“3G” Trial: An RNA Editing Signature to Guide Gastric Cancer Chemotherapy. (Cancer Res, Feb 2021)

Omer An 1Yangyang Song 1Xinyu Ke 1Jimmy Bok-Yan So 2Raghav Sundar 3Henry Yang 1Sun Young Rha 4Ming Hui Lee 5Su Ting Tay 6Xuewen Ong 7Angie Lay Keng Tan 5Matthew Chau Hsien Ng 8Erwin Tantoso 9Leilei Chen 10Patrick Tan 11Wei Peng Yong 12Singapore Gastric Cancer Consortium 13

Author Information

1Cancer Science Institute of Singapore, National University of Singapore.
2Department of Surgery, National University of Singapore, National University of Singapore.
3Haematology-Oncology, National University Health System.
4Division of Medical Oncology, Department of Internal Medicine, Yonsei University College of Medicine.
5Cancer and Stem Cell Biology, Duke NUS Medical School.
6Cancer and Stem Cell Biology Program, Duke NUS Graduate Medical School.
7Cancer and Stem Cell Biology, Duke NUS Graduate Medical School.
8Division of Medical Oncology, National Cancer Centre Singapore.
9Gene Function Prediction, Bioinformatics Institute.
10Cancer Science Institute of Singapore, National University of Singapore polly_chen@nus.edu.sg.
11Cancer and Stem Cell Biology Program, Duke-NUS Medical School.
12Department of Haematology-Oncology, National University Hospital of Singapore.
13Singapore Gastric Cancer Consortium.

Abstract:

Gastric cancer (GC) 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 GC. 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 GC 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 GC 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 TCGA, we conducted a transcriptome-wide RNA editing analysis of a cohort of 104 patients with advanced GC and identified an RNA editing (GCRE) signature to guide GC chemotherapy. RNA editing events stood as a prognostic and predictive biomarker in advanced GC. 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, GC 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 GC. Overall, this newly defined GCRE signature reliably stratifies patients with advanced GC and predicts response from chemotherapy.

PMID: 33558338  DOI: 10.1158/0008-5472.CAN-20-2872