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Identification of Circular RNAs as a Novel Biomarker for Ovarian Endometriosis.

Byline: Xiao-Xuan. Xu, Shuang-Zheng. Jia, Yi. Dai, Jun-Ji. Zhang, Xiao-Yan. Li, Jing-Hua. Shi, Jin-Hua. Leng, Jing-He. Lang

Background: Endometriosis is a challenging disease with symptoms such as dysmenorrhea and infertility. However, its etiology is still vague and there is still no effective markers or treatment. This study aimed to profile the circular RNAs (circRNAs) expressed in eutopic endometrium from patients with ovarian endometriosis and explore potential clues to the pathogenesis of endometriosis, providing an evidence for clinical diagnosis and treatment. Methods: A total of 63 clinical samples, including control endometrium (n = 22) and eutopic endometrium (n = 41), were collected from Peking Union Medical College Hospital between May 1, 2016, and December 31, 2016. Of them, four samples in each group were used for circRNA microarray. Then, four upregulated circRNAs were screened out for quantitative real-time polymerase chain reaction (qRT-PCR) validation. After that, bioinformatics analysis was performed to predict miRNAs targeted by validated circRNAs and investigate the circRNA-miRNA-mRNA interactions. Results: Among 88 differentially expressed circRNAs, 11 were upregulated and 77 were downregulated in eutopic endometrium of patients with endometriosis. qRT-PCR validation results for two upregulated circRNAs (circ_0004712 and circ_0002198) matched the microarray results. The area under the receiver operating characteristic curve of circ_0002198 for distinguishing ovarian endometriosis was 0.846 (95% confidence interval [CI]: 0.752-0.939; P < 0.001) while that of circ_0004712 was 0.704 (95% CI: 0.571-0.837; P = 0.008). On the basis of target prediction, we depicted the molecular interactions between the identified circRNAs and their dominant target miRNAs, as well as constructed a circRNA-miRNA-mRNA network. Conclusions: This study provides evidence that circRNAs are differentially expressed between eutopic and normal endometrium, which suggests that circRNAs are candidate factors in the activation of endometriosis. circ_0002198 and circ_0004712 may be potential novel biomarkers for the diagnosis of ovarian endometriosis.


Endometriosis is considered as a challenging disorder. Over 176 million women worldwide have been tormented by endometriosis associated pain and infertility, which severely affects their quality of life.[1],[2] Unfortunately, there are still no specific markers and therapies. The essential reason for such adversity is due to the elusive pathogenesis. It is to date widely assumed that ectopic lesions arise through retrograde endometrial fragments during menstruation. Not all the women suffered endometriosis despite most women undergoing retrograde menstruation. The affected women may have certain susceptible factors, which partially comes down to the eutopic endometrium.[3]

Evidences have indicated that gene expression level in eutopic endometrium of endometriosis is aberrantly altered by comparison with control endometrium.[4],[5] These alterations of eutopic endometrium might be the source of the pathogenesis of endometriosis, which keep endometrial debris easier alive in the ectopic site. Recently, emerging evidences reveal that circular RNAs (circRNAs) are involved in regulating gene expression as competitive endogenous RNAs (ceRNAs).[6],[7],[8] Moreover, circRNAs are characterized by covalently linked terminals and high stability as well as abundant expression level.[9],[10] All abovementioned characteristics make circRNAs become evaluate indicators for diagnosis, prognosis, and therapeutic-response prediction. However, the relationship between circRNAs and endometriosis is unknown.

Given their pivotal biological roles, we investigated and identified dysregulated circRNAs in eutopic endometrium to offering new idea for diagnosis and treatment.


Ethical approval

This study was approved by the Institutional Review Board and Hospital Local Ethics Committee (No. JS-875). All participants provided informed consent.

Study population

A total of 63 clinical samples were collected at the Department of Obstetrics and Gynecology of Peking Union Medical College Hospital between May 1, 2016, and December 31, 2016. Eutopic endometrium samples were collected from 41 women who underwent hysteroscopic and laparoscopic surgery for ovarian endometriosis (22-46 years old; proliferative phase: n = 28; secretory phase: n = 13; American Fertility Society [AFS] Stage III-IV). Tissue samples of control endometrium were acquired from another 22 women without endometriosis who underwent hysteroscopy and laparoscopy for other benign ovarian cysts, infertility or uterine septum (no endometriosis, 25-43 years old; proliferative phase: n = 16; secretory phase: n = 6), similarly with a previous study.[11] All patients met the criteria as follows: regular menstruation (25-32 days), no hormonotherapy for at least 6 months, and histopathology confirmation. All obtained samples were excluded from abnormalities of endometrium by the pathological diagnosis, and proliferative and secretory endometrium phases were distinguished by hematoxylin and eosin staining. Tissue collection and storage were conducted as described previously.[12] Four samples for each group were randomly selected for a microarray analysis. Besides, all the samples were validated by quantitative real-time polymerase chain reaction (qRT-PCR).

Total RNA isolation and quality control

Total RNA was isolated with TRIzol reagent (Invitrogen Life Technologies, Carlsbad, CA, USA) according to the manufacturer's protocol. RNA quantity and quality were measured using a NanoDrop ND-1000 (Thermo Fisher Scientific, Wilmington, DE, USA). RNA integrity and genomic DNA contamination were assessed by denaturing agarose gel electrophoresis.

Circular RNA microarray analysis

The Arraystar Human circRNA Array 8 x 15 K V2 Microarray (Arraystar, Rockville, MD, USA) contains 15,000 probes for 13,617 human circRNAs, all of which have been confirmed by Jeck et al .,[10] Salzman et al .,[13] Memczak et al .,[14] Zhang et al .,[15] Zhang et al .,[16] Guo et al .,[17] and You et al .[18] Total RNA was first digested with Rnase R (Epicentre, Madison, WI, USA) to remove linear RNAs and enrich for circRNAs. Then, the enriched circRNA was amplified and transcribed into fluorescent complementary RNA, utilizing random primers according to the Arraystar Super RNA Labeling protocol (Arraystar). After hybridization and washing, processed slides were scanned using an Agilent Scanner G2505C (Agilent Technology, Santa Clara, CA, USA). Thereafter, Agilent Feature Extraction software (version, Agilent Technology, Santa Clara, CA, USA) was utilized to analyze acquired array images. Quantile normalization and subsequent data were processed using the R software package (version 3.3.1; R Foundation Inc. Vienna, Austria).

Quantitative real-time polymerase chain reaction validation

During the qRT-PCR validation stage, we recruited 41 endometria from patients with endometriosis and 22 normal endometria for control. Total isolated RNA was reversely transcribed using SuperScript III Reverse Transcriptase (Invitrogen Life Technologies). Subsequently, qRT-PCR was performed by ViiA 7 RT-PCR System (Applied Biosystems, Foster City, CA, USA) in a 10-[micro]l reaction volume, including 5-[micro]l 2 x PCR Master Mix (Arraystar), 0.5 [micro]l/10 [micro]mol/L forward/reverse primers, 2 [micro]l cDNA, and 2 [micro]l RNAase-free H[sub]2O. The cycling program was initiated from 95[degrees]C for 10 min, followed by 40 cycles of 95[degrees]C for 10 s and 60[degrees]C for 60 s. Divergent primers were designed and optimized for circRNAs. [Supplementary Table 1 [SUPPORTING:1]] listed all the PCR primers, the specificity of which was verified by a single-peak on the melting curve. The threshold cycle method (2−??CT) was used to calculate relative expression levels, which were normalized to [sz]-actin levels.

Bioinformatics analysis

To further elucidate the role of circRNAs in endometriosis, we first used the Arraystar target prediction software based on TargetScan [19] and miRanda [20] to predict the targeted miRNAs of each circRNA, which described interactions between circRNAs and miRNAs. According to the miRNA support vector regression (mirSVR) algorithm, we ranked the top five predicted miRNA targets for each circRNA. Then, we used TargetScan and miRDB to predict the related target genes according to the miRNAs targeted by circRNAs. Finally, the interaction network was depicted using the validated circRNAs and predicted miRNAs/mRNAs, preliminarily accounting for interactions of circRNAs-miRNAs-mRNAs in pathogenesis of endometriosis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses further annotated the function and signaling pathways of these genes.

Statistical analysis

Data were first explored by the tests of normality. If the normal distribution was satisfied, Student's t -tests was used; otherwise, nonparametric Mann-Whitney U -test was used. The thresholds for differentially expressed circRNAs were expressed as an absolute value of fold change (FC) >2 (EuE = 1) and P < 0.05. Above statistical analyses were processed with R software version 3.3.1 and GraphPad Prism 5 (GraphPad Software, La Jolla, CA, USA).


Clinical characteristics of the participants

In the study, a total of 63 endometrial biopsies were obtained from women with laparoscopically and histopathologically proven presence ( n = 41) or absence ( n = 22) of endometriosis. The clinical characteristics of the participants were presented in [Supplementary Table 2 [SUPPORTING:2]] and [Supplementary Table 3 [SUPPORTING:3]] where the mean (standard deviation) ages of patients in endometriosis and control group were 32 [+ or -] 6 years and 32 [+ or -] 5 years, respectively. There were no differences in age, cycle phase, parity, and infertility between two groups. Patients with endometriosis were more likely to gain moderate-to-severe dysmenorrhea (visual analogue scale [VAS] ≥4) and high level of CA125 by comparison with controls ( Z = −2.627, P = 0.009 and t = 7.529, P < 0.001, respectively). All the patients with endometriosis were judged to be Stage III and IV according to the AFS staging system.

Circular RNA expression profiles in eutopic endometrium relative to those in normal endometrium

According to the circRNA microarray, a total of 88 circRNAs, 11 significantly upregulated and 77 significantly downregulated, were differentially expressed between eutopic endometrium and normal endometrium. The two types of endometrial tissue could be clearly distinguished using hierarchical clustering, scatterplot, and volcano plots [Figure 1]. Hierarchical clustering indicated the relative expression level of circRNAs in eutopic and normal endometrium. Scatter plot evaluated the variation in circRNA expression between the two groups. Volcano plot displayed the statistical significance of differentially expressed circRNAs between cases and controls.{Figure 1}

Quantitative real-time polymerase chain reaction validation of selected circular RNAs

To confirm the differentially expressed circRNAs in the microarray, four circRNAs were selected for validation based on the following criteria: (1) upregulated in eutopic endometrium, (2) FCs >2, (3) P < 0.05, (4) raw intensity >200, (5) exonic-related circRNAs, and (6) length between 200 and 3000 bp. Of them, two circRNAs ( circ_0004712 and circ_0002198 ) matched the microarray results and met the statistical cutoff by comparison with control endometrium [ Z = −2.653, P = 0.008; Z = −4.498, P < 0.001; [Figure 2]a. circRNA_0002503 was expressed at a higher level in the eutopic endometrium of patients with endometriosis; however, the difference was not statistically significant. And, circ_0000141 could not be amplified by qPCR %[Figure 2]a. Intriguingly, the two validated circRNAs were not affected by the menstrual cycle [Figure 2]b. We also performed a subgroup analysis between VAS and CA125, respectively, where patients with endometriosis were classified as two groups: one with moderate-to-severe dysmenorrhea (VAS ≥4) or CA125 >35 U/ml and the other with VAS <4 or CA125 ≤35 U/ml. As a result, no significant association between the two validated circRNAs and VAS or CA125 was found [Supplementary Figure 1 [SUPPORTING:4]]. Receiver operating characteristic curve analyses revealed that circ_0004712 and circ_0002198 were valuable biomarkers for distinguishing women with or without endometriosis, with area under curve (AUC) value of 0.704 (95% confidence interval [ CI ]: 0.571-0.837; P = 0.008) and 0.846 (95% CI : 0.752-0.939; P = 0.000), respectively [Figure 3]. The diagnostic power of circ_0004712 achieved notable improvement when the circ_0004712 and circ_0002198 werecombined, while that of circ_0002198 was not improved (AUC = 0.819; 95% CI : 0.713-0.925; P = 0.000).{Figure 2}{Figure 3}

Prediction of target miRNAs and mRNAs

To explore the interactions between circRNAs and miRNAs, we predicted the target miRNAs of each circRNA. Moreover, the dominant miRNAs targeted by top 10 up- and downregulated circRNAs were ranked based on mirSVR scores [Supplementary Table 4 [SUPPORTING:5]]. Of them, miR455-3p, miR876-3p, miR661, and miR323a-5p were found to be the common targets of both circ_0004712 and circ_0002198. The details of the molecular interactions between these two circRNAs and above target miRNAs are depicted in [Figure 4]. To further study how the two circRNAs regulate gene expression as ceRNAs, we also predicted the related target genes according to the miRNAs targeted by circRNAs. On basis of above prediction, a total of 29 miRNAs and 62 mRNAs were recognized as downstream targets of circ_0004712 and circ_0002198 . Thereafter, the circRNA-miRNA-mRNA network was constructed, which clarified the gene regulatory relationships in endometriosis [Figure 5].{Figure 4}{Figure 5}

Enrichment analysis of circular RNA-targeted genes

GO and KEGG analysis was applied to enrich the function of circRNA-targeted genes [Figure 6]. The data indicated that the target genes of these circRNAs were mainly involved in the biological processes of creatine metabolic process, glutamine family amino acid metabolic process, and negative regulation of striated muscle cell [Figure 6]a. The main cell component which target genes participated in were mitochondrial inner membrane, organelle inner membrane, and mitochondrion, respectively [Figure 6]a. With regard to the molecular function, the circRNA-targeted genes play a role in phosphotransferase activity, SNAP receptor activity, and carboxylic ester hydrolase activity [Figure 6]a. In addition, KEGG analysis revealed that target genes might participate in arginine/proline metabolism and cytokine-cytokine receptor interaction [Figure 6]b.{Figure 6}


In our study, we identified 88 differentially expressed circRNAs, 11 upregulated and 77 downregulated, in eutopic endometrium of patients with endometriosis compared with those in normal endometrium. Two of four upregulated circRNAs were confirmed by qPCR following a microarray screening. The two circRNAs, circ_0004712 and circ_0002198 , identified in the present study have not been reported in other diseases. However, we found that the increased level of circ_0004712 and circ_0002198 can help identify the patients with endometriosis.

To explore the role of circRNAs in endometriosis, we first performed prediction of target miRNAs for circRNAs. In the rank of top 5 target miRNAs, it was found that circ_0004712 and circ_0002198 act together to target miR455-3p, miR876-3p, miR661, and miR323a-5p, which have not been reported in endometriosis yet. Nevertheless, in preeclampsia patients, miR455-3p was significantly downregulated and was linked to the suppression of hypoxia signaling.[21] In atherosclerosis, miR876 can induce endothelial cell apoptosis.[22] Moreover, miR-661 was able to activate p53 to inhibit cell cycle progression.[23] As regards the miR-323a-5p, in patients with refractory epilepsy caused by focal cortical dysplasia, its elevated level was positively correlated with the duration of epilepsy, seizure frequency, and poor prognosis.[24]

Subsequently, we also predicted the related target genes according to the miRNAs targeted by circRNAs. On basis of above prediction, a total of 29 miRNAs and 62 mRNAs were recognized as downstream targets of circ_0004712 and circ_0002198 . Among them, 4 targeted miRNAs and 2 mRNAs have been reported to be associated with endometriosis. For example, miR-503, repressed in endometriosis, induces apoptosis and cell cycle arrest and inhibits cell proliferation, angiogenesis, and contractility of ovarian endometriotic stromal cells.[25] miR-196a, overexpressed in eutopic endometrium, activates the MEK/ERK signal and represses the progesterone receptor and decidualization from women with endometriosis.[26] miR-196b, downregulated in endometriotic stromal cells, inhibits proliferation and induces apoptosis by targeting c-myc and Bcl-2 expression.[27] Hypoxia-coordinated AUF1/miR-148a was reported to destabilize DNA methyltransferase 1 mRNA during the pathogenesis of endometriosis.[28] Besides, TNFRSF6B ( NM_003823 ) and PGC-1a ( NM_002630 ) have beenfound to participate in pathogenesis of endometriosis. For instance, decoy receptor 3 (DcR3)/TNFRSF6B , a pleiotropic immunomodulator regulated by estrogen, promotes cell adhesion and enhances endometriosis development by activating focal adhesion kinase (FAK).[29] PGC-1a , highly expressed in ovarian endometrioma, promotes local estrogen biosynthesis by stimulating aromatase expression and activity.[30]

Finally, the circRNA/miRNA/mRNA network was constructed. Functional analyses and prediction of the target genes of circRNAs were carried out in eutopic and control endometrium for the first time. The two identified circRNAs were predicted to mediate arginine and proline metabolism via CKMT1A and CKMT1B . Both genes are effective modulators of ATP synthase-coupled respiration and belongs to mitochondrial creatine kinases (MtCK), which were found to be implicated in several tumors with poor prognosis.[31],[32],[33],[34] Overexpressed MtCK may be part of a metabolic adaptation of cancer cells and could sustain high energy turnover, but would be also protective against stress situations like hypoxia and possibly protect cells from apoptosis.[35] Although endometriosis is a benign disease, it exhibits malignant-like biological behaviors, including adhesion, aggression, and angiogenesis. Consequently, we speculated that CKMT1A - and CKMT1B -mediated metabolic pathways are involved in endometriosis progression. In addition, cytokine-cytokine receptor interaction signaling pathways were predicted to have strong relationships with the target genes, such as CCL23 ( ENST00000591423 ) , CCR10 ( NM_016602 ), and TNFRSF6B (NM_003823) . CCL23 has been reported to enhance endothelial cell migration, invasion, adhesion, and angiogenesis,[36],[37] which were also the pathophysiologic processes involved in endometriosis. CCR10 and its receptors regulated tissue-specific migration, maintenance, and functions of immune cells. Increasing evidence also found that CCR10 /ligands were frequently exploited by epithelium-originated cancer cells for their survival, proliferation, and evasion from immune surveillance.[38] Moreover, the evidence revealed that TNFRSF6B stimulated endometriosis development by activating FAK.[29]

The findings highlight the relationship between circRNAs and ovarian endometriosis, which will provide a novel biomarker for screening ovarian endometriosis and help explore the role of circRNAs in the activation of endometriosis. However, this study had several limitations. First, the sample size was small and all cases were revised AFS Stage III-IV; thus, further validation involving in larger cohorts of patients with early stages of this disease is warranted. Second, noninvasive biomarkers are more likely to evaluate the diagnostic value of circRNA in clinical applications. Further studies will be needed to assess the level of circRNA in peripheral blood or menstrual blood samples. Third, the molecular mechanism and function of the present circRNAs should be tested by associated experiments in the future.

Overall, we revealed for the first time, the circRNA expression patterns and an associated circRNA-miRNA-mRNA network between women with and without endometriosis. circ_0004712 and circ_0002198 were confirmed to be novel biomarkers in discriminating endometriosis from controls. Our findings lay the foundation for in-depth mechanistic studies on endometriosis, which can strengthen the reliability of the two identified circRNAs as diagnostic and therapeutic targets.

Supplementary information is linked to the online version of the paper on the Chinese Medical Journal website.


We thank KangChen Bio-tech, Shanghai, China, for conducting microarray profiling.

Financial support and sponsorship

This study was supported by grants from the National Key R&D Program of China (No. 2017YFC1001200) and National Natural Science Foundation of China (No. 81270681).

Conflicts of interest

There are no conflicts of interest.


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Title Annotation:Original Article
Author:Xu, Xiao-Xuan; Jia, Shuang-Zheng; Dai, Yi; Zhang, Jun-Ji; Li, Xiao-Yan; Shi, Jing-Hua; Leng, Jin-Hua
Publication:Chinese Medical Journal
Article Type:Report
Geographic Code:9CHIN
Date:Mar 18, 2018
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