Five serum-based miRNAs were identified as potential diagnostic biomarkers in gastric cardia adenocarcinoma

Abstract

BACKGROUND:

Circulating microRNAs (miRNAs) have been implicated as novel biomarkers for various types of cancers. The aim of the study is to identify serum miRNAs with potential in detecting gastric cardia adenocarcinoma (GCA).

METHODS:

A three-phase study was designed with 102 GCA patients and 84 cancer-free controls. In the screening phase (3 GCA pools vs. 1 normal control (NC) pool), a total of 35 miRNAs were identified using quantitative reverse transcription polymerase chain reaction (qRT-PCR) based Exiqon panel. Subsequently, these miRNAs were further assessed by qRT-PCR in the training phase (30 GCAs vs. 30 NCs) and testing phase (72 GCAs vs. 54 NCs). Finally, the expression levels of the identified miRNAs were assessed in GCA tissues and exosomes.

RESULTS:

Five up-regulated miRNAs (miR-200a-3p, miR-296-5p, miR-132-3p, miR-485-3p and miR-22-5p) were identified in serum of the GCA patients compared with NCs. The areas under the receiver operating characteristic curve (AUCs) of the five-miRNA panel were 0.766 and 0.724 for the training and testing phases, respectively. In addition, miR-200a-3p, miR-296-5p, miR-485-3p and miR-22-5p were significantly up-regulated in GCA tissues. However, none of the miRNAs in the exosomes showed different expression between GCA patients and NCs.

CONCLUSIONS:

We identified a five-miRNA panel in peripheral serum samples as a non-invasive biomarker in detection of GCA.

1. Introduction

Gastric cancer, the second leading cause of cancer death worldwide [1], has two main sites: cardia (proximal, gastroesophageal junction) and non-cardia (fundus, body, distal and lesser or greater curvature). Exactly, gastric cardia cancer occurs in the 1 cm proximal and 2 cm distal region of the esophagogastric junction according to the AEG classification proposed by Siewert [2]. Gastric cardia adenocarcinoma (GCA) is the main histological type of gastric cardia cancer. Recent studies have suggested that GCA has distinct epidemiological, histopathological, molecular biological, characteristics which distinguished this tumor from the adenocarcinomas of distal stomach [3, 4, 5, 6]. In China, GCA is one of the prevalent fatal malignancies and shares much similar geographic distributions with esophageal squamous cell carcinoma (ESCC). Over the past few decades, GCA becomes one of the most rapidly growing malignant tumors in western countries [7], which increased by approximately fivefold to six-fold [8, 9], whereas the incidence of non-cardia gastric cancer and esophageal carcinoma remained stable or decreased during this period. In China, the incidence rate of GCA is about 50/100,000, and the local area (Henan province) was as high as 190/10,000 [10]. Diagnosis is often delayed for many patients due to the lack of specific symptoms. The patients with advanced stages have no chance of surgery, thus leading to a poor 5-year survival rate, approximately 25% [11]. Currently, endoscopic mucosal biopsy is the gold standard for the diagnosis of GCA. For its expensive price and invasiveness, it is difficult to be popularized in China. Moreover, the existing tumor markers, such as CEA, CA724 and CA199, have no sufficient sensitivity and specificity for diagnosis of GCA [12]. Accordingly, it is urgent for us to find novel and reliable non-invasive biomarkers for GCA detection as a critical step towards early intervention and reducing mortality.

MicroRNAs (miRNAs) are short non-coding RNAs (20-22nt) that can regulate a wide range of biological processes, including cell proliferation, apoptosis, aging, differentiation and cell-cycle control, by repressing translation or promoting degradation of target mRNAs [13]. Generally, a single miRNA can regulate multiple target genes, and miRNAs may serve as either tumor suppressors or oncogenes in various cancers [14]. Accumulating research demonstrated that the miRNA expression profiles could distinguish cancer patients from normal individuals [15, 16, 17]. Meanwhile, circulating miRNAs could be stably detected in peripheral blood [18]. These findings showed that circulating miRNAs could act as excellent non-invasive biomarkers for the detection and diagnosis of various types of cancers. Most studies have explored the miRNA expression data in non-cardia gastric cancer, or several studies related with gastric cancer [19] included some patients with gastric cardia adenocarcinoma [20], but few focused on GCA. Liu et al. found that significant downregulation and proximal promoter methylation of miR-203a and miR-203b in GCA tissues [21], which focused on the mechanism of miRNA in GCA. Gao et al. [10] performed miRNA profiles with GCA tissues, which was invasively obtained by endoscope or surgery. However, no study comprehensively conducted circulating miRNA profiles in GCA. Thus, there is an urgent need for the detection of circulating miRNA in GCA.

In present study, a three-phase study was designed to identify serum miRNA-panel as an effective biomarker for diagnosis of GCA. Firstly, the serum miRNA expression profile of GCA patients were screened using quantitative reverse transcription polymerase chain reaction (qRT-PCR) based miRCURY LNA microRNA Array. The candidate miRNAs were further evaluated in the training and testing phases by qRT-PCR. Moreover, the identified miRNAs were assessed in the GCA tissues and exosomes.

2. Materials and methods

2.1 Study design, patients and samples

All of the 102 GCA cases and 84 normal controls (NCs) were recruited from First Affiliated Hospital of Nanjing Medical University between 2014 and 2015. The anatomical sites of the GCA are in 1 cm proximal and 2 cm distal region of the esophagogastric junction. All of the GCA patients were newly diagnosed and confirmed by histopathology, who were not treated with chemoradiotherapy before blood or tissue collection. Blood samples were collected by SST Advance tubes (Becton, Dickinson and Company) and separated within 6 hours in order to prevent the contamination by cellular nucleic acids. The serum samples were stored at $-$ 80 ${}^{\circ }$ C until analysis. Tissue samples were obtained from GCA patients underwent surgery and preserved in liquid nitrogen. Tumor stage was according to the 7th edition of the American Joint Committee on Cancer TNM staging system.

Our study was designed for three phases. In the screening phase, 30 GCA serum samples and 10 NCs were randomly selected and pooled as 3 GCA samples and 1 NC sample (10 samples were pooled as 1 pool sample). According to the manufacturer’s protocol, a total of 25 ng RNA isolated from each pooled serum sample was reverse transcribed to cDNA by using the miRCURY Locked Nucleic Acid (LNA ${}^{\text{TM}}$ ) Universal Reverse Transcription (RT) microRNA PCR, Polyadenylation and cDNA synthesis kit (Exiqon miRNA qPCR panel, Vedbaek, Denmark). Then through 7900HT real-time PCR system (Applied Biosystems, Foster City, CA, USA) with Exiqon miRCURY-Ready-to-Use PCR-Human-panel-I+II- V1.M (Exiqon miRNA qPCR panel, Vedbaek, Denmark), it could detect 179 miRNAs in plasma/serum to identify differently expressed miRNAs. The criteria for composition data in the study were those miRNAs with 5 Ct less than the negative control (No Template Control, NTC) and with Ct $<$ 37. An RNA spike-in (UniSp6) and a DNA spike-in (Sp3) were used as quality controls to assess if the technical performance of all samples was similar. Melting curves were checked in all assays. Normalized Ct value was performed based on the average of the normalizer assays in the panel which included miR-191-5p, miR-423-5p, miR-425-5p and miR-93-5. Ct and 2 ${}^{-\mathrm{\Delta }\mathrm{\Delta }\text{Ct}}$ were calculated using the following formulae: $\mathrm{\Delta }$ Ct $=$ average Ct (assay) – average Ct (normalizer assays), $\mathrm{\Delta }\mathrm{\Delta }$ Ct $=$ $\mathrm{\Delta }$ CT (GCA case) – $\mathrm{\Delta }$ CT (NC), which represented the normalized Ct values and the relative expression levels of miRNAs. In the training phase, the dysregulated miRNAs were assessed by using qRT-PCR in 30 GCAs and 30 NCs. In the testing phase, 72 GCA serum samples and 54 NCs were further validated. In addition, the identified miRNAs were assessed in 24 pairs of GCA tissues and matched normal tissues. These miRNAs were further detected in the serum exosomes (23 GCAs vs. 24 NCs) to investigate the potential form of the miRNAs in serum of GCA patients.

Our study was approved by Institutional Review Boards of the First Affiliated Hospital of Nanjing Medical University, and each subject signed an informed consent.

The study was conducted according to the approved guidelines by Hospital Ethics Committee.

2.2 Exosomes isolation

According to the manufacturer’s instructions, 200 ul serum of each sample was incubated by using ExoQuick Exosome Precipitation Solution (System Biosciences, Mountain View, Calif) for 30–60 min at 2–8 ${}^{\circ }$ C, and then centrifugated at 13,000 rpm for 2 min. Removal of the supernatant, the exosome pellets were retained for the extraction of RNA.

2.3 RNA extraction

MirVana PARIS Kit (Ambion, Austin, TX, USA) was used to extract RNA from 200 $\mu$ l serum or exosomes following the protocol. For tissue samples, total RNA was extracted using Trizol (Invitrogen, Carlsbad, CA, USA). Then, the total RNA was dissolved in 100 $\mu$ l of RNase-free water and stored at $-$ 80 ${}^{\circ }$ C until analysis. Finally, ultraviolet spectrophotometer was used to detect the concentration and purity of RNA.

Table 1

Clinical characteristics of 102 GCA patients and 84 normal controls

	Training phase				Testing phase
	Cases		Controls		Cases		Controls
	(%)		(%)		(%)		(%)
Number	N $=$ 30		N $=$ 30		N $=$ 72		N $=$ 54
Age
$<$ 65	10	(33.3)	12	(40.0)	31	(43.1)	25	(46.3)
$⩾$ 65	20	(66.7)	18	(60.0)	41	(56.9)	29	(53.7)
Gender
Male	21	(70.0)	19	(63.3)	54	(75.0)	32	(59.3)
Female	9	(30.0)	11	(36.7)	18	(25.0)	22	(40.1)
Differentiation grade
Well/moderate	14	(46.7)			37	(51.4)
Poorly	16	(53.3)			35	(48.6)
TNM stage
I	3	(10)			13	(18.0)
II	9	(30)			19	(26.4)
III	12	(40)			31	(43.1)
IV	6	(20)			9	(12.5)

2.4 Quantitative RT-PCR

MiRNA was amplified by using the specific primers of reverse transcription (RT) and polymerase chain reaction (PCR) from Bulge-Loop ${}^{\text{TM}}$ miRNA qRT-PCR Primer Set (RiboBio, Guangzhou, China). The level of fluorescence emitted by SYBR Green (SYBR ${}^{\mathrm{\circledR }}$ Premix Ex Taq ${}^{\text{TM}}$ II, TaKaRa) was the index for us to quantitatively evaluate the amplified RNA product. RT reactions were performed at 42 ${}^{\circ }$ C for 60 min followed by 70 ${}^{\circ }$ C for 10 min. The qRT-PCR was conducted on LightCycler ${}^{\mathrm{\circledR }}$ 480 Real-Time PCR System (Roche Diagnostics, Mannheim, Germany) in 384-well plates at 95 ${}^{\circ }$ C for 20 sec, 40 cycles of 95 ${}^{\circ }$ C for 10 sec, followed by 60 ${}^{\circ }$ C for 20 sec and 70 ${}^{\circ }$ C for 10 sec. Melting curve analysis was performed to evaluated the specificity of PCR products.

The expression of miRNAs in serum samples and exosomes was determined using the 2 ${}^{-\mathrm{\Delta }\mathrm{\Delta }\text{Ct}}$ method relative to endogenous reference miRNA (miR-103a-3p). The relative levels of miRNAs in tissue specimens were calculated using the comparative 2 ${}^{-\mathrm{\Delta }\mathrm{\Delta }\text{Ct}}$ method relative to RNU6B (U6) [22].

2.5 Statistical analysis

The software geNorm and the comparative Ct method were applied to evaluate the stability of candidate reference miRNA expression based on expression level both in cases and controls. The lower stability value ( $M$ ) indicates higher expression stability.

All the statistical analyses were performed using SPSS software (version 22.0, IBM, USA). Mann-Whitney test was used to compare the differential miRNAs expression in different groups. Demographic and clinical characteristics among groups were analyzed by the ${\chi }^2$ test. Multiple logistic regression analysis was applied on the data from the testing and training stages to establish the miRNA signature in our study. The receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were used to estimate the diagnostic value of the dysregulated miRNAs for GCA. A $p<$ 0.05 was considered as statistical significance.

Figure 1.

Overview of the experiment design. GCA: gastric cardia adenocarcinoma; NC: normal control.

Figure 2.

Expression levels of the five miRNAs in the serum of 102 GCA patients and 84 controls (in the training and testing phases). Y axis was presented as log10 (concentration; fmol/L). A: miR-200a-3p; B: miR-296-5p; C: miR-132-3p; D: miR-485-3p; E: miR-22-5p; T: tumor; N: normal controls. Horizontal line: mean with 95% CI.

Figure 3.

Receiver-operating characteristic (ROC) curve analyses of the five-miRNA signature to discriminate GCA patients form normal controls. A: the combined two phases of training and testing phases (102 GCA vs. 84 NCs); B: training phase (30 GCA vs. 30 NCs); C: testing phase (72 GCA vs. 54 NCs). AUC: areas under the curve.

Figure 4.

Expression of the five miRNAs in the tumor tissues of 24 GCA patients and 24 NCs. miR-200a-3p, miR-296-5p, miR-485-3p, miR-22-5p were significantly up-regulated in GCA tissues by qRT-PCR. A: miR-200a-3p; B: miR-296-5p; C: miR-485-3p; D: miR-22-5p; E: miR-132-3p; T: tumor; N: normal controls. Horizontal line: mean with 95% CI.

Figure 5.

Expression of the five miRNAs in the serum exosomes of 23 GCA patients and 24 NCs. A: miR-200a-3p; B: miR-296-5p; C: miR-132-3p; D: miR-485-3p; E: miR-22-5p; T: tumor; N: normal controls. Horizontal line: mean with 95% CI.

3. Results

3.1 Characteristics of the subjects

A total of 186 subjects, including 102 GCA patients and 84 NCs, were enrolled in our study to assess the dysregulated miRNAs in serum of GCA patients. The clinical and pathology characteristics of the subjects were listed in Table 1. All of the subjects were divided into two phases after the screening phase: the training phase and the testing phase (The flow chat of the study was shown in Fig. 1). There was no significant difference in age or gender between GCA patients and NCs in each phase.

3.2 MiRNAs screening

To identify candidate miRNAs in peripheral serum of GCA patients, a total of 179 human miRNAs were initially analyzed by the Exiqon miRCURY-Ready-to-Use-PCR-Human-panel-I+II-V1.M based on the qRT-PCR platform in 3 GCA and 1 NC pooled serum samples (10 subjects for each pool). By qRT-PCR, each miRNA was assayed twice on 384-well plates. Only the ones that had a Ct value less than 37 and 5 lower than negative control were included in the further analysis. Eventually, 35 miRNAs showed at least a 1.5-fold altered expression (Table S1) in all 3 GCA pooled samples compared to the NC pooled sample. These miRNAs were chosen to further validation.

3.3 Evaluation of candidate miRNAs in serum by qRT-PCR

To select a stable endogenous reference, geNorm software was used for evaluation of the stability of candidate reference miRNA (miR-16-5p [23], miR-425 [24], miR-103a-3p [25] and miR-191-5p [26]). As shown in Fig. S1, miR-103a-3p and miR-191-5p were the most stable miRNAs with lower $M$ values. However, miR-103a-3p with lower mean Ct value was chosen as the control in our study.

The candidate miRNAs selected in the screening phase were further examined by using qRT-PCR between 30 GCAs and 30 NCs. Twelve miRNAs, in the training phase, with mean fold change $>$ 1.5 and $P<$ 0.05 were chosen to further detection (Table S2). In the testing phase, the 12 miRNAs were validated in a larger sample set comprising 72 GCAs and 54 NCs. At last, five miRNAs (miR-200a-3p, miR-296-5p, miR-132-3p, miR-485-3p and miR-22-5p) showed concordant with the training phase. By combining the results of the two phases, all of the five miRNAs were significantly up-regulated in GCA patients compared with controls (Fig. 2), which showed that these miRNAs in peripheral serum of GCA patients might serve as potentially diagnostic biomarkers.

3.4 Diagnostic value of the candidate miRNAs

To evaluate the diagnostic value of the 5 miRNAs, the data from training and testing phases were combined. The AUC were 0.658, 0.663, 0.642, 0.692 and 0.674 for miR-200a-3p, miR-296-5p, miR-132-3p, miR-485-3p and miR-22-5p, respectively (Fig. S2). The AUC was 0.734 (95% CI: 0.662–0.807; Fig. 3A), when we combined the 5 miRNAs together as a panel, which showed higher accuracy than individual miRNA in discriminating GCA cases from NCs. Meanwhile, we also assessed the five-miRNA panel in the training and testing phases, and the AUCs were 0.766 (95% CI: 0.642–0.890; Fig. 3B) and 0.724 (95% CI: 0.634–0.814; Fig. 3C), respectively.

To understand the association of the five serum miRNAs, we assessed different TNM stages for all 102 patients. However, there was no different expression of each miRNA in GCA patients with stage III $+$ IV compared to those with stage I $+$ II (Fig. S3). When came to the GCA patients with stage I and II, each miRNA also had no different expression (Fig. S4). Moreover, we also analyzed the expression levels of the five miRNAs in GCA patients with metastasis to those without. No significant difference was found between the two cohorts as well (Fig. S5).

3.5 The candidate miRNAs in tissue samples and serum exosomes

To validate the consistency of the miRNAs in serum and tissue of GCA patients, the expression levels of the five miRNAs were examined in additional 24 tissue samples. As shown in Fig. 4, the expression of miR-200a-3p, miR-296-5p, miR-485-3p, and miR-22-5p was significantly higher ( $P<$ 0.05) in GCA patients than those in the NCs, which maintained the consistency in serum.

For further research, the five miRNAs in serum exosomes were investigated in additional 23 serum samples to explore the potential form of the candidate miRNAs. When compared to controls, none of the five miRNAs (miR-200a-3p, miR-296-5p, miR-132-3p, miR-485-3p and miR-22-5p) from GCA patients showed significant difference in the serum exosomes (Fig. 5).

3.6 Bioinformatics analysis of candidate miRNAs

To decipher the potential function of the candidate miRNAs, DIANA-TarBasev7.0 was utilized to identify the target genes of each candidate miRNAs. We put the five identified miRNAs into the DIANA-miRPath v3.0, a pathway analysis web-server for miRNA targets, to investigate the pathways with Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Ontology (GO) analysis (Table S3). KEGG analysis showed that TGF-beta signaling pathway seemed to be regulated by miR-200a-3p and miR-132-3p. GO analysis demonstrated miR-296-5p, miR-132-3p and miR-22-5p were related to TRIF-dependent toll-like receptor signaling pathway.

4. Discussion

The incidence of GCA gradually increased over the last 40 years, in contrast to the decreasing incidence of gastric cancer worldwide. Moreover, GCA may carry a worse long-term survival. Deans and Lehmann et al. demonstrated that GCA had distinct tumor characteristics and biological behaviors compared with non-cardia gastric adenocarcinoma [27, 28]. These findings suggested that cardia cancer is a distinct disease from gastric cancer, which may require different diagnosis and treatment strategies. Unfortunately, there is currently lack of noninvasive methods for the diagnosis of GCA. MiRNAs are known to play important roles in cancers. Majority of the studies to date have investigated the diagnostic value of peripheral circulating miRNAs in non-cardia gastric cancer samples.

In the present study, we focused on the GCA, aiming to discover a panel of serum miRNAs which might have potential value in detecting GCA. A total of 102 GCA patients were classified as the type II Siewert tumor [10, 29], the true cardia cancer, locating in 1 cm proximal and 2 cm distal region of the esophagogastric junction. A three-phase study was designed to identify a panel of serum miRNAs as an effective biomarker. In the screening phase, Exiqon miRNA qPCR panels, which showed better sensitivity and linearity than TaqMan platform while less abundant miRNAs were measured [30], was used to analyze differential expression profiling of serum miRNAs in 3 GCA and 1 NC pooled samples. Normalization is a necessary step for reliable qRT-PCR assays. The critical step in the following validation phases was to choose proper endogenous reference miRNAs. MiR-16-5p is relatively stable in the circulation and has been applied as endogenous reference in many studies [23]. The other three miRNAs, such as miR-425 [24], miR-103a-3p [25] and miR-191-5p [26] were also used as reference miRNAs in some studies. In our study, identified by the geNorm algorithm, miR-103a-3p revealed lower $M$ value with higher expression was chosen as the internal reference for data normalization. Eventually, through the testing and training stages, miR-200a-3p, miR-296-5p, miR-132-3p, miR-485-3p and miR-22-5p were found to be significantly up-regulated in GCA, which might act as potential biomarkers in diagnosis of GCA. In addition, the expression levels of the five miRNAs were further verified in GCA tissues. MiR-200a-3p, miR-296-5p, miR-485-3p, and miR-22-5p but not miR-132-3p maintained the consistency significantly higher expression in GCA patients than those in the NCs.

Among the five identified miRNAs, miR-200a-3p is a member of miR-200 family (miR-200a, -200b, -200c, -141, -429). The miR-200 family were highly expressed within epithelial cells and acted as master regulators by targeting zinc finger-box bind homeobox 1 (ZEB1) and 2 (ZEB2) to maintain epithelial integrity [31]. Chang et al. [32] showed that miR-200a-3p was significantly down-regulated in gastric cancer tissues compared with normal tissues. It could act as tumor suppressor by targeting ZEB 1/ZEB 2, through the Wnt/ $\beta$ -catenin pathway in gastric adenocarcinoma [33]. Interestingly, Chen et al. [34] revealed that miR-200a-3p was down-regulated in gastric adenocarcinoma tissues ( $p=$ 0.04) but up-regulated in esophageal adenocarcinoma (EAC) tissues ( $p=$ 0.001). Saad et al. [35] further found that miR-200a-3p was significantly up-regulated in early EAC stages, suggesting it might play a role in EAC tumor development rather than progression. In the present study, we found miR-200a-3p was significantly up-regulated in GCA serum as well as in tissues. KEGG analysis showed that miR-200a-3p might interact with the TGF-beta signaling pathway, which could play divergent roles in different stages of cancers [36]. Thus, it is necessary to explore the underlying mechanisms of miR-200a-3p in GCA. Serum miR-296-5p was ever reported as a potential biomarker in our previous study of gastric cancer (GC) [17]. In the serum samples of GCA, miR-296-5p, a mature form of miR-296, showed significantly up-regulated when compared with NCs. MiR-296 has a major role in angiogenesis by directly targeting the hepatocyte growth factor-regulated tyrosine kinase substrate (HGS) in glioma cells [37] and known to enhance the invasiveness of glioblastomas cells by down-regulating caspase-8 (CASP 8) and nerve growth factor receptor (NGFR) [38]. When comes to the GC, high expression of miR-296-5p increased proliferation in GC through repression of Caudal-related homeobox 1 (CDX 1), which was an intestinal-specific transcription factor, function as anti-growth [39]. For miR-132-3p, consonantly with the present study, our previous study [17] suggested that it was overexpressed in serum samples of gastric cancer patients. Overexpression of miR-132-3p enhanced cell proliferation and tumor growth, and functioned as an oncogene by suppression of FoxO 1 translation in GC [40]. Liu et al. [41] who studied the expression and clinical significance of miR-132-3p in gastric cancer, showed that high expression of miR-132-3p in GC tissues was related with more frequent lymph node metastasis, more advanced stage and poorer overall survival. MiR-485-3p was reportedly [42] related to the mitochondrial respiration and cell migration and invasion by inhibiting PGC-1 $\alpha$ , which was a novel regulator of cancer metabolism. Moreover, Lucotti et al. [43] and Chen et al. [44] showed that miR-485-3p could mediate drug responsiveness by down regulation of nuclear factor (NF)-YB and activation of topoisomerase Ii $\alpha$ (Top2 $\alpha$ ), which indicated that miR-485-3p could be a therapeutic target to modulate resistance in tumor cells. The other miRNA, miR-22-5p was down-regulated in GC tissues and could inhibit migration and invasion of gastric cancer cell [45]. Wang et al. [46] found that miR-22-5p might act as a suppressor in GC. They showed that patients with lower expression of miR-22-5p were involved with worse stages and had greater extent of lymph node metastasis and distant metastasis. In our study, the two miRNAs (miR-485-3p and miR-22-5p) were all up-regulated significantly in GCA serum and tissues, which might play important roles in GCA. We speculated that specimen origin was the main cause of difference. GCA has distinct epidemiologic and biological characteristics which distinguished this tumor from the adenocarcinomas of distal stomach. Further research should be implemented to explore the mechanism of these miRNAs in GCA formation and development.

The diagnostic value of the peripheral miRNA identified in this study has also been evaluated in some other cancers. Up-regulated miR-200a-3p could have diagnostic utility in various cancers, including ovarian cancer [47], pancreatic cancer [48] and breast cancer [49]. Overexpressed miR-296-5p could be a diagnostic biomarker in esophageal squamous cell carcinoma [50]. Down-regulated plasma miR-132-3p was found in malignant mesothelioma patients [51]. In a word, the specificity of peripheral miRNA as biomarker is necessary to be further studied.

Circulating miRNAs were believed to be derived from tumor tissues and were released into the bloodstream by passively leaked or actively transported [52]. As they were extremely stable even can against RNase degradation [18], circulating miRNAs were demonstrated contained in exosomes [53], or protected by the formation of a protein-miRNA complex [54]. Herein, we assessed the expression of the five miRNAs in GCA tissues. The results showed that all the five miRNAs were up-regulated in the GCA tissue samples compared to normal controls, while the miR-200a-3p, miR-296-5p, miR-485-3p and miR-22-5p yielded statistical significance. Our findings confirmed the theory of the origin of circulating miRNAs. Then, we further explored exosomal miRNA in serum samples of GCA patients to study the potential form of the five serum miRNAs. It turned out that none of the five miRNAs (miR-200a-3p, miR-296-5p, miR-132-3p, miR-485-3p and miR-22-5p) from GCA patients showed significant difference in the serum exosomes compared to controls. Arroyo et al. [54] showed that potentially 90% of miRNAs studied copurified with the ribonucleoprotein complex (Ago2 ribonucleoprotein complex), but a minority of specific miRNAs associated predominantly with vesicles. The theory may explain our results. The five miRNAs remained stable in the blood might form Ago2-miRNA complex, rather than via the package of exosomes.

There were some limitations in our research. Firstly, the study was single-center and the samples of serum and tissue were not large enough, which may result in possible bias in the outcomes. Secondly, we used the KEGG analysis and GO analysis to evaluate the relationships between candidate miRNAs and pathways, but not through experiments. Thus, future studies are warranted to explore the function of the miRNAs in GCA. In addition, our study focused on GCA, which arose in the boundary between esophagus and stomach. The relationship and specificity of the miRNAs in esophagus cancer and gastric cancer should also be explored in the future.

In summary, we identified a five-miRNA signature, which could function as a non-invasive biomarker in the detection of GCA, and it may contribute to the popularity of cancer screening. Our work comprehensively explored the miRNA in peripheral serum of GCA, which might serve as a basis for further functional studies.