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Scientific Reports logoLink to Scientific Reports
. 2017 Aug 22;7:9060. doi: 10.1038/s41598-017-09076-6

Circular RNAs expression profiles in human gastric cancer

Yuan Dang 1, Xiaojuan Ouyang 1, Fan Zhang 1, Kai Wang 1, Youdong Lin 1, Baochang Sun 1, Yu Wang 2, Lie Wang 2,, Qiaojia Huang 1,
PMCID: PMC5567231  PMID: 28831102

Abstract

Circular RNAs (circRNAs) are implicated in a variety of cancers. However, the roles of circRNAs in gastric cancer (GC) remain largely unknown. In the current study, circRNAs expression profiles were screened in GC, using 5 pairs of GC and matched non-GC tissues with circRNA chip. Preliminary results were verified with quantitative PCR (qRT-PCR). Briefly, total of 713 circRNAs were differentially expressed in GC tissues vs. non-GC tissues (fold change ≥ 2.0, p < 0.05): 191 were upregulated, whereas 522 were downregulated in GC tissues. qRT-PCR analysis of randomly selected 7 circRNAs from the 713 circRNAs in 50 paired of GC vs. non-GC control tissues confirmed the microarray data. Gene ontology (GO) and KEGG pathway analyses showed that many circRNAs are implicated in carcinogenesis. Among differentially expressed circRNAs, hsa_circ_0076304, hsa_circ_0035431, and hsa_circ_0076305 had the highest magnitude of change. These results provided a preliminary landscape of circRNAs expression profile in GC.

Introduction

Gastric cancer (GC) is one of the most common cancers worldwide1. Diagnosis and treatment have improved over the last decades, but the 5-year survival rate remains low in patients with advanced GC2. A lack of reliable and efficient early diagnostic biomarkers, as well as, poorly understood molecular mechanisms of this disease is a major factor. To improve patient outcome, identifying effective biomarkers with early diagnostic value is essential. Novel biomarkers may also reflect the characteristics of cancer and clarify the molecular mechanisms of GC.

Over the past decade, the roles of non-coding RNA in cancer have been under intense investigation, encompassing miRNAs to long non-coding RNAs (lncRNA) and recently identified circular RNAs (circRNAs)3, 4. Accumulating evidence has demonstrated that both miRNAs and lncRNAs are closely associated with human cancers; many play crucial roles in cancer progression. Recent studies have implicated circRNAs in cancer development5. However, there have been relatively few reports describing circRNAs in GC.

CircRNAs are novel circular non-coding RNAs that are covalently closed6. CircRNAs could mediate the activity of microRNAs through binding and functioning as their sponges. Increasing evidence has suggested that circRNAs are often abnormally expressed in human cancers, and contribute to oncogenesis through miRNAs7. CircRNAs regulate cancer-related pathways and linear RNA transcription as well as protein expression8, 9. However, the expression levels and potential roles of circRNAs in GC are still poorly understood. In the present study, we investigated the alteration of circRNA expression profiles in GC tissues.

Materials and Methods

Tissue samples

A total of 55 patients (44 men and 11 women; mean age 59.8 years with a range of 23–81) with GC who underwent radical resection of the primary lesions between June 2014 and May 2015 at the Fuzhou General Hospital were included in this study. All tissues were histologically identified, diagnosed as gastric adenocarcinoma, and graded according to the guidelines of modified American Joint Committee on Cancer (AJCC). The initial screening step (Table 1) was conducted with microarray chip assay in 5 pairs of GC vs. non-GC tissue sample; the remaining 50 pairs were used for verification with quantitative reverse transcription PCR (qRT-PCR). Prior to analysis, all tissue samples were processed using a previously published method10 and stored at −80 °C.

Table 1.

The information of patients with gastric cancer subjected to circRNA expression profile chip assay.

NO Gender (male or female) Age (years) Histological type Histologic differentiation TNM stage
286 M 74 Ulcerative Moderately T2N0Mx
287 M 74 Ulcerative Poorly T4aN1Mx
292 M 78 Ulcerative Moderately T4aN2Mx
313 M 58 Ulcerative Moderately-poorly T2N0Mx
326 M 61 Ulcerative Moderately T4aN0Mx

RNA preparation for chip assay

TRIzol reagent (Invitrogen, Carlsbad, CA, USA) and mirVana miRNA Isolation Kit (Ambion, Austin, TX, USA) were used to isolate and purify total RNA. Sample quality (purity) was verified using standard spectrophotometer (ND-1000). The RNA integrity was assessed by electrophoresis with denaturing agarose gel.

Labeling and hybridization

After removing linear RNAs with ribonuclease R, RNA (5 μg from each sample) was reverse transcribed into cDNA using random primers containing T7 promoter by First Strand Enzyme Mix Kit. The DNA-RNA mixture was transformed to the second strand DNA by Second Strand Enzyme Mix. This DNA was used as a template to synthesize cRNA by the T7 enzyme mix. Subsequently, the cRNA was used as a template to obtain cDNA by reverse transcription through CbcScript II enzyme combined with random primers. This cDNA, in turn, was used as a template to synthesize the complementary strand DNA labeled fluorescently by Klenow Fragment enzyme combined with random primers and dNTP with fluorescent tags such as Cy3-dCTP and Cy5-dCTP. The samples were then hybridized with a  CapitalBio Technology Human CircRNA Array v1 (Agilent, USA).

Signals were scanned by Agilent G2565CA Microarray Scanner. Images were introduced into Agilent Feature Extraction to obtain raw data (v10.7). Differential expression was analyzed with Agilent GeneSpring software, and the processing included raw data quantile normalization and data analysis. Post quantile normalization by log2-ratio, low-intensity filtering was conducted, and circRNAs with at least 60 percent samples flagged as “Detected” were selected for further analysis: differentially expressed circRNAs were analyzed with Independent samples t-test. CircRNAs with ≥2.0 fold-changes (FC) and p < 0.05 were selected as circRNAs with significant differential expression11.

Bioinformatics analysis

circRNA targets identified with profiling data were subjected to gene ontology (GO) and KEGG pathway analyses based on their correlated mRNAs using Gene Ontology (http://www.geneongoloty.org/) and KOBAS software (KEGG Orthology-Based Annotation System). The differentially expressed circRNAs-targeted miRNAs were sought and predicted by miRanda software coupled with statistical analysis. In order to understand the association between circRNAs and their related miRNAs, 3 most significantly altered circRNAs were used to draw the circRNA-miRNA network using miRanda combined with patterning software. The circRNAs expression profile microarray chip assay and data and bioinformatics analysis were carried out by Capitalbio Corporation (Beijing, China).

qRT-PCR assay

Total RNA was extracted by TRIzol reagent as described previously10. The expression levels of 7 randomly selected differentially expressing circRNAs (Fold changes ≥ 2, p < 0.05) were measured by qRT-PCR; among them, 2 were upregulated and 5 were downregulated in the GC tissues: (upregulated: hsa_circ_0081146, hsa_circ_0084720), (downregulated: hsa_circ_0060108, hsa_circ_0057104, hsa_circ_0054971, hsa_circ_0063561, and hsa_circ_0058766). GAPDH expression was used as an internal reference. The primers used for these amplifications are listed in Table S1. PCRs were a relative estimation in triplicate as per the following temperature profile:denaturation 95 °C for 10 min followed by amplification by 40 cycles of 95 °C for 10 s and 60 °C for 1 min10.

Statistical analysis

For comparisons involving multiple groups, data were analyzed by analysis of variance (ANOVA); For analysis involving only two groups, data were analyzed with Student’s t-test. Results are expressed as the mean ± SEM. p < 0.05 was regarded as statistically significant. Data analysis was performed by Statistical Program for Social Sciences (SPSS) 22.0 software (SPSS, Chicago, IL, USA).

Compliance with ethical standards

The tissue samples used in this study were obtained with patients informed consent. All the methods were performed in compliance with the permitted or institutional protocols.This study was approved by the Fuzhou General Hospital Ethics Committee (No. 2014CXTD04). This article does not contain any studies with animals performed by any of the authors.

Results

CircRNAs expression profiles in GC

The microarray screening detected a total of 62,998 circRNAs, in GC, non-GC or both tissues (such information could be accessed with GSE100170 at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = GSE100170). As illustrated in Fig. 1, 713 of these exhibited differential expressions between GC and non-GC tissues (FC ≥ 2.0, p < 0.05) (Table S2), among which 191 were upregulated and the remaining 522 were downregulated in cancer tissues. A total of 207 circRNAs were differentially expressed between GC and non-GC tissues by both long and short probes (the two kinds of probe were named CBC1 and CBC2, respectively), among which 57 were upregulated and 150 were downregulated. The magnitude of fold change was highest for hsa_circ_0044516 in upregulated circRNAs (fold changes = 6.28, p = 0.036), and hsa_circ_0076305 for downregulated circRNAs (fold changes = −125.95, p = 0.030). Hierarchical clustering (Fig. 1A), volcano plots (Fig. 1B), and scatter plots (Fig. 1C) revealed that the expression profiles of circRNAs between GC and non-GC tissues were diverse. The top up- and down-regulated circRNAs are displayed in Table 2.

Figure 1.

Figure 1

Hierarchical clustering, volcano plots, and scatter plots exhibited the differentially expressed circRNAs in gastric cancer tissues compared to paired non-gastric cancer tissues. (A) Hierarchical clustering, numbers were the samples used for the microarray assay. C: cancer tissues, N: non-cancerous tissues. (B) Differentially expressed circRNAs were displayed by volcano plots. The green and red parts indicated >2 fold-decreased and -increased expression of the dysregulated circRNAs in GC tissues, respectively (p < 0.05). (C) Differentially expressed circRNAs were displayed by scatter plots. The green and red parts indicated >2 fold-decreased and -increased expression of the dysregulated circRNAs in GC tissues (p < 0.05).

Table 2.

The top up- and down-regulated differentially expressed circRNAs in GC tissues compared to those in non-cancerous tissues by both probes.

Name Probe CBC1 Probe CBC2 chr gene symbol
p FC (abs) Regulation p FC (abs) Regulation
hsa_circ_0076305 0.029925665 125.95259 down 0.03022709 109.61993 down chr6 PGC
hsa_circ_0076304 0.014676455 31.56073 down 0.011826442 28.374382 down chr6 PGC
hsa_circ_0035431 0.00300389 20.631256 down 0.003938972 21.39568 down chr15 CGNL1
hsa_circ_0000390 0.01983777 12.444183 down 0.026148466 7.417858 down chr12 FGD4
hsa_circ_0037362 0.027888432 10.314745 down 0.014241457 8.81237 down chr16 C16orf73
hsa_circ_0076307 0.025423396 9.498694 down 0.020947674 15.158471 down chr6 PGC
hsa_circ_0037361 0.027664987 9.436992 down 0.002388634 12.108136 down chr16 C16orf73
hsa_circ_0007315 0.042465463 9.14959 down 0.03788745 8.887227 down chr3 PVRL3
hsa_circ_0027969 0.014839446 8.641936 down 0.03794105 7.963011 down chr12 SLC41A2
hsa_circ_0001679 0.031237341 8.059054 down 0.04918231 6.926098 down chr7 GLCCI1
hsa_circ_0035435 0.014802514 7.2164187 down 0.045140408 5.798211 down chr15 CGNL1
hsa_circ_0027971 0.03575782 7.201395 down 0.008316714 9.217224 down chr12 SLC41A2
hsa_circ_0073770 0.008143293 6.911025 down 0.006314759 6.7912025 down chr5 SLC12A2
hsa_circ_0074239 0.002184121 6.5593286 down 0.003311638 5.6043277 down chr5 C5orf32
hsa_circ_0051995 0.020385692 6.4125986 down 0.027742783 5.7211037 down chr19 VRK3
hsa_circ_0025842 0.024139885 6.305559 down 0.019139148 6.9465156 down chr12 FGD4
hsa_circ_0077736 0.048207846 6.2890162 down 0.033191722 6.435054 down chr6 CEP85L
hsa_circ_0006034 0.01381651 6.038208 down 0.003529549 6.7874093 down chr5 SLC12A2
hsa_circ_0066971 0.011570533 5.8554688 down 0.036805384 5.452018 down chr3 EAF2
hsa_circ_0035432 0.011778097 5.5990286 down 0.011175622 6.2109637 down chr15 CGNL1
hsa_circ_0044516 0.036079686 6.276136 up 0.04336383 5.479236 up chr17 COL1A1
hsa_circ_0044518 0.037375137 5.72242 up 0.04342119 3.3064938 up chr17 COL1A1
hsa_circ_0077033 0.018847013 5.221709 up 0.023423905 5.7803392 up chr6 COL12A1
hsa_circ_0006401 0.013833045 4.9873238 up 0.017758103 4.545301 up chr2 COL6A3
hsa_circ_0081090 0.036175337 4.5390043 up 0.021447672 6.136692 up chr7 COL1A2
hsa_circ_0058132 0.045273677 4.3983254 up 0.022904716 4.0176225 up chr2 FN1
hsa_circ_0081146 0.010543266 4.187957 up 0.011812083 4.0625715 up chr7 COL1A2
hsa_circ_0058100 0.047036752 4.166924 up 0.04413781 4.6881175 up chr2 FN1
hsa_circ_0081091 0.008671624 3.9734251 up 0.014162468 3.2844515 up chr7 COL1A2
hsa_circ_0091742 0.005013032 3.8982337 up 0.014553196 5.383641 up chrX BGN
hsa_circ_0058097 0.049916536 3.8704908 up 0.033016972 4.187093 up chr2 FN1
hsa_circ_0081136 0.013954006 3.6851623 up 0.021678727 3.2075522 up chr7 COL1A2
hsa_circ_0044519 0.03606566 3.6805367 up 0.03702461 6.5064387 up chr17 COL1A1
hsa_circ_0016294 0.034532506 3.5717776 up 0.038935255 3.4514186 up chr1 CD55
hsa_circ_0081143 0.002223194 3.5639381 up 0.03638 3.226277 up chr7 COL1A2
hsa_circ_0044515 0.048010923 3.5043917 up 0.047074426 5.2711334 up chr17 COL1A1
hsa_circ_0081066 0.040320095 3.4538522 up 0.006778345 3.5394926 up chr7 COL1A2
hsa_circ_0016292 0.016833305 3.2611954 up 0.017872557 3.1238286 up chr1 CD55
hsa_circ_0091743 0.015532353 3.1929755 up 0.006474511 3.045686 up chrX BGN
hsa_circ_0020788 0.005037079 3.030931 up 0.005184689 3.8050945 up chr11 TCONS_00063837_H19

FC: Fold changes. abs: absolute value.

The results of qRT-PCR verification of the differentially expressed circRNAs

Seven differentially expressed circRNAs were randomly selected for qRT-PCR verification  by using 50 paired of samples. The results confirmed the upregulation of hsa_circ_0081146 and hsa_circ_0084720 in GC, and downregulation of hsa_circ_0060108, hsa_circ_0057104, hsa_circ_0054971, hsa_circ_0063561, and hsa_circ_0058766 in GC (Fig. 2).

Figure 2.

Figure 2

Verification of the differentially expressed circRNAs by qRT-PCR. The expression of 7 lncRNAs in 50 paired GC tissues was detected by qRT-PCR, which were shown by the expression fold changes. Comparison of the results obtained from qPCR and microarray assay revealed satisfactory consistency.

The results of bioinformatics analysis

Differentially expressed circRNAs could be mapped to all chromosomes, except for chromosome 21 and Y. A lot of miRNAs were predicted to be their targets (Table 3). 1026 miRNAs were predicted to be the targets of hsa_circ_0001210, which is an intragenic circRNA, located on chromosome 22 with a length of 25285 nt and downregulated in GC. 116 mRNAs were shown to be the potential corresponding linear transcripts of these dysregulated circRNAs (Table S3). GO, KEGG, and enrichment (Table S4) analyses suggest that these differentially expressed circRNAs are relevant to several vital physiological processes, cellular components, molecular functions, and critical signaling pathways such as growth factor binding, cell adhesion molecule binding, and response to transforming growth factor beta (TGF-β). Many of the known pathways associated with carcinogenesis, such as focal adhesion pathway, PI3K–Akt signaling pathway, and degradation of the extracellular matrix pathway were also implicated. Figure 3A–C illustrated the top 30 significantly enriched GO terms, pathway terms, and disease terms.

Table 3.

The numbers of potential targeted miRNAs of the differentially expressed circRNAs.

ProbeName p FC (abs) Regulation chr gene symbol No. miRNA targets
hsa_circ_0006401 0.013833045 4.9873238 up chr2 COL6A3 17
hsa_circ_0014202 0.008794556 2.5519805 up chr1 S100A10 4
hsa_circ_0016292 0.016833305 3.2611954 up chr1 CD55 0
hsa_circ_0016294 0.034532506 3.5717776 up chr1 CD55 0
hsa_circ_0018424 0.004929639 2.2052047 up chr10 BICC1 1
hsa_circ_0020788 0.005037079 3.030931 up chr11 TCONS_00063837_H19 0
hsa_circ_0020790 0.002316416 2.4726825 up chr11 TCONS_00063837_H19 0
hsa_circ_0034428 0.03272182 2.6071007 up chr15 THBS1 87
hsa_circ_0034475 0.028014906 2.2003295 up chr15 THBS1 23
hsa_circ_0034495 0.018290553 2.2112164 up chr15 THBS1 3
hsa_circ_0034496 0.023052732 2.150319 up chr15 THBS1 8
hsa_circ_0035137 0.026556138 2.3628845 up chr15 FBN1 1
hsa_circ_0044513 0.044563152 2.5272765 up chr17 COL1A1 46
hsa_circ_0044515 0.048010923 3.5043917 up chr17 COL1A1 180
hsa_circ_0044516 0.036079686 6.276136 up chr17 COL1A1 191
hsa_circ_0044517 0.03509533 2.7368069 up chr17 COL1A1 230
hsa_circ_0044518 0.037375137 5.72242 up chr17 COL1A1 245
hsa_circ_0044519 0.03606566 3.6805367 up chr17 COL1A1 267
hsa_circ_0044521 0.03614439 2.4449718 up chr17 COL1A1 176
hsa_circ_0046707 0.033796836 2.1029172 up chr18 SMCHD1 5
hsa_circ_0057391 0.04772664 2.256704 up chr2 COL3A1 193
hsa_circ_0057403 0.03509203 2.146545 up chr2 COL3A1 46
hsa_circ_0058097 0.049916536 3.8704908 up chr2 FN1 159
hsa_circ_0058100 0.047036752 4.166924 up chr2 FN1 56
hsa_circ_0058132 0.045273677 4.3983254 up chr2 FN1 9
hsa_circ_0077033 0.018847013 5.221709 up chr6 COL12A1 13
hsa_circ_0077055 0.038407695 2.5744588 up chr6 COL12A1 0
hsa_circ_0077056 0.04552718 2.9007647 up chr6 COL12A1 1
hsa_circ_0077057 0.04089677 2.6701639 up chr6 COL12A1 0
hsa_circ_0080229 0.03741656 2.027931 up chr7 EGFR 0
hsa_circ_0081066 0.040320095 3.4538522 up chr7 COL1A2 243
hsa_circ_0081084 0.032507733 2.7151222 up chr7 COL1A2 136
hsa_circ_0081089 0.03845984 2.0764067 up chr7 COL1A2 163
hsa_circ_0081090 0.036175337 4.5390043 up chr7 COL1A2 227
hsa_circ_0081091 0.008671624 3.9734251 up chr7 COL1A2 260
hsa_circ_0081092 0.044405155 2.7602344 up chr7 COL1A2 4
hsa_circ_0081111 0.005212786 4.0334992 up chr7 COL1A2 237
hsa_circ_0081125 0.013989674 2.8943481 up chr7 COL1A2 182
hsa_circ_0081136 0.013954006 3.6851623 up chr7 COL1A2 156
hsa_circ_0081137 0.039436605 2.9486153 up chr7 COL1A2 112
hsa_circ_0081138 0.047790088 2.2264013 up chr7 COL1A2 121
hsa_circ_0081143 0.002223194 3.5639381 up chr7 COL1A2 89
hsa_circ_0081146 0.010543266 4.187957 up chr7 COL1A2 121
hsa_circ_0081149 0.045875933 2.6191776 up chr7 COL1A2 69
hsa_circ_0081152 0.011682078 2.843584 up chr7 COL1A2 99
hsa_circ_0081155 0.00731891 2.8246753 up chr7 COL1A2 94
hsa_circ_0081159 0.006505117 2.5019772 up chr7 COL1A2 76
hsa_circ_0081160 0.04243376 2.0236626 up chr7 COL1A2 4
hsa_circ_0081163 0.044002496 2.5647683 up chr7 COL1A2 10
hsa_circ_0081167 0.0097287 3.1536498 up chr7 COL1A2 24
hsa_circ_0084720 0.02980772 3.712714 up chr8 SULF1 4
hsa_circ_0087215 0.023945637 2.500071 up chr9 ANXA1
hsa_circ_0089433 0.008899449 2.1055155 up chr9 COL5A1 364
hsa_circ_0090450 1.11E-04 3.8579054 up chrX TIMP1 11
hsa_circ_0090452 0.003296774 2.235864 up chrX TIMP1 5
hsa_circ_0091742 0.005013032 3.8982337 up chrX BGN 192
hsa_circ_0091743 0.015532353 3.1929755 up chrX BGN 181
hsa_circ_0000019 0.020847283 2.5991628 down chr1 DDI2 0
hsa_circ_0000258 0.042388447 2.687611 down chr10 PDCD11 0
hsa_circ_0000390 0.01983777 12.444183 down chr12 FGD4 0
hsa_circ_0000580 0.04103441 4.64374 down chr14 None 0
hsa_circ_0000615 0.047749862 5.541818 down chr15 ZNF609 17
hsa_circ_0000642 0.040490992 2.6040976 down chr15 ZFAND6 2
hsa_circ_0001074 0.030960364 3.0543585 down chr2 ORC4 0
hsa_circ_0001112 0.018396724 2.6625469 down chr2 DGKD 0
hsa_circ_0001114 5.34E-04 3.171953 down chr2 DGKD 0
hsa_circ_0001210 0.03488208 2.5489702 down chr22 None 1026
hsa_circ_0001216 0.026226409 3.7022111 down chr22 XBP1 2
hsa_circ_0001438 0.029758973 6.8401494 down chr4 LARP1B 0
hsa_circ_0001679 0.031237341 8.059054 down chr7 GLCCI1 2
hsa_circ_0001998 0.025869323 2.7446353 down chr14 FUT8 0
hsa_circ_0002110 0.018834386 2.806639 down chr12 AMN1 0
hsa_circ_0002138 0.032208133 3.2452636 down chr15 USP3 0
hsa_circ_0002190 0.030215895 2.5628076 down chr7 KLHDC10 1
hsa_circ_0002422 0.037262026 4.9764647 down chr3 FNDC3B 7
hsa_circ_0002449 0.005389997 4.227186 down chr5 C5orf32 3
hsa_circ_0002504 0.03395744 2.3386385 down chr17 ENGASE 4
hsa_circ_0003012 0.0350584 5.214465 down chr12 SLC41A2 0
hsa_circ_0003201 0.017809883 2.6226783 down chr4 TBC1D14 0
hsa_circ_0003787 0.009270906 5.055101 down chr5 RGNEF 2
hsa_circ_0003911 0.0193295 3.0724642 down chr16 CNOT1 8
hsa_circ_0004689 0.043355685 6.3922377 down chr1 SWT1 0
hsa_circ_0005028 0.004585072 2.5328124 down chr3 TSEN2 0
hsa_circ_0005135 0.025206376 2.680219 down chr19 LOC100506033 1
hsa_circ_0006034 0.01381651 6.038208 down chr5 SLC12A2 1
hsa_circ_0006511 0.008116972 2.9554853 down chr2 FARP2 2
hsa_circ_0007315 0.042465463 9.14959 down chr3 PVRL3 0
hsa_circ_0007538 0.021333938 2.2191985 down chr1 C1orf27 0
hsa_circ_0007619 0.024274996 6.2581415 down chr4 LARP1B 0
hsa_circ_0007715 0.02931771 3.3169591 down chr19 CIRBP 4
hsa_circ_0007754 0.007596167 2.5428722 down chr13 PCCA 0
hsa_circ_0007840 0.01876142 2.3082905 down chr15 COX5A 0
hsa_circ_0008962 0.023675451 2.5180075 down chr5 ELL2 0
hsa_circ_0011092 0.027778216 2.8495584 down chr1 STX12 0
hsa_circ_0014614 0.046407204 3.509566 down chr1 DAP3 1
hsa_circ_0015948 0.036354423 2.187048 down chr1 IPO9 4
hsa_circ_0017445 0.032844365 4.300893 down chr10 WDR37 0
hsa_circ_0017974 0.003326846 2.0536025 down chr10 KIAA1217 3
hsa_circ_0020752 0.038835317 3.8155284 down chr11 None 18
hsa_circ_0020757 0.045137018 3.7709012 down chr11 None 481
hsa_circ_0020762 0.049438722 3.4821498 down chr11 None 729
hsa_circ_0020763 0.024364103 7.188659 down chr11 None 623
hsa_circ_0022351 0.048745744 2.1941059 down chr11 C11orf9 22
hsa_circ_0023597 0.025558302 2.48522 down chr11 XRRA1 2
hsa_circ_0025842 0.024139885 6.305559 down chr12 FGD4 14
hsa_circ_0025847 0.01065637 6.9226236 down chr12 FGD4 0
hsa_circ_0027969 0.014839446 8.641936 down chr12 SLC41A2 1
hsa_circ_0027971 0.03575782 7.201395 down chr12 SLC41A2 1
hsa_circ_0028323 0.03792535 4.157252 down chr12 TMEM116 0
hsa_circ_0029235 0.04259122 2.0699773 down chr12 DDX55 0
hsa_circ_0031281 0.016793832 2.7682478 down chr14 SLC7A8 0
hsa_circ_0031423 0.020782415 2.8116136 down chr14 SCFD1 2
hsa_circ_0035431 0.00300389 20.631256 down chr15 CGNL1 46
hsa_circ_0035432 0.011778097 5.5990286 down chr15 CGNL1 74
hsa_circ_0035435 0.014802514 7.2164187 down chr15 CGNL1 9
hsa_circ_0035875 0.039918724 2.113102 down chr15 SPG21 0
hsa_circ_0036510 0.028307231 2.6944883 down chr15 ZFAND6 1
hsa_circ_0037361 0.027664987 9.436992 down chr16 C16orf73 0
hsa_circ_0037362 0.027888432 10.314745 down chr16 C16orf73 0
hsa_circ_0037861 0.017640278 3.1812923 down chr16 TXNDC11 0
hsa_circ_0037862 0.02676344 5.1893096 down chr16 TXNDC11 3
hsa_circ_0037863 0.014628965 3.431537 down chr16 TXNDC11 11
hsa_circ_0038521 0.012550134 3.4246309 down chr16 CDR2 41
hsa_circ_0039090 0.008517502 2.1161213 down chr16 SRCAP 467
hsa_circ_0039216 0.032217234 2.741417 down chr16 GPT2 1
hsa_circ_0039218 0.028291393 3.9539077 down chr16 GPT2 15
hsa_circ_0039271 0.047586497 2.770235 down chr16 PHKB 4
hsa_circ_0039658 0.04334005 3.0598512 down chr16 CNOT1 14
hsa_circ_0039940 0.016690876 2.131468 down chr16 SLC7A6 0
hsa_circ_0040081 0.013927639 2.3884165 down chr16 NQO1 0
hsa_circ_0040373 0.021966241 3.0635164 down chr16 AP1G1 11
hsa_circ_0040388 0.018369772 2.0574872 down chr16 AP1G1 3
hsa_circ_0041440 0.023598213 2.3573241 down chr17 RAP1GAP2 53
hsa_circ_0042853 0.049323324 2.8299448 down chr17 TCONS_00025103 0
hsa_circ_0042968 0.027372789 2.9627814 down chr17 SUZ12 1
hsa_circ_0045272 0.041974243 2.0751245 down chr17 ERN1 7
hsa_circ_0047700 0.02186925 5.2570233 down chr18 ME2 0
hsa_circ_0047785 0.049457386 2.5616474 down chr18 ATP8B1 6
hsa_circ_0047975 0.044554852 2.6958208 down chr18 ZNF236 40
hsa_circ_0048201 0.024692174 2.7309535 down chr19 STK11 110
hsa_circ_0048536 0.049628958 2.0178084 down chr19 EEF2 63
hsa_circ_0049289 0.034041822 4.4006753 down chr19 SLC44A2 226
hsa_circ_0051047 0.04167667 2.575785 down chr19 FCGBP 432
hsa_circ_0051050 0.043033753 3.2892206 down chr19 FCGBP 3
hsa_circ_0051995 0.020385692 6.4125986 down chr19 VRK3 14
hsa_circ_0054086 0.032298878 3.289804 down chr2 HEATR5B 6
hsa_circ_0054186 0.044439603 3.2368143 down chr2 MAP4K3 0
hsa_circ_0054970 0.030601952 5.295868 down chr2 SLC1A4 0
hsa_circ_0054971 0.02345602 3.2384007 down chr2 SLC1A4 0
hsa_circ_0056240 0.008702193 3.180426 down chr2 PTPN4 0
hsa_circ_0057104 0.047582004 4.0253515 down chr2 PDK1 1
hsa_circ_0057105 0.03679815 3.6738498 down chr2 PDK1 2
hsa_circ_0057106 0.047164652 4.9790606 down chr2 PDK1 1
hsa_circ_0057480 0.030882323 3.0643332 down chr2 PMS1 1
hsa_circ_0058443 0.008067183 4.725038 down chr2 ACSL3 1
hsa_circ_0058762 0.012233879 4.721563 down chr2 DGKD 0
hsa_circ_0058766 0.002712246 3.6002114 down chr2 DGKD 1
hsa_circ_0058767 0.020062199 2.9678054 down chr2 DGKD 18
hsa_circ_0058768 0.001202278 2.1620224 down chr2 DGKD 75
hsa_circ_0058769 0.001321101 2.6733668 down chr2 DGKD 32
hsa_circ_0058770 0.005304494 5.227343 down chr2 DGKD 0
hsa_circ_0060108 0.011829588 2.895927 down chr20 FER1L4 217
hsa_circ_0062721 0.03316098 3.6204636 down chr22 XBP1 26
hsa_circ_0063555 0.038891237 2.0088708 down chr22 ACO2 23
hsa_circ_0063561 0.016673693 2.77844 down chr22 ACO2 35
hsa_circ_0063562 0.03148357 4.083042 down chr22 ACO2 9
hsa_circ_0063563 0.015282579 3.6569278 down chr22 ACO2 9
hsa_circ_0063567 0.019898534 2.1735334 down chr22 ACO2 0
hsa_circ_0065143 0.040677425 2.0057971 down chr3 SETD2 57
hsa_circ_0066873 0.048354574 3.8894832 down chr3 TIMMDC1 0
hsa_circ_0066877 0.034795098 3.1437237 down chr3 TIMMDC1 0
hsa_circ_0066971 0.011570533 5.8554688 down chr3 EAF2 0
hsa_circ_0067450 0.01625185 7.951924 down chr3 PPP2R3A 6
hsa_circ_0068032 0.035557568 4.645977 down chr3 NAALADL2 5
hsa_circ_0069113 0.027285358 2.006047 down chr4 TBC1D14 0
hsa_circ_0069114 0.002569319 2.1330538 down chr4 TBC1D14 0
hsa_circ_0070936 0.04316312 2.6107051 down chr4 LARP1B 7
hsa_circ_0071107 0.006979433 3.2499113 down chr4 ARHGAP10 2
hsa_circ_0071321 9.78E-04 4.8015165 down chr4 FGA 3
hsa_circ_0072309 0.002072746 7.3090854 down chr5 LIFR 0
hsa_circ_0072789 0.009060388 3.3077662 down chr5 MARVELD2 9
hsa_circ_0072997 0.048613824 2.7817066 down chr5 RGNEF 1
hsa_circ_0072998 0.015955605 5.7427354 down chr5 RGNEF 0
hsa_circ_0073006 0.014696714 2.9636796 down chr5 RGNEF 35
hsa_circ_0073035 0.013912499 2.19241 down chr5 HMGCR 0
hsa_circ_0073244 0.004625377 4.716427 down chr5 EDIL3 0
hsa_circ_0073582 0.019003673 3.4118779 down chr5 EPB41L4A 0
hsa_circ_0073763 0.029358098 2.9471374 down chr5 SLC12A2 2
hsa_circ_0073768 0.029927656 4.6921773 down chr5 SLC12A2 1
hsa_circ_0073769 0.005703302 3.6955311 down chr5 SLC12A2 1
hsa_circ_0073770 0.008143293 6.911025 down chr5 SLC12A2 1
hsa_circ_0073771 0.031154156 4.1421623 down chr5 SLC12A2 1
hsa_circ_0073772 0.031598363 3.3706727 down chr5 SLC12A2 1
hsa_circ_0073955 0.03778204 4.6350393 down chr5 SEC. 24 A 21
hsa_circ_0074239 0.002184121 6.5593286 down chr5 C5orf32 13
hsa_circ_0075447 0.043269653 4.7036705 down chr6 GMDS 0
hsa_circ_0075538 0.018290881 4.5513425 down chr6 F13A1 19
hsa_circ_0076303 0.0419991 2.85898 down chr6 PGC 16
hsa_circ_0076304 0.014676455 31.56073 down chr6 PGC 35
hsa_circ_0076305 0.029925665 125.95259 down chr6 PGC 49
hsa_circ_0076307 0.025423396 9.498694 down chr6 PGC 1
hsa_circ_0077168 0.04191364 2.536258 down chr6 BCKDHB 1
hsa_circ_0077736 0.048207846 6.2890162 down chr6 CEP85L 2
hsa_circ_0082915 0.022677844 2.0698295 down chr7 SLC4A2 2
hsa_circ_0083027 0.02473872 3.3468018 down chr7 MLL3 8
hsa_circ_0084925 0.017582932 5.8715267 down chr8 KIAA1429 0
hsa_circ_0088633 0.002749995 2.1568172 down chr9 GARNL3 0

Figure 3.

Figure 3

Results of Gene Ontology, KEGG pathway, and disease enrichment analysis. (A) Top 30 classes of GO enrichment terms. (B) Top 30 classes of KEGG pathway enrichment terms. (C) Top 30 disease enrichment terms.

CircRNA-miRNA network

The 3 circRNAs with most robust differential expression were used to construct a  represent circRNA-miRNA network. The CBC1 and CBC2 probes identified a total of 207 differentially expressed circRNAs; among these circRNAs, hsa_circ_0076304, hsa_circ_0035431, and hsa_circ_0076305 had the highest magnitude of difference. Figure 4 illustrates the interaction of the 3 circRNAs with miRNA.

Figure 4.

Figure 4

Represent circRNA-miRNA network. This network was based on the expression profile results and the related software. The 3 dysregulated circRNAs, hsa_circ_0076304, hsa_circ_0035431, and hsa_circ_0076305 (purple red nodes) having the highest magnitude of change, were predicted to be functionally connected with their targeted miRNAs in the network.

Discussion

CircRNAs are recently identified as disease-related and ubiquitously expressed noncoding RNAs, that can act as sponges of miRNAs and affect the expression of parent gene1114. During the past several years, increasing evidence suggested that circRNAs play a vital role in cancer development and may be used as novel biomarkers1518. By comparing circRNAs expression profiles in parental cell line and established cell line with radioresistant effects, Su et al. found that dysregulated circRNAs are related to the progression of radiation resistance in esophageal cancer cells19. Huang et al.20 reported that dysregulated lncRNAs and circRNAs are linked to the development of bladder cancer. They identified that several hundreds of circRNAs showed altered expression in bladder cancer tissues as analyzed by the expression profiles of 4 paired cancer and para-carcinoma tissues. They postulated that several of the dysregulated circRNAs are functional molecules and contribute to bladder cancer tumorigenesis. In the present study, 207 circRNAs were found to be differentially expressed  between GC and non-cancerous tissues by both CBC1 and CBC2 probes in the microarray chip. Hsa_circ_0044516 had the highest magnitude of upregulation, whereas hsa_circ_0076305 had the highest magnitude of downregulation. The randomly selected 7 circRNAs that were significantly altered were further verified by qRT-PCR. These results conformed the validity of the microarray findings.

Some of the previously identified circRNAs are implicated  to be associated with tumorigenesis and malignant behavior of cancer cells, such as uncontrolled growth, proliferation, migration, and invasion. For example, Hsa_circ_0067934 has been shown to be upregulated in esophageal squamous cell carcinoma (ESCC)21, and associated with poor tumor differentiation. In their findings, hsa_circ_0067934 was able to increase ESCC cell proliferation, migration, and cell cycle progression21. Xu et al.22 showed that patients with hepatocellular carcinoma (HCC) with higher expression level of circular RNA ciRS-7 (Cdr1as) in cancerous tissues had shorter median recurrent time than those with lower circRNA expression. Additionally, Cdr1as was related to the high hepatic microvascular invasion (MVI) in HCC, and the mechanism may be associated with its potential activity as the sponge of miR-7. Therefore, the study concluded that Cdr1as might be a novel biomarker and treatment target for MVI.

CircRNAs can regulate the transcription of parent genes. In the present study, we identified 116 corresponding linear mRNAs. GO and pathway enrichment analysis showed that these mRNAs are involved in critical pathways associated with cancer, including the PI3K-AKT pathway. Previously studies have shown that activation of the PI3K-AKT pathway promote cancer cell growth and proliferation23, 24. One of the potential targets of hsa_circ_0039090, hsa-let-7c-5p is  associated with stage I endometrioid endometrial carcinoma progression potentially through regulation of cell cycle pathway25. Hsa-miR-107, one of the targets of several dysregulated circRNAs identified in the present study, is widely confirmed to be associated with cancers2630, which is the downstream target of circTCF25, and the interaction between this circRNA with miR-107 and miR-103a-3p leads to increased proliferation and migration of bladder cancer cells31.

CircRNA-miRNA network is a widely accepted approach for exploring the function of dysregulated circRNAs and the interaction between these two types of non-coding RNAs. Hence, this network was constructed based on the microarray data. Among altered circRNAs, hsa_circ_0076304, hsa_circ_0035431, and hsa_circ_0076305 had the highest magnitude of difference. Concurrently, the potential links between them and the most important targeted miRNAs were established.

In summary, this study provided a preliminary landscape of circRNA differential expression in GC vs. non-GC. Further studies are required to explore their potential as biomarkers for GC as well as their pathologic role.

Electronic supplementary material

Table S1 (84.7KB, pdf)
Table S2 (588.2KB, xlsx)
Table S3 (94KB, xls)
Table S4 (451KB, xlsx)

Acknowledgements

This work was supported by the Innovation Team Foundation of Fuzhou General Hospital (No. 2014CXTD04; to Lie Wang), the National Natural Science Foundation of China (No. 81372788; to Qiaojia Huang), the Medical Scientific Research Key Foundation of Nanjing Command (No. 11Z032; Qiaojia Huang), and the Natural Science Foundation of Fujian Province (No. 2014J01427; to Qiaojia Huang).

Author Contributions

Y.D. performed the qRT-PCR and collected data. X.O., K.W., F.Z., Y.L. and B.S. participated in samples collected. L.W. and Y.W. guided major fresh samples collected. L.W. also contributed to the major funding support. Q.H. designed the study. Q.H. and Y.D. wrote the manuscript. All authors read and approved the final manuscript.

Competing Interests

The authors declare that they have no competing interests.

Footnotes

Electronic supplementary material

Supplementary information accompanies this paper at doi:10.1038/s41598-017-09076-6

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Lie Wang, Email: fzptwk@xmu.edu.cn.

Qiaojia Huang, Email: huangqj100@126.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1 (84.7KB, pdf)
Table S2 (588.2KB, xlsx)
Table S3 (94KB, xls)
Table S4 (451KB, xlsx)

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