Plasma microRNAs as novel biomarkers for endometriosis and endometriosis-associated ovarian cancer

Abstract

Purpose: Endometriosis, a largely benign, chronic inflammatory disease, is an independent risk factor for endometrioid and clear cell epithelial ovarian tumors. We aimed to identify plasma miRNAs that can be used to differentiate patients with endometriosis and ovarian cancer from healthy individuals.

Experimental design: We conducted a two-stage exploratory study to investigate the use of plasma miRNA profiling to differentiate between patients with endometriosis, patients with endometriosis-associated ovarian cancer (EAOC), and healthy individuals. In the first stage, using global profiling of more than 1,000 miRNAs via reverse transcriptase quantitative PCR (RT-qPCR) in a 20-patient initial screening cohort, we identified 23 candidate miRNAs, which are differentially expressed between healthy controls (n = 6), patients with endometriosis (n = 7), and patients with EAOC (n = 7) based on the fold changes. In the second stage, the 23 miRNAs were further tested in an expanded cohort (n = 88) of healthy individuals (n = 20), endometriosis (n = 33), EAOC (n = 14), and serous ovarian cancer cases (SOC; n = 21, included as controls).

Results: We identified three distinct miRNA signatures with reliable differential expression between healthy individuals, patients with endometriosis, and patients with EAOC. When profiled against the control SOC category, our results revealed different miRNAs, suggesting that the identified signatures are reflective of disease-specific pathogenic mechanisms. This was further supported by the fact that the majority of miRNAs differentially expressed in human EAOCs were mirrored in a double transgenic mouse EAOC model.

Conclusion: Our study reports for the first time that distinct plasma miRNA expression patterns may serve as highly specific and sensitive diagnostic biomarkers to discriminate between healthy, endometriosis, and EAOC cases.

Figure 1

Plasma miRNA expression profiles can distinguish different disease categories. A) Unsupervised hierarchical clustering was applied to miRNAs with < 30% missing values in healthy controls, endometriosis, and EAOC samples (n=20, 33, and 14, respectively). Different distance measure and link were explored. Samples are classified into three clusters based on the expression signature of 23 plasma miRNAs. B) Principal component analysis was applied to markers with adjusted p value < 0.2 in either one of the three groups’ pair-wised comparisons. First three components were used for the three-dimensional plot. Norm, healthy controls; Endo, endometriosis.

Figure 2

The leave-one-out cross validation receiver operating characteristic (ROC) curves of Logistic regression model for four groups’ pair-wised comparisons are plotted based on the top three markers. Area under curve (AUC) is also provided. SN, sensitivity; SP, specificity.

Figure 3

Increased expression of plasma miRNAs along with the progression of diseases from endometriosis to EAOC, but not in SOC samples. The eight miRNAs are derived from shared top 10 most differentially expressed miRNAs in both endometriosis and EAOC samples compared to healthy controls. y-axis, log₂ of folder changes of plasma miRNA expression (log₂(FC)). Norm, healthy controls; Serous, SOC; Endo, endometriosis.

Figure 4

The plasma miRNA expression signature that differentiates healthy controls from EAOC patients can be detected in a mouse endometrioid ovarian cancer model. A) Left panel shows ovarian tumor at the Ad-Cre injected site (arrow), but no tumor formation seen on non-injected left ovary. Middle panel is 10X HE staining of a cross section of mouse ovarian tumor with ovary (Ov), oviduct (Od), and ovarian tumor (OvT). Right panel shows magnified image of ovarian tumor with endometrioid histology (40X). B) Expression of orthologous miRNAs in healthy mice (n=5) and mice with EAOC (n=6). Four out of the five miRNAs are significantly upregulated in most of the mice with EAOC as compared to normal (p = 0.00009, 0.000433, 0.000209, and 0.00014 for miR-16, 21, 15b, and 195, respectively; student’s t-test), similar to the profiles in human EAOC samples. miR-191 did not reach statistical significance, although there is also a trend that expression of plasma miR-191 is elevated in EAOC mice compared to that of in normal mice. Equal amount of RNA extracted from mouse serum was used for RT and qPCR. The raw CT values were plotted because currently there is no consensus on endogenous plasma miRNA in mouse that can be used for normalization. C, mice with EAOC tumors; N, normal control mice.

Figure 5

NanoString analysis reveals very low correlation of miRNA expression between matching tissue and plasma of EAOC and endometriosis patients. Left panel, comparison of three matched endometriosis tissue and plasma samples; Right panel, comparison of three matched EAOC tissue and plasma samples. The NanoString data were normalized using the nSolver software. x-axis, copy number of miRNAs in tissue samples; y-axis, copy number of miRNAs in plasma samples. Endo, endometriosis.