The incidence rate of lung adenocarcinoma (LUAD) is increasing gradually and the mortality is still high. Recent advances in the genomic profile of LUAD have identified a number of driver alterations in specific genes, enabling molecular classification and targeted therapy accordingly. However, only a fraction of LUAD patients with those driver mutations could benefit from targeted therapy, and the remaining large numbers of patients were unclassified. RNA editing events are those nucleotide changes in the RNA. Currently, the role of RNA editing events in tumorigenesis and their potential clinical utility have been reported in a series of studies. However, the profiles of the RNA editing events and their clinical relevance in LUAD remained largely unknown.
“We describe a comprehensive landscape of RNA editing events in LUAD by integrating transcriptomic and genomic data from our NJLCC project and TCGA project. We find that the global RNA editing level is significantly increased in tumor tissues and is highly heterogeneous across LUAD patients. The high RNA editing level in tumors can be attributed to both RNA and DNA alterations.” said Dr. Cheng Wang, the first author for this work. The results indicated that the pattern of RNA editing events could represent the global characteristics of lung adenocarcinoma. “We then define a new molecular subtype, EC3, based on most variable RNA editing sites. The patients of this subtype show the poorest prognosis. Importantly, the subtype is independent of classic molecular subtypes based on gene expression or DNA methylation. We further propose a simplified prediction model including eight RNA editing sites to accurately distinguish EC3 subtype. ” said Dr. Wang. Molecular typing based on a few RNA editing sites may have enormous potential in the clinics. “By applying the simplified model, we find that the EC3 subtype is associated with the sensitivity of specific chemotherapy drugs.” said Dr. Wang.
“Our study comprehensively describes the general pattern of RNA editing in LUAD. More importantly, we propose a novel molecular subtyping strategy of LUAD based on RNA editing that could predict the prognosis of patients. A simplified model with a few editing sites makes the strategy potentially available in the clinics.” said Professor Hongbing Shen, the corresponding author.