167P - Ascites-derived circulating microRNAs as potential diagnostic biomarkers of gastric cancer-associated malignant ascites

Peritoneal carcinomatosis with malignant ascites is associated with dismal prognosis in gastric cancer. Malignant ascites is the most relevant body fluid in which to seek diagnostic biomarkers for peritoneal carcinomatosis. We aimed to identify and validate ascites-derived circulating microRNAs (miRNAs) that are differentially expressed between liver cirrhosis-associated benign ascites (LC-ascites) and gastric cancer-associated malignant ascites (GC-ascites). MiRNA expression levels were investigated in three independent cohorts. Overall, 165 ascites samples (73 LC-ascites and 92 GC-ascites) were obtained from the National Biobank of Korea. Initially, microarrays were used to screen the expression levels of 2,006 miRNAs in the discovery cohort (n=22). Subsequently, quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analyses were used to validate the expression levels of selected miRNAs in the training (n=70) and validation (n=73) cohorts. In addition, the levels of carcinoembryonic antigen (CEA) were determined in the ascites samples. A total of 36 miRNAs were identified as having the potential to discriminate GC-ascites from LC-ascites via microarray analyses. Expression levels of miR-574-3p, miR-181b-5p, miR-4481, and miR-181d were significantly lower in the GC-ascites samples than in the LC-ascites samples via qRT-PCR analyses, and miR-181b-5p showed the best diagnostic performance for GC-ascites (area under the curve [AUC] = 0.798 and 0.846 for the training and validation cohorts, respectively). The diagnostic performance of CEA for GC-ascites was improved if miR-181b-5p and CEA were analyzed together (AUC = 0.981 and 0.946 for the training and validation cohorts, respectively). We identified ascites-derived circulating miRNAs capable of differentiating non-malignant ascites and GC-ascites, and demonstrated that the combined use of miR-181b-5p and CEA produces the optimal diagnostic yield. The authors. National Research Foundation of Korea (NRF). All authors have declared no conflicts of interest.