The Interplay between RNA Editing Regulator ADAR1 and Immune Environment in Colorectal Cancer

Identification and characterization of ADAR1 mutations and changes in gene expression in human cancers

ADAR1 (Adenosine deaminase action on RNA1) is involved in post-transcriptional RNA editing. ADAR1 mutations have been identified in many cancers but its role in tumor formation is still not well understood. Here we used available cancer genomes deposited on CSOMIC and cBioPortal to identify and characterize mutations and changes in ADAR1 expression in cancer cells. We identify several high frequency substitutions including one at R767 which is located in one of the dsRNA interacting domains. In silico protein structure analysis suggest the R767 mutations affect the protein stability and are likely to destabilize interaction with dsRNA. Gene expression analysis shows that in samples with under-expressed ADAR1, there is a statistically significant increase in expression of BLCAP (Bladder Cancer Associated Protein). Although BLCAP was initially identified in bladder cancers, more recent evidence shows that it is a tumor suppressor and BLCAP mutations have been detected in many cancer cells. Epistatic analysis using the cBioPortal mutual exclusivity calculator for the TCGA pan-cancer data shows that co-mutations between ADAR1 and other genes regulated by it are likely in cancer cells except for PTEN, AKT1 and BLCAP. This suggests that when ADAR1 function is impaired, PTEN, AKT1 and BLCAP become essential for survival of cancer cells. We also identified several samples with high mutation burden between ADAR1 and other genes regulated primarily in endometrial cancers. Finally, we show that the deaminase domain is highly conserved in metazoans and mutations within conserved residues do occur in human cancers suggesting that destabilization of the enzyme function is contributing to cancer development.

Prognostic analysis and risk assessment based on RNA editing in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, and prognosis assessment is crucial for guiding treatment decisions. In this study, we aimed to develop a personalized prognostic model for HCC based on RNA editing. RNA editing is a post-transcriptional process that can affect gene expression and, in some cases, play a role in cancer development. By analyzing RNA editing sites in HCC, we sought to identify a set of sites associated with patient prognosis and use them to create a prognostic model. We gathered RNA editing data from the Synapse database, comprising 9990 RNA editing sites and 250 HCC samples. Additionally, we collected clinical data for 377 HCC patients from the Cancer Genome Atlas (TCGA) database. We employed a multi-step approach to identify prognosis-related RNA editing sites (PR-RNA-ESs). We assessed how patients in the high-risk and low-risk groups, as defined by the model, fared in terms of survival. A nomogram was developed to predict the precise survival prognosis of HCC patients and assessed the prognostic model's utility through a receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Our analysis identified 33 prognosis-related RNA editing sites (PR-RNA-ESs) associated with HCC patient prognosis. Using a combination of LASSO regression and cross-validation, we constructed a prognostic model based on 13 PR-RNA-ESs. Survival analysis demonstrated significant differences in the survival outcomes of patients in the high-risk and low-risk groups defined by this model. Additionally, the differential expression of the 13 PR-RNA-ESs played a role in shaping patient survival. Risk-prognostic investigations further distinguished patients based on their risk levels. The nomogram enabled precise survival prognosis prediction. Our study has successfully developed a highly personalized and accurate prognostic model for individuals with HCC, leveraging RNA editing data. This model has the potential to revolutionize clinical evaluation and medical management by providing individualized prognostic information. The identification of specific RNA editing sites associated with HCC prognosis and their incorporation into a predictive model holds promise for improving the precision of treatment strategies and ultimately enhancing patient outcomes in HCC.

RNA editing and immune control: from mechanism to therapy

Adenosine-to-inosine RNA editing, catalyzed by the enzymes ADAR1 and ADAR2, stands as a pervasive RNA modification. A primary function of ADAR1-mediated RNA editing lies in labeling endogenous double-stranded RNAs (dsRNAs) as 'self', thereby averting their potential to activate innate immune responses. Recent findings have highlighted additional roles of ADAR1, independent of RNA editing, that are crucial for immune control. Here, we focus on recent progress in understanding ADAR1's RNA editing-dependent and -independent roles in immune control. We describe how ADAR1 regulates various dsRNA innate immune receptors through distinct mechanisms. Furthermore, we discuss the implications of ADAR1 and RNA editing in diseases, including autoimmune diseases and cancers.

Harnessing ADAR-Mediated Site-Specific RNA Editing in Immune-Related Disease: Prediction and Therapeutic Implications

ADAR (Adenosine Deaminases Acting on RNA) proteins are a group of enzymes that play a vital role in RNA editing by converting adenosine to inosine in RNAs. This process is a frequent post-transcriptional event observed in metazoan transcripts. Recent studies indicate widespread dysregulation of ADAR-mediated RNA editing across many immune-related diseases, such as human cancer. We comprehensively review ADARs' function as pattern recognizers and their capability to contribute to mediating immune-related pathways. We also highlight the potential role of site-specific RNA editing in maintaining homeostasis and its relationship to various diseases, such as human cancers. More importantly, we summarize the latest cutting-edge computational approaches and data resources for predicting and analyzing RNA editing sites. Lastly, we cover the recent advancement in site-directed ADAR editing tool development. This review presents an up-to-date overview of ADAR-mediated RNA editing, how site-specific RNA editing could potentially impact disease pathology, and how they could be harnessed for therapeutic applications.

A-to-I RNA editing shows dramatic up-regulation in osteosarcoma and broadly regulates tumor-related genes by altering microRNA target regions

A-to-I RNA editing is a prevalent type of RNA modification in animals. The dysregulation of RNA editing has led to multiple human cancers. However, the role of RNA editing has never been studied in osteosarcoma, a complex bone cancer with unknown molecular basis. We retrieved the RNA-sequencing data from 24 primary osteosarcoma patients and 3 healthy controls. We systematically profiled the RNA editomes in these samples and quantitatively identified reliable differential editing sites (DES) between osteosarcoma and normal samples. RNA editing efficiency is dramatically increased in osteosarcoma, presumably due to the significant up-regulation of editing enzymes ADAR1 and ADAR2. Up-regulated DES in osteosarcoma are enriched in 3'UTRs. Strikingly, such 3'UTR sites are further enriched in microRNA binding regions of gene EMP2 and other oncogenes, abolishing the microRNA suppression on target genes. Accordingly, the expression of these tumor-promoting genes is elevated in osteosarcoma. There might be an RNA editing-dependent pathway leading to osteosarcoma. We expanded our knowledge on the potential roles of RNA editing in oncogenesis. Based on these molecular features, our work is valuable for future prognosis and diagnosis of osteosarcoma.

Functional Proteomic Profiling Analysis in Four Major Types of Gastrointestinal Cancers

Gastrointestinal (GI) cancer accounts for one in four cancer cases and one in three cancer-related deaths globally. A deeper understanding of cancer development mechanisms can be applied to cancer medicine. Comprehensive sequencing applications have revealed the genomic landscapes of the common types of human cancer, and proteomics technology has identified protein targets and signalling pathways related to cancer growth and progression. This study aimed to explore the functional proteomic profiles of four major types of GI tract cancer based on The Cancer Proteome Atlas (TCPA). We provided an overview of functional proteomic heterogeneity by performing several approaches, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), t-stochastic neighbour embedding (t-SNE) analysis, and hierarchical clustering analysis in oesophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and rectum adenocarcinoma (READ) tumours, to gain a system-wide understanding of the four types of GI cancer. The feature selection approach, mutual information feature selection (MIFS) method, was conducted to screen candidate protein signature subsets to better distinguish different cancer types. The potential clinical implications of candidate proteins in terms of tumour progression and prognosis were also evaluated based on TCPA and The Cancer Genome Atlas (TCGA) databases. The results suggested that functional proteomic profiling can identify different patterns among the four types of GI cancers and provide candidate proteins for clinical diagnosis and prognosis evaluation. We also highlighted the application of feature selection approaches in high-dimensional biological data analysis. Overall, this study could improve the understanding of the complexity of cancer phenotypes and genotypes and thus be applied to cancer medicine.