Genomic Positional Dissection of RNA Editomes in Tumor and Normal Samples

A novel computational method enables RNA editome profiling during human hematopoiesis from scRNA-seq data

RNA editing is a post-transcriptional modification with a cell-specific manner and important biological implications. Although single-cell RNA-seq (scRNA-seq) is an effective method for studying cellular heterogeneity, it is difficult to detect and study RNA editing events from scRNA-seq data because of the low sequencing coverage. To overcome this, we develop a computational method to systematically identify RNA editing sites of cell types from scRNA-seq data. To demonstrate its effectiveness, we apply it to scRNA-seq data of human hematopoietic stem/progenitor cells (HSPCs) with an annotated lineage differentiation relationship according to previous research and study the impacts of RNA editing on hematopoiesis. The dynamic editing patterns reveal the relevance of RNA editing on different HSPCs. For example, four microRNA (miRNA) target sites on 3' UTR of EIF2AK2 are edited across all HSPC populations, which may abolish the miRNA-mediated inhibition of EIF2AK2. Elevated EIF2AK2 may thus activate the integrated stress response (ISR) pathway to initiate global translational attenuation as a protective mechanism to maintain cellular homeostasis during HSPCs' differentiation. Besides, our findings also indicate that RNA editing plays an essential role in the coordination of lineage commitment and self-renewal of hematopoietic stem cells (HSCs). Taken together, we demonstrate the capacity of scRNA-seq data to exploit RNA editing events of cell types, and find that RNA editing may exert multiple modules of regulation in hematopoietic processes.

The Integrative Studies on the Functional A-to-I RNA Editing Events in Human Cancers

Adenosine-to-inosine (A-to-I) RNA editing, constituting nearly 90% of all RNA editing events in humans, has been reported to contribute to the tumorigenesis in diverse cancers. However, the comprehensive map for functional A-to-I RNA editing events in cancers is still insufficient. To fill this gap, we systematically and intensively analyzed multiple tumorigenic mechanisms of A-to-I RNA editing events in samples across 33 cancer types from The Cancer Genome Atlas. For individual candidate among ∼ 1,500,000 quantified RNA editing events, we performed diverse types of downstream functional annotations. Finally, we identified 24,236 potentially functional A-to-I RNA editing events, including the cases in APOL1, IGFBP3, GRIA2, BLCAP, and miR-589-3p. These events might play crucial roles in the scenarios of tumorigenesis, due to their tumor-related editing frequencies or probable effects on altered expression profiles, protein functions, splicing patterns, and microRNA regulations of tumor genes. Our functional A-to-I RNA editing events (https://ccsm.uth.edu/CAeditome/) will help better understand the cancer pathology from the A-to-I RNA editing aspect.

The Potential Regulation of A-to-I RNA Editing on Genes in Parkinson's Disease

Parkinson's disease (PD) is characterized by dopaminergic neurodegeneration and an abnormal accumulation of α-synuclein aggregates. A number of genetic factors have been shown to increase the risk of PD. Exploring the underlying molecular mechanisms that mediate PD's transcriptomic diversity can help us understand neurodegenerative pathogenesis. In this study, we identified 9897 A-to-I RNA editing events associated with 6286 genes across 372 PD patients. Of them, 72 RNA editing events altered miRNA binding sites and this may directly affect miRNA regulations of their host genes. However, RNA editing effects on the miRNA regulation of genes are more complex. They can (1) abolish existing miRNA binding sites, which allows miRNAs to regulate other genes; (2) create new miRNA binding sites that may sequester miRNAs from regulating other genes; or (3) occur in the miRNA seed regions and change their targets. The first two processes are also referred to as miRNA competitive binding. In our study, we found 8 RNA editing events that may alter the expression of 1146 other genes via miRNA competition. We also found one RNA editing event that modified a miRNA seed region, which was predicted to disturb the regulation of four genes. Considering the PD-related functions of the affected genes, 25 A-to-I RNA editing biomarkers for PD are proposed, including the 3 editing events in the EIF2AK2, APOL6, and miR-4477b seed regions. These biomarkers may alter the miRNA regulation of 133 PD-related genes. All these analyses reveal the potential mechanisms and regulations of RNA editing in PD pathogenesis.

Genetic control of RNA editing in neurodegenerative disease

A-to-I RNA editing diversifies human transcriptome to confer its functional effects on the downstream genes or regulations, potentially involving in neurodegenerative pathogenesis. Its variabilities are attributed to multiple regulators, including the key factor of genetic variants. To comprehensively investigate the potentials of neurodegenerative disease-susceptibility variants from the view of A-to-I RNA editing, we analyzed matched genetic and transcriptomic data of 1596 samples across nine brain tissues and whole blood from two large consortiums, Accelerating Medicines Partnership-Alzheimer's Disease and Parkinson's Progression Markers Initiative. The large-scale and genome-wide identification of 95 198 RNA editing quantitative trait loci revealed the preferred genetic effects on adjacent editing events. Furthermore, to explore the underlying mechanisms of the genetic controls of A-to-I RNA editing, several top RNA-binding proteins were pointed out, such as EIF4A3, U2AF2, NOP58, FBL, NOP56 and DHX9, since their regulations on multiple RNA-editing events were probably interfered by these genetic variants. Moreover, these variants may also contribute to the variability of other molecular phenotypes associated with RNA editing, including the functions of 3 proteins, expressions of 277 genes and splicing of 449 events. All the analyses results shown in NeuroEdQTL (https://relab.xidian.edu.cn/NeuroEdQTL/) constituted a unique resource for the understanding of neurodegenerative pathogenesis from genotypes to phenotypes related to A-to-I RNA editing.

Clinical relevance of RNA editing profiles in lung adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is the most frequently occurring lung cancer worldwide, with increasing death rates. It belongs to the non-small cell lung cancer (NSCLC) type and has a strong association with previous smoking history. Growing evidence has demonstrated the significance of adenosine-to-inosine RNA editing (ATIRE) dysregulation in cancer. The aim of the present study was to evaluate ATIRE events that might be clinically useful or tumorigenic.

Methods: To explore survival-related ATIRE events in LUAD, its ATIRE profiles, gene expression data, and corresponding patients’ clinical information were downloaded from the Cancer Genome Atlas (TCGA) and the synapse database. We evaluated 10441 ATIRE in 440 LUAD patients from the TCGA database. ATIRE profiles were merged with TCGA survival data. We selected prognostic ATIRE sites, using a univariate Cox analysis (p < 0.001). Cox proportional hazards regression and lasso regression analysis were used to determine survival-related ATIRE sites, create risk ratings for those sites, and build a prognostic model and a nomogram for assessing overall survival (OS). Six ATIRE sites were used in the prognostic model construction and patients were randomly divided into a validation cohort (n = 176) and a training cohort (n = 264). The “Pheatmap” program was used to create risk curves that included risk score, survival time, and expression of ATIRE sites. We also determined the clinical prediction model’s discrimination. The decision curve analysis and the 1-, 2-, and 3-year corrective curves were simultaneously used to evaluate the nomogram. We also evaluated the relationship between the amount of ATIRE sites and host gene expression and the impact of ATIRE expression on transcriptome expression.

Results: The pyroglutamyl-peptidase I (PGPEP1) chr19:18476416A > I, ankyrin repeat domain 36B pseudogene 1 (ANKRD36BP1) (dist = 3,795), T-box transcription factor (TBX19) (dist = 29815) chr1:168220463A > I, Syntrophin Beta 2 (SNTB2) chr16:69338598A > I, hook microtubule-tethering protein 3 (HOOK3) chr8:42883441A > I, NADH dehydrogenase flavoprotein 3 (NDUFV3) chr21:44329452A > I, and FK506-binding protein 11 (FKBP11) chr12:49316769A > I were used in the prognostic model construction. High levels of risk score were significantly associated with worse OS and progression-free survival. Tumour stage and risk score were related to OS in LUAD patients. The predictors were among the prognostic nomogram model’s risk score, age, gender, and tumor stage. The calibration plot and C-index (0.718) demonstrated the significant accuracy of nomogram’s predictions. ATIRE level was markedly elevated in tumor tissues and was highly variable between patients.

Conclusion: Events involving ATIRE in LUAD were highly functional and clinically relevant. The RNA editing-based model provides a solid framework for further investigation of the functions of RNA editing in non-coding areas and may be used as a unique method for predicting LUAD survival.

Genome-wide identification of A-to-I RNA editing events provides the functional implications in PDAC

Introduction

RNA editing, a wide-acknowledged post-transcriptional mechanism, has been reported to be involved in the occurrence and development of cancer, especially the abnormal alteration of adenosine to inosine. However, fewer studies focus on pancreaticcancer. Therefore, we aimed to explore the possible linkages between altered RNA editing events and the development of PDAC.

Method

We characterized the global A-to-I RNA editing spectrum from RNA and matched whole-genome sequencing data of 41 primary PDAC and adjacent normal tissues. The following analyses were performed: different editing level and RNA expression analysis,pathway analysis, motif analysis, RNA secondary structure analysis, alternative splicing events analysis, and survival analysis.The RNA editing of single-cell RNA public sequencing data was also characterized.

Result

A large number of adaptive RNA editing events with significant differences in editing levels were identified, which are mainly regulated by ADAR1. Moreover, RNA editing in tumors has a higher editing level and more abundant editing sites in general. 140genes were screened out since they were identified with significantly different RNA editing events and were significantly different in expression level between tumor and matched normal samples. Further analysis showed a preference that in the tumor-specific group, they are mainly enriched in cancer-related signal pathways, while in the normal tissue-specific group, they are mainly enriched in pancreatic secretion. At the same time, we also found positively selected differentially edited sites in a series of cancer immune genes, including EGF, IGF1R, and PIK3CD. RNA editing might participate in pathogenisis of PDAC through regulating the alternative splicing and RNA secondary structure of important genesto further regulate gene expression and protein synthesis, including RAB27B and CERS4. Furthermore, single cell sequencing results showed that type2 ductal cells contributed the most to RNA editing events in tumors.

Conclusion

RNA editing is an epigenetic mechanism involved in the occurrence and development of pancreatic cancer, which has the potential to diagnose of PDAC and is closely related to the prognosis.

ADeditome provides the genomic landscape of A-to-I RNA editing in Alzheimer's disease

A-to-I RNA editing, contributing to nearly 90% of all editing events in human, has been reported to involve in the pathogenesis of Alzheimer's disease (AD) due to its roles in brain development and immune regulation, such as the deficient editing of GluA2 Q/R related to cell death and memory loss. Currently, there are urgent needs for the systematic annotations of A-to-I RNA editing events in AD. Here, we built ADeditome, the annotation database of A-to-I RNA editing in AD available at https://ccsm.uth.edu/ADeditome, aiming to provide a resource and reference for functional annotation of A-to-I RNA editing in AD to identify therapeutically targetable genes in an individual. We detected 1676 363 editing sites in 1524 samples across nine brain regions from ROSMAP, MayoRNAseq and MSBB. For these editing events, we performed multiple functional annotations including identification of specific and disease stage associated editing events and the influence of editing events on gene expression, protein recoding, alternative splicing and miRNA regulation for all the genes, especially for AD-related genes in order to explore the pathology of AD. Combing all the analysis results, we found 108 010 and 26 168 editing events which may promote or inhibit AD progression, respectively. We also found 5582 brain region-specific editing events with potentially dual roles in AD across different brain regions. ADeditome will be a unique resource for AD and drug research communities to identify therapeutically targetable editing events. Significance: ADeditome is the first comprehensive resource of the functional genomics of individual A-to-I RNA editing events in AD, which will be useful for many researchers in the fields of AD pathology, precision medicine, and therapeutic researches.

RNA editing affects cis-regulatory elements and predicts adverse cancer survival

BACKGROUND

RNA editing exerts critical impacts on numerous biological processes and thus are implicated in crucial human phenotypes, including tumorigenesis and prognosis. While previous studies have analyzed aggregate RNA editing activity at the sample level and associated it with overall cancer survival, there is not yet a large-scale disease-specific survival study to examine genome-wide RNA editing sites' prognostic value taking into account the host gene expression and clinical variables.

METHODS

In this study, we solved comprehensive Cox proportional models of disease-specific survival on individual RNA-editing sites plus host gene expression and critical demographic covariates. This allowed us to interrogate the prognostic value of a large number of RNA-editing sites at single-nucleotide resolution.

RESULTS

As a result, we identified 402 gene-proximal RNA-editing sites that generally predict adverse cancer survival. For example, an RNA-editing site residing in ZNF264 indicates poor survival of uterine corpus endometrial carcinoma, with a hazard ratio of 2.13 and an adjusted p-value of 4.07 × 10-7 . Some of these prognostic RNA-editing sites mediate the binding of RNA binding proteins and microRNAs, thus propagating their impacts to extensive regulatory targets.

CONCLUSIONS

In conclusion, RNA editing affects cis-regulatory elements and predicts adverse cancer survival.

RNA editing signatures identify melanoma patients who respond to Pembrolizumab or Nivolumab treatment

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Global RNA editing levels or ADAR expression do not correlate with response to immunotherapy in melanoma patients.

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RNA editing signatures within genes can segregate patients that will respond to immunotherapy across patient cohorts.

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Recurrent RNA editing sites, those that are shared between melanoma patients, provide accurate prognostic predictions.

Immunotherapy has improved the prognosis for many melanoma patients; however, our capacity to predict patient responses and to understand the biological differences between patients who will or will not respond is limited. Gene expression profiling of tumors from patients who respond to immunotherapy has focused on deriving primarily immune-related signatures; however, these have shown limited predictive power. Recent studies have highlighted the role of RNA editing in modulating resistance to immunotherapy. To evaluate the utility of RNA editing activity as a discriminative tool in predicting immunotherapy response, we conducted a retrospective analysis of RNA-sequencing data from melanoma patients treated with Pembrolizumab or Nivolumab. Here, we developed RNA editing signatures that can identify patients who will respond to immunotherapy with very high accuracy and confidence. Our analysis demonstrates that RNA editing is a strong discriminative tool for examining sensitivity of melanoma patients to immunotherapy.

Identification and Analysis of RNA Editing Events in Ovarian Serous Cystadenoma Using RNA-seq Data

BACKGROUND

Recent studies have revealed thousands of A-to-I RNA editing events in primates. These events are closely related to the occurrence and development of multiple cancers, but the origination and general functions of these events in ovarian cancer remain incompletely understood.

OBJECTIVE

To further the determination of molecular mechanisms of ovarian cancer from the perspective of RNA editing.

METHODS

Here, we used the SNP-free RNA editing Identification Toolkit (SPRINT) to detect RNA editing sites. These editing sites were then annotated, and related functional analysis was performed.

RESULTS

In this study, about 1.7 million RES were detected in each sample, and 98% of these sites were due to A-to-G editing and were mainly distributed in non-coding regions. More than 1,000 A-- to-G RES were detected in CDS regions, and nearly 700 could lead to amino acid changes. Our results also showed that editing in the 3'UTR regions could influence miRNA-target binding. We predicted the network of changed miRNA-mRNA interaction caused by the A-to-I RNA editing sites. We also screened the differential RNA editing sites between ovarian cancer and adjacent normal tissues. We then performed GO and KEGG pathway enrichment analysis on the genes that contained these differential RNA editing sites. Finally, we identified the potential dysregulated RNA editing events in ovarian cancer samples.

CONCLUSION

This study systematically identified and analyzed RNA editing events in ovarian cancer and laid a foundation to explore the regulatory mechanism of RNA editing and its function in ovarian cancer.

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

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.

Genome-Wide Characterization of RNA Editing Sites in Primary Gastric Adenocarcinoma through RNA-seq Data Analysis

RNA editing is a posttranscriptional nucleotide modification in humans. Of the various types of RNA editing, the adenosine to inosine substitution is the most widespread in higher eukaryotes, which is mediated by the ADAR family enzymes. Inosine is recognized by the biological machinery as guanosine; therefore, editing could have substantial functional effects throughout the genome. RNA editing could contribute to cancer either by exclusive editing of tumor suppressor/promoting genes or by introducing transcriptomic diversity to promote cancer progression. Here, we provided a comprehensive overview of the RNA editing sites in gastric adenocarcinoma and highlighted some of their possible contributions to gastric cancer. RNA-seq data corresponding to 8 gastric adenocarcinoma and their paired nontumor counterparts were retrieved from the GEO database. After preprocessing and variant calling steps, a stringent filtering pipeline was employed to distinguish potential RNA editing sites from SNPs. The identified potential editing sites were annotated and compared with those in the DARNED database. Totally, 12362 high-confidence adenosine to inosine RNA editing sites were detected across all samples. Of these, 12105 and 257 were known and novel editing events, respectively. These editing sites were unevenly distributed across genomic regions, and nearly half of them were located in 3′UTR. Our results revealed that 4868 editing sites were common in both normal and cancer tissues. From the remaining sites, 3985 and 3509 were exclusive to normal and cancer tissues, respectively. Further analysis revealed a significant number of differentially edited events among these sites, which were located in protein coding genes and microRNAs. Given the distinct pattern of RNA editing in gastric adenocarcinoma and adjacent normal tissue, edited sites have the potential to serve as the diagnostic biomarkers and therapeutic targets in gastric cancer.

ADARs, RNA editing and more in hematological malignancies

Adenosine-to-inosine (A-to-I) editing is the most prevalent type of RNA editing in humans, mediated by the adenosine deaminases acting on RNA (ADARs). Physiologically, these enzymes are present in the nucleus and/or the cytoplasm, where they catalyze the conversion of adenosines (A) to inosines (I) on double-stranded mRNA molecules. Aberrant ADAR-mediated-editing is a prominent feature in a variety of cancers. Importantly, the biological functions of ADARs and its functional implications in hematological malignancies have recently been unraveled. In this review, we will highlight the functions of ADARs and their involvements in cancer, specifically in hematological malignancies. RNA editing-independent function of cellular processes by ADARs and the potential of developing novel therapeutic approaches revolving RNA editing will also be discussed.

Advancing Pan-cancer Gene Expression Survial Analysis by Inclusion of Non-coding RNA

Non-coding RNAs occupy a significant fraction of the human genome. Their biological significance is backed up by a plethora of emerging evidence. One of the most robust approaches to demonstrate non-coding RNA's biological relevance is through their prognostic value. Using the rich gene expression data from The Cancer Genome Altas (TCGA), we designed Advanced Expression Survival Analysis (AESA), a web tool which provides several novel survival analysis approaches not offered by previous tools. In addition to the common single-gene approach, AESA computes the gene expression composite score of a set of genes for survival analysis and utilizes permutation test or cross-validation to assess the significance of log-rank statistic and the degree of over-fitting. AESA offers survival feature selection with post-selection inference and utilizes expanded TCGA clinical data including overall, disease-specific, disease-free, and progression-free survival information. Users can analyse either protein-coding or non-coding regions of the transcriptome. We demonstrated the effectiveness of AESA using several empirical examples. Our analyses showed that non-coding RNAs perform as well as messenger RNAs in predicting survival of cancer patients. These results reinforce the potential prognostic value of non-coding RNAs. AESA is developed as a module in the freely accessible analysis suite MutEx. Abbreviation: ACC: Adrenocortical Carcinoma (n = 92); BLCA: Bladder Urothelial Carcinoma (n = 412); BRCA: Breast Invasive Carcinoma (n = 1098); CESC: Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (n = 307); CHOL: Cholangiocarcinoma (n = 51); COAD: Colon Adenocarcinoma (n = 461); DLBC: Lymphoid Neoplasm Diffuse Large B-cell Lymphoma (n = 58); ESCA: Oesophageal Carcinoma (n = 185); GBM: Glioblastoma Multiforme (n = 617); HNSC: Head and Neck Squamous Cell Carcinoma (n = 528); KICH: Kidney Chromophobe (n = 113); KIRC: Kidney Renal Clear Cell Carcinoma (n = 537); KIRP: Kidney Renal Papillary Cell Carcinoma (n = 291); LAML: Acute Myeloid Leukaemia (n = 200); LGG: Brain Lower Grade Glioma (n = 516); LIHC: Liver Hepatocellular Carcinoma (n = 377); LUAD: Lung Adenocarcinoma (n = 585); LUSC: Lung Squamous Cell Carcinoma (n = 504); MESO: Mesothelioma (n = 87); OV: Ovarian Serous Cystadenocarcinoma (n = 608) PAAD: Pancreatic Adenocarcinoma (n = 185); PCPG: Pheochromocytoma and Paraganglioma (n = 179); PRAD: Prostate Adenocarcinoma (n = 500); READ: Rectum Adenocarcinoma (n = 172); SARC: Sarcoma (n = 261); SKCM: Skin Cutaneous Melanoma (n = 470); STAD: Stomach Adenocarcinoma (n = 443); TGCT: Testicular Germ Cell Tumours (n = 150); THCA: Thyroid Carcinoma (n = 507) THYM: Thymoma (n = 124); UCEC: Uterine Corpus Endometrial Carcinoma (n = 560); UCS: Uterine Carcinosarcoma (n = 57); UVM: Uveal Melanoma (n = 80).

APOBEC3-Mediated RNA Editing in Breast Cancer is Associated with Heightened Immune Activity and Improved Survival

APOBEC3 enzymes contribute significantly to DNA mutagenesis in cancer. These enzymes are also capable of converting C bases at specific positions of RNAs to U. However, the prevalence and significance of this C-to-U RNA editing in any cancer is currently unknown. We developed a bioinformatics workflow to determine RNA editing levels at known APOBEC3-mediated RNA editing sites using exome and mRNA sequencing data of 1040 breast cancer tumors. Although reliable editing determinations were limited due to sequencing depth, editing was observed in both tumor and adjacent normal tissues. For 440 sites (411 genes), editing was determinable for ≥5 tumors, with editing occurring in 0.6%-100% of tumors (mean 20%, SD 14%) at an average level of 0.6%-20% (mean 7%, SD 4%). Compared to tumors with low RNA editing, editing-high tumors had enriched expression of immune-related gene sets, and higher T cell and M1 macrophage infiltration, B and T cell receptor diversity, and immune cytolytic activity. Concordant with this, patients with increased RNA editing in tumors had better disease- and progression-free survivals (hazard ratio = 1.67-1.75, p < 0.05). Our study identifies that APOBEC3-mediated RNA editing occurs in breast cancer tumors and is positively associated with elevated immune activity and improved survival.