Systematic Characterization and Analysis of the Landscape and Regulation of Rna Editing in Human Cancers

Adenosine-to-inosine (A-to-I) RNA editing, catalyzed by adenosine deaminase acting on RNA (ADAR) family genes, is the most common type of RNA editing in humans and emerging as a molecular mechanism regulating RNA activity and protein diversity. Several lines of evidence have suggested a role of A-to-I RNA editing in a wide range of human diseases, including cancer and neurological disorders. Editing alterations have been associated with cancer progression and drug sensitivity. Moreover, numerous editing patterns have been found in tumors from a range of cancer types. Although expression pattern of ADARs is associated with the change in editing level, it cannot fully explain the complexity of RNA editing regulation observed in various cancer types, suggesting the presence of currently unidentified A-to-I editing regulators. We have examined the editing patterns and transcriptomes data of several cancer types and found that besides ADARs, the expression patterns of several splicing factors correlated well with editing variations. These preliminary results suggested that editing patterns and transcriptomes data might be able to pinpoint regulatory components of A-to-I editing. With the advent of the next generation sequencing (NGS) technology, The Cancer Genome Atlas (TCGA) have collected abundant sequencing data of paired tumor and normal cells from various tissues, which offers an extremely powerful means for studying RNA editing sites and the frequency at those sites as well as relative gene expression profiles. Benefiting from their efforts and the availability of large-scale human protein-protein interaction (PPI) data, we could investigate regulatory mechanism(s) of A-to-I editing at a systems level. The goal of the extended project is to unravel the landscape and regulatory mechanism(s) of RNA editing in cancerogenesis through a systematic characterization of RNA editomes in TCGA datasets, a network-based analysis that integrates RNA editomes with gene expression and PPI data, and then experimental validation of the roles of the identified regulators in cancerogenesis. Our specific aims are: 1. To characterize the full spectrum of A-to-I editing profiles in TCGA datasets. We will detect editing sites missed by current methods using unmapped RNA-sequencing reads from TCGA. The obtained RNA editomes gives a good understanding of editing differences between tumor and normal cells and are useful for predicting key editing regulators. 2. To identify candidate pan-cancer/cancer-specific A-to-I editing regulators. We propose to identify key regulators by contrasting between tumor and normal cells, between cancer types, and between normal tissues using RNA editomes, gene expression profiles and PPIs. 3. To experimentally determine the interactions between regulators and RNA substrates. To further narrow down candidate regulatory genes, we will perform RNA interference screen and overexpression experiments. We will also characterize RNAs editomes perturbed by selected regulators using deep sequencing to examine their roles in cancerogenesis. Through the proposed research plan, we might be able to clarify the underlying regulatory mechanism(s) that govern A-to-I editing during cancerogenesis at a systems level. This is an important step forward in getting a better understanding of cancer biology. Furthermore, unraveling the relationship between editing regulators and their substrates should provide valuable insights into the potential role of these regulators as pathogenic drivers, diagnostic biomarkers and therapeutic targets of cancer.