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Abstract

Gastric cancer is one of the most common cancers in the world. However, current medical technologies have not identified a reliable method to cure advanced gastric cancer, and early gastric cancer is difficult to diagnose. Therefore, we focused on circular RNAs (circRNAs) that have been proven to be involved in the carcinogenesis of gastric cancer. We first used quantitative reverse transcription-polymerase chain reaction (qRT-PCR) to evaluate the expression levels of hsa_circ_0005654 in 301 tissues, including 122 healthy gastric mucosa samples, 68 paired tissues from early gastric cancer and adjacent nontumor mucosae obtained by submucosal dissection, and 43 chronic gastritis tissues. Then, we analyzed the relationship between the expression levels of hsa_circ_0005654 and the clinicopathological characteristics of patients with early gastric cancer. We ultimately confirmed the clinical diagnostic value of hsa_circ_0005654 through generating receiver operating characteristic (ROC) curves and comparing the areas under the ROC curves (AUCs).

Our data revealed that hsa_circ_0005654 was significantly downregulated in early gastric cancer tissues compared with matched normal mucosae ( $P<$ 0.001). Meanwhile, the expression levels of hsa_circ_0005654 in early gastric cancer tissues were also obviously lower than those in chronic gastritis tissues ( $P<$ 0.001). The AUCs of early gastric cancer tissues vs. paired normal adjacent mucosae, and that of early gastric cancer vs. healthy controls, were 0.927 and 0.924, respectively. These results clearly demonstrated that hsa_circ_0005654 may serve as a new and promising diagnostic biomarker for screening early gastric cancer. The AUC, sensitivity and specificity of hsa_circ_0005654 are significantly higher than those of present gastric cancer associated-biomarkers.

Keywords

Early gastric cancer circular RNA hsa_circ_0005654 biomarker clinical significance

1. Introduction

Cancer incidence and mortality are rapidly growing in the world [1, 2]. In spite of chemotherapy having a crucial therapeutic value, surgery, which causes substantial patient suffering, is the only known form of curative treatment for most patients with advanced gastric malignancy and soft-tissue sarcomas [3, 4, 5]. In other words, modern medicine still lacks effective treatments for advanced gastric cancer. Accordingly, it is urgently necessary for us to seek new biomarkers of early gastric cancer.

Circular RNAs (circRNAs) that have higher tissue specificity and more stable structures compared with linear RNAs are a unique set of noncoding RNAs [6]. Basically, circRNAs are synthesized by a proactive back-splice event as loops without 5’ caps and 3’ poly (A) tails, and as a consequence, they are difficult to be degraded by ribonucleases including RNase R and exonucleases and more likely to maintain stable expression and thus can be used as biomarkers in diagnosis [7, 8].

CircRNAs play a vital role in gene regulation, neural development and in the initiation and progression of numerous diseases such as atherosclerotic vascular diseases, neurological disorders, cardiovascular diseases and most heart diseases [9, 10, 11, 12, 13]. In addition, some researchers found that circRNAs in human saliva can be used as disease biomarkers [14]. Additionally, some findings indicated that circ_10720, hsa_circ_0064428 and circMTO1 may serve as potential new biomarkers of hepatocellular carcinoma; plasma circ_002453 was also identified as a diagnostic biomarker of lupus nephritis; and hsa_circ_0036877 as a potential novel blood biomarker for early pre-eclampsia was discovered by some scientists [15, 16, 17, 18, 19]. What’s more, fusion circRNAs (f-circRNAs) that are produced from transcribed exons of distinct genes are able to increase the cellular proliferation rate and contribute to cellular transformation and tumorigenesis [20].

Gastric cancer is one of the most common malignant tumors in the world and the second leading cause of cancer-related death worldwide, especially in Eastern Asia, Eastern Europe, and South America [21, 22]. Although surgical techniques integrated with chemotherapy strategies have developed at a rapid pace in recent years, the treatment effectiveness of advanced gastric cancer has not shown any improvement. This is mainly because most patients with gastric cancer cannot be diagnosed in the early phase and thus lose their best curative chance; a recent study suggested that 90% of early gastric cancer patients can be cured [23]. Therefore, the key to overcoming the gastric cancer problem is to diagnose it earlier. Early gastric cancer is gastric cancer limited to the mucosal or superficial submucosal layers regardless of lymph node metastasis, with 0-IIa, 0-IIb, 0-IIc, 0-IIa $+$ IIc, or 0-IIc $+$ IIa gastric cancer morphology [24, 25].

Endoscopy followed by pathological diagnosis is still the gold standard for gastric cancer diagnosis. As we all know, endoscopy is a subjective method of diagnosis that may result in misdiagnoses, and whether we can find gastric cancer correctly relies entirely on the experience of the endoscopists. The traditional biomarkers, for example, carbohydrate antigen 19-9 (CA19-9), whose sensitivity and specificity are 60.5% and 55.9%, respectively, cannot diagnose early gastric cancer effectively [26]. Thus, to improve the diagnostic rate of early gastric cancer, finding high-efficiency biomarkers is crucially important.

New types of biomarkers have successfully been identified in recent years [27, 28, 29]. More interestingly, Li et al. found that a combination of different circRNAs that have been identified as cancer biomarkers may increase the specificity and sensitivity of detecting a variety of malignancies as compared with a single circRNA [30].

On account of circRNAs as a category of new biomarkers being related to a large variety of diseases, we began to focus our attention on investigating the roles of circRNAs in gastric cancer. We have explored the global circular RNA expression profile of human gastric cancer [31]. A total of 308 circRNAs, including 201 downregulated circRNAs and 107 upregulated, were found significantly aberrantly expressed in gastric cancer tissues [31]. In this study, we focused our attention on investigating the role of hsa_circ_0005654 (http://www.circbase.org/cgi-bin/simplesearch.cgi) inthe diagnosis of early gastric cancer. Its gene is located at chr4:121675707–121732604; its associated-gene symbol is PRDM5 (PR/SET domain 5). The reason why hsa_circ_0005654 was chosen in this study is that it is one of the differentially expressed circRNAs between gastric cancer tissues and adjacent normal tissues in our previous microarray screening study (GEO No. GSE89143, Guo, 2016; https://www.ncbi.nlm.nih. gov/geo/query/acc.cgi?acc=GSE89143) [31]. Its chan- ge fold is more than 4-fold and the changing trends between each paired cancer and adjacent tissues were consistent [26]. More important, its expression levels are relatively high [26]. These characteristics indicated hsa_circ_0005654 has potential as an easily detectable biomarker. In this study, to explore its possible early diagnostic value for gastric cancer, we used early gastric cancer mucosae from submucosal dissection. We found that hsa_circ_0005654 expression levels were correlated with various clinicopathological factors. Our results showed that hsa_circ_0005654 may be an early gastric cancer biomarker.

2. Materials and methods

2.1 Patients’ samples

In this study, a total of 301 tissues were collected. Among them, sixty-eight early gastric cancer mucosae and paired adjacent mucosae were collected from early gastric cancer patients who received treatments through endoscopic submucosal dissection (ESD) procedures, which are small endoscopic surgeries conducted by experienced endoscopists to entirely remove early gastric cancer tissues under endoscopy, at the Affiliated Hospital of Medical School of Ningbo University between September 2016 and February 2018. Furthermore, 122 healthy gastric mucosa samples and forty-three chronic gastritis tissues were obtained from biopsy specimens. All tissues were immediately stored in RNA-fixer Reagent (Bioteke, Beijing, China) after removal from these patients’ stomachs and preserved at $-$ 80 ${{}^{\circ}}$ C until use. Moreover, the corresponding adjacent nontumor mucosae without cancer cells were taken 5.0 cm from the edge of the tumors, as analyzed by two experienced pathologists. No patients had received any chemotherapy or other treatments before the tissues were obtained.

The diagnosis of every sample was confirmed histo-pathologically. Written informed consent forms were obtained before the experiments. Histologic grade was assessed following the National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines for Oncology (V. 2.2018). All of these specimens and data were collected in a double-blind manner. The Human Research Ethics Committee of Ningbo University (IRB No. 20100303) approved all aspects of this research.

2.2 Total RNA isolation

Total RNA was isolated from all tissues covering the frozen early gastric cancer mucosae, healthy gastric mucosa samples, chronic gastritis tissues and adjacent nontumor mucosae using TRIzol reagent (Invitrogen, Karlsruhe, Germany) following the manufacturer’s instructions. Then, 20 $\mu$ L diethylpyrocarbonate (DEPC)-treated water was added to dissolve the total RNA. Subsequently, the concentration and purity of the total RNA samples were measured using the DeNovix DS-11 $+$ a spectrophotometer (DeNovix, Wilmington, DE, USA).

2.3 Electrophoresis of total RNA

To assess the RNA integrity, 1.5% agarose/ethidium bromide gel electrophoresis was used.

2.4 Reverse transcription

cDNA was synthesized from 2 $\mu$ g total RNA using the GoScript Reverse Transcription (RT) System (Promega, Madison, WI, USA) following the manufacturer’s instructions. In brief, the 20- $\mu$ L reaction mixture of 4 $\mu$ L GoScript ${}^{\rm TM}$ 5 $\times$ RT reaction buffer, 2 $\mu$ L MgCl ${}_{2}$ (25 mM), 1 $\mu$ L Oligo (dT) ${}_{15}$ primer (0.5 $\mu$ g), 1 $\mu$ L random primer (0.5 $\mu$ g), 1 $\mu$ L PCR nucleotide mix (10 mM), 0.5 $\mu$ L recombinant RNasin ribonuclease (20 units) and 2 $\mu$ g total RNA was incubated at 42 ${{}^{\circ}}$ C for 1 h. No-template reaction was used as a control.

2.5 Quantitative detection of hsa_circ_0005654

The real-time quantitative reverse transcription-polymerase chain reactions (qRT-PCR) were carried out using GoTaq qPCR Master Mix (Promega) on an Mx3005P Real-Time PCR System (Stratagene, La Jolla, CA, USA) in a 25- $\mu$ L reaction volume containing 12.5 $\mu$ L qPCR mix, 5.5 $\mu$ L DEPC-treated water, 5 $\mu$ L cDNA product, 1 $\mu$ L upstream primer and 1 $\mu$ L downstream primer. The qRT-PCR system was run using the following conditions: 95 ${{}^{\circ}}$ C for 10 min, then 45 cycles at 94 ${{}^{\circ}}$ C for 15 s, 58 ${{}^{\circ}}$ C for 30 s, and 72 ${{}^{\circ}}$ C for 30 s. Primers of hsa_circ_0005654 were designed with the help of the Primer designing tool (https://www.ncbi.nlm.nih.gov/tools/primer-blast/) and synthesized by Sangon Biotech (Shanghai, China). For the divergent primers that overlapped the splice junction to detect hsa_circ_0005654, their sequences were as follows: 5’-GAGTTCATATCCGGAG CCACA-3’ and 5’-CCTGTAGGCTTGATGCTGAAG A-3’. For glyceraldehyde 3-phosphate dehydrogenase (GAPDH, as a control), their sequences were as follows: 5’-AAGGTGAAGGTCGGAGTCAA-3’ (forward primer) and 5’-AATGAAGGGGTCATTGATGG -3’ (reverse primer). Data analysis was performed by the $\Delta$ quantification cycle ( $\Delta C_{\rm q}$ ) method. $\Delta C_{\rm q}$ $=$ Cq ${}_{\rm(circRNA)}$ $-$ Cq ${}_{\rm(GAPDH)}$ [29]. Two independent experiments were performed.

2.6 Electrophoresis and sequencing of qRT-PCR products

To identify the qRT-PCR products integrity, gel electrophoresis was used. After that, the qRT-PCR products of hsa_circ_0005654 were purified by using a UNIQ-10 PCR Product Purification Kit (ThermoFisher Scientific, Waltham, MA, USA) and then cloned into the pUCm-T vector (ThermoFisher Scientific). Subsequently, DNA sequencing was performed by the ThermoFisher Scientific Company, Ltd.

2.7 Statistical analysis

Statistical analyses were performed using Statistical Program for Social Science version 22 (SPSS 22.0) software (SPSS Inc., Chicago, IL, USA) and GraphPad Prism 8.0 (GraphPad Software, La Jolla, CA, USA). Student’s t-test (two tailed) was used for comparisons between two groups and one-way analysis of variance (ANOVA) was used for multigroup comparisons. A $P$ -value $<$ 0.05 was considered as statistically significant. Then, receiver operating characteristic (ROC) curves were established.

3. Results

3.1 General characteristics of the subjects

About half of patients in the early gastric cancer group were men (52.9%). The average age of diagnosis of early gastric cancer was 66 years old (Table 1).

Table 1
The relationship between hsa_circ_0005654 expression levels ( $\Delta C_{\rm q})$ in early gastric carcinomatous mucosae from ESD operations and the clinicopathological factors of patients with early gastric cancer

Characteristics	No. of patients (%)	Mean $\pm$ SD	$P$ value
Age (years)
$\geqslant$ 60	49 (72.1)	11.102 $\pm$ 1.472	0.612
$<$ 60	19 (27.9)	11.300 $\pm$ 1.349
Sex
Male	36 (52.9)	11.146 $\pm$ 1.609	0.714
Female	32 (47.1)	11.170 $\pm$ 1.227
Tumor location
Sinuses ventriculi	29 (49.2)	11.123 $\pm$ 1.637	0.934
Gastric body	10 (16.9)	11.107 $\pm$ 0.875
Gastric angulus	13 (22.0)	10.960 $\pm$ 0.850
Cardia	4 (6.8)	11.688 $\pm$ 2.332
Others	3 (5.1)	11.322 $\pm$ 1.781
Pathologic diagnosis
Adenocarcinoma	16 (34.8)	11.193 $\pm$ 1.248	0.620
[l]Intraepithelial
neoplasia	24 (52.2)	10.966 $\pm$ 1.595
[l]Intramucosal
carcinoma	6 (13.0)	11.603 $\pm$ 1.355
Differentiation
Well	13 (31.0)	10.736 $\pm$ 0.904	0.512
Moderate	10 (23.8)	11.460 $\pm$ 1.339
Poor	19 (45.2)	11.071 $\pm$ 1.809
Helicobacter pylori infection
Positive	5 (11.6)	10.406 $\pm$ 0.514	0.117
Negative	38 (88.4)	11.389 $\pm$ 1.347

ESD: endoscopic submucosal dissection.

3.2 RNA quality

The ratio of A ${}_{260}$ /A ${}_{280}$ was used to indicate the purity of the total RNA. Most of the samples’ values were 1.8–2.0. The integrity of all RNA samples was confirmed by agarose gel electrophoresis (Supplementary Fig. S1).

3.3 Hsa_circ_0005654 was downregulated in early gastric cancer mucosae and chronic gastritis tissues

Since no previous studies have evaluated the expression of hsa_circ_0005654 in early gastric cancer, the qRT-PCR method was used to measure hsa_circ_00056 54 expression levels in tissues from early gastric cancer mucosae, healthy gastric mucosa samples and chronic gastritis tissues. After electrophoresis of qRT-PCR products (Supplementary Fig. S2), we confirmed the head-to-tail splicing junction of hsa_circ_0005654 through sequencing of the product of qRT-PCR (Supplementary Fig. S3), which was consistent with the sequence of that from the circBase (http://www.circbase. org/cgi-bin/singlerecord.cgi?id=hsa_circ_0005654).As shown in Figs 1 and 2, expression of hsa_circ _0005654 was obviously downregulated in early gastric cancer mucosae ( $P<$ 0.001). What’s more, hsa_circ_0005654 expression was also lower in chro-nic gastritis tissues (Fig. 2). There is also a remarkable difference of hsa_circ_0005654 levels between early gastric cancer mucosae and chronic gastritis tissues (Fig. 2, $P<$ 0.001).

Figure 1.

Hsa_circ_0005654 showed a statistically downregulated expression in early gastric cancer mucosae and matched adjacent nontumor gastric mucosae. Real-time qRT-PCR was used to determine the expression level. The $\Delta C_{q}$ value was determined by subtracting the Cq value of GAPDH from the Cq value of circRNA. A larger $\Delta C_{\rm q}$ value indicates lower expression. $n=$ 68.

Figure 2.

Expression of hsa_circ_0005654 in mucosae samples from 122 healthy participants, 43 chronic gastritis patients and 68 patients with early gastric cancer was detected by qRT-PCR. The expression of hsa_circ_0005654 in mucosae samples of early gastric cancer ( $\Delta C_{\rm q}$ : mean $\pm$ SD, 11.1574 $\pm$ 1.4316) was significantly higher than health controls ( $\Delta C_{\rm q}$ : mean $\pm$ SD, 8.6208 $\pm$ 1.6562) and higher than in chronic gastritis tissues ( $\Delta C_{\rm q}$ : mean $\pm$ SD, 10.3398 $\pm$ 0.8381). A higher $\Delta C_{\rm q}$ value indicates lower expression.

3.4 Potential diagnostic values of hsa_circ_0005654 in early gastric cancer

We found that hsa_circ_0005654 expression levels were significantly lower in early gastric cancer mucosae vs. matched nontumor mucosae (Fig. 1). Meanwhile, hsa_circ_0005654 expression levels were also downregulated in early gastric cancer compared with healthy tissues (Fig. 2). Later, we used ROC curves to investigate the diagnostic value of hsa_circ_0005654 in distinguishing early gastric cancer tissues andmatched normal adjacent nontumor mucosae. The area under the ROC curve (AUC) was 0.927 ( $P<$ 0.001, Fig. 3). The results of using healthy gastric mucosae as controls, with AUC 0.924 ( $P<$ 0.001, Fig. 4), confirmed its diagnostic value.

Figure 3.

Receiver operation characteristics curve was constructed for differentiating early gastric carcinomatous from adjacent nontumor tissues.

Figure 4.

Receiver operation characteristics curve was constructed for differentiating early gastric carcinomatous from healthy controls.

4. Discussion

Gastric cancer is the most aggressive digestive system neoplasm [32]. Despite the great efforts that have been made to explore better curative strategies in recent years, combined therapy of surgery and radiotherapy or chemotherapy are still unable to prolong the survival of patients with advanced gastric cancer, and targeted agents have not provided patients with advanced gastric cancer satisfactory outcomes [33, 34]. In contrast, the 5-year survival rate of early gastric cancer can reach 90–95% [35]. Therefore, it’s essential for us to discover gastric cancer and cure it at an early stage. However, present clinical diagnostic biomarkers including CEA and CA19-9, which have low sensitivity and specificity, cannot satisfy the need of early diagnosis of gastric cancer [26]. Thus, it’s necessary and meaningful for us to find a new high-efficient biomarker to discover early gastric cancer.

CircRNAs are abundant and evolutionarily conserved molecules [36, 37]. In recent years, with the development of novel bioinformatics approaches and high-throughput RNA deep sequencing (RNA-seq) technology, a large number and variety of circRNAs have been found [38, 39]. To date, because circRNAs are covalently closed, single-stranded circular transcripts and possess a longer half-life compared with ordinary noncoding RNA, they have become hotspots in the noncoding RNA research field [20, 40]. Despite an increasing number of studies on circRNAs, the expression profiles and functions of circRNAs in early gastric cancer are still unknown. CircRNAs have some important characteristics such as unique structures, conservation across species, cell type-specific and tissue-specific expression patterns, and stability in blood, saliva and exosomes [14, 28, 41]. Moreover, circRNAs’ expression in human cells are sometimes more extensive than their linear subclasses [42]. Because of these characteristics, circRNAs may potentially be used as biomarkers and therapeutic targets of early gastric cancer.

In this study, we investigated whether hsa_circ_000 5654 could be an early biomarker of gastric cancer. To achieve this goal, we used samples taken from patients during ESD operations. These gastric cancer mucosae are samples of early gastric cancer and are good materials for screening early biomarkers of gastric cancer.

Our qRT-PCR results showed that the expression of hsa_circ_0005654 was significantly lower in early gastric cancer mucosae than in adjacent nontumor mucosae and healthy gastric mucosa samples (Fig. 1). We further found that hsa_circ_0005654 was downregulated in chronic gastritis tissues (Fig. 2). In addition, we also discovered that there was a significant difference in expression levels of hsa_circ_0005654 between early gastric cancer mucosae and chronic gastritis tissues (Fig. 2). Additionally, we have explored the early diagnostic value of hsa_circ_0005654 (Figs 3 and 4). To our knowledge, this is the first report on hsa_circ_0005654 expression in early gastric cancer.

In recent studies, several laboratories have proven that compared with ordinary protein-based diagnostic methods, some circRNA-based diagnostic methods have remarkably higher diagnostic values [43, 44, 45, 46]. Based on our data, hsa_circ_0005654 can be used as a new potential biomarker in the diagnosis of early gastric cancer. Its sensitivity and specificity were 91.2% and 85.3%, respectively. The false positive rate and false negative rate were 14.7% and 8.8%, respectively. The positive predictive value and negative predictive value were 86.11% and 90.63%, respectively. Compared with the current clinical diagnostic biomarkers CEA and CA19-9, hsa_circ_0005654 had a higher sensitivity and specificity for screening for early gastric cancer.

5. Conclusion

Due to its high stability, hsa_circ_0005654 could be used as a novel early diagnostic biomarker of gastric cancer.

Footnotes

Acknowledgments

This work was supported by the National Natural Science Foundation of China (no. 81772279), the Scientific Innovation Team Project of Ningbo (no. 2017C110019), the National Undergraduate Training Program for Innovation and Entrepreneurship (no. 201811646025), the Student Research and Innovation Program of Ningbo University (no. 2018SRIP2507 and no. 2019SRIP1902), and the K. C. Wong Magna Found in Ningbo University.

Conflict of interest

The authors declare that no competing interests exist.

Supplementary data

Figure S1.

Representative results of 1.5% agarose/ ethidium bromide gel electrophoresis of total RNA from three representative early gastric cancer mucosae samples.

Figure S2.

Representative results of electrophoresis of qRT-PCR products. M, DNA ladder. 1 and 2, early gastric cancer mucosae; 3 and 4, adjacent nontumor mucosae; 5, healthy gastric mucosa; 6, chronic gastritis tissues.

Figure S3.

Representative sequencing results of the products of qRT-PCR for the detection of hsa_circ_0005654 in early gastric carcinomatous mucosae.

References

Bray

et al., Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries, CA Cancer J Clin 68(6) (2018), 394–424.

Liu

Zhang

and Wang

, Small ubiquitin-like modifier/sentrin-specific peptidase 1 associates with chemotherapy and is a risk factor for poor prognosis of non-small cell lung cancer, J Clin Lab Anal 32(9) (2018), e22611.

Yang

et al., Molecular analysis of gastric cancer identifies genomic markers of drug sensitivity in Asian gastric cancer, J Cancer 9(16) (2018), 2973–2980.

Fillon

, Surgery remains the best solution for patients with soft-tissue sarcomas, CA Cancer J Clin 69(1) (2019), 3–4.

Zhou

et al., HLA-DQB1*03 genotype and perioperative blood transfusion are not conducive to the prognosis of patients with gastric cancer, J Clin Lab Anal 32(7) (2018), e22443.

Zhang

et al., Circular RNA regulation of myogenesis, Cells 8(8) (2019), E885.

Tian

et al., Reduced expression of circRNA hsa_circ_ 0003159 in gastric cancer and its clinical significance, J Clin Lab Anal 32(3) (2018), e22281.

Chuang

et al., Integrative transcriptome sequencing reveals extensive alternative trans-splicing and cis-back splicing in human cells, Nucleic Acids Res 46(7) (2018), 3671–3691.

et al., Circular RNA: A new star of noncoding RNAs, Cancer Lett 365(2) (2015), 141–148.

10.

Piwecka

et al., Loss of a mammalian circular RNA locus causes miRNA deregulation and affects brain function, Science 357(6357), (2017), eaam8526.

11.

Zhou

et al., circRNA mediates silica-induced macrophage activation via HECTD1/ZC3H12A-dependent ubiquitination, Theranostics 8(2) (2018), 575–592.

12.

Hanan

Soreq

and Kadener

, CircRNAs in the brain, RNA Biol 14(8) (2017), 1028–1034.

13.

Bei

et al., Circular RNAs as potential theranostics in the cardiovascular system, Mol Ther Nucleic Acids 13 (2018), 407–418.

14.

Bahn

J.H.

et al., The landscape of microRNA, Piwi-interacting RNA, and circular RNA in human saliva, Clin Chem 61(1) (2015), 221–230.

15.

Weng

et al., Global microarray profiling identified hsa_ circ_0064428 as a potential immune-associated prognosis biomarker for hepatocellular carcinoma, J Med Genet 56(1) (2019), 32–38.

16.

Han

et al., Circular RNA circMTO1 acts as the sponge of microRNA-9 to suppress hepatocellular carcinoma progression, Hepatology 66(4) (2017), 1151–1164.

17.

Ouyang

et al., Using plasma circRNA_002453 as a novel biomarker in the diagnosis of lupus nephritis, Mol Immunol 101 (2018), 531–538.

18.

Meng

et al., Twist1 regulates vimentin through Cul2 circular RNA to promote EMT in hepatocellular carcinoma, Cancer Res 78(15) (2018), 4150–4162.

19.

et al., Competing endogenous RNA expression profiling in pre-eclampsia identifies hsa_circ_0036877 as a potential novel blood biomarker for early pre-eclampsia, Clin Epigenetics 10 (2018), 48.

20.

Guarnerio

et al., Oncogenic role of fusion-circRNAs derived from cancer-associated chromosomal translocations, Cell 166(4) (2016), 1055–1056.

21.

Cutsem

E.V.

et al., Gastric cancer, Lancet 388(10060) (2016), 2654–2664.

22.

Chen

et al., Cancer statistics in China, 2015, CA Cancer J Clin 66(2) (2016), 115–132.

23.

Yong

and Chung

, A simple biomarker scoring matrix for early gastric cancer detection, Proteomics 16(22) (2016), 2921–2930.

24.

Banks

et al., British Society of Gastroenterology guidelines on the diagnosis and management of patients at risk of gastric adenocarcinoma, Gut 68(9) (2019), 1545–1575.

25.

et al., Convolutional neural network for the diagnosis of early gastric cancer based on magnifying narrow band imaging, Gastric Cancer (2019), doi 10.1007/s10120-019-00992-2.

26.

Chen

et al., Using circular RNA hsa_circ_0000190 as a new biomarker in the diagnosis of gastric cancer, Clin Chim Acta 466 (2017), 167–171.

27.

Yao

et al., Circular RNA 0068669 as a new biomarker for hepatocellular carcinoma metastasis, J Clin Lab Anal 32(8) (2018), e22572.

28.

et al., Plasma circular RNA profiling of patients with gastric cancer and their droplet digital RT-PCR detection, J Mol Med (Berl) 96(1) (2018), 85–96.

29.

Zhao

et al., Clinical values of circular RNA 0000181 in the screening of gastric cancer, J Clin Lab Anal 32(4) (2018), e22333.

30.

et al., Diagnostic performance of circular RNAs in human cancers: A systematic review andmeta-analysis, Mol Genet Genomic Med 7(7) (2019), e00749.

31.

Shao

et al., Global circular RNA expression profile of human gastric cancer and its clinical significance, Cancer Med 6(6) (2017), 1173–1180.

32.

Gong

et al., After neoadjuvant chemotherapy platelet/ lymphocyte ratios negatively correlate with prognosis in gastric cancer patients, J Clin Lab Anal 32(5) (2018), e22364.

33.

Ahn

D.H.

and Grothey

, Continued disappointments with targeted agents in first-line therapy of advanced gastric cancers, Lancet Oncol 18(11) (2017), 1427–1428.

34.

Jiang

et al., Radiomic signature of (18)F fluorodeoxyglucose PET/CT for prediction of gastric cancer survival and chemotherapeutic benefits, Theranostics 8(21) (2018), 5915–5928.

35.

et al., Circular RNA 0000096 affects cell growth and migration in gastric cancer, Br J Cancer 116(5) (2017), 626–633.

36.

Xie

et al., Downregulated expression of hsa_circ_0074362 in gastric cancer and its potential diagnostic values, Biomark Med 12(1) (2018), 11–20.

37.

Pamudurti

N.R.

et al., Translation of circRNAs, Mol Cell 66(1) (2017), 9–21.

38.

Starke

et al., Exon circularization requires canonical splice signals, Cell Rep 10(1) (2015), 103–11.

39.

et al., ExoRBase: A database of circRNA, lncRNA and mRNA in human blood exosomes, Nucleic Acids Res 46(D1) (2018), D106–D112.

40.

Shang

et al., The novel roles of circRNAs in human cancer, Mol Cancer 18(1) (2019), 6.

41.

Chen

et al., circEPSTI1 as a prognostic marker and mediator of triple-negative breast cancer progression, Theranostics 8(14) (2018), 4003–4015.

42.

Memczak

et al., Circular RNAs are a large class of animal RNAs with regulatory potency, Nature 495(7441) (2013), 333–338.

43.

Zhang

et al., CircRNA_104075 stimulates YAP-dependent tumorigenesis through the regulation of HNF4a and may serve as a diagnostic marker in hepatocellular carcinoma, Cell Death Dis 9(11) (2018), 1091.

44.

Bei

et al., Circular RNAs as potential theranostics in the cardiovascular system, Mol Ther Nucleic Acids 13 (2018), 407–418.

45.

Chen

et al., PRMT5 Circular RNA promotes metastasis of urothelial carcinoma of the bladder through sponging miR-30c to induce epithelial-mesenchymal transition, Clin Cancer Res 24(24) (2018), 6319–6330.

46.

Qiao

et al., Circular RNA expression profile and analysis of their potential function in Psoriasis, Cell Physiol Biochem 50(1) (2018), 15–27.

Identification of hsa_circ_0005654 as a new early biomarker of gastric cancer

Abstract

Keywords

1. Introduction

2. Materials and methods

2.1 Patients’ samples

2.2 Total RNA isolation

2.3 Electrophoresis of total RNA

2.4 Reverse transcription

2.5 Quantitative detection of hsa_circ_0005654

2.6 Electrophoresis and sequencing of qRT-PCR products

2.7 Statistical analysis

3. Results

3.1 General characteristics of the subjects

Table 1 The relationship between hsa_circ_0005654 expression levels ( Δ C q ) in early gastric carcinomatous mucosae from ESD operations and the clinicopathological factors of patients with early gastric cancer

3.3 Hsa_circ_0005654 was downregulated in early gastric cancer mucosae and chronic gastritis tissues

5. Conclusion

Footnotes

Acknowledgments

Conflict of interest

Supplementary data

References

Table 1
The relationship between hsa_circ_0005654 expression levels ( $\Delta C_{\rm q})$ in early gastric carcinomatous mucosae from ESD operations and the clinicopathological factors of patients with early gastric cancer