"3G" Trial: An RNA Editing Signature to Guide Gastric Cancer Chemotherapy

Abstract

Gastric cancer cases are often diagnosed at an advanced stage with poor prognosis. Platinum-based chemotherapy has been internationally accepted as first-line therapy for inoperable or metastatic gastric cancer. To achieve greater benefits, selection of patients eligible for this treatment is critical. Although gene expression profiling has been widely used as a genomic classifier to identify molecular subtypes of gastric cancer and to stratify patients for different chemotherapy regimens, its prediction accuracy can be improved. Adenosine-to-inosine (A-to-I) RNA editing has emerged as a new player contributing to gastric cancer development and progression, offering potential clinical utility for diagnosis and treatment. Using a systematic computational approach followed by both in vitro validations and in silico validations in The Cancer Genome Atlas (TCGA), we conducted a transcriptome-wide RNA editing analysis of a cohort of 104 patients with advanced gastric cancer and identified an RNA editing (GCRE) signature to guide gastric cancer chemotherapy. RNA editing events stood as a prognostic and predictive biomarker in advanced gastric cancer. A GCRE score based on the GCRE signature consisted of 50 editing sites associated with 29 genes, predicting response to chemotherapy with a high accuracy (84%). Of note, patients demonstrating higher editing levels of this panel of sites presented a better overall response. Consistently, gastric cancer cell lines with higher editing levels showed higher chemosensitivity. Applying the GCRE score on TCGA dataset confirmed that responders had significantly higher levels of editing in advanced gastric cancer. Overall, this newly defined GCRE signature reliably stratifies patients with advanced gastric cancer and predicts response from chemotherapy. Significance: This study describes a novel A-to-I RNA editing signature as a prognostic and predictive biomarker in advanced gastric cancer, providing a new tool to improve patient stratification and response to therapy.