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03 June 2020 : Clinical Research  

Circulating miR-19a-3p and miR-483-5p as Novel Diagnostic Biomarkers for the Early Diagnosis of Gastric Cancer

Jieyao Cheng1BCEF, Aiming Yang1AG*, Shujun Cheng2A, Lin Feng2CD, Xi Wu1CD, Xinghua Lu1G, Ming Zu1B, Jianfang Cui1B, Hang Yu1B, Long Zou1B

DOI: 10.12659/MSM.923444

Med Sci Monit 2020; 26:e923444

Abstract

BACKGROUND: MicroRNAs (miRNAs) are attracting substantial interest as promising noninvasive biomarkers for gastric cancer (GC). Our study aimed to identify circulating miRNAs that are potential noninvasive markers for precancerous lesions and early gastric cancers (EGCs).

MATERIAL AND METHODS: Plasma specimens were obtained from 58 gastritis subjects, 54 patients with precancerous lesions, and 38 EGC patients for study.

RESULTS: Significant differences in the plasma expression levels of miR-19a-3p, miR-22-3p, miR-146a-5p, and miR-483-5p (all P<0.05) were observed between EGC patients and gastritis subjects. Multivariable analysis showed that age (OR, 1.054; 95% CI, 1.006–1.104), miR-19a-3p expression (OR, 3.676; 95% CI, 1.914–7.061), and miR-483-5p expression (OR, 1.589; 95% CI, 1.242–2.033) were independently associated with EGCs and precancerous lesions. A combined diagnostic model incorporating these 3 variables for the prediction of EGCs and precancerous lesions was derived. The area under the receiver operating characteristic curve (AUC) of the model was 0.84; the sensitivity was 87.7% and the specificity was 62.8% at the cutoff value of –0.08.

CONCLUSIONS: Plasma miR-19a-3p and miR-483-5p are promising and powerful noninvasive markers for the early detection of GC. Patients are more willing to undergo noninvasive diagnostic procedures than gastroscopy for cancer screening, economizing limited medical resources.

Keywords: Biological Markers, Precancerous Conditions, Area Under Curve, Biomarkers, Tumor, Circulating MicroRNA, Early Detection of Cancer, ROC Curve, Sensitivity and Specificity

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750