Droplet digital PCR-based circulating microRNA detection serve as a promising diagnostic method for gastric cancer.

Background: Novel non-invasive biomarkers for gastric cancer (GC) are needed, because the present diagnostic methods for GC are either invasive or insensitive and non-specific in clinic. The presence of stable circulating microRNAs (miRNAs) in plasma suggested a promising role as GC biomarkers.

Methods: Based on the quantitative droplet digital PCR (ddPCR), four miRNAs (miR-21, miR-93, miR-106a and miR-106b) related to the presence of GC were identified in plasma from a training cohort of 147 participants and a validation cohort of 28 participants.

Results: All circulating miRNA levels were significantly higher in the plasma of GC patients compared to healthy controls (P < 0.05). Through a combination of four miRNAs by logistic regression model, receiver operating characteristic (ROC) analyses yielded the highest AUC value of 0.887 in discriminating GC patients from healthy volunteers. Furthermore, miR-21, miR-93 and miR-106b levels were significantly related to an advanced TNM stage in GC patients. ROC analyses of the combined miRNA panel also showed the highest AUC value of 0.809 in discriminating GC patients with TNM stage I and II from stage III and IV. Through combining four miRNAs and clinical parameters, a classical random forest model was established in the training stage. In the validation cohort, it correctly discriminated 23 out of 28 samples in the blinded phase (false rate, 17.8%).

Conclusions: Using the ddPCR technique, circulating miR-21, miR-93, miR-106a and miR-106b could be used as diagnostic plasma biomarkers in gastric cancer patients.