Abstract
Ovarian cancer patients are recognized with poor prognosis. This study aimed to identify microRNAs in plasma for predicting response to treatment and outcome. We have investigated microRNAs in plasma from ovarian cancer patients enrolled in a large multicenter study (ICON7), investigating the effect of adding bevacizumab to standard chemotherapy in patients diagnosed with epithelial ovarian cancer. Patients with different histology, grade, and FIGO stages were included (n = 207) in this study. Screening of 754 unique microRNAs was performed in the discovery phase (n = 91) using TaqMan Low Density Arrays. The results were validated using single assays and RT-qPCR. Low levels of miR-200b, miR-1274A (tRNALys5), and miR-141 were significantly associated with better survival, confirmed with log-rank test in the validation set. The level of miR-1274A (tRNALys5) correlated with outcome was especially pronounced in the high-grade serous tumors. Interestingly, low level of miR-200c was associated with 5-month prolongation of PFS when treated with bevacizumab compared to standard chemotherapy. We found prognostic significance of miR-200b, miR-141, and miR-1274A (tRNALys5) in all histological types, where miR-1274A (tRNALys5) may be a specific marker in high-grade serous tumors. The level of miR-200c may be predictive of effect of treatment with bevacizumab. However, this needs further validation.
Highlights
Chemoresistance is an obstacle for effective treatment of ovarian cancer
We used plasma samples collected from 207 patients with epithelial ovarian cancer
For patients selected for the discovery set, the group with long progression free survival (PFS) had a median survival of 29 months and the group with short PFS had a median PFS of 7.8 months
Summary
Chemoresistance is an obstacle for effective treatment of ovarian cancer. The majority of the ovarian cancer patients are diagnosed at late stage with poor overall survival [1], due to lack of symptoms in early stage. For patients with spread of disease, the survival rate is low with standard chemotherapy [2]. Despite development of new drugs, many patients do not benefit from the treatment with these drugs. Patients responding to given treatment cannot be distinguished from those without response prior to administration. Epithelial ovarian cancer can be divided into 5 histological subtypes: high-grade serous, low-grade serous, mucinous, clear cell, and endometrioid, of which high-grade serous carcinomas are the most common and most studied histological type [2]
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