A major obstacle to improving prognoses in ovarian cancer is the lack of effective screening methods for early detection. Circulating microRNAs (miRNAs) have been recognized as promising biomarkers that could lead to clinical applications. Here, to develop an optimal detection method, we use microarrays to obtain comprehensive miRNA profiles from 4046 serum samples, including 428 patients with ovarian tumors. A diagnostic model based on expression levels of ten miRNAs is constructed in the discovery set. Validation in an independent cohort reveals that the model is very accurate (sensitivity, 0.99; specificity, 1.00), and the diagnostic accuracy is maintained even in early-stage ovarian cancers. Furthermore, we construct two additional models, each using 9–10 serum miRNAs, aimed at discriminating ovarian cancers from the other types of solid tumors or benign ovarian tumors. Our findings provide robust evidence that the serum miRNA profile represents a promising diagnostic biomarker for ovarian cancer.

Advanced ovarian cancers are highly metastatic due to frequent peritoneal dissemination, resulting in dismal prognosis. Here we report the functions of cancer-derived extracellular vesicles (EVs), which are emerging as important mediators of tumour metastasis. The EVs from highly metastatic cells strongly induce metastatic behaviour in moderately metastatic tumours. Notably, the cancer EVs efficiently induce apoptotic cell death in human mesothelial cells in vitro and in vivo, thus resulting in the destruction of the peritoneal mesothelium barrier. Whole transcriptome analysis shows that MMP1 is significantly elevated in mesothelial cells treated with highly metastatic cancer EVs and intact MMP1 mRNAs are selectively packaged in the EVs. Importantly, MMP1 expression in ovarian cancer is tightly correlated with a poor prognosis. Moreover, MMP1 mRNA-carrying EVs exist in the ascites of cancer patients and these EVs also induce apoptosis in mesothelial cells. Our findings elucidate a previously unknown mechanism of peritoneal dissemination via EVs.

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BACKGROUND: This study examined the clinical significance of CCNE1 (Cyclin E1) amplification and assessed whether CCNE1 is a potential therapeutic target in ovarian cancer. METHODS: CCNE1 expression and amplification in ovarian cancer was assessed by immunohistochemistry, fluorescence in situ hybridization and clinical data collected by retrospective chart review. CCNE1 gene knockdown using silencing RNA and a CCNE1 gene transfection system were used to asses CCNE1 function in tissue samples of ovarian cancer. RESULTS: Gene amplification was identified in 18 (20.4%) of 88 ovarian carcinomas. CCNE1 copy number significantly correlated with CCNE1 protein expression (r ¼ 0.522, P < .0001). CCNE1 amplification significantly correlated with shorter disease-free survival and overall survival (P < .001). There were nonsignificant trends between high protein expression and poor disease-free survival (P ¼ .2865) and overall survival (P ¼ .1248). Multivariate analysis showed gene amplification was an independent prognostic factor for disease-free survival and overall survival after standard platinum-taxane chemotherapy (P ¼ .0274, P ¼ .0023). Profound growth inhibition and apoptosis were observed in silencing RNA-treated cancer cells with gene amplification compared with results in cancer cells with CCNE1 moderate expression without gene amplification or with low CCNE1 expression. CCNE1 overexpression stimulated proliferation in ovarian cancer cell lines ES2 and TOV-21G, which have lower endogenous CCNE1 expression. CONCLUSIONS: These findings indicate that CCNE1 overexpression is critical to growth and survival of ovarian cancer tumors with CCNE1 gene amplification. Furthermore, they suggest that CCNE1 silencing RNA-induced phenotypes depend on amplification status of ovarian cancers. Therefore, CCNE1-targeted therapy may benefit ovarian cancer patients with CCNE1 amplification.