Identification of key eRNAs for intervertebral disc degeneration by integrated multinomial bioinformatics analysis

BACKGROUND

Intervertebral disc degeneration (IVDD) is a common degenerative condition leading to abnormal stress distribution under load, causing intervertebral stenosis, facet joint degeneration, and foraminal stenosis. Very little is known about the molecular mechanism of eRNAs in IVDD.

METHODS

Gene expression profiles of 38 annulus disc samples composed of 27 less degenerated discs (LDs) and 11 more degenerated discs (MDs) were retrieved from the GEO database. Then, differentially expressed enhancer RNAs (DEeRNAs), differentially expressed target genes (DETGs), and differentially expressed transcription factors (DETFs), hallmark of cancer signalling pathways according to GSVA; the types and quantity of immune cells according to CIBERSORT; and immune gene sets according to ssGSEA were analysed to construct an IVDD-related eRNA network. Then, multidimensional validation was performed to explore the interactions among DEeRNAs, DETFs and DEGs in space.

RESULTS

A total of 53 components, 14 DETGs, 15 DEeRNAs, 3 DETFs, 5 immune cells, 9 hallmarks, and 7 immune gene sets, were selected to construct the regulatory network. After validation by online multidimensional databases, 21 interactive DEeRNA-DEG-DETF axes related to IVDD exacerbation were identified, among which the C1S-CTNNB1-CHD4 axis was the most significant.

CONCLUSION

Based upon the results of our study, we theorize that the C1S-CTNNB1-CHD4 axis plays a vital role in IVDD exacerbation. Specifically, C1S recruits CTNNB1 and upregulates the expression of CHD4 in IVDD, and subsequently, CHD4 suppresses glycolysis and activates oxidative phosphorylation, thus generating insoluble collagen fibre deposits and leading to the progression of IVDD. Overall, these DEeRNAs could comprise promising therapeutic targets for IVDD due to their high tissue specificity.

Hammerhead-type FXR agonists induce an enhancer RNA Fincor that ameliorates nonalcoholic steatohepatitis in mice

The nuclear receptor, farnesoid X receptor (FXR/NR1H4), is increasingly recognized as a promising drug target for metabolic diseases, including nonalcoholic steatohepatitis (NASH). Protein-coding genes regulated by FXR are well known, but whether FXR also acts through regulation of long non-coding RNAs (lncRNAs), which vastly outnumber protein-coding genes, remains unknown. Utilizing RNA-seq and global run-on sequencing (GRO-seq) analyses in mouse liver, we found that FXR activation affects the expression of many RNA transcripts from chromatin regions bearing enhancer features. Among these we discovered a previously unannotated liver-enriched enhancer-derived lncRNA (eRNA), termed FXR-induced non-coding RNA (Fincor). We show that Fincor is specifically induced by the hammerhead-type FXR agonists, including GW4064 and tropifexor. CRISPR/Cas9-mediated liver-specific knockdown of Fincor in dietary NASH mice reduced the beneficial effects of tropifexor, an FXR agonist currently in clinical trials for NASH and primary biliary cholangitis (PBC), indicating that amelioration of liver fibrosis and inflammation in NASH treatment by tropifexor is mediated in part by Fincor. Overall, our findings highlight that pharmacological activation of FXR by hammerhead-type agonists induces a novel eRNA, Fincor, contributing to the amelioration of NASH in mice. Fincor may represent a new drug target for addressing metabolic disorders, including NASH.

Prognostic and onco-immunological value of immune-related eRNAs-driven genes in lung adenocarcinoma

BACKGROUND

We aimed to comprehensively analyze the clinical value of immune-related eRNAs-driven genes in lung adenocarcinoma (LUAD) and find the potential biomarkers for prognosis and therapeutic response to improve the survival of this malignant disease.

MATERIALS AND METHODS

Pearson's correlation analysis was performed to identify the immune-related eRNAs-driven genes. Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were used to construct this prognostic risk signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to investigate the underlying molecular mechanism. The single sample gene set enrichment analysis (ssGSEA) algorithm was conducted to evaluate the immune status based on the signature. The quantitative real-time PCR (qRT-PCR) analysis was performed to evaluate the expression value of the signature genes between LUAD tissues and adjacent lung tissues.

RESULTS

Five immune-related eRNAs-driven genes (SHC1, GDF10, CCL14, FYN, and NOD1) were identified to construct a prognostic risk signature with favorable predictive capacity. The patients with high-risk scores based on the signature were significantly associated with the malignant clinical features compared with those with low-risk scores. Kaplan-Meier analysis demonstrated that the sample in the low-risk group had a prolonged survival compared with those in the high-risk group. This risk signature was validated to have a promising predictive capacity and reliability in diverse clinical situations and independent cohorts. The functional enrichment analysis demonstrated that humoral immune response and intestinal immune network for IgA production pathway might be the underlying molecular mechanism related to the signature. The proportion of the vast majority of immune infiltrating cells in the high-risk group was significantly lower than that in the low-risk group, and the immunotherapy response rate in the low-risk group was significantly higher than that in the high-risk group. Moreover, BI-2536, sepantronium bromide, and ULK1 were the potential drugs for the treatment of patients with higher risk scores. Finally, the experiment in vivo and database analysis indicated that CCL14, FYN, NOD1, and GDF10 are the potential LUAD suppressor and SHC1 is a potential treatment target for LUAD.

CONCLUSION

Above all, we constructed a prognostic risk signature with favorable predictive capacity in LUAD, which was significantly associated with malignant features, immunosuppressive tumor microenvironment, and immunotherapy response and may provide clinical benefit in clinical decisions.

Comprehensive profiling of enhancer RNA in stage II/III colorectal cancer defines two prognostic subtypes with implications for immunotherapy

BACKGROUND

Recently, enhancer RNAs (eRNAs) have garnered attention as pivotal biomarkers for the onset and progression of cancer. However, the landscape of eRNAs and the implications of eRNA-based molecular subtypes in stage II/III colorectal cancer (CRC) remain largely unexplored.

METHODS

Comprehensive profiling of eRNAs was conducted on a public stage II/III CRC cohort with total RNA-seq data. We used unsupervised clustering of prognostic eRNAs to establish an eRNA-based subtyping system. Further evaluations included molecular characteristics, immune infiltration, clinical outcomes, and drug responses. Finally, we validated the eRNA-based subtyping system in The Cancer Genome Atlas (TCGA) CRC cohort.

RESULTS

We identified a total of 6453 expressed eRNAs, among which 237 were prognostic. A global upregulation of eRNAs was observed in microsatellite-stable (MSS) CRCs when compared to microsatellite instability-high (MSI-H) CRCs. Through consensus clustering, two novel molecular subtypes, termed Cluster 1(C1) and Cluster 2(C2), were further identified. C1, associated with the activation of epithelial-mesenchymal transition (EMT), hypoxia, and KRAS signaling pathways, showed poorer prognosis. C2, correlated with the canonical CRC subtype, exhibited superior survival outcomes. In addition, C1 showed enrichment with immune infiltration and more sensitivity to immune checkpoint inhibitors.

CONCLUSION

Our study unravels the molecular heterogeneity of stage II/III CRC at the eRNA level and highlights the potential applications of the novel eRNA-based subtyping system in predicting prognosis and guiding immunotherapy.

An Emerging Role for Enhancer RNAs in Brain Disorders

Noncoding DNA undergoes widespread context-dependent transcription to produce noncoding RNAs. In recent decades, tremendous advances in genomics and transcriptomics have revealed important regulatory roles for noncoding DNA elements and the RNAs that they produce. Enhancers are one such element that are well-established drivers of gene expression changes in response to a variety of factors such as external stimuli, cellular responses, developmental cues, and disease states. They are known to act at long distances, interact with multiple target gene loci simultaneously, synergize with other enhancers, and associate with dynamic chromatin architectures to form a complex regulatory network. Recent advances in enhancer biology have revealed that upon activation, enhancers transcribe long noncoding RNAs, known as enhancer RNAs (eRNAs), that have been shown to play important roles in enhancer-mediated gene regulation and chromatin-modifying activities. In the brain, enhancer dysregulation and eRNA transcription has been reported in numerous disorders from acute injuries to chronic neurodegeneration. Because this is an emerging area, a comprehensive understanding of eRNA function has not yet been achieved in brain disorders; however, the findings to date have illuminated a role for eRNAs in activity-driven gene expression and phenotypic outcomes. In this review, we highlight the breadth of the current literature on eRNA biology in brain health and disease and discuss the challenges as well as focus areas and strategies for future in-depth research on eRNAs in brain health and disease.

Identification of an immune-related eRNA prognostic signature for clear cell renal cell carcinoma

BACKGROUND

Immune-related enhancer RNAs (eRNAs) have garnered significant attention in cancer metabolism research, yet their specific roles in ccRCC have remained elusive.

METHODS

We retrieved eRNA expression profiles from TCGA database and identified immune-related eRNAs (IREs) by assessing their co-expression with immune genes. Utilizing consensus clustering, we organized these IREs into two distinct clusters. The construction of an IREs signature was accomplished through the LASSO and multivariate Cox analysis. Furthermore, we performed Cell Counting Kit-8 and clonogenic assays to assess changes in the proliferative capacity of Caki-1 and 769-P cells.

RESULTS

The existence of two clusters of immune-related eRNAs in ccRCC, each with distinctive prognostic and immunological attributes. Cluster B exhibited immunosuppressive properties and displayed a positive correlation with immunosuppressive cells. Functional enrichment analysis unveiled their involvement in several tumor-promoting pathways, metabolic pathways and immune pathways. The IREs signature demonstrated its potential to accurately predict patient immune and prognostic characteristics. AC003092.1, an eRNA strongly associated with patient survival, emerged as a potential oncogene significantly linked to adverse prognosis and the presence of immunosuppressive cells and checkpoints in ccRCC patients. Notably, AC003092.1 displayed marked upregulation in ccRCC tissues and cell lines, and its knockdown substantially inhibited the proliferation of Caki-1 and 769-P cells.

CONCLUSION

We established a robust predictive model that played a vital role in determining the prognosis, clinicopathological characteristics and immune cell infiltration patterns of ccRCC patients. IRE, particularly AC003092.1, which was strongly associated with survival, hold promise as novel immunotherapeutic targets for ccRCC.

eRNAbase: a comprehensive database for decoding the regulatory eRNAs in human and mouse

Enhancer RNAs (eRNAs) transcribed from distal active enhancers serve as key regulators in gene transcriptional regulation. The accumulation of eRNAs from multiple sequencing assays has led to an urgent need to comprehensively collect and process these data to illustrate the regulatory landscape of eRNAs. To address this need, we developed the eRNAbase (http://bio.liclab.net/eRNAbase/index.php) to store the massive available resources of human and mouse eRNAs and provide comprehensive annotation and analyses for eRNAs. The current version of eRNAbase cataloged 10 399 928 eRNAs from 1012 samples, including 858 human samples and 154 mouse samples. These eRNAs were first identified and uniformly processed from 14 eRNA-related experiment types manually collected from GEO/SRA and ENCODE. Importantly, the eRNAbase provides detailed and abundant (epi)genetic annotations in eRNA regions, such as super enhancers, enhancers, common single nucleotide polymorphisms, expression quantitative trait loci, transcription factor binding sites, CRISPR/Cas9 target sites, DNase I hypersensitivity sites, chromatin accessibility regions, methylation sites, chromatin interactions regions, topologically associating domains and RNA spatial interactions. Furthermore, the eRNAbase provides users with three novel analyses including eRNA-mediated pathway regulatory analysis, eRNA-based variation interpretation analysis and eRNA-mediated TF-target gene analysis. Hence, eRNAbase is a powerful platform to query, browse and visualize regulatory cues associated with eRNAs.

Bivalent activity of super-enhancer RNA LINC02454 controls 3D chromatin structure and regulates glioma sensitivity to temozolomide

Glioma cell sensitivity to temozolomide (TMZ) is critical for effective treatment and correlates with patient survival, although mechanisms underlying this activity are unclear. Here, we reveal a new mechanism used by glioma cells to modulate TMZ sensitivity via regulation of SORBS2 and DDR1 genes by super-enhancer RNA LINC02454. We report that LINC02454 activity increases glioma cell TMZ sensitivity by maintaining long-range chromatin interactions between SORBS2 and the LINC02454 enhancer. By contrast, LINC02454 activity also decreased glioma cell TMZ sensitivity by promoting DDR1 expression. Our study suggests a bivalent function for super-enhancer RNA LINC02454 in regulating glioma cell sensitivity to TMZ.

Comprehensive Pan-Cancer Mutation Density Patterns in Enhancer RNA

Significant advances have been achieved in understanding the critical role of enhancer RNAs (eRNAs) in the complex field of gene regulation. However, notable uncertainty remains concerning the biology of eRNAs, highlighting the need for continued research to uncover their exact functions in cellular processes and diseases. We present a comprehensive study to scrutinize mutation density patterns, mutation strand bias, and mutation burden in eRNAs across multiple cancer types. Our findings reveal that eRNAs exhibit mutation strand bias akin to that observed in protein-coding RNAs. We also identified a novel pattern, in which mutation density is notably diminished around the central region of the eRNA, but conspicuously elevated towards both the beginning and end. This pattern can be potentially explained by a mechanism involving heightened transcriptional activity and the activation of transcription-coupled repair. The central regions of the eRNAs appear to be more conserved, hinting at a potential mechanism preserving their structural and functional integrity, while the extremities may be more susceptible to mutations due to increased exposure. The evolutionary trajectory of this mutational pattern suggests a nuanced adaptation in eRNAs, where stability at their core coexists with flexibility at their extremities, potentially facilitating their diverse interactions with other genetic entities.