Abstract

Circular RNAs (circRNAs) are an endogenous RNAs with a covalently closed cyclic structure. They have emerged recently as key regulators in the development and progression of human cancers. However, the clinical values of most circRNAs in gastric cancer (GC) are unknown. Hsa_circ_0065149, one of the dysregulated circRNAs in gastric carcinogenesis detected by circRNA microarray, was chose as a targeted circRNA in this study. We firstly enlarged sample size and identified the level changes of hsa_circ_0065149 among four stages of gastric tumorigenesis from healthy gastric mucosa, gastritis, intestinal metaplasia to GC. Then, the potential relationship between hsa_circ_0065149 expression levels and GC patients' clinicopathological factors was investigated. Moreover, the clinical significance of hsa_circ_0065149 in plasma exosomes and gastric juice were explored. Receiver operating characteristic (ROC) curve and Kaplan-Meier survival curve were constructed to evaluate diagnostic and prognostic values. Finally, bioinformatics analysis was performed to excavate the potential functions of hsa_circ_0065149. Hsa_circ_0065149 expression was only significantly down-regulated in gastric cancer, not changed among healthy gastric mucosa and gastritis intestinal metaplasia. Low hsa_circ_0065149 expression levels in GC tissues were significantly associated with tumor diameter (P= 0.034) and perineural invasion (P= 0.037). GC patients with low hsa_circ_0065149 levels had a much longer overall survival than those in high group (P= 0.020). More important, hsa_circ_0065149 levels were significantly decreased in plasma exosomes of early GC patients. As a screening biomarker for early GC, hsa_circ_0065149 in plasma exosomes has higher sensitivity and specificity than traditional clinical biomarkers. Bioinformatics analysis suggest that the abnormal expression of hsa_circ_0065149 may play an important role during gastric carcinogenesis. Those results indicate that hsa_circ_0065149 in exosmoes is an indicator for early GC screening and prognosis prediction.

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