Differentially expressed circRNAs in melanocytes and melanoma cells and their effect on cell proliferation and invasion

  • Authors:
    • Qi Wang
    • Jia Chen
    • Aijun Wang
    • Lichun Sun
    • Li Qian
    • Xiao Zhou
    • Yu Liu
    • Shijie Tang
    • Xiang Chen
    • Yan Cheng
    • Ke Cao
    • Jianda Zhou
  • View Affiliations

  • Published online on: February 13, 2018     https://doi.org/10.3892/or.2018.6263
  • Pages: 1813-1824
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Abstract

Circular RNAs (circRNAs) play critical roles in the occurrence of human diseases, including cancer. However, the detailed functions of circRNAs in melanoma have not been fully elucidated. In the present study, a circRNA microarray was performed to analyze the variability of circRNAs in the low-metastatic melanoma WM35 cell line and in the high-metastatic melanoma WM451 cell line in comparison to control human melanocytes. The results revealed that five circRNAs were upregulated and four circRNAs were downregulated in both the WM35 and WM451 cells. qRT-PCR revealed an upregulated expression of circ0000082 and circ0016418 and a downregulation of circ0023988, circ0008157 and circ0030388 in the cells which was consistent with the results of the microarray assay. Functional tests revealed that knockdown of circ0023988, circ0008157 or circ0030388 significantly promoted the proliferation and invasion of the WM35 cells. Following the silencing of circ0000082 or circ0016418 in WM451 cells, the proliferation and invasion of the WM451 cells were inhibited. Bioinformatic analysis predicted that the circ0000082-, circ0023988- and circ0008157-circRNA-miRNA-mRNA network may participate in the occurrence, development, invasion and metastasis of malignant tumors. The present study revealed several differentially expressed circRNAs, indicating that the newly identified circRNAs may provide new therapeutic targets for melanoma.

Introduction

Melanoma is a highly malignant skin tumor derived from melanocytes and its incidence has been rapidly increasing worldwide (1). Melanoma is not sensitive to radiotherapy, chemotherapy or biological immunotherapy and metastasizes at an early clinical stage (2). Therefore, it is crucial to understand the molecular mechanisms underlying the development of melanoma. Although researchers worldwide have performed extensive research on gene mutations, epigenetics, immune abnormalities and the tumor microenvironment of melanoma, its precise mechanism remains poorly understood. Studies on non-coding RNA, notably circular RNA (circRNA), may provide a breakthrough for the explanation of the mechanism of melanoma and the identification of early intervention targets and biomarkers for early diagnosis.

Circular RNAs (circRNAs) have been reported as a novel type of non-coding RNAs, which form covalently-closed continuous loops without 5′ to 3′ polarity or polyadenylated tails (3,4). They mainly arise from exons or introns and are differentially generated by back-splicing or lariat-introns (5). circRNAs are characterized by stable structure, high abundance and tissue-specific expression. These characteristics imply that circRNAs hold a great potential as novel clinical diagnostic and prognostic markers and as new treatment targets of diseases (68). Increasing evidence has revealed that circRNAs specifically serve as miRNA sponges, regulate alternative splicing and modulate the expression of parental genes (911). It has been proved that circRNA-CDR1 contains miR-7 binding sites and exerts a negative regulatory effect in miR-7 as an endogenous miRNA sponge and an upregulator of miR-7-targeted genes in the nervous system (12,13). In esophageal squamous cell carcinoma, cir-ITCH was downregulated in cancerous tissue and functioned as a sponge of miR-7, miR-17 and miR-214. Therefore, it enhanced the level of ITCH which negatively regulates the Wnt/β-catenin signaling pathway (14).

To date, a study concerning the expression of circRNAs in melanoma has not been reported. Therefore, in the present study, we performed the profiling of circRNA expression in normal melanocytes and melanoma cells with different invasive abilities using circRNA microarray analysis. Furthermore, we investigated differentially expressed circRNAs, as well as the changes in melanoma cell proliferation and invasion after circRNA-siRNA transfection. In addition, we analyzed the features of the circRNA-expression profiling and predicted miRNAs competitively binding to circRNAs. Finally, we provided important experimental evidence for clarifying the occurrence, the development, the invasion and metastasis of melanoma and for exploring the non-coding RNA regulatory networks related to the malignant phenotype of melanoma.

Materials and methods

Cell culture and reagents

The human melanocytes HM, the low-metastatic melanoma cell line WM35 and the high-metastatic melanoma cell line WM451 were purchased from the American Type Culture Collection (ATCC; Manassas, VA, USA). The cells were incubated with Dulbecco's modified Eagle's medium (DMEM; Gibco; Thermo Fisher Scientific, Inc., Waltham, MA, USA) containing 10% fetal bovine serum (FBS) in a 5% CO2 incubator at 37°C. The reagents in the present study included an RNA-free extraction kit (Invitrogen Life Technologies, Carlsbad, CA, USA), an Opti-MEM I Reduced-Serum medium (Invitrogen Life Technologies), Transwell 6-well plates, (8-µm pore size; Corning Incorporated, Corning, NY, USA), Matrigel basement membrane (Becton, Dickinson and Company, Franklin Lakes, NJ, USA), RNase-free glycogen in RNase water (Invitrogen Life Technologies), Arraystar Human circRNA Array (8×15 K; Arraystar, Rockville, MD, USA) including 5,396 circRNAs, GoldView dye (SBS Genetech Co., Ltd., Shanghai, China), 2X PCR Master Mix (Arraystar) and SuperScript III Reverse Transcriptase (Invitrogen Life Technologies). The experiments were conducted by Kangchen Biotech Co., Ltd. (Shanghai, China).

RNA extraction

Total RNA was extracted from the cells using the RNA extraction kit according to the manufacturer's instructions and examined by 1% agarose gel electrophoresis. Both the 28S and 18S bands were clear and the brightness of the 28S band was roughly two-fold higher than that of the 18S band, indicating the integrity of total RNA. Ultraviolet spectrophotometry was used to determine the concentration and purity of RNA. The D260/D280 nm ratio was 1.8–2.1 These results indicated that the purity of total RNA was suitable for subsequent circRNA microarray analysis and quantitative fluorescence PCR.

circRNA microarray

For analyzing the acquired array images, the Agilent Feature Extraction software (version 11.0.1.1; Agilent Technologies, Inc., Santa Clara, CA, USA) was performed. Following the instructions of the Arraystar Super RNA Labeling kit (Arraystar), total RNA of each sample was amplified with random primers and reverse transcribed into fluorescent-labeled cRNA. Subsequently, fluorescent-labeled cRNA was hybridized on an Arraystar Human circRNA Array (8×15 K; Arraystar) and then incubated in an Agilent Hybridization oven at 65°C for 17 h. After washing, the samples were scanned on an Agilent scanner (G2505C).

Data collection and analysis of circRNA microarray

Fluorescence intensity was scanned in a microarray scanner and loaded to the Agilent Feature Extraction software to read and analyze the original data. The R software package (limma package, Cytoscape http://www.cytoscape.org/ 3.3.2, R environment https://www.r-project.org/ reversion 3.42) was used for quantile normalization and subsequent data processing. Differentially expressed circRNAs between groups was screened by fold change and P-value. A value of P<0.05 was considered to indicate a statistically significant difference. Cluster analysis revealed differential circRNA expression using Cluster 3.0 software (R programming language package: Gplots).

Prediction for circRNA-miRNA-mRNA network

The circRNA-microRNA interaction was predicted using Arraystar miRNA target-prediction software (Arraystar) and GCBI (https://www.gcbi.com.cn/gclib/html/index) based on TargetScan and miRanda software packages. A site with a higher matching score was noted. The map of circRNA-miRNA interaction network was illustrated using Cytoscape 3.01 (Cytoscape Consortium San Diego, CA, USA).

Real-time quantitative fluorescence PCR

Five differentially expressed circRNAs were verified by real-time quantitative fluorescence PCR. Reverse transcription reaction was carried out according to the instructions of the SuperScript III Reverse Transcriptase reverse transcription kit (Invitrogen Life Technologies). The ViiA 7 Real-Time PCR system was used for quantitative detection of PCR. The PCR primers were designed and synthesized by Invitrogen Biotechnology Co., Ltd. (Shanghai, China). The primer sequences and related information are listed in Table I. GAPDH served as an internal standard for normalization. The PCR conditions were as follows: 95°C for 10 min, 95°C for 10 sec and 60°C for 60 sec, for a total of 40 cycles. The 2−ΔΔCt value refers to the relative expression level of circRNAs. The experiments were performed in triplicate.

Table I.

The primers for qRT-PCR.

Table I.

The primers for qRT-PCR.

GenePrimer sequenceLength (bp)
GAPDHF: 5′GGGAAACTGTGGCGTGAT3′
R: 5′GAGTGGGTGTCGCTGTTGA3′299
circRNA0000082F: 5′CGGATTAGAAACCTCGACACC3′
R: 5′TGGACCACAGGAGCATCATT3′270
circRNA0016418F: 5′CTCCGACCCAAGTGAGAAGC3′
R: 5′CAGCCTGTAGTTTGGGACC3′124
circRNA0023988F: 5′TGGTGGTGGTGCTATTCCTC3′
R: 5′TCTCCTGGTTCTCCTGCTTG3′265
circRNA0008157F: 5′GAATTCTAAGCAGCACAACATCA3′
R: 5′GGGTCCATGTCTTTGCCTCT3′161
circRNA0030388F: 5′TGGGACATCCATCAGATAAGAA3′
R: 5′CTGTAGTGGGAGGCAGTGTTT3′169

[i] F, forward; R, reverse.

Transfection

The cells were transfected with five differentially expressed circRNAs which were verified using qRT-PCR as follows: 24 h before transfection, 5×104 cells were seeded in 2 ml of basal medium containing FBS. The cells were ready for transfection when they reached 70% confluency. Lipofectamine™ 2000 (5 µl) was diluted in 250 µl of Opti-MEM® I, mixed gently and incubated at room temperature for 5 min, and then 7.5 µl siRNA-circRNAs was diluted in 250 µl of Opti-MEM® I, mixed gently and incubated at room temperature for 5 min. Diluted siRNA-circRNAs and Lipofectamine™ 2000 were mixed together gently and the complexes were incubated at room temperature for 20 min. The siRNA-circRNAs-Lipofectamine™ 2000 transfection complexes were added in 6-well plates and mixed by gently rocking the plate back and forth. The plates were incubated at 37°C in a CO2 incubator for 24–72 h. The transfected cells were observed under a fluorescence microscope (CKX53; Olympus, Tokyo, Japan) to assess the transfection efficiency.

Cell proliferation assay

After transfection, the cell density in each group was adjusted to 1×105 cells/ml and the cells were seeded in 96-well plates in a volume of 100 µl per well, and placed at 37°C in a CO2 incubator for 24 h. The WM35 cells were divided into four groups: i) negative control group, ii) si-circ0023988, iii) si-circ0008157 and iv) si-circ0030388 treated group. The WM451 cells were divided into three groups: i) negative control, ii) si-circ0000082 and iii) si-circ0016418 group. Methyl thiazolyl tetrazolium (MTT) (50 µl, 1 mg/ml) was added to each well and the plates were incubated for 4 h at 37°C, until MTT was reduced to formazan. The supernatant was aspirated and 150 µl DMSO was added to each well, and then the plates were placed on a horizontal shaker and shaked for 10 min to dissolve the formazan. The optical density (OD) value of each well was detected using an enzyme-linked immunosorbent assay (ELISA) reader at 570 nm. Cells without treatment served as a control and the blank well was used for zero adjustment. The cell survival rate were calculated using the following formula: Cell survival rate = (OD value of the experiment group/OD value of the control group) × 100%.

Cell invasion assay

The upper chamber surface of the basement membrane of the Transwell chambers was coated with 50 mg/l Matrigel 1:8 dilution and air dried at 4°C. Diluted Matrigel (60–80 µl, 3.9 µg/µl) was added to the polycarbonate membrane in the upper chamber and placed at 37°C for 30 min to allow the Matrigel to polymerize. The cells were digested and after terminating the digestion, the cells were centrifuged and then the culture medium was discarded. After washing with PBS for 1–2 times, the cells were resuspended in serum-free media containing bovine serum albumin (BSA). The cell density was adjusted to 5×104/ml. One milliliter of medium-containing FBS was added to the lower chambers of 6-well plates, cell supernatant was added to the upper chambers and after 72 and 24-h incubation for the WM451 and the WM35 cells respectively, the membranes were removed. The cells on the Matrigel and upper chambers were removed with a cotton swab, the membrane was removed and fixed with 95% alcohol for 15–20 min and stained with hematoxylin for 10 min. The cells were counted and imaged under an inverted microscope (CKX53; Olympus).

Statistical analysis

The data are presented as the mean ± SD as analyzed using SPSS 13.0 (SPSS, Inc., Chicago, IL, USA) and deemed to have statistical significance at P<0.05 using the Student's t-test, one-way analysis of variance (ANOVA) or χ2 test.

Results

Differentially expressed circRNAs

Genome scan (Fig. 1A) and cluster analysis (Fig. 1B) were used to identify abnormal expression of circRNAs among the HM, WM35 and WM451 cells. Approximately 5,396 circRNAs were detected using the Arraystar Human circRNA Array data analysis. The results of the heat maps are displayed in Fig. 1B. The data obtained from circRNA microarray analysis were normalized. Approximately 5,396 circRNAs were detected by the Arraystar Human circRNA Array data. The results of the genome scans and differentially expressed circRNAs among the HM, WM35 and WM451 cells are displayed in Fig. 1. Data obtained from circRNA microarray analysis were normalized. circRNAs with expression levels that increased 2-fold were upregulated and circRNAs with expression levels that decreased 2-fold were downregulated. Different fold changes of circRNA expression according to chip analyses are summarized in Table II. CircRNA microarray analysis results demonstrated that compared with HM cells, 797 circRNAs were upregulated and 969 circRNAs were downregulated in WM35 cells, while 307 circRNAs were upregulated and 312 circRNAs were downregulated in WM451 cells. Only five circRNAs (circ0001056, circ0000082, circ0016418, circ0008602 and circ0033496) were upregulated as well as four circRNAs (circ0023988, circ0008157, circ0030388 and circ0023990) were downregulated both in WM35 and WM451 cells. Compared with the WM35 cells, 977 circRNAs were upregulated and 757 circRNAs were downregulated in the WM451 cells (Table II). In WM35 vs. HM cells, WM451 vs. HM cells and WM451 vs. WM35 cells, four circRNAs (circ0023988, circ0023990, circ0008157 and circ0030388) were all downregulated (Table III).

Table II.

Differential expression of circRNA according to chip analyses.

Table II.

Differential expression of circRNA according to chip analyses.

A, Upregulated circRNA

Fold changeWM35 vs. HMWM451 vs. HMWM451 vs. WM35
>20002
10–200532
5–10226126
2–5795276817

B, Downregulated circRNA

>20151
10–201080
5–10892013
2–5869279743

[i] circRNA, circular RNA.

Table III.

Differential expression of circRNAs according to chip analyses.

Table III.

Differential expression of circRNAs according to chip analyses.

A, Upregulated

Fold change

circRNAWM35 vs. HM WM451 vs. HMmiRNA binding sites
circ00010563.45 2.13miR-30b-3p, miR-619-5p, miR-665, miR-153-5p, miR-149-5p
circ00000822.39 4.65miR-30b-3p, miR-23a-5p, miR-143-5p, miR-106b-3p, miR-508-5p
circ00164182.63 3.63miR-214-5p, miR-153-5p, miR-657, miR-450a-2-3p, miR-605-3p
circ00086022.69 3.28miR-544a, miR-200c-3p, miR-148a-3p, miR-362-5p, miR-17-3p
circ00334962.031 2.15miR-612, miR-502-5p, miR-1264, miR-105-3p, miR-423-5p

B, Downregulated
Fold change

circRNAWM35 vs. HMWM451 vs. HMWM451 vs. WM35miRNA binding sites

circ0023988–2.08–5.64–2.71miR-655-5p, miR-448, miR-485-5p, miR-613, miR-103a-3p
circ0023990–2.55–10.12–3.96miR-485-5p, miR-613, miR-339-5p, miR-329-5p, miR-873-5p
circ0008157–2.38–4.92–2.06miR-136-3p, miR-365b-5p, miR-365a-5p, miR-329-5p, miR-335-3p
circ0030388–2.39–17.82–7.45miR-449b-5p, miR-449a, miR-34a-5p, miR-34c-5p, miR-200a-3p

[i] circRNAs, circular RNAs.

Differential expression of circRNAs verified by real-time quantitative fluorescence PCR

Five upregulated circRNAs and four downregulated circRNAs were found by microarray analysis and qRT-PCR was used to verify the background expression levels of the above-mentioned circRNAs in melanoma cells. GAPDH served as an internal standard for normalization. The results revealed that circ0000082 and circ0016418 had higher expression levels and circ0023988, circ0008157 and circ0030388 had lower expression levels both in the WM35 and the WM451 cells, compared with the HM cells (Fig. 2). The above-mentioned five circRNAs were verified by real-time quantitative fluorescence PCR and the PCR results were generally consistent with those of the circRNA microarray, which confirmed that the microarray analysis results were reliable (Table IV). The other four circRNAs with low basal expression were excluded (circ0001056, circ0033496, circ0008602 and circ0023990).

Table IV.

Differential expression of circRNAs according to qRT-PCR.

Table IV.

Differential expression of circRNAs according to qRT-PCR.

Fold change

circRNAWM35 vs. HMWM451 vs. HMWM451 vs. WM35Expression
circ00000821.675.233.31Up
circ00164181.191.411.19Up
circ00239880.640.160.24Down
circ00081570.0560.020.268Down
circ00303880.8160.310.384Down

[i] Up, upregulated; Down, downregulated; circRNAs, circular RNAs.

Knockdown of the expression levels of circRNAs

In order to interfere with circRNA expression levels, circ0023988, circ0008157, or circ0030388 siRNAs were transfected into WM35 cells, while circ0000082 or circ0016418 siRNA swere transfected into WM451 cells. The highest transfection efficiency was observed at 24 h and the transfection efficiency was >80% by comparing the cells in bright field and fluorescent views of the same field (Fig. 3). Therefore, these results indicated that the transfection efficiency was satisfactory and the cells could be used for the following experiments.

Changes in cell proliferation after siRNA-circRNAs transfection

Twenty-four hours after the WM35 and WM451 cells were transfected with siRNA-circRNAs, the cell proliferation in each group was detected by an MTT assay. The results revealed that at 24 and 48 h after transfection, the OD values of low-metastatic melanoma WM35 cells in the si-circ0023988, si-circ0008157 and si-circ0030388 groups were significantly higher than that in the negative control group (P<0.05), indicating that silencing of circ0023988, circ0008157 and circ0030388 promoted the proliferation of the WM35 cells (Fig. 4A). At 24, 48 and 72 h after transfection, the OD values of high-metastatic melanoma WM451 cells in the si-circ0000082 and si-circ0016418 groups were significantly lower than that in the negative control group (P<0.05), indicating that silencing of circ0000082 and circ0016418 inhibited the proliferation of the WM451 cells (Fig. 4B).

Changes in cell invasion after siRNA-circRNA transfection

The transfected WM35 and WM451 cells were subjected to invasion assays for 24 and 72 h, respectively. The cells that passed through the basement membrane were counted by light microscope (CKX53; Olympus) at ×200 magnification. The cell numbers in the si-circ0023988, si-circ0008157 and si-circ0030388 groups were 87.3±12,103.3±10 and 88.3±5.7, respectively, which were significantly higher than these in the negative control group (34.3±1.5) (P<0.05, Fig. 5A), indicating that the invasion ability of low-metastatic melanoma WM35 cells was enhanced by silencing of circ0023988, circ0008157 and circ0030388. Compared with the negative control group, the WM451 cell numbers in the si-circ0000082 and si-circ0016418 groups were lower (48.3±3.5, 44.3±5 vs. 86.3±5.1) (P<0.05, Fig. 5B). These results indicated that silencing of circ0000082 and circ0016418 decreased the invasion capability of high-metastatic melanoma WM451 cells and that circ0000082 and circ0016418 have a promoting effect on the invasion of WM451 cells.

Competing endogenous RNA (ceRNA) analysis of circ0000082, circ0023988 and circ0008157

In accordance with the results of real-time quantitative fluorescence PCR, ceRNAs of apparently differentially expressed circ0000082, circ0023988 and circ0008157 were found by mutually targeted MRE enrichment analysis (MuTaME, https://cm.jefferson.edu/rna22/Precomputed/) and then a regulatory network of circRNA-miRNA-mRNA was constructed using Cytoscape 3.01 (Fig. 6). Prediction results (Table V) revealed that circ0000082 possibly competitively bound to 64 miRNAs and impacted the expression of 425 target genes. Furthermore, circ0023988 possibly competitively bound to 78 miRNAs and impacted the expression of 33 target genes. In addition, circ0008157 possibly competitively bound to 111 miRNAs and impacted the expression of 52 target genes. Subsequently, combining with the confirmed melanoma-related miRNAs, we selected miRNAs that impacted the occurrence and development of melanoma, competitively binding to circ0000082, circ0023988 and circ0030388 and the possible impacted target genes (Fig. 6). The results are displayed in Table VI.

Table V.

Predicted ceRNAs for circRNAs.

Table V.

Predicted ceRNAs for circRNAs.

circRNASponge miRNA numbersTarget gene numbers
circ0000082  64425
circ0023988  78  33
circ0030388111  52

[i] ceRNAs, competing endogenous RNA.

Table VI.

Predicted circRNA-miRNA-mRNA network in melanoma.

Table VI.

Predicted circRNA-miRNA-mRNA network in melanoma.

circRNAmiRNATarget gene
circRNA0000082miR-30b-3pBMP8A, C2orf44, C6orf25, CAST, FOXRED2, HPSE, SYN2, TBRG1, TBX15, TBXA2R, ZNF814
miR-143-5p[44]CLDN19, DENR, DLG2, DPCR1, GEMIN7, LIX1, MAFF
miR-149-3p[45]ADAR, ALPPL2, APLNR, CCDC117, HOXA1, HOXB4, IGF2BP1, IL1F5, IL17RD, IQGAP3, KCNIP2, KCNS1, KCNIP1, KIAA1467, RRP15, RRP1B, ZNF649, ZNF764
miR-328-5p[46]ELK1, ETV6, E2F2, FAM73B, FKBP5, FOXG1, RRP1B, STARD3, UBL4A, VAMP2, ZFP106
circRNA0030388miR-30b-3pBMP8A, CAST, C2orf44, C6orf25, FOXRED2, HPSE, SYN2, TBRG1, TBX15, TBXA2R, ZNF814
miR-34a-5p[47]HPSE
miR-34b-5pALG1, RPS6KL1
miR-34c-5pHPSE, MDM4, RHOJ, RPS6KL1
miR-200a-3p[49]CYTSB, OR7D2, PHLPP2, SCD5, SPECC1
miR-210-5pCCBP2, HEYL, SH3TC2, ZNF329, ZNF619
circRNA0023988miR-15a-5pDCP1A, DRP2, EPB41L4A, GALC, HIGD1A, PDIK1L, SERPINB9
miR-15b-5p[50]
miR-16-5p
miR-17-3p
miR-21-3p[51]HIGD1A
miR-29a-3p[53]
miR-29b-3p[53]
miR-29c-3p[53]NOTCH2
miR-144-5p[55]BTN1A1
miR-195-5p[54]
miR-206

Discussion

CircRNAs are widely expressed in human cells and their expression levels can be 10-fold or higher compared to their linear isomers. Compared with traditional linear RNA (containing 5′ and 3′ends), circRNAs form a covalently-closed continuous loop and cannot be affected by RNA exonuclease. Their expression is more stable and circRNAs cannot be easily degraded. Thus, circRNAs have significant superiority in the development and application of new clinical diagnostic markers (1517). Abnormal expression of circRNAs is observed in many cancers, such as the expression of circ104912 in laryngeal squamous cell cancer (18), of circ0001649 in hepatocellular carcinoma (19) and circ001988 in colorectal cancer (20). Most circRNAs play a regulatory role at the transcriptional and post-transcriptional levels and only a few function at the transcriptional level.

Little is known about the specific biological functions of circRNAs. Several recent breakthrough studies confirmed that some circRNAs could be used as competing endogenous RNAs (ceRNAs) to exert a regulatory effect on gene expression. CircRNA molecules enrich miRNA binding sites (21), which function as miRNA sponges (22) and play an important regulatory role in disease by interacting with disease-related miRNAs. Hansen et al (12) first found that circRNA-CDR1as (also called ciRS-7) abundantly expressed in human brain tissue, is antisense to the cerebellar degeneration-related protein 1 transcript (CDR1as). CDR1as contains 70 miR-7 binding sites and plays a negative regulatory role in miR-7 as an endogenous miRNA sponge. miR-7 is an important regulatory factor for a variety of cancer-related pathways (2326). Thus, ciRS-7 is likely to be an important regulatory factor in the development of nervous system disease and cancer (27,28). In colorectal cancers, circ001569 has been identified as a sponge of miR-145, which can inhibit tumor development through the upregulation of the expression of miR-145 target genes E2F5, BAG4 and FMNL2 (29). In bladder carcinomas, circTCF25 acts as a sponge for miR-103a and miR-107 which downregulate the expression of CDK6 and promote cell proliferation and migration (30). The above-mentioned studies indicate that circRNAs also function as ceRNAs, reveal a new regulation mode of circRNA on target genes by competitively binding to miRNA and reveal that circRNAs participate in various physiological and pathological processes.

The present study demonstrated that hundreds of circRNAs are differentially expressed in melanoma cell lines and normal melanocytes. Further comprehensive analysis revealed that the expression of circ0001056, circ0000082, circ0016418, circ0008602 and circ0033496 was upregulated in the WM35 and WM451 cells, indicating that they may play a similar role as cancer-promoting genes in the occurrence and development of melanoma. In WM35 vs. HM cells, WM451 vs. HM cells and WM451 vs. WM35 cells, the expression of circ0023988, circ0023990, circ0008157 and circ0030388 was downregulated. In combination with numerous previous studies (3143), our prediction results of the miRNA binding sites on the above-mentioned circRNAs using Arraystar miRNA target prediction software and GCBI (https://www.gcbi.com.cn/gclib/html/index) based on TargetScan and miRanda software revealed that miR-143-5p, miR-449a, miR-657, miR-200c-3p and miR-423-5p were abnormally expressed in a variety of tumor tissues (colorectal cancer, lung adenocarcinoma, breast, liver and ovarian cancer). The related target genes are involved in proliferation, apoptosis and cell cycle of various malignant tumor cells by participating in the Wnt/β-catenin, Notch, PI3K/AKT, NF-κB, p53, autophagy, angiogenesis and other signaling pathways. They produce a marked effect on tumorigenesis, invasion, metastasis and sensitivity to radiotherapy and chemotherapy (Table VII). Based on the results of qRT-PCR, significantly differentially-expressed circRNAs were silenced using siRNA interference, and then transfected into WM35 and WM45 cells. Compared with the WM451 cells, the proliferation and invasion of WM35 cells were promoted after the upregulated circRNAs (circ0023988, circ0008157 and circ0030388) in low-metastatic melanoma WM35 cells were silenced. Compared with the WM35 cells, the silencing of the upregulated circRNAs (circ0000082 and circ0016418) in high-metastatic melanoma WM451 cells inhibited the proliferation and invasion of WM451 cells, confirming that circ0030388, circ0016418, circ0023988, circ0008157 and circ0000082 were closely related to the proliferation and invasion of melanoma cells. The ceRNAs of circ0000082, circ0023988 and circ0008157 were further analyzed using MuTaMe. Many predicted miRNAs and target genes have been verified to be strongly associated with the proliferation, invasion and metastasis of melanoma in previous studies (4455) (Table VI). Although, the present study has identified the abnormally expressed circRNAs in MM cell lines, confirmed the adverse or positive effect on tumor development of five specific circRNAs and predicted the potential biological functions by previously reported circRNA-miRNA-mRNA networks, several limitations still exist. Only cell viability and invasion abilities of the identified circRNAs were evaluated, therefore it would be better to investigate other deeper functions in a future study, such as the regulation on cell material and energy metabolism, tumor metastasis or immune function. In addition, for the predicted circRNA targets, including miRNAs and mRNAs, more research is warranted to clarify in detail the underlying mechanisms of such circRNAs. Subsequently, on the basis of predicted miRNA, we will combine a microarray of mRNA sequencing before and after the predicted circRNA silencing and attempt to examine changes of the target genes. We may reveal the exact regulatory mechanisms of the circRNA-miRNA-mRNAs network which influence the occurrence and development of melanoma. Finally, we will analyze the effects of differentially expressed circRNAs combined miRNAs and target genes on melanoma according to the pathological type and prognosis of melanoma patients.

Table VII.

Functions of potential miRNAs target circRNAs.

Table VII.

Functions of potential miRNAs target circRNAs.

circRNAmiRNACancerTarget geneFunction
circRNA0001056miR-665GSRCC Invasion, metastasis, chemosensitivity
circRNA0000082miR-508-5pgastric cancer ABCB1[38], ZNRD1[38] chemosensitivity
miR-143-5pCRC, gastric cancerCOX-2Invasion and metastasis
circRNA0016418miR-214-5pHCC
miR-657HCC, laryngeal carcinoma TLE1[39]Proliferation
circRNA0008602miR-362-5pHCCCYLDProliferation, clone, invasion and metastasis
miR-544aNSCLCCDH1Proliferation, clone, invasion and metastasis
miR-200c-3pCRC, ovarian cancer
miR-17PCa, CRC, HCC, glioblastoma[41]TIMP3, PTEN[40] GalNT7[40], DNA-PK MDM2Proliferation, invasion and metastasis; cell cycle, angiogenesis; radiation and chemotherapy sensitivity
circRNA0033496miR-612HCC AKT2[43]Proliferation, invasion and metastasis
miR-502-5pCRC, breast cancer Rab1B[42], TRAF2Proliferation, cell cycle, apoptosis
miR-423-5pPC, CRC, HCC, gastric cancerβ-catenin, TFF1Proliferation, invasion and metastasis; cell cycle; apoptosis; chemosensitivity
circRNA0023990miR-339-5pNSCLC, CRC, breast cancer BCL-6[32], PRL-1[31] MDM2[33]Proliferation, invasion and metastasis
circRNA0030388miR-449aNSCLC, MM, gastric cancer, ovarian cancer, glioblastoma, endometrial cancerc-MET lncRNA NEAT1 E2F3, NOTCH1[36] CDK6, MAZ[37]Proliferation, cell cycle; apoptosis; chemotherapy sensitivity
miR-34c-5pCRC, PCa, glioblastoma, NPC, endometrial cancer Notch[34], Bmf c-myc, E2F3 MAPTcell cycle; apoptosis; radiation and chemotherapy sensitivity
miR-200a-3povarian cancer, glioblastoma MGMT[35]Chemotherapy sensitivity

[i] GSRCC, gastric signet ring cell carcinoma; PC, pancreatic carcinoma; CRC, colorectal cancer; NSCLC, non-small cell lung cancer; PCa, prostatic cancer; MM, melanoma.

Acknowledgements

The present study was supported by grants from the National Natural Science Foundation of China (nos. 8130168, 81272192 and 81171882) and the Hunan Natural Science Foundation (no. 2015JJ4053).

Competing interests

The authors declare that they have no competing interests.

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April 2018
Volume 39 Issue 4

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Online ISSN:1791-2431

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APA
Wang, Q., Chen, J., Wang, A., Sun, L., Qian, L., Zhou, X. ... Zhou, J. (2018). Differentially expressed circRNAs in melanocytes and melanoma cells and their effect on cell proliferation and invasion. Oncology Reports, 39, 1813-1824. https://doi.org/10.3892/or.2018.6263
MLA
Wang, Q., Chen, J., Wang, A., Sun, L., Qian, L., Zhou, X., Liu, Y., Tang, S., Chen, X., Cheng, Y., Cao, K., Zhou, J."Differentially expressed circRNAs in melanocytes and melanoma cells and their effect on cell proliferation and invasion". Oncology Reports 39.4 (2018): 1813-1824.
Chicago
Wang, Q., Chen, J., Wang, A., Sun, L., Qian, L., Zhou, X., Liu, Y., Tang, S., Chen, X., Cheng, Y., Cao, K., Zhou, J."Differentially expressed circRNAs in melanocytes and melanoma cells and their effect on cell proliferation and invasion". Oncology Reports 39, no. 4 (2018): 1813-1824. https://doi.org/10.3892/or.2018.6263