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Identification of circular RNAs as novel biomarkers and potentially functional competing endogenous RNA network for myelodysplastic syndrome patients

Abstract Circular RNAs (circRNAs) have been identified to exert vital biological functions and can be used as new biomarkers in a number of tumors. However, little is known about the functions of circRNAs in myelodysplastic syndrome (MDS). Here, we aimed to investigate circRNA expression profiles and to investigate the functional and clinical value of circRNAs in MDS. Differential expression of circRNAs between MDS and control subjects was analyzed using circRNA arrays, in which we identified 145 upregulated circRNAs and 224 downregulated circRNAs. Validated by real‐time quantitative PCR between 100 MDS patients and 20 controls, three upregulated (hsa_circRNA_100352, hsa_circRNA_104056, and hsa_circRNA_104634) and three downregulated (hsa_circRNA_103846, hsa_circRNA_102817, and hsa_circRNA_102526) circRNAs matched the arrays. The receiver operating characteristic curve analysis of these circRNAs showed that the area under the curve was 0.7266, 0.8676, 0.7349, 0.7091, 0.8806, and 0.7472, respectively. Kaplan‐Meier survival analysis showed that only hsa_circRNA_100352, hsa_circRNA_104056, and hsa_circRNA_102817 were significantly associated with overall survival. Furthermore, we generated a competing endogenous RNA network focused on hsa_circRNA_100352, hsa_circRNA_104056, and hsa_circRNA_102817. Analyses using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes showed that the three circRNAs were linked with some important cancer‐related functions and pathways.

Circular RNAs are a new type of endogenous RNA, whose 5′ and 3′ ends are joined together by splicing to form a covalent closed continuous loop. This structure is typically nonpolyadenylate and resistant to exonucleases, hence making them more stable than their linear counterparts. Circular RNAs are abundant, conserved, and stable in the cytoplasm. They have tissue-specific and developmental stage-specific expression patterns and act as miRNA sponges and RNA-binding proteins to regulate gene expression at the transcriptional and posttranscriptional level. 2 Circular RNAs have also been reported to be abundant and stable in human serum, especially in exosomes. Their expression patterns are significantly different between tumor samples and normal tissues, suggesting that circRNAs could be used as a biomarker for tumor diagnosis and prognosis. 3,4 Researchers have identified the clinical value of circRNAs in a number of cancers, including, lung cancer, 5 hepatocellular carcinoma, 6,7 and colorectal cancer. 8,9 However, little is known about the roles of circRNAs in MDS.
In this study, we aim to discover novel functional circRNAs and potential diagnostic and prognostic values of MDS by identification of differentially expressed circRNAs in BM of MDS patients.
The circRNA expression profile was analyzed by circRNA array and then validated by qPCR. Receiver operating characteristic curve analysis and the Kaplan-Meier method with the log-rank test were used to assess the diagnostic and prognostic value of circRNAs. Bioinformatic analysis was also used to set a circRNA-miRNA-mRNA interaction network and predict possible functions of circRNAs.

| Patient recruitment and sample description
One hundred MDS patients (refractory anemia, n = 2; refractory anemia with ringed sideroblasts, n = 2; RCMD, n = 83; RAEB-1, n = 4; RAEB-2, n = 6; and MDS, unclassifiable, n = 3) and 20 control subjects were recruited from Shanghai Huashan hospital between 2007 and 2016. Patients with RCMD were newly diagnosed based on the 2008 WHO criteria and had not yet undergone treatment. 10 Controls refer to samples from patients with benign blood diseases.
Bone marrow aspiration is a traumatic procedure, and it is not widely accepted by patients. Together with ethical considerations, it is difficult to collect BM samples from healthy people. Therefore, samples of patients with benign blood diseases were enrolled as controls.
Due to hematological count anomalies or hypersplenism, these patients had undergone BM tests and no abnormalities were found.
After 2 years of follow-up, the BM of these patients remained normal. Bone marrow samples (5 mL) were collected from all 100 MDS patients and 20 control subjects. Blood samples (3 mL) were collected using an EDTA anticoagulated vacutainer from the 100 MDS patients. Bone marrow and PBMCs were isolated from all subjects using a Ficoll solution within 12 hours after sample collection. The study was approved by the institutional review board at Huashan Hospital of Fudan University and informed consent was obtained from each study participant.

| RNA isolation and reverse transcription
Total RNA was extracted from each sample of BM and PBMCs using the QIAamp RNA Blood Mini Kit (Qiagen) following the manufacturer's instructions. RNA quality was assessed using the Bio-Rad Experion electrophoretogram instrument (Bio-Rad). The purity of RNA was assessed by measuring the optical density of 260/280 ratio using a NanoDrop spectrophotometer. Samples were used in reverse transcription reactions when the A260/A280 was between 1.8 and 2.0. RNA samples were reverse transcribed into cDNA using Takara PrimeScript RT Master Mix (Takara) according to the manufacturer's protocol and stored at −80°C until further use.

| Quantitative real-time PCR assay
Real-time qPCRs were carried out using the CBX 1000 Sequence Detection System (Applied Biosystems). SYBR Premix Ex Taq PCR reagents (Takara) were used for amplification and detection following the manufacturer's instructions. Specifically, 10 μL reaction mixture containing 5 μL SYBR Green premix, 0.2 μL of each 10 mol/L primer, 1 μL cDNA, and 3.6 μL diethylpyrocarbonate-treated water was heated at 95°C for 30 s and subsequently subjected to 40 cycles of 95°C for 5 s and 60°C for 30 s. The C T value was the fractional cycle number at which the fluorescence exceeded the given threshold. We used GAPDH to normalize the qPCR. The relative expression levels of circRNAs were determined using the 2 −∆CT method. Divergent primers were selected for circRNAs and primers for GAPDH were synthesized by Biosune. All qRT-PCR primer sequences are illustrated in Table 1.

| Sanger sequencing
Products of qRT-PCR were sent for Sanger sequencing to determine the full-length sequence and confirm the splice junctions of the selected circRNAs. Sanger sequencing was carried out by Biosune. The characteristics of the nine patients were shown in Table 2. Data were quality controlled and normalized. P value and fold change were calculated using the Student's t test. Differentially expressed circRNAs were selected based on threshold values of fold change greater than or equal to 2 and P value less than or equal to .05.

| Bioinformatics analysis
Circular RNA-miRNA interaction was predicted by TargetScan and miRanda. Target mRNAs of miRNAs were analyzed by TargetScan, miRDB, and miRWalk. Cytoscape 3.8.0 software 11 was used to visualize the circRNA-miRNA-mRNA network. Gene Ontology annotation and KEGG analysis were undertaken using an R package named clusterProfiler. 12

| Statistical analysis
All data were verified as nonnormal distributed using Shapiro-Wilk tests and presented as median (25%, 75%). The Mann-Whitney U test was used to analyze the data, with a significant value cut-off of P < .05. The clinical diagnostic value of any given circRNA was verified by ROC curve analysis, in which AUC > 0.5 and P < .05 indicated diagnostic value. The cut-off value and corresponding sensitivity and specificity were identified through ROC curve analysis. Kaplan-Meier survival analysis was carried out to analyze the prognostic value and the statistical significance was obtained using the log-rank test. The χ 2 -test or Fisher's exact test was used to compare the difference of categorical variables between patients with lower and higher circRNA expression. The correlation between circRNA expression levels in BM and PB samples was evaluated using Spearman's correlation test.
Statistical analyses were undertaken using GraphPad Prism 6.

| Bone marrow circRNA expression profile in MDS patients
To identify differentially expressed circRNAs between MDS patients and control subjects, we extracted BM total RNA from five MDS patients and four control subjects for circRNA array assay analysis.
Three hundred and sixty-nine circRNAs were differently expressed out of the 3459 circRNAs in the array, of which 145 circRNAs were upregulated and 224 were downregulated in MDS patient samples. the amplified product of circRNA was consistent with the CircBase sequence; (b) results of the Sanger sequencing confirmed the backsplice junctions of the circRNAs selected; and (c) the specificity of the amplified circRNA product was confirmed by electrophoresis.

| Validating the results of circRNA array
These inclusion criteria for selection proved that the selected circR-NAs naturally existed as a loop in BM and could be amplified by qRT-PCR. To identify the most clinically applicable biomarker, we chose six circRNAs that showed the highest fold differences (P < .05) between MDS and control subjects. Information of circRNAs is listed in Table 3. Then we verified the six circRNAs by qRT-PCR in a cohort consisting of 20 control subjects and 100 MDS patients. The results were consistent with the circRNA array ( Figure 1).

| Receiver operating characteristic analysis of six circRNAs in MDS patients
To compare the diagnostic value of the previously selected six circRNAs as candidate biomarkers of MDS, we undertook ROC curve analysis for each circRNA with the same cohort of 20 control subjects and 100 MDS patients. As shown in Figure 2, the AUC was larger than 0.500 (P < .05) for six circRNAs, suggesting their potential diagnostic value. Notably, the AUC of hsa_circRNA_104056 was 0.89 (P < .001), which was the largest among the selected circRNAs. The sensitivity and specificity of each circRNA were determined based on the cut-off value (shown in Table 4). Hsa_circRNA_104056 had the highest sensitivity and specificity (0.8 and 0.8421, respectively).

| Kaplan-Meier survival analysis of six circRNAs in MDS patients
We then detected whether the alteration of each circRNA expression could predict the prognosis of MDS patients. The survival curves for patients with MDS according to different circRNA expression levels are shown in Figure 3. We found that the elevated

| Association between circRNA expression level with clinicopathological characteristics of MDS patients
To determine the clinical significance of expression level of circRNAs, we divided the MDS patients into two groups based on the median RQ value of circRNAs. As shown in Table 5, we found that higher hsa_circRNA_100352 expression was more frequently seen in patients younger than 60 years of age (P = .020), or patients with lower Revised International Prognostic Scoring System (IPSS-R) scores (P = .019).
Upregulation of hsa_circRNA_104056 was significantly associated with cytogenetics (P = .033). The cytogenetic of patients with higher hsa_circRNA_100352 expression were more likely to be good. However, the expression level of hsa_circRNA_102817 has no significant correlation with any of these clinicopathologic characteristics. Abbreviations: AUC, area under the receiver operating characteristic curve; CI, confidence interval.

| Spearman's correlation test showed that there was no correlation between expression level of circRNAs in BM and PB samples
As BM aspiration is invasive and not easily accepted by patients,

| Circular RNA-miRNA-mRNA network
Arraystar's homemade miRNA target prediction software based on database TargetScan and miRanda were used to predicted miRNAs that could bind to hsa_circRNA_100352, hsa_circRNA_104056, or hsa_circRNA_102817. The results are listed in Table 6 and Figure 5.
Target mRNAs of miRNAs were analyzed using three databases, TargetScan, miRDB, and miRWalk. Targets that have been annotated by all databases were filtered out. The circRNA-miRNA-mRNA network was developed to predict potential target mRNAs of circRNAs based on the mechanism that circRNAs can bind to miRNAs, which can further silence certain gene expression by degrading the mRNA transcripts. The circRNA-miRNA-mRNA network diagram was drawn using Cytoscape 3.8.0( Figure 6).

| Gene Ontology and KEGG analyses
The lists of all the predicted genes were analyzed by the GO and KEGG approaches in R. Specifically, these genes were most enriched in the biological process of response to transforming growth factorβ and cell cycle arrest (P < .01), cellular component in the histone deacetylase complex and transcription regulator complex (P < .01), molecular function in SMAD binding, and cadherin binding (P < .05) ( Figure 7A). The KEGG analysis revealed that these genes were enriched in viral carcinogenesis, transcriptional misregulation in cancer, and p53 signaling pathway ( Figure 7B).   factor-κB, 18 and miR-143-5p/hypoxia-inducible factor-1α pathway. 19 These miRNAs can influence cell proliferation, differentiation, invasion, and apoptosis, and play important roles in several tumors.

ACK N OWLED G M ENTS
This work was supported in part by grants from the National Natural Science Foundation of China (Grant No. 81270583).

D I SCLOS U R E
The authors have no conflict of interest.