Plasma microRNAs as potential new biomarkers for early detection of early gastric cancer

Abstract

BACKGROUND Early gastric cancer (EGC), compared with advanced gastric cancer (AGC), has a higher 5-year survival rate. However, due to the lack of typical symptoms and the difficulty in diagnosing EGC, no effective biomarkers exist for the detection of EGC, and gastroscopy is the only detection method. AIM To provide new biomarkers with high specificity and sensitivity through analyzed the differentially expressed microRNAs (miRNAs) in EGC and AGC and compared them with those in benign gastritis (BG). METHODS We examined the differentially expressed miRNAs in the plasma of 30 patients with EGC, AGC, and BG by miRNA chip analysis. Then, we analyzed and selected the significantly different miRNAs using bioinformatics. Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) confirmed the relative transcription level of these miRNAs in another 122 patients, including patients with EGC, AGC, Helicobacter pylori ( H. pylori )-negative gastritis (Control-1), and H. pylori -positive atrophic gastritis (Control-2). To establish a diagnostic model for the detection of plasma miRNA in EGC, we chose miRNAs that can be used to determine EGC and AGC from Control-1 and Control-2 and miRNAs in EGC from all other groups. RESULTS Among the expression profiles of the miRNA chips in the three groups in the discovery set, of 117 aberrantly expressed miRNAs, 30 confirmed target prediction, whereas 14 were included as potential miRNAs. The RT-qPCR results showed that 14 potential miRNAs expression profiles in the two groups exhibited no differences in terms of H. pylori -negative gastritis (Control-1) and H. pylori -positive atrophic gastritis (Control-2). Hence, these two groups were incorporated into the Control group. A combination of four types of miRNAs, miR-7641, miR-425-5p, miR-1180-3p and miR-122-5p, were used to effectively distinguish the Cancer group (EGC + AGC) from the Control group [area under the curve (AUC) = 0.799, 95% confidence interval (CI): 0.691-0.908, P < 0.001]. Additionally, miR-425-5p, miR-24-3p, miR-1180-3p and miR-122-5p were utilized to distinguish EGC from the Control group (AUC = 0.829, 95%CI: 0.657-1.000, P = 0.001). Moreover, the miR-24-3p expression level in EGC was lower than that in the AGC (AUC = 0.782, 95%CI: 0.571-0.993, P = 0.029), and the miR-4632-5p expression level in EGC was significantly higher than that in AGC (AUC = 0.791, 95%CI: 0.574-1.000, P = 0.024). CONCLUSION The differentially expressed circulatory plasma miR-425-5p, miR-1180-3p, miR-122-5p, miR-24-3p and miR-4632-5p can be regarded as a new potential biomarker panel for the diagnosis of EGC. The prediction and early diagnosis of EGC can b...

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