36.8weeks (range 13-64.8weeks). Median follow-up time was 12months. 28 patients were eligible for efficacy analysis. ORR is 41.4% (95% confidence interval (CI), 23.3%-59.4%). DCR is 68.9% (95% CI, 52.1%-85.8%). Median PFS is 5.1months (95% CI, 3.8m-6.5m). Median OS is 14.5months (95% CI, 12.4m-16.4m). The most common treatment-related adverse events (AEs) were hand-foot syndrome (51.7%), hypertension (34.6%), nausea and vomiting (31.0%). 3 patients had no significant toxicity. 9 patients experienced grade 3 treatment-related AEs. CONCLUSIONS: Apatinib 500mg daily p.o. is a feasible treatment in patients with recurrent, platinum-resistant, pretreated EOC. Multi-center prospective studies enrolling more patients are needed.