Study Of Biomarker Screening And Validation Of Plasma MicroRNAs For Ovarian Cancer

ObjectiveOvarian cancer is the fifth leading cause of cancer death in women worldwide.While the survival rates of women with early stage ovarian cancer are high,most cases are diagnosed late.Due to asymptomatic development and few screening options,almost 70%of women present at late stages of carcinogenesis.Sensitive,non-invasive biomarkers that can facilitate disease detection,staging and prediction of therapeutic outcome are highly desirable to improve survival rate and help to determine optimized treatment for ovarian cancer.The small non-coding RNAs,microRNAs(miRNAs),have recently been identified as critical regulators for various diseases including cancer and may represent a novel class of cancer biomarkers.The purpose of this study was to identify and validate circulating microRNAs in human plasma for use as such biomarkers in ovarian cancer.MethodsTaqMan Low Density Array was used to screen the plasma biomarker for diagnosis and prognosis in ovarian cancer,and then,real-time PCR assay was used for the validation.By the case-control study and detailed statistical analysis,we found a group of ovarian cancer plasma biomarkers.We evaluated the diagnosis value for ovarian cancer through comparing the sensitivity and specificity of the miRNAs candidate.Kaplan-Meier curves and Cox regression analysis were used to evaluate the relationship between the expression of miRNAs and survival.Finally we established the multiple index model used for diagnosis and prognosis in ovarian cancer.Results1.We scan the circulating plasma miRNAs by TaqMan Low Density Array,then identify and validated 30 markers in plasma samples among 113 cases and 30 controls by real-time PCR assay.2.We found that compared with normal,there are 10 miRNAs(miR-205,miR-200a,miR-184,miR-34a*,miR-141,miR-483-5p,miR-193b*,let-7e*,miR-363*,miR-770-5p)expressed higher in ovarian cancer group,while the miR-98 and let-7f have the lower levels in ovarian cancer.3.Kaplan-Meier survival curves showed that miR-98 low expression correlated with poor prognosis in disease free period,miR-141 and miR-573 high expression correlated with poor prognosis in early stages,miR-21*and miR-643 high expression correlated with poor prognosis in late stages.4.Logistic regression model was built up with 7 miRNAs,which have high sensitivity and specificity,for the diagnosis of ovarian cancer.Regression equation is logitP = 22.9879-1.235 ×miR34a*+ 1.122 ×let7f-0.366 ×miR141-1.542 ×miR200a-0.347 ×miR205-0.008 ×miR483-5p + 1.798 ×miR98,and the area of receiver operating characteristic curve(ROC)is 0.974(95%CI:0.923-0.995,P<0.0001).Conclusion1.TaqMan Low Density Array,which is used to analyze the plasma miRNAs expression,was proved to be simple and feasible.2.Plasma miRNAs may become the biomarker for the diagnosis of ovarian cancer,which has a lot of potential applications.3.As the biomarker for the prognosis of ovarian cancer,plasma miRNAs may provide the prediction of the survival.4.Combination of these identified miRNAs and CA-125,a widely used marker for ovarian cancer,may further improve the accuracy of detection.