Sample collection
A total of 82 patients with GC admitted to the Cancer Hospital Affiliated to Hainan Medical College and examined in the endoscopy center from January 2017 to December 2018 were recruited in this study after institutional ethics clearance. Inclusion criterial were: (1) <80 years of age; (2) complete clinical data available; (3) scheduled selective GC surgery; (4) no previous chemotherapy besides adjuvant treatment before operation; (5) no active gastrointestinal bleeding or obstruction. Exclusion criteria were: (1) uncontrolled diabetes or hypertension, coronary heart disease, stroke, cardiovascular, and/or cerebrovascular diseases; (2) severe underlying diseases such as pulmonary, liver, and/or kidney dysfunctions; (3) requiring resection of other organs. Of the 82 patients, four were selected for the circRNA chip screening study. They included two men (one with T3N1M0, moderately differentiated adenocarcinoma; one with T3N2M0, poorly differentiated adenocarcinoma) and two women (one with T3N1M0, moderately differentiated adenocarcinoma; one with T3N2M0, poorly differentiated adenocarcinoma). The average age, weight, and height of the four patients were 56.7 years, 58.3 kg, and 168 cm, respectively. The remaining 78 patients with GC (Table 1) were selected for endoscopic biopsy and gastric fluid sample collection. These patients were included in the validation study of differential circRNA expression. The diagnostic criteria for early GC (EGC) and advanced GC (AGC) were based on the National Comprehensive Cancer Network clinical practice guidelines in oncology (version 3.2016). Additionally, 30 patients with chronic nonatrophic gastritis (CNAG) and 30 with chronic atrophic gastritis (CAG) were randomly selected as the control group. The diagnostic criteria for CNAG and CAG were according to the consensus opinion of the 2012 Chinese Chronic Gastritis of Gastroenterology Branch of the Chinese Medical Association.
GC specimens were obtained by cutting 0.5 cm3 of the whole layer of the GC tissue, whereas paracancerous tissue specimens were obtained by cutting 0.5 cm3 of the mucosa at least 5 cm away from the tumor body. The samples were separated from the body, quickly sliced to the required size, placed into storage tubes and stored in liquid nitrogen.
Endoscopic tissue and gastric juice samples were extracted from 78 patients with GC (21 patients with EGC and 57 with AGC), 30 with CNAG, and 30 with CAG. Table 1 illustrates the baseline characteristics of the patient and control groups. All specimens were collected and pretreated according to a previously described protocol and preserved at -80°C until RNA extraction [30].
Total RNA extraction and reverse transcription
Total RNA from tissue and gastric fluid samples were extracted using TRIzol reagent (Invitrogen, Life Technologies Inc., Germany). RNA concentration was measured by reading absorbance at 260 nm (OD260) on a NanoDrop ND-1000 instrument (Thermo Fisher Scientific, DE, USA). RNA integrity was verified by denaturing agarose gel electrophoresis. Finally, total RNA was transcribed into cDNA through the GoScript Reverse Transcription (RT) system (Promega, WI, USA) following the manufacturer’s protocol.
Microarray hybridization of circRNAs
GC tissue samples and matched adjacent noncancerous tissue specimens were selected for circRNA expression profiling using Human circRNA Array v2 (Arraystar, MD, USA). Total RNA was digested with RNase R (20 U/μL, Epicentre, Inc., Madison, WI, USA) to remove linear RNAs and enrich circRNAs. The enriched circRNAs were amplified and transcribed into fluorescent cRNA by the random priming method (Super RNA Labelling Kit; Arraystar). Labeled cRNAs were hybridized onto Human circRNA Array v2 (8 × 15 K, Arraystar). Slides were incubated for 17 h at 65°C in a hybridization oven (Agilent, CA, USA). After washing the slides, the arrays were scanned on an Agilent Scanner (G2505C). The scanned images were then imported into the Agilent Feature Extraction software for grid alignment and data extraction. Quantile normalization and subsequent data processing were performed with the R software package. The expression profile of circRNAs, identified through volcano plot filtering between GC and paired adjacent noncancerous tissue samples, was statistically significant [fold change (FC) ≥ 2.0 and P ≤ 0.05]. Hierarchical clustering was performed to depict the distinguishable expression pattern of circRNAs among samples. The circRNA/microRNA interaction was predicted using TargetScan [31] & miRanda [32].
Quantitative reverse transcription–polymerase chain reaction
The eight most upregulated and downregulated circRNAs exhibiting the greatest differences in expression between groups were selected for quantitative reverse transcription–polymerase chain reaction (qRT–PCR) verification in the four GC specimens and their adjacent tissues. qRT–PCR was performed with GoTaq qPCR Master Mix (Promega) on an Mx3005P Real-Time PCR System (Stratagene, CA, USA) in accordance with the manufacturer’s protocols. Divergent primers of the top eight upregulated and downregulated circRNAs and convergent primers of β-actin (H) were designed and synthesized by Aksomics (Shanghai) Biotechnology Co. Ltd. The divergent primers could only amplify circRNA and differentiate contaminants from the linear isoforms. Table 2 lists the circRNA primer sequences used for this procedure.
RT-PCR was performed as follows: 40 cycles of 95°C for 10 s and 60°C for 60 s for amplification; annealing at 95°C for 10 s, 60°C for 60 s, and 95°C for 15 s with slow heating from 60°C to 99°C (at 0.05°C/s).
The target and housekeeping genes in each sample were analyzed by RT-PCR. According to the gradient dilution DNA standard curve, the expression levels of the target and housekeeping genes in each sample were directly generated on an Applied Biosystems ViiA™ 7 Real-Time PCR System (ThermoFisher Scientific, USA). Target gene concentration in each sample divided by that of the housekeeping gene was considered the relative expression level of the gene.
Statistical analysis
Statistical analyses were performed with the SPSS 22.0 software (SPSS, IL, USA). When comparing the GC and paired noncancerous tissue groups for profile differences, the “FC” (ratio of group averages) between the groups for each circRNA was computed. The statistical significance of the difference was estimated by the t test. CircRNAs with FCs ≥ 2.0 were considered to be significantly differentially expressed. The analysis outputs were filtered, and differentially expressed circRNAs were ranked according to characteristics such as FC value, P value, and chromosome location. Differences in hsa_circ_000780 levels between the GC and paired adjacent noncancerous tissues were assessed by the t test for paired data; multiple groups (CNAG, CAG, EGC, and AGC) were assessed by one-way analysis of variance with post-hoc LSD test. Correlations between hsa_circ_000780 levels and clinicopathological factors were further analyzed by the Analyze–Correlate–Bivariate menu of SPSS 22.0. A P value < 0.05 was considered statistically significant.