134P - Identification, development and validation of a circulating miRNA-based diagnostic signature for early detection of gastric cancer

Background

Although endoscopic surveillance remains the gold standard for diagnosing asymptomatic gastric cancer (GC) patients, associated costs and its invasive nature render it inadequate as a screening approach. Development of less invasive tests is needed for surveillance of early stage GCs. Over the last decade, tumor-derived miRNAs in peripheral blood are emerging as promising disease biomarkers. Herein we have conducted a comprehensive miRNA expression profiling, followed by bioinformatic analysis to establish a novel serum-based miRNA signature for the diagnosis of patients with GC.

Methods

We analyzed tissue miRNA expression profiles in three patient cohorts (n = 602) in an in-silico discovery step, during which the robustness of candidate biomarkers was tested and validated. The performance of this miRNA signature was evaluated in a serum training cohort (n = 327). Using a logistic regression model, the panel was further refined, and this circulating miRNA signature was validated in two prospective cohorts (n = 174, 175).

Results

Genome-wide analysis of miRNA expression data resulted in identification of 10-miRNAs that distinguished cancer tissues from normal mucosa in three independent datasets (AUC = 0.984, 0.939 and 1.000). Using a serum training cohort, the miRNA candidates were further refined to six-circulating-miRNA signature. This miRNA signature demonstrated a robust diagnostic value in the training cohort. Subsequently we demonstrated robustness of the signature in two prospective cohorts (AUC = 0.87, 0.86). Remarkably, the 6-circulating-miRNA signature was able to detect early stage GC patients robustly (AUC = 0.855). Furthermore, the signature was significantly superior at identifying patients with GC to conventional tumor markers, CEA (P = 0.0001) and CA19-9 (P = 0.0001).

Conclusions

Using a comprehensive data analysis followed by substantial clinical validations, involving over 1600 GC tissue and serum specimens across 7 independent cohorts, we developed a novel 6-circulating-miRNA signature, which demonstrated an unprecedented diagnostic value and a great promise for early non-invasive detection of GC.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Daisuke Izumi.

Funding

NIH.

Disclosure

All authors have declared no conflicts of interest.