Plasma miRNAs as Diagnostic and Prognostic Biomarkers for Ovarian Cancer

1Ovarian cancer is the fifth leading cause of cancer death in women worldwide, and epithelial ovarian cancer (EOC) is the most lethal gynecologic neoplasm. Because EOC is usually asymptomatic and few screening tests are available, almost 70% of women present with advanced-stage (stage III or IV) disease, with 5-year survival rates of less than 30%. In contrast, patients who are diagnosed with stage I disease have a 5-year survival rate of up to 90%, and patients with stage II disease have a 5-year survival rate of up to 70%. Therefore, the early detection of EOC may greatly improve clinical outcomes. Sensitive, non-invasive biomarkers that can facilitate disease detection and staging and predict therapeutic outcome are needed to improve survival rates and determine optimal treatments.

2Carbohydrate antigen-125 (CA-125) is the most frequently used biomarker for ovarian cancer detection, but it is only elevated in approximately 50% of stage I EOCs and 70%–90% of advanced cases. Hence, there is a critical need for novel biomarkers that are more sensitive and specific for detecting EOC when used alone or in combination with CA-125. Recently, microRNAs (miRNAs), a family of small regulatory RNAs, emerged as possible plasma markers for human disease, including cancer, because of their relative stability in the circulation.

3MiRNAs are small, non-protein-encoding RNAs that post-transcriptionally regulate gene expression by suppressing specific target mRNAs,. Specific circulating miRNAs have been associated with different tumor types, including lung cancer,, colon cancer,, prostate cancer, ovarian cancer,, and pancreatic cancer,. Taylor et al. compared the miRNA profiles of tumor-derived exosomes that had been isolated from the serum of ovarian cancer patients with those from matched tumor tissues from the same patients. However, these studies were limited by having small sample sizes and evaluating few clinical factors. The purpose of this study was to identify and validate circulating miRNAs in human plasma for use as diagnostic and prognostic biomarkers in ovarian cancer. We sought to compare these identifid plasma miRNAs with CA-125, especially to increase the sensitivity of EOC detection in patients with normal CA-125 serum levels.

4We designed a multi-stage, retrospective, nested case-control study to determine whether serum miRNA profiles can be used to predict EOC development. All samples were grouped into screening, training, and validation sets (Fig. 1). A total of 560 plasma samples (360 cases and 200 controls) were obtained from Tianjin Medical University Cancer Institute and Hospital (TCIH) and Cancer Center of Nanjing Medical University between July 2007 and June 2010. The cases and controls were well matched for age among the training and validation sets. All EOC patients had been histopathologically diagnosed with primary ovarian cancer. All patients recruited to this study had not received chemotherapy or radiotherapy prior to the blood draws. And all blood samples were obtained before surgery. The International Federation of Gynaecology and Obstetrics (FIGO) staging system was used to stage cases. All patients and controls were genetically unrelated, ethnic Han Chinese women who were permanent residents of the urban area of Tianjin and Nanjing. Controls with cardiovascular, respiratory, digestive, urinary, reproductive, and endocrine diseases were excluded.

5The study protocols were approved by the Tianjin and Nanjing Center review committees. Informed consent was obtained, and all participants were personally interviewed by trained interviewers using a pre-tested questionnaire to obtain information on demographic data, menstrual and reproductive history, lifestyle, environmental exposure, and family history of cancer. After the interview, a 5-ml venous blood sample was collected. Among these cases, 44 matching ovarian tumor tissue samples were obtained from Tianjin center for this study. EOC tumor tissue samples and tissue RNA were obtained from the Tissue Bank Facility of the TCIH, which collects all solid tumor tissues from surgical patients when possible.

6CA-125 levels of plasma samples were acquired from electronic medical records of the two centers. Patients’ follow-up data were acquired, and survival duration was calculated from the date of diagnosis to the date of death or last follow-up in March 2012.

7To detect generalizable miRNA signatures, we pooled serum samples of 10 early-stage cases (stage I), 10 late-stage cases (stage IIIc-IV), and 10 healthy controls, respectively, and analyzed these three pool samples using a TaqMan low-density array (TLDA set 2.0, Applied Biosystems) chip screening in the discovery stage. The TLDA version 2.0 (Sanger miRBase v14 human) included 667 human miRNAs. Microarray data have been deposited in National Center for Biotechnology Information’s (NCBI’s) Gene Expression Omnibus (NCBIGEO GSE50472).

8The miRNAs identified in the screening set were validated using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) on individual plasma samples of 76 EOC patients and 30 normal controls.

9The validation set comprised a two-phase process. Promising associations from the screening and training set were evaluated in the validation phase I set, comprising 134 cases and 70 controls from Tianjin Center. A receiver operating characteristic (ROC) curve-based risk assessment analysis was then performed to determine the discriminating effect of candidate plasma miRNAs. The validation phase II set included samples of 77 EOC cases and 50 normal controls were from Tianjin Center and 73 EOC cases and 50 normal controls were from Nanjing Center.

10Blood was collected in EDTA tubes (BD Biosciences) and processed to isolate plasma. Blood was centrifuged at 1,200 g at ambient temperature for 10 minutes, and supernatant plasma was transferred to a fresh tube and stored at −80°C.

11RNA was isolated from the plasma samples of healthy donors and ovarian cancer patients. In brief, 250 µl of plasma was thawed on ice and spun at 14,000 g at 4°C for 10 minutes to remove lymphocytes. We then lysed 200 µl of supernatant with an equal amount of QIAzol lysis reagent (Qiagen, Shanghai, China). For plasma pools used to screen human ovarian cancer biomarker candidates, we created the pool sample by combining 110 µl of each of 10 samples. The pool was mixed by inversion and spun at 14,000 g for 10 min; 1 ml of supernatant was transferred to a new tube for RNA isolation. For normalization, 5 µl of 25 fmol synthetic Caenorhabditis elegans miRNA cel-miR-39 was added to each denatured sample. Small RNA was isolated using miRNeasy Mini (Qiagen) following the manufacturer’s protocol except that RNA was eluted in 30 µl of pre-heated nuclease-free water. To isolate total RNA from ovarian tumor tissues, the frozen samples were first homogenized in TRIzol reagent (Invitrogen, San Diego, CA) using an Omni-Mixer Homogenizer (Omni International, Kennesaw, GA). Total RNA was isolated using the standard TRIZOL method (Invitrogen), according to the manufacturer’s instructions. The quality of total RNA was verified with a Bioanalyzer 2100 (Agilent Technologies).

12MiRNA expression of the pool sample was profiled using TLDA. In brief, the RNA was reverse transcribed using the TaqMan miRNA reverse transcription kit, and the TaqMan miRNA multiplex RT assays, Human Pool Set. An amount of 9.16 µl of plasma RNA solution was transcribed in 15 µl of RT mixture. The tubes were incubated at 16°C for 30 minutes, followed by 42°C for 30 minutes and 85°C for 5 minutes. The TaqMan PreAmp master mix kit (Applied Biosystems) is intended to increase the quantity of cDNA available for analysis before using the TLDA. The 25 µl reaction mixture consisted of 2.5 µl of undiluted cDNA combined with 12.5 µl of TaqMan PreAmp master mix, 2.5 µl of Megaplex PreAmp primers, and 7.5 µl of nuclease-free water. The pre-amplification step was performed according to the manufacturer’s protocol. The product was diluted by adding 75 µl of nuclease-free water, and 9 µl of the diluted mixture was combined with 450 µl of TaqMan Universal PCR master mix and 441 µl of nuclease-free water. After loading 100 µl of each multiplex pool mixture, the array (TaqMan Human MicroRNA Array Set v2.0) was centrifuged and sealed. Amplification was performed on an Applied Biosystems 7900 HT thermal cycler (Applied Biosystems) using the manufacturer’s recommended cycling conditions. Data were analyzed using RQ Manager Software version 1.2 and 7900 Sequence Detection System 2.4 (Applied Biosystems).

13To determine miRNA levels in plasma samples, we used the ABI miRT-PCR system, with the following conditions: 2.5 µl of enriched small RNAs from plasma samples or 10 ng of total RNA from tissue samples were reverse transcribed using the TaqMan miRNA reverse transcription kit (Applied Biosystems) in 7.5 µl of reaction buffer with the target-specific primers. The tubes were incubated at 16°C for 30 minutes, followed by 42°C for 30 minutes and 85°C for 5 minutes. After priming, a 1∶20 dilution was used as the template for the PCR stage using TaqMan 2× Universal PCR master mix (Applied Biosystems) on an ABI Prism 7900. We measured triplicate wells using a 15-µl final reaction volume and the following cycling conditions: 10 minutes at 95°C, followed by 50 cycles of 95°C for 15 seconds and 60°C for 1 minute. The 7900 Sequence Detection System 2.4 software defaults were used to compute the relative change in expression by the 2−ΔΔCt method with 95% confidence.

14The relative levels of miRNA were quantified using the 2−ΔΔCt method, and the data were analyzed as the log10 of the relative quantity of the target miRNA. The statistical significance was determined using the Wilcoxon signed-rank or t-test between patients and controls. ROC curves were generated to assess the diagnostic accuracy of each candidate miRNA, and the sensitivity and specificity of the optimum cut-off point were defined as those values that maximized the area under the ROC curve (AUC). A stepwise logistic regression model was used to select diagnostic miRNA markers on the basis of the training data set. The correlation between survival (overall survival [OS] and progression free survival [PFS]) and plasma miRNAs was analyzed using the Kaplan-Meier method and log-rank test. A Cox proportional hazards regression analysis was used to determine whether plasma miRNA was an independent prognostic factor for EOC.

15We used the statistical software packages SAS version 9.0 (SAS Institute, Cary, NC) and MedCalc (Mariakerke, Belgium). The graphs were generated with GraphPad Prism 5.0 (GraphPad Software, Inc., La Jolla, CA). All statistical tests were two-sided, and a P value of <0.05 was considered significant.

16We collected 560 plasma samples (360 cases and 200 controls) and associated clinical and demographic data for this study; the cases included 179 serous tumors (49.7%), 86 endometrioid tumors (23.9%), 33 mucinous tumors (9.2%), 15 clear cell tumors (4.2%), and 47 adenocarcinomas, Not Otherwise Specified (NOS) (13.0%). The participants’ characteristics are presented in Table 1 and Table S1. The distributions of most risk factors were generally similar between patients and controls (Table S1). In patients, there was no significant difference in the distribution of FIGO stages, histologic grade, or CA-125 levels between the training and validation groups (Table 1).

17Using the TLDA chip, we screened 667 human miRNAs to find the significantly different miRNA expression levels between cases and controls. To efficiently screen multiple miRNA biomarker candidates, we first generated three pools of plasma aliquots that had been derived from early- and late-stage EOC patients and healthy controls. Compared with the control pool, there were 43 and 50 miRNAs that were differentially expressed in the early-stage and late-stage case pool, respectively. Among these significant miRNAs, there were 30 miRNAs crossed. Thirty differentially expressed plasma miRNAs were identified between EOC patients and healthy controls (Fig. 2A and Table S2).

18In the training set, we used qRT-PCR to detect the aforementioned 30 significant miRNAs in a case-control study that included 76 EOC cases and 30 healthy controls. Nine miRNAs (miR-205, miR-200a, miR-184, miR-34a*, miR-141, miR-483-5p, miR-193b*, let-7e*, and miR-363*) were detected at higher levels in cases than in controls, whereas miR-98 and let-7f were detected at lower levels (illustrated by a volcano plot and heat map, Fig. 2B).

19In the validation phase I set, the expression profiles of 11 candidate miRNAs was further evaluated using the qRT-PCR method in 134 EOC cases and 70 controls. MiR-205 and let-7f had different expression levels between cases and controls. Compared with in controls, plasma miR-205 levels were significantly higher (P = 0.012) (Fig. 2C, left panel) and let-7f levels were significantly lower (P = 1.97×10−10) in EOC patients (Fig. 2D, left panel).

20A ROC analysis was used to evaluate the sensitivity and specificity of the two candidate plasma miRNA markers. The AUC of miR-205 and let-7f were 0.609 (95% CI, 0.538 to 0.677; sensitivity = 30.1%, specificity = 94.2%) (Fig. 2C, right panel) and 0.780 (95% CI, 0.717 to 0.835; sensitivity = 66.9%, specificity = 84.2%), respectively (Fig. 2D, right panel).

21A stepwise logistic regression model was used to estimate the joint power of miR-205 and let-7f at predicting the risk of EOC in the validation phase I set. MiR-205 and let-7f were effective at discriminating cases from controls [Fig. S1A; logit (P = EOC) = −0.610−3.075×let-7f+1.532×miR-205 was used to construct the ROC curve]. The AUC of the miRNA panel (let-7f and miR-205) was 0.831 (95% CI, 0.772 to 0.880; sensitivity = 62.4%, specificity = 92.9%) (Fig. 3A), which was significantly higher than the AUCs of miR-205 (P<0.001) and let-7f (P = 0.008) alone (Fig. S1B).

22The two-miRNA panel also distinguished between early-stage cases (stage I) and controls, with an AUC of 0.895 (95% CI, 0.822 to 0.967; sensitivity = 77.8%, specificity = 90.0%, Fig. 3B). In the validation phase I set, about 89.3% of EOC patients had CA-125 elevation, the other patients failed to be detected by CA-125. The diagnostic accuracy of the miRNA panel was evaluated according to the CA-125 level. In the low CA-125 (<35 U/ml) group (n = 14, 10.7% of all cases, Table 1) in the validation phase I set, the AUC of the miRNA panel was 0.814 (95% CI, 0.700 to 0.929; sensitivity = 68.4%, specificity = 92.9%, Fig. 3C).

23The two-miRNA panel was further evaluated in the validation phase II set of 250 plasma samples (150 EOC patients and 100 healthy controls). The AUC of the miRNA panel was 0.813 (95% CI, 0.759 to 0.860; sensitivity = 71.3%, specificity = 82.0%, Fig. 3D) in all validation phase II samples. The AUC was 0.783 (95% CI, 0.699 to 0.853; sensitivity = 70.0%, specificity = 82.0%, Fig. 3E) in early-stage cases (stage I) and controls, respectively. The diagnostic accuracy of the miRNA panel was then evaluated according to the CA-125 level. In the low CA-125 (<35 U/ml) group (n = 14, 9.3% of cases, Table 1) of validation phase II, the AUC of the miRNA panel was 0.726 (95% CI, 0.634 to 0.805; sensitivity = 64.3%, specificity = 72.0%, Fig. 3F).

24To further determine whether plasma let-7f and miR-205 levels are predictive of prognosis, we performed an analysis of OS and PFS in all patients from the training and validation sets. A Kaplan–Meier survival curves analysis did not reveal an association between let-7f or miR-205 levels and OS (Fig. S2). However, lower plasma let-7f expression was significantly correlated with poor PFS in all patients (P = 0.006, log-rank test) (Fig. 4A), especially in stage III and IV cases (P = 0.002, log-rank test). A multivariate Cox regression analysis demonstrated that plasma let-7f was a significant prognostic indicator of EOC in PFS (HR = 2.07, 95% CI = 1.27–3.37) (Table 2).

25We determined whether the expression of miRNAs in plasma at different stages was correlated with that in matching tumor tissues. We examined 11 significant miRNAs (miR-205, miR-200a, miR-184, miR-34a*, miR-141, miR-483-5p, miR-193b*, let-7e*, miR-363*, miR-98 and let-7f) of training set in matched tumor tissue samples. The comparative analysis revealed that the tumor expression of miR-483-5p, but not let-7f, was strongly correlated with the plasma expression (r = 0.541, P = 1.52×10−4) (Fig. S3A). We also found that miR-483-5p was expressed at higher levels in stage III and IV tumor tissues than in stage I and II (P = 0.048) (Fig. S3B), consistent with the levels in plasma (P = 0.043) (Fig. S3C). MiR-483-5p was expressed at higher levels in plasma in advanced stages (stage III and IV) than in early stages (stage I and II) (Fig. S3C). No other miRNA levels in plasma were correlated with levels in tumor tissues.

26EOC accounts for most ovarian malignancies. Since the discovery of CA-125 in 1981, numerous studies have documented its role as a diagnostic and recurrence tool in EOC patients,. Approximately 80% of EOC patients have CA-125 elevation. CA-125 is useful for monitoring disease, assessing therapy response, and detecting relapse,. However, it performs poorly in detecting the early stages of ovarian cancer development. New diagnostic markers of ovarian cancer are needed for screening. Currently, several circulating miRNAs have been identified for use in different cancer types,,,. In this study, we found that let-7f and miR-205 are highly promising as diagnostic and progressive biomarkers in EOC.

27Using a stringent validation process and a logistic regression model, we demonstrated that the let-7f-miR-205 miRNA panel had high accuracy in EOC diagnosis, especially in patients with stage I disease. Importantly, this panel can be used in low-CA-125 patients to identify early-stage EOC.

28The let-7/miR-98 family was one of the first mammalian miRNAs to be identified. Let-7 was originally observed in the nematode C. elegans, and the expression levels of many let-7-family members have been found to be reduced in various cancers,,,,. Let-7f is involved in physiological and pathological processes, including carcinogenesis. Previous studies have demonstrated that it acts as a tumor suppressor in many cancers, including renal cell carcinoma, papillary thyroid cancer, and gastric cancer. The let-7 miRNA family is selectively secreted into the extracellular environment via exosomes, which may be important in cancer surveillance. A decrease in let-7 in the extracellular environment, such as in plasma, may thus create a cancer- and metastasis-friendly environment. In our study, we found that plasma let-7f can be used as an EOC detection and prognosis biomarker. Compared with healthy controls, ovarian cancer patients have lower levels of plasma let-7f. In EOC patients, these lower levels were also predictive of poor prognosis.

29MiR-205 is a highly conserved miRNA among different species, including humans. The miR-200 family (miR-200a, miR-200b, miR-200c, miR-141, and miR-429) and miR-205 are frequently downregulated in advanced cancer. Studies have shown that by targeting the transcriptional repressors of E-cadherin, ZEB1 and ZEB2, the miR-200 family is involved in epithelial-to-mesenchymal transition (EMT) and tumor invasion. Increased expression of miR-205 has also been observed in endometrial adenocarcinoma, head and neck squamous cell carcinoma cell lines, squamous cell lung carcinoma, and ovarian cancer. By contrast, reduced expression of miR-205 has been reported in melanoma and cancers of the esophagus, kidney, bladder,, breast, and prostate. MiR-205 may function as an oncogene or tumor suppressor gene, depending on cellular context. In our study, plasma miR-205 was expressed at higher levels in EOC patients than in healthy controls. However, there was no difference in miR-205 expression between EOC tumor tissues and adjacent healthy tissues.

30The loss of let-7 in cancer results in reverse embryogenesis and dedifferentiation, and miR-205 has been identified as a powerful regulator of EMT. Recent findings have connected let-7 with stem cell maintenance and suggest a connection between EMT and stem cell formation. The conversion of an epithelial cell to a mesenchymal cell plays a key role in both embryonic development and cancer invasion and metastasis. Cells undergoing EMT lose their epithelial morphological characteristics, reorganize their cytoskeleton, and acquire a motile phenotype through the up- and down-regulation of several molecules, including tight and adherent junction proteins and mesenchymal markers. In ovarian cancer EMT, let-7f and miR-205 participate in the EMT process by regulating their target genes. Circulating levels of let-7f and miR-205 may be a reflection of the EMT process; thus, it is important to investigate their role in regulating the extracellular environment.

31Many studies have demonstrated that circulating miRNAs in blood samples originate from tumor tissues, inflammatory foci, endothelial cell damage, and normal peripheral blood mononuclear cells and platelets. In this study, we analyzed ovarian cancer tissues and found that miR-483-5p expression was correlated with plasma levels. This result suggests that tumor-derived exosomes can explain a small part of the origin of plasma miRNA. In addition, higher miR-483-5p expression was found in advanced EOC than in early EOC, both in tumor tissue and plasma. To our knowledge, this is the first study to find that miR-483-5p may be related to ovarian cancer progression. Recently, serum miR-483-5p was identified as a potential biomarker to detect hepatocellular carcinoma.

32In summary, we identified plasma let-7f and miR-205 as potential biomarkers for ovarian cancer diagnosis, especially for the early detection of EOC. Let-7f may also be a prognostic marker of ovarian cancer. Circulating miRNAs have been found to be stable, specific, and sensitive biomarkers. On the basis of our data, we propose that specific miRNAs that are associated with circulating exosomes are early markers for ovarian cancer and can be used to determine stage, prognosis, and therapy response.