Enhancer RNAs in cancer: regulation, mechanisms and therapeutic potential

hnRNPA0 promotes MYB expression by interacting with enhancer lncRNA MY34UE-AS in human leukemia cells

MYB is a key regulator of hematopoiesis and erythropoiesis, and dysregulation of MYB is closely involved in the development of leukemia, however the mechanism of MYB regulation remains still unclear so far. Our previous study identified a long noncoding RNA (lncRNA) derived from the -34 kb enhancer of the MYB locus, which can promote MYB expression, the proliferation and migration of human leukemia cells, and is therefore termed MY34UE-AS. Then the interacting partner proteins of MY34UE-AS were identified and studied in the present study. hnRNPA0 was identified as a binding partner of MY34UE-AS through RNA pulldown assay, which was further validated through RNA immunoprecipitation (RIP). hnRNPA0 interacted with MY34UE-AS mainly through its RRM2 domain. hnRNPA0 overexpression upregulated MYB and increased the proliferation and migration of K562 cells, whereas hnRNPA0 knockdown showed opposite effects. Rescue experiments showed MY34UE-AS was required for above mentioned functions of hnRNPA0. These results reveal that hnRNPA0 is involved in leukemia through upregulating MYB expression by interacting with MY34UE-AS, suggesting that the hnRNPA0/MY34UE-AS axis could serve as a potential target for leukemia treatment.

Pan-cancer analysis of super-enhancer-induced LINC00862 and validation as a SIRT1-promoting factor in cervical cancer and gastric cancer

Immune checkpoints inhibitors are effective but it needs more precise biomarkers for patient selection. We explored the biological significance of LINC00862 in pan-cancer by bioinformatics. And we studied its regulatory mechanisms using chromatin immunoprecipitation and RNA immunoprecipitation assays etc. TCGA and single-cell sequencing data analysis indicated that LINC00862 was overexpressed in the majority of tumor and stromal cells, which was related with poor prognosis. LINC00862 expression was related with immune cell infiltration and immune checkpoints expression, and had a high predictive value for immunotherapy efficacy. Mechanistically, LINC00862 competitively bound to miR-29c-3p to unleash SIRT1's tumor-promoting function. SIRT1 inhibitor-EX527 were screened by virtual screening and verified by in vitro and vivo assays. Notably, acetyltransferase P300-mediated super-enhancer activity stimulated LINC00862 transcription. Collectively, LINC00862 could be a diagnostic and prognostic biomarker. LINC00862 could also be a predictive biomarker for immunotherapy efficacy. Super-enhancer activity is the driver for LINC00862 overexpression in cervical cancer and gastric cancer.

Downregulation of enhancer RNA AC003092.1 is associated with poor prognosis in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is the most common histological type of renal cancer, enhancer RNA plays a significant role in tumor growth, however, it has been less studied in renal cancer. The aim of this study was to investigate the role of eRNA AC003092.1 in KIRC. Clinical and RNA expression data were downloaded from a TCGA database, and performed bioinformatics analysis, including expression level analysis, survival analysis, clinical correlation analysis, immune correlation analysis. We further confirmed the expression level of AC003092.1 between normal and tumor cell, predicted the biological role of AC003092.1 in KIRC, and performed cell proliferation and wound healing assays, followed by GSEA enrichment analysis and western blot to detect the proteins of the enriched pathway. Bioinformatics results showed that AC003092.1 expression was elevated in tumor tissues, and knockdown of AC003092.1 expression inhibited cell proliferation and migration. GSEA and western blot results showed that knockdown AC003092.1 expression alleviated the extracellular matrix (ECM) process in KIRC cell lines. Our study provides evidence that AC003092.1 play an important role in KIRC, and AC003092.1 may promote tumor cell progression by affecting the ECM process during tumor development.

CCAT1 lncRNA is chromatin-retained and post-transcriptionally spliced

Super-enhancers are unique gene expression regulators widely involved in cancer development. Spread over large DNA segments, they tend to be found next to oncogenes. The super-enhancer c-MYC locus forms long-range chromatin looping with nearby genes, which brings the enhancer and the genes into proximity, to promote gene activation. The colon cancer-associated transcript 1 (CCAT1) gene, which is part of the MYC locus, transcribes a lncRNA that is overexpressed in colon cancer cells through activation by MYC. Comparing different types of cancer cell lines using RNA fluorescence in situ hybridization (RNA FISH), we detected very prominent CCAT1 expression in HeLa cells, observed as several large CCAT1 nuclear foci. We found that dozens of CCAT1 transcripts accumulate on the gene locus, in addition to active transcription occurring from the gene. The accumulating transcripts are released from the chromatin during cell division. Examination of CCAT1 lncRNA expression patterns on the single-RNA level showed that unspliced CCAT1 transcripts are released from the gene into the nucleoplasm. Most of these unspliced transcripts were observed in proximity to the active gene but were not associated with nuclear speckles in which unspliced RNAs usually accumulate. At larger distances from the gene, the CCAT1 transcripts appeared spliced, implying that most CCAT1 transcripts undergo post-transcriptional splicing in the zone of the active gene. Finally, we show that unspliced CCAT1 transcripts can be detected in the cytoplasm during splicing inhibition, which suggests that there are several CCAT1 variants, spliced and unspliced, that the cell can recognize as suitable for export.

Pathogenic role of super-enhancers as potential therapeutic targets in lung cancer

Lung cancer is still one of the deadliest malignancies today, and most patients with advanced lung cancer pass away from disease progression that is uncontrollable by medications. Super-enhancers (SEs) are large clusters of enhancers in the genome's non-coding sequences that actively trigger transcription. Although SEs have just been identified over the past 10 years, their intricate structure and crucial role in determining cell identity and promoting tumorigenesis and progression are increasingly coming to light. Here, we review the structural composition of SEs, the auto-regulatory circuits, the control mechanisms of downstream genes and pathways, and the characterization of subgroups classified according to SEs in lung cancer. Additionally, we discuss the therapeutic targets, several small-molecule inhibitors, and available treatment options for SEs in lung cancer. Combination therapies have demonstrated considerable advantages in preclinical models, and we anticipate that these drugs will soon enter clinical studies and benefit patients.

Integrated analysis of transcriptome and epigenome reveals ENSR00000272060 as a potential biomarker in gastric cancer

Background: Enhancer RNAs (eRNAs) are involved in gene expression regulation. Although functional roles of eRNAs in the pathophysiology of neoplasms have been reported, their involvement in gastric cancer (GC) is less known. Materials & methods: A network-based integrative approach was utilized for analyzing transcriptome and epigenome alterations in GC, and an eRNA was selected for experimental validation. Survival analysis and clinicopathological associations were also performed. Results: A hub eRNA, ENSR00000272060, showed significantly increased expression in tumor versus nontumor tissues, as well as an association with clinicopathological features. A seven-gene prognostic model was also constructed. Conclusion: The constructed network provides a comprehensive understanding of the underlying processes implicated in the progression of GC, along with a starting point from which to derive potential diagnostic/prognostic biomarkers.

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.

LINC00887 Acts as an Enhancer RNA to Promote Medullary Thyroid Carcinoma Progression by Binding with FOXQ1

BACKGROUND

Medullary thyroid carcinoma (MTC) is a rare but aggressive endocrine malignancy that originates from the parafollicular C cells of the thyroid gland. Enhancer RNAs (eRNAs) are non-coding RNAs transcribed from enhancer regions, which are critical regulators of tumorigenesis. However, the roles and regulatory mechanisms of eRNAs in MTC remain poorly understood. This study aims to identify key eRNAs regulating the malignant phenotype of MTC and to uncover transcription factors involved in the regulation of key eRNAs.

METHODS

GSE32662 and GSE114068 were used for the identification of differentially expressed genes, eRNAs, enhancers and enhancer-regulated genes in MTC. Metascape and the transcription factor affinity prediction method were used for gene function enrichment and transcription factor prediction, respectively. qRT-PCR was used to detect gene transcription levels. ChIP-qPCR was used to assess the binding of histone H3 lysine 27 acetylation (H3K27ac)-enriched regions to anti- H3K27ac. RIP-qPCR was used to detect the binding between FOXQ1 and LINC00887. CCK8 and Transwell were performed to measure the proliferation and invasion of MTC cells, respectively. Intracellular reactive oxygen species (ROS) levels were quantified using a ROS assay kit.

RESULTS

Four eRNAs (H1FX-AS1, LINC00887, MCM3AP-AS1 and A1BG-AS1) were screened, among which LINC00887 was the key eRNA promoting the proliferation and invasion of MTC cells. A total of 135 genes controlled by LINC00887-regulated enhancers were identified; among them, BCL2, PRDX1, SFTPD, TPO, GSS, RAD52, ZNF580, and ZFP36L1 were significantly enriched in the "ROS metabolic process" term. As a transcription factor regulating genes enriched in the "ROS metabolic process" term, FOXQ1 could recruit LINC00887. Overexpression of FOXQ1 restored LINC00887 knockdown-induced downregulation of GSS and ZFP36L1 transcription in MTC cells. Additionally, FOXQ1 overexpression counteracted the inhibitory effects of LINC00887 knockdown on the proliferation and invasion of MTC cells and the promotion of intracellular ROS accumulation induced by LINC00887 knockdown.

CONCLUSION

LINC00887 was identified as a key eRNA promoting the malignant phenotype of MTC cells. The involvement of FOXQ1 was essential for LINC00887 to play a pro-tumorigenic role in MTC. Our findings suggest that the FOXQ1/LINC00887 axis is a potential therapeutic target for MTC.

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.

Identification of a Novel Long Non-Coding RNA G8110 That Modulates Porcine Adipogenic Differentiation and Inflammatory Responses

Long non-coding RNAs (lncRNAs) have been extensively studied, and their crucial roles in adipogenesis, lipid metabolism, and gene expression have been revealed. However, the exact regulatory or other mechanisms by which lncRNAs influence the functioning of mesenteric adipose tissue (MAT) remain largely unknown. In this paper, we report the identification of a new lncRNA, named G8110, from the MAT of Bama pigs. The coordinated expression levels of lncRNA G8110 and NFE2L1 were significantly decreased in the MAT of obese Bama pigs compared with those in the MAT of lean pigs. Using a bone mesenchymal stem cell adipogenic differentiation model, we found that lncRNA G8110 played a role in adipocyte differentiation by positively regulating NFE2L1. We also found that lncRNA G8110 inhibited the formation of intracellular lipid synthesis, promoted lipid metabolism, and inhibited the expression of inflammatory cytokines. Our findings regarding lipid synthesis may further promote the role of lncRNAs in driving adipose tissue remodeling and maintaining metabolic health.

Integrative approaches based on genomic techniques in the functional studies on enhancers

With the development of sequencing technology and the dramatic drop in sequencing cost, the functions of noncoding genes are being characterized in a wide variety of fields (e.g. biomedicine). Enhancers are noncoding DNA elements with vital transcription regulation functions. Tens of thousands of enhancers have been identified in the human genome; however, the location, function, target genes and regulatory mechanisms of most enhancers have not been elucidated thus far. As high-throughput sequencing techniques have leapt forwards, omics approaches have been extensively employed in enhancer research. Multidimensional genomic data integration enables the full exploration of the data and provides novel perspectives for screening, identification and characterization of the function and regulatory mechanisms of unknown enhancers. However, multidimensional genomic data are still difficult to integrate genome wide due to complex varieties, massive amounts, high rarity, etc. To facilitate the appropriate methods for studying enhancers with high efficacy, we delineate the principles, data processing modes and progress of various omics approaches to study enhancers and summarize the applications of traditional machine learning and deep learning in multi-omics integration in the enhancer field. In addition, the challenges encountered during the integration of multiple omics data are addressed. Overall, this review provides a comprehensive foundation for enhancer analysis.

Prognosis of colon cancer patients based on enhancer RNAs-related genes

PURPOSE

Colon cancer (CC) is a cancer of the large intestine with high prevalence and poor prognosis. enhancer RNAs. Therefore, valuable tools or biomarkers for predicting patient status, directing clinical practice, and reducing overtreatment are needed. Enhancer RNAs (eRNAs), a class of noncoding RNAs transcribed from enhancers, have been shown to function as regulators of oncogene or tumor suppressor gene expression. The aim of our study was to explore the potential roles of eRNAs and their target enhancer-related genes (ERGs) in the prognosis of CC.

METHODS

Selected CC cases (stage I-III) from The Cancer Genome Atlas database were used as a training set, and cases from the Gene Expression Omnibus were used as the validation set. ERGs associated with prognosis were screened through three steps: potential, candidate, and prognosis ERGs. Multivariate Cox proportional hazards analysis was used to identify independent prognostic factors, and a nomogram was created. Calibration curves were drawn by comparing predicted and observed survival probability. For validation, the calibration curves and ROC analysis were also applied to two external validation sets. The biological significance and clinical application of the genes obtained were investigated.

RESULTS

Based on the multiple tiers of strict screening, 11 prognostic ERGs were obtained, which were combined to obtain a prognosis signature. A compound nomogram integrating age, TNM classification, and the prognostic signature was constructed. The model was reliable in distinguishing the risk of patients with stage I-III CC, with AUCs of 0.78 and 0.70 at 5 and 7 years, respectively. There was good reproducibility in calibration curves. The prognostic model also yielded good prediction capability in the validation sets.

CONCLUSION

In this study, the usefulness and specificity of the ERGs in prognosis were described, which should be considered a key feature in the clinical guidance of CC patients with early stage. We concluded that the major implications of the eRNAs and ERGs should be valued, which would be an emerging hallmark in the prognosis of cancer.

Carcinogen-induced super-enhancer RNA promotes nasopharyngeal carcinoma metastasis through NPM1/c-Myc/NDRG1 axis

Chemical carcinogen is one etiology of nasopharyngeal carcinoma (NPC) occurrence, N,N'-Dinitrosopiperazine (DNP) has been verified to cause NPC cell metastasis and generate induced pluripotent stem cells (iPSCs). To investigate the oncogenic mechanism of DNP, NPC cells were exposed to DNP, and subjected to RNA-seq, GRO-seq, ChIP-seq, and data analysis. The results showed that the super-enhancer RNA (seRNA) participates in DNP-mediated NPC metastasis through regulating N-myc downstream regulated gene 1 (NDRG1). Mechanistically, DNP exposure upregulates the levels of NPC metastatic seRNA (seRNA-NPCm), seRNA-NPCm interacted with a special super-enhancer (SE) upstream of NDRG1 gene and bound to nucleophosmin (NPM1)/c-Myc complex at the NDRG1 promoter, resulting in an increase of NDRG1 transcription. Functional studies showed that DNP significantly increased the metastatic capability of NPC cells in vitro and in vivo. Knockdown of seRNA-NPCm in NPC cells impaired the capability of metastasis. Furthermore, stably overexpressing seRNA-NPCm significantly increased the metastatic ability of NPC cells, while restoration of NDRG1 levels in these cells restored their metastatic capacity. Finally, the immunohistochemistry and in situ hybridization analyses revealed that the expression of seRNA-NPCm in NPC patients is positively correlated with NDRG1, and the NDRG1 level independently predicts poor prognosis of NPC patients. Collectively, DNP induces seRNA-NPCm, and seRNA-NPCm promotes NPC metastasis through NPM1/c-Myc/NDRG1 axis.

COVID-19 mRNA vaccines as hypothetical epigenetic players: Results from an in silico analysis, considerations and perspectives

OBJECTIVES

To investigate in silico the occurrence of epigenetic crosstalk by nucleotide sequence complementarity between the BNT162b2 mRNA vaccine and whole human genome, including coding and noncoding (nc)RNA genes. To correlate these results with those obtained with the original spike (S) gene of Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2).

METHODS

The publicly available FASTA sequence of the BNT162b2 mRNA vaccine and the SARS-CoV-2 isolate Wuhan-Hu-1 S gene (NC_045512.2) were used separately as key input to the Ensembl.org library to evaluate base pair match to human GRCh38 genome. Human coding and noncoding genes harboring hits were assessed for functional activity and health effects using bioinformatics tools and GWAS databases.

RESULTS

The BLAT analysis against the human GRCh38 genome revealed a total of 37 hits for BNT162b2 mRNA and no hits for the SARS-CoV-2 S gene. More specifically, BNT162b2 mRNA matched 19 human genes whose protein products are variously involved in enzyme reactions, nucleotide or cation binding, signaling, and carrier functions. In BLASTN analysis of ncRNA genes, BNT162b2 mRNA and SARS-CoV-2 S gene matched 17 and 24 different human genomic regions, respectively. Overall, characterization of the matched noncoding sequences revealed stronger interference with epigenetic pathways for BNT162b2 mRNA compared with the original S gene.

CONCLUSION

This pivotal in silico analysis shows that SARS-CoV-2 S gene and the BNT162b2 mRNA vaccine exhibit Watson-Crick nucleotide complementarity with human coding or noncoding genes. Although they do not share the same complementarity pattern, both may disrupt epigenetic mechanisms in target cells, potentially leading to long-term complications.

Identification of the enhancer RNAs related to tumorgenesis of pituitary neuroendocrine tumors

Background

Pituitary neuroendocrine tumors (PitNETs), which originate from the pituitary gland, account for 10%-15% of all intracranial neoplasms. Recent studies have indicated that enhancer RNAs (eRNAs) exert regulatory effects on tumor growth. However, the mechanisms underlying the eRNA-mediated tumorigenesis of PitNETs have not been elucidated.

Methods

Normal pituitary and PitNETs tissues were used to identify the differentially expressed eRNAs (DEEs). Immune gene sets and hallmarks of cancer gene sets were quantified based on single sample gene set enrichment analysis (ssGSEA) algorithm using GSVA. The perspective of immune cells among all samples was calculated by the CIBERSORT algorithm. Moreover, the regulatory network composed of key DEEs, target genes of eRNAs, hallmarks of cancer gene sets, differentially expressed TF, immune cells and immune gene sets were constructed by Pearson correlation analysis. Small molecular anti-PitNETs drugs were explored by CMap analysis and the accuracy of the study was verified by in vitro and in vivo experiments, ATAC-seq and ChIP-seq.

Results

In this study, data of 134 PitNETs and 107 non-tumorous pituitary samples were retrieved from a public database to identify differentially expressed genes. In total, 1128 differentially expressed eRNAs (DEEs) (494 upregulated eRNAs and 634 downregulated eRNAs) were identified. Next, the correlation of DEEs with cancer-related and immune-related gene signatures was examined to establish a co-expression regulatory network comprising 18 DEEs, 50 potential target genes of DEEs, 5 cancer hallmark gene sets, 2 differentially expressed transcription factors, 4 immune cell types, and 4 immune gene sets. Based on this network, the following four therapeutics for PitNETs were identified using Connectivity Map analysis: ciclopirox, bepridil, clomipramine, and alexidine. The growth-inhibitory effects of these therapeutics were validated using in vitro experiments. Ciclopirox exerted potential growth-inhibitory effects on PitNETs. Among the DEEs, GNLY, HOXB7, MRPL33, PRDM16, TCF7, and ZNF26 were determined to be potential diagnostic and therapeutic biomarkers for PitNETs.

Conclusion

This study illustrated the significant influence of eRNAs on the occurrence and development of PitNETs. By constructing the co-expression regulation network, GNLY, HOXB6, MRPL33, PRDM16, TCF7, and ZNF26 were identified as relatively significant DEEs which were considered as the novel biomarkers of diagnosis and treatment of PitNETs. This study demonstrated the roles of eRNAs in the occurrence and development of PitNETs and revealed that ciclopirox was a potential therapeutic for pituitary adenomas.

Non-coding RNAs in enzalutamide resistance of castration-resistant prostate cancer

Enzalutamide (Enz) is a next-generation androgen receptor (AR) antagonist used to treat castration-resistant prostate cancer (CRPC). Unfortunately, the relapsing nature of CRPC results in the development of Enz resistance in many patients. Non-coding RNAs (ncRNAs) are RNA molecules that do not encode proteins, which include microRNAs (miRNA), long ncRNAs (lncRNAs), circular RNAs (circRNAs), and other ncRNAs with known and unknown functions. Recently, dysregulation of ncRNAs in CRPC, particularly their regulatory function in drug resistance, has attracted more and more attention. Herein, we introduce the roles of dysregulation of different ncRNAs subclasses in the development of CRPC progression and Enz resistance. Recently determined mechanisms of Enz resistance are discussed, focusing mainly on the role of AR-splice variant-7 (AR-V7), mutations, circRNAs and lncRNAs that act as miRNA sponges. Also, the contributions of epithelial-mesenchymal transition and glucose metabolism to Enz resistance are discussed. We summarize the different mechanisms of miRNAs, lncRNAs, and circRNAs in the progression of CRPC and Enz resistance, and highlight the prospect of future therapeutic strategies against Enz resistance.

Development of a novel prognostic signature derived from enhancer RNA-regulated genes in head neck squamous cell carcinoma

BACKGROUND

Enhancer RNAs (eRNAs) are increasingly recognized as prognostic biomarkers-across human cancers. Here, we sought to develop a novel eRNA-regulated genes (ERGs)-derived prognostic signature for head neck squamous cell carcinoma (HNSCC).

METHODS

Candidate ERGs were identified via co-expression between individual survival-related eRNAs and their putative targets by Spearman's correlation analyses. The ERG signature was developed by univariate Cox regression, Kaplan-Meier survival analysis and maximum AUC in 1000 iterations of LASSO-penalized multivariate Cox regression. An ERG nomogram incorporating ERG signature and selected clinicopathological parameters were constructed by multivariate Cox regression. Biological roles of eRNA of interest were further explored in vitro.

RESULTS

The ERG signature successfully stratified patients into subgroups with distinct survival in multiple cohorts. An ERG nomogram was developed with satisfactory performance in prognostication. Inhibition of ENSR00000165816 significantly reduced transcript level of SLC2A9 and impaired cell proliferation and invasion.

CONCLUSION

Our results establish ERG signature and nomogram as powerful prognostic predictors for HNSCC.

Insights into Enhancer RNAs: Biogenesis and Emerging Role in Brain Diseases

Enhancers are cis-acting elements that control the transcription of target genes and are transcribed into a class of noncoding RNAs (ncRNAs) termed enhancer RNAs (eRNAs). eRNAs have shorter half-lives than mRNAs and long noncoding RNAs; however, the frequency of transcription of eRNAs is close to that of mRNAs. eRNA expression is associated with a high level of histone mark H3K27ac and a low level of H3K27me3. Although eRNAs only account for a small proportion of ncRNAs, their functions are important. eRNAs can not only increase enhancer activity by promoting the formation of enhancer-promoter loops but also regulate transcriptional activation. Increasing numbers of studies have found that eRNAs play an important role in the occurrence and development of brain diseases; however, further research into eRNAs is required. This review discusses the concept, characteristics, classification, function, and potential roles of eRNAs in brain diseases.

Crosstalk between SOX Genes and Long Non-Coding RNAs in Glioblastoma

Glioblastoma (GBM) continues to be the most devastating primary brain malignancy. Despite significant advancements in understanding basic GBM biology and enormous efforts in developing new therapeutic approaches, the prognosis for most GBM patients remains poor with a median survival time of 15 months. Recently, the interplay between the SOX (SRY-related HMG-box) genes and lncRNAs (long non-coding RNAs) has become the focus of GBM research. Both classes of molecules have an aberrant expression in GBM and play essential roles in tumor initiation, progression, therapy resistance, and recurrence. In GBM, SOX and lncRNAs crosstalk through numerous functional axes, some of which are part of the complex transcriptional and epigenetic regulatory mechanisms. This review provides a systematic summary of current literature data on the complex interplay between SOX genes and lncRNAs and represents an effort to underscore the effects of SOX/lncRNA crosstalk on the malignant properties of GBM cells. Furthermore, we highlight the significance of this crosstalk in searching for new biomarkers and therapeutic approaches in GBM treatment.

Circular RNAs and Untranslated Regions in Acute Myeloid Leukemia

Before the advent of next-generation sequencing, research on acute myeloid leukemia (AML) mostly centered on protein-coding genes. In recent years, breakthroughs in RNA sequencing technologies and whole transcriptome analysis have led to the discovery that approximately 97.5% of the human genome is transcribed into non-coding RNAs (ncRNAs). This paradigm shift has led to an explosion of research interest in different classes of non-coding RNAs, such as circular RNAs (circRNAs) as well as non-coding untranslated regions (UTRs) of protein-coding messenger RNAs. The critical roles of circRNAs and UTRs in AML pathogenesis have become increasingly apparent. In this review, we discuss the cellular mechanisms of circRNAs and summarize recent studies that reveal their biological roles in AML. Furthermore, we also review the contribution of 3'UTRs to disease progression. Finally, we discuss the potential of circRNAs and 3'UTRs as new biomarkers for disease stratification and/or the prediction of treatment response and targets for the development of RNA-directed therapeutic applications.

Transcriptional and Epigenetic Regulation of Context-Dependent Plasticity in T-Helper Lineages

Th cell lineage determination and functional specialization are tightly linked to the activation of lineage-determining transcription factors (TFs) that bind cis-regulatory elements. These lineage-determining TFs act in concert with multiple layers of transcriptional regulators to alter the epigenetic landscape, including DNA methylation, histone modification and three-dimensional chromosome architecture, in order to facilitate the specific Th gene expression programs that allow for phenotypic diversification. Accumulating evidence indicates that Th cell differentiation is not as rigid as classically held; rather, extensive phenotypic plasticity is an inherent feature of T cell lineages. Recent studies have begun to uncover the epigenetic programs that mechanistically govern T cell subset specification and immunological memory. Advances in next generation sequencing technologies have allowed global transcriptomic and epigenomic interrogation of CD4+ Th cells that extends previous findings focusing on individual loci. In this review, we provide an overview of recent genome-wide insights into the transcriptional and epigenetic regulation of CD4+ T cell-mediated adaptive immunity and discuss the implications for disease as well as immunotherapies.

Transcriptomic Profiling Reveals an Enhancer RNA Signature for Recurrence Prediction in Colorectal Cancer

BACKGROUND

Colorectal cancer (CRC) is one of the most fatal malignancies worldwide, and this is in part due to high rates of tumor recurrence in these patients. Currently, TNM staging remains the gold standard for predicting prognosis and recurrence in CRC patients; however, this approach is inadequate for identifying high-risk patients with the highest likelihood of disease recurrence. Recent evidence has revealed that enhancer RNAs (eRNAs) represent a higher level of cellular regulation, and their expression is frequently dysregulated in several cancers, including CRC. However, the clinical significance of eRNAs as recurrence predictor biomarkers in CRC remains unexplored, which is the primary aim of this study.

RESULTS

We performed a systematic analysis of eRNA expression profiles in colon cancer (CC) and rectal cancer (RC) patients from the TCGA dataset. By using rigorous biomarker discovery approaches by splitting the entire dataset into a training and testing cohort, we identified a 22-eRNA panel in CC and a 19-eRNA panel in RC for predicting tumor recurrence. The Kaplan-Meier analysis showed that biomarker panels robustly stratified low and high-risk CC (p = 7.29 × 10-5) and RC (p = 6.81 × 10-3) patients with recurrence. Multivariate and LASSO Cox regression models indicated that both biomarker panels were independent predictors of recurrence and significantly superior to TNM staging in CC (HR = 11.89, p = 9.54 × 10-4) and RC (HR = 3.91, p = 3.52 × 10-2). Notably, the ROC curves demonstrated that both panels exhibited excellent recurrence prediction accuracy in CC (AUC = 0.833; 95% CI: 0.74-0.93) and RC (AUC = 0.834; 95% CI: 0.72-0.92) patients. Subsequently, a combination signature that included the eRNA panels and TNM staging achieved an even greater predictive accuracy in patients with CC (AUC = 0.85).

CONCLUSIONS

Herein, we report a novel eRNA signature for predicting recurrence in patients with CRC. Further experimental validation in independent clinical cohorts, these biomarkers can potentially improve current risk stratification approaches for guiding precision oncology treatments in patients suffering from this lethal malignancy.

The integrative analysis based on super-enhancer related genes for predicting different subtypes and prognosis of patient with lower-grade glioma

Objective: Emerging evidence revealed that super-enhancer plays a crucial role in the transcriptional reprogramming for many cancers. The purpose aimed to explored how the super-enhancer related genes affects the prognosis and tumor immune microenvironment (TIME) of patients with low-grade glioma (LGG). Methods: In this study, the differentially expressed genes (DEGs) between LGG cohorts and normal brain tissue cohort were identified by the comprehensive analysis of the super-enhancer (SE) related genes. Then non-negative matrix factorization was performed to seek the optimal classification based on the DEGs, while investigating prognostic and clinical differences between different subtypes. Subsequently, a prognostic related signature (SERS) was constructed for the comprehensive evaluation in term of individualized prognosis, clinical characteristics, cancer markers, genomic alterations, and immune microenvironment of patients with LGG. Results: Based on the expression profiles of 170 DEGs, we identified three SE subtypes, and the three subtypes showed significant differences in prognostic, clinicopathological features. Then, nine optimal SE-related genes were selected to construct the SERS through the least absolute shrinkage and selection operator Cox regression analysis. Survival analysis showed that SERS had strong and stable predictive ability for the prognosis of LGG patients in the The Cancer Genome Atlas, China Glioma Genome Atlas, and Remdrandt cohorts, respectively. We also found that SERS was highly correlated with clinicopathological features, tumor immune microenvironment, cancer hallmarks, and genomic alterations in LGG patients. In addition, the predictive power of SERS for immune checkpoint inhibitor treatment is also superior. The qRT-PCR results and immunohistochemical results also confirmed the difference in the expression of four key genes in normal cells and tumors, as well as in normal tissues and tumor tissues. Conclusion: The SERS could be suitable to utilize individualized prognosis prediction and immunotherapy options for LGG patients in clinical application.

Non-coding RNAs and glioma: Focus on cancer stem cells

Glioblastoma and gliomas can have a wide range of histopathologic subtypes. These heterogeneous histologic phenotypes originate from tumor cells with the distinct functions of tumorigenesis and self-renewal, called glioma stem cells (GSCs). GSCs are characterized based on multi-layered epigenetic mechanisms, which control the expression of many genes. This epigenetic regulatory mechanism is often based on functional non-coding RNAs (ncRNAs). ncRNAs have become increasingly important in the pathogenesis of human cancer and work as oncogenes or tumor suppressors to regulate carcinogenesis and progression. These RNAs by being involved in chromatin remodeling and modification, transcriptional regulation, and alternative splicing of pre-mRNA, as well as mRNA stability and protein translation, play a key role in tumor development and progression. Numerous studies have been performed to try to understand the dysregulation pattern of these ncRNAs in tumors and cancer stem cells (CSCs), which show robust differentiation and self-regeneration capacity. This review provides recent findings on the role of ncRNAs in glioma development and progression, particularly their effects on CSCs, thus accelerating the clinical implementation of ncRNAs as promising tumor biomarkers and therapeutic targets.

A predictive signature based on enhancer RNA associates with immune infiltration and aids treatment decision in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a prevalent urinary malignancy. Despite the recent development of better diagnostic tools and therapy, the five-year survival rate for individuals with advanced and metastatic ccRCC remains dismal. Unfortunately, ccRCC is less susceptible to radiation and chemotherapy. Consequently, targeted therapy and immunotherapy play a crucial role in the treatment of ccRCC. Enhancer RNAs (eRNAs) are noncoding RNAs transcribed by enhancers. Extensive research has shown that eRNAs are implicated in a variety of cancer signaling pathways. However, the biological functions of eRNAs have not been systematically investigated in ccRCC. In this study, we conducted a comprehensive investigation of the role of eRNAs in the onset and management of ccRCC. Patient prognosis-influencing eRNAs and target genes were chosen to construct a predictive signature. On the basis of the median riskscore, ccRCC patients were split into high- and low-risk subgroups. The prediction efficiency was assessed in several cohorts, and multi-omics analysis was carried out to investigate the differences and underlying mechanisms between the high- and low-risk groups. In addition, we investigated its potential to facilitate clinical treatment choices. The riskscore might be used to forecast a patient’s response to immunotherapy and targeted therapy, giving a revolutionary method for selecting treatment regimens with pinpoint accuracy.

Emerging Role of Enhancer RNAs as Potential Diagnostic and Prognostic Biomarkers in Cancer

Enhancers are distal cis-acting elements that are commonly recognized to regulate gene expression via cooperation with promoters. Along with regulating gene expression, enhancers can be transcribed and generate a class of non-coding RNAs called enhancer RNAs (eRNAs). The current discovery of abundant tissue-specific transcription of enhancers in various diseases such as cancers raises questions about the potential role of eRNAs in disease diagnosis and therapy. This review aimed to demonstrate the current understanding of eRNAs in cancer research with a focus on the potential roles of eRNAs as prognostic and diagnostic biomarkers in cancers.

Enhancer RNA (eRNA) in Human Diseases

Enhancer RNAs (eRNAs), a class of non-coding RNAs (ncRNAs) transcribed from enhancer regions, serve as a type of critical regulatory element in gene expression. There is increasing evidence demonstrating that the aberrant expression of eRNAs can be broadly detected in various human diseases. Some studies also revealed the potential clinical utility of eRNAs in these diseases. In this review, we summarized the recent studies regarding the pathological mechanisms of eRNAs as well as their potential utility across human diseases, including cancers, neurodegenerative disorders, cardiovascular diseases and metabolic diseases. It could help us to understand how eRNAs are engaged in the processes of diseases and to obtain better insight of eRNAs in diagnosis, prognosis or therapy. The studies we reviewed here indicate the enormous therapeutic potency of eRNAs across human diseases.

Integrative Analysis of N6-Methyladenosine-Related Enhancer RNAs Identifies Distinct Prognosis and Tumor Immune Micro-Environment Patterns in Head and Neck Squamous Cell Carcinoma

Simple Summary

Head and neck squamous cell carcinoma (HNSCC) has high morbidity and mortality. The interaction between immune cells and tumor cells in the tumor micro-environment is an important factor affecting the tumor progression and prognosis of HNSCC patients. More biomarkers and targets need to be explored to improve patient outcomes. The m⁶A modification on enhancer RNAs (eRNAs) is associated with the signature of active enhancer, and the function of m⁶A driving eRNAs in tumor progression has not been reported. In this study, we screened and identified a risk model containing 5 m⁶A-related eRNA, which can better predict the survival and immunotherapy outcome of patients. The role of m⁶A-related eRNA in HNSCC cells was verified in vitro. We also combined the risk score and multiple clinical features to construct a nomogram for predicting OS of HNSCC patients, which provides an effective quantitative analysis tool for guiding the personalized precise treatment for patients.

Abstract

At present, the prognostic value of N6-methyladenosine (m6A)-related enhancer RNAs (eRNAs) for head and neck squamous cell carcinoma (HNSCC) still remains unclear. Our study aims to explore the prognostic value of m6A-related eRNAs in HNSCC patients and their potential significance in immune infiltration and immunotherapy. We constructed a 5 m6A-related eRNAs risk model from The Cancer Genome Atlas (TCGA) HNSCC dataset, using univariate and multivariate Cox and least absolute shrinkage and selection operator (LASSO) regression analysis. Based on the SRAMP website and in vitro experiments, it was verified that these 5 m6A-related eRNAs had m6A sites, the expression of which was regulated by corresponding m6A regulators. Moreover, we constructed a nomogram base on 5 m⁶A-related eRNAs and confirmed the consistency and robustness of an internal TCGA testing set. Further analysis found that the risk score was positively associated with low overall survival (OS), tumor cell metastasis, metabolic reprogramming, low immune surveillance, lower expression of immune-related genes, and higher expression of targeted genes. Finally, we verified that silencing MIR4435-2HG inhibited HNSCC cell migration and invasion. This study contributes to the understanding of the characteristics of m6A-related eRNAs in HNSCC and provides a reference for effective immunotherapy and targeted therapy.

Genome-wide analysis of the FOXA1 transcriptional regulatory network identifies super enhancer associated LncRNAs in tamoxifen resistance

Breast cancer is the leading cause of death in female cancers, and what’s worse, tamoxifen resistance occurs in almost 30% breast cancer patients and has seriously attenuated the therapeutic effect. It is widely studied that epigenetic regulation has played important role in the development of tamoxifen resistance. FOXA1 is a pioneer transcription factor that can translate epigenetic signature into transcription regulation and also drive genome-wide enhancer reprogramming in breast cancer. However, the chromatin super enhancer landscape orchestrated by FOXA1 and the key downstream targets of the FOXA1 oncogenic network in tamoxifen resistance remain elusive. Through analyzing the FOXA1 ChIP-seq data in tamoxifen sensitive MCF7 and tamoxifen resistant MCF7/TamR cells, we show that the FOXA1 chromatin occupancy is enhanced in both the promoter and enhancer regions, and the recruitment events may be E2 dependent in both MCF7 and MCF7/TamR cells. By integratively analyzing the FOXA1 ChIP-seq data and RNA-seq data of MCF7 and MCF7/TamR cells, we find that the enhanced or reduced FOXA1 chromatin binding densities may synchronize the transcriptional activity in tamoxifen resistance. Besides, we identify 1003 super enhancer associated protein coding genes and five super enhancer associated lncRNAs (ATP1A1−AS1, CASC11, CASC15, KCTD21−AS1, LINC00885) in tamoxifen resistance. By KM survival analysis, we find that high expression level of ATP1A1−AS1 and its sense transcript ATP1A1 indicates favorable clinical outcome among the luminal endocrine treated breast cancer patients. Further coexpression analysis indicates that ATP1A1-AS1 is significantly correlated with ATP1A1, and RT-qPCR results show that they both are downregulated in MCF7/TamR cells. Our study shows that the FOXA1 transcriptional regulatory network may promote the development of tamoxifen resistance, and identifies one super enhancer associated lncRNA ATP1A1-AS1 that may work as promising biomarker or drug target in tamoxifen resistance.

An enhancer RNA-based risk model for prediction of bladder cancer prognosis

Background

Bladder cancer patients have a high recurrence and poor survival rates worldwide. Early diagnosis and intervention are the cornerstones for favorable prognosis. However, commonly used predictive tools cannot meet clinical needs because of their insufficient accuracy.

Methods

We have developed an enhancer RNA (eRNA)-based signature to improve the prediction for bladder cancer prognosis. First, we analyzed differentially expressed eRNAs in gene expression profiles and clinical data for bladder cancer from The Cancer Genome Atlas database. Then, we constructed a risk model for prognosis of bladder cancer patients, and analyzed the correlation between this model and tumor microenvironment (TME). Finally, regulatory network of downstream genes of eRNA in the model was constructed by WGCNA and enrichment analysis, then Real-time quantitative PCR verified the differentiation of related genes between tumor and adjacent tissue.

Results

We first constructed a risk model composed of eight eRNAs, and found the risk model could be an independent risk factor to predict the prognosis of bladder cancer. Then, the log-rank test and time-dependent ROC curve analysis shown the model has a favorable ability to predict prognosis. The eight risk eRNAs may participate in disease progression by regulating cell adhesion and invasion, and up-regulating immune checkpoints to suppress the immunity in TME. mRNA level change in related genes further validated regulatory roles of eRNAs in bladder cancer. In summary, we constructed an eRNA-based risk model and confirmed that the model could predict the prognosis of bladder cancer patients.

Comprehensive transcriptomic analysis of immune-related eRNAs associated with prognosis and immune microenvironment in melanoma

Background

Recent evidence suggests that enhancer RNAs (eRNAs) play key roles in cancers. Identification of immune-related eRNAs (ireRNAs) in melanoma can provide novel insights into the mechanisms underlying its genesis and progression, along with potential therapeutic targets.

Aim

To establish an ireRNA-related prognostic signature for melanoma and identify potential drug candidates.

Methods

The ireRNAs associated with the overall survival (OS-ireRNAs) of melanoma patients were screened using data from The Cancer Genome Atlas (TCGA) via WGCNA and univariate Cox analysis. A prognostic signature based on these OS-ireRNAs was then constructed by performing the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. The immune landscape associated with the prognostic model was evaluated by the ESTIMATE algorithm and CIBERSORT method. Finally, the potential drug candidates for melanoma were screened through the cMap database.

Results

A total of 24 OS-ireRNAs were obtained, of which 7 ireRNAs were used to construct a prognostic signature. The ireRNAs-related signature performed well in predicting the overall survival (OS) of melanoma patients. The risk score of the established signature was further verified as an independent risk factor, and was associated with the unique tumor microenvironment in melanoma. We also identified several potential anti-cancer drugs for melanoma, of which corticosterone ranked first.

Conclusions

The ireRNA-related signature is an effective prognostic predictor and provides reliable information to better understand the mechanism of ireRNAs in the progression of melanoma.

Comprehensive characterization of enhancer RNA in hepatocellular carcinoma reveals three immune subtypes with implications for immunotherapy

Hepatocellular carcinoma (HCC) is highly heterogeneous. Molecular subtyping for guiding immunotherapy is warranted. Previous studies have indicated that enhancer RNAs (eRNAs) are involved in tumor heterogeneity and immune infiltration. However, the eRNA landscape and its correlation with immune infiltration in HCC remain unknown. Here we first revealed the genome-wide eRNA landscape in two HCC cohorts. Then we divided individuals with HCC into three immune-related clusters (C1, C2, and C3) based on eRNA expression profiles. The prognosis, biological properties, immune infiltration, clinical features, genomic features, and drug response were analyzed. C1 was enriched in immune infiltration and potentially sensitive to immune checkpoint inhibitors (ICIs). C2 displayed features of immune depletion, high proliferation activity, malignant clinical features, and the worst prognosis. C2 may benefit from targeted therapy. C3 presented moderate immune infiltration, metabolism-related signatures, and the best prognosis. Transarterial chemoembolization (TACE) may be effective for C3. Finally, we constructed a 51-eRNA classifier for subtype prediction and validated its efficacy in The Cancer Genome Atlas (TCGA) cohort and Sun Yat-sen University Cancer Center (SYSUCC) cohort. Our results provide a novel method for immune classification of HCC, shed new light on tumor heterogeneity, and may aid in HCC immunotherapy.

Repression of enhancer RNA PHLDA1 promotes tumorigenesis and progression of Ewing sarcoma via decreasing infiltrating T‐lymphocytes: A bioinformatic analysis

Background: The molecular mechanisms of EWS-FLI-mediating target genes and downstream pathways may provide a new way in the targeted therapy of Ewing sarcoma. Meanwhile, enhancers transcript non-coding RNAs, known as enhancer RNAs (eRNAs), which may serve as potential diagnosis markers and therapeutic targets in Ewing sarcoma.

Materials and methods: Differentially expressed genes (DEGs) were identified between 85 Ewing sarcoma samples downloaded from the Treehouse database and 3 normal bone samples downloaded from the Sequence Read Archive database. Included in DEGs, differentially expressed eRNAs (DEeRNAs) and target genes corresponding to DEeRNAs (DETGs), as well as the differentially expressed TFs, were annotated. Then, cell type identification by estimating relative subsets of known RNA transcripts (CIBERSORT) was used to infer portions of infiltrating immune cells in Ewing sarcoma and normal bone samples. To evaluate the prognostic value of DEeRNAs and immune function, cross validation, independent prognosis analysis, and Kaplan–Meier survival analysis were implemented using sarcoma samples from the Cancer Genome Atlas database. Next, hallmarks of cancer by gene set variation analysis (GSVA) and immune gene sets by single-sample gene set enrichment analysis (ssGSEA) were identified to be significantly associated with Ewing sarcoma. After screening by co-expression analysis, most significant DEeRNAs, DETGs and DETFs, immune cells, immune gene sets, and hallmarks of cancer were merged to construct a co-expression regulatory network to eventually identify the key DEeRNAs in tumorigenesis of Ewing sarcoma. Moreover, Connectivity Map Analysis was utilized to identify small molecules targeting Ewing sarcoma. External validation based on multidimensional online databases and scRNA-seq analysis were used to verify our key findings.

Results: A six-different-dimension regulatory network was constructed based on 17 DEeRNAs, 29 DETFs, 9 DETGs, 5 immune cells, 24 immune gene sets, and 8 hallmarks of cancer. Four key DEeRNAs (CCR1, CD3D, PHLDA1, and RASD1) showed significant co-expression relationships in the network. Connectivity Map Analysis screened two candidate compounds, MS-275 and pyrvinium, that might target Ewing sarcoma. PHLDA1 (key DEeRNA) was extensively expressed in cancer stem cells of Ewing sarcoma, which might play a critical role in the tumorigenesis of Ewing sarcoma.

Conclusion: PHLDA1 is a key regulator in the tumorigenesis and progression of Ewing sarcoma. PHLDA1 is directly repressed by EWS/FLI1 protein and low expression of FOSL2, resulting in the deregulation of FOX proteins and CC chemokine receptors. The decrease of infiltrating T‐lymphocytes and TNFA signaling may promote tumorigenesis and progression of Ewing sarcoma.

Construction of the prognostic enhancer RNA regulatory network in osteosarcoma

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Our enhancer RNAs-based prognostic model showed good predictive ability in osteosarcoma.

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CCAAT enhancer binding protein alpha (CEBPA) may regulate CD8A molecule (CD8A).

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CD8A activation may promote CD3E molecule (CD3E) expression and activate allograft rejection in CD8+ T cells.

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Above signal axis provided new insights in the mechanism of osteosarcoma tumorigenesis.

Background

Osteosarcoma (OS) is a common malignant tumor in osteoarticular system, the 5-year overall survival of which is poor. Enhancer RNAs (eRNAs) have been implicated in the tumorigenesis of various cancer types, whereas their roles in OS tumorigenesis remains largely unclear.

Methods

Differentially expressed eRNAs (DEEs), transcription factors (DETFs), target genes (DETGs) were identified using limma (Linear Models for Microarray Analysis) package. Prognosis-related DEEs were accessed by univariate Cox regression analysis. A multivariate model was constructed to evaluate the prognosis of OS samples. Prognosis-related DEEs, DETFs, DETGs, immune cells, and hallmark gene sets were co-analyzed to construct an regulatory network. Specific inhibitors were also filtered by connectivity Map analysis. External validation and scRNA-seq analysis were performed to verify our key findings.

Results

3,981 DETGs, 468 DEEs, 51 DETFs, and 27 differentially expressed hallmark gene sets were identified. A total of Multivariate risk predicting model based on 18 prognosis-related DEEs showed a high accuracy (area under curve (AUC) = 0.896). GW-8510 was the candidate inhibitor targeting prognosis-related DEEs (mean = 0.670, p < 0.001). Based on the OS tumorigenesis-related regulation network, we identified that CCAAT enhancer binding protein alpha (CEBPA, DETF) may regulate CD8A molecule (CD8A, DEE), thereby promoting the transcription of CD3E molecule (CD3E, DETG), which may affect allograft rejection based on CD8+ T cells.

Conclusion

We constructed an eRNA-based prognostic model for predicting the OS patients’ prognosis and explored the potential regulation network for OS tumorigenesis by an integrated bioinformatics analysis, providing promising therapeutic targets for OS patients.

A comprehensive prognostic and immune analysis of enhancer RNA identifies IGFBP7-AS1 as a novel prognostic biomarker in Uterine Corpus Endometrial Carcinoma

BACKGROUND

Long non-coding RNAs (lncRNA) have been implicated in a hand of studies that supported an involvement and co-operation in Uterine Corpus Endometrial Carcinoma (UCEC). Enhancer RNAs (eRNA), a functional subtype of lncRNA, have a key role throughout the genome to guide protein production, thus potentially associated with diseases.

METHODS

In this study, we mainly applied the Cancer Genome Atlas (TCGA) dataset to systematically discover crucial eRNAs involving UCEC. For the key eRNAs in UCEC, we employed RT-qPCR to compare eRNA expression levels in tumor tissues and paired normal adjacent tissues from UCEC patients for validation. Furthermore, the relationships between the key eRNAs and immune activities were measured from several aspects, including the analysis for tumor microenvironment, immune infiltration cells, immune check point genes, tumor mutation burden, and microsatellite instability, as well as m6A related genes. Finally, the key eRNAs were verified by a comprehensive pan-cancer analysis.

RESULTS

IGFBP7 Antisense RNA 1 (IGFBP7-AS1) was identified as the key eRNA for its expression patterns of low levels in tumor tissues and favorable prognostic value in UCEC correlated with its target gene IGFBP7. In RT-qPCR analysis, IGFBP7-AS1 and IGFBP7 had down-regulated expression in tumor tissues, which was consistent with previous analysis. Moreover, IGFBP7-AS1 was found closely related with immune response in relevant immune analyses. Besides, IGFBP7-AS1 and its target gene IGFBP7 correlated with a multi-omics pan-cancer analysis.

CONCLUSIONS

Finally, we suggested that IGFBP7-AS1 played a key role in impacting on clinical outcomes of UCEC patients for its possible influence on immune activity.

Prognostic Ability of Enhancer RNAs in Metastasis of Non-Small Cell Lung Cancer

(1) Background: Non-small cell lung cancer (NSCLC) is the most common lung cancer. Enhancer RNA (eRNA) has potential utility in the diagnosis, prognosis and treatment of cancer, but the role of eRNAs in NSCLC metastasis is not clear; (2) Methods: Differentially expressed transcription factors (DETFs), enhancer RNAs (DEEs), and target genes (DETGs) between primary NSCLC and metastatic NSCLC were identified. Prognostic DEEs (PDEEs) were screened by Cox regression analyses and a predicting model for metastatic NSCLC was constructed. We identified DEE interactions with DETFs, DETGs, reverse phase protein arrays (RPPA) protein chips, immunocytes, and pathways to construct a regulation network using Pearson correlation. Finally, the mechanisms and clinical significance were explained using multi-dimensional validation unambiguously; (3) Results: A total of 255 DEEs were identified, and 24 PDEEs were selected into the multivariate Cox regression model (AUC = 0.699). Additionally, the NSCLC metastasis-specific regulation network was constructed, and six key PDEEs were defined (ANXA8L1, CASTOR2, CYP4B1, GTF2H2C, PSMF1 and TNS4); (4) Conclusions: This study focused on the exploration of the prognostic value of eRNAs in the metastasis of NSCLC. Finally, six eRNAs were identified as potential markers for the prediction of metastasis of NSCLC.

An Integrative Analysis Revealing ZFHX4-AS1 as a Novel Prognostic Biomarker Correlated with Immune Infiltrates in Ovarian Cancer

Ovarian cancer (OC) is the main cause of deaths worldwide in female reproductive system malignancies. Growing studies have indicated that eRNAs could regulate cellular activities in various tumors. Yet the potential roles of eRNAs in OC progression have not been elucidated. Thus, comprehensive assays were needed to screen the critical eRNAs and to explore their possible function in OC. We used Kaplan–Meier methods to identify survival-associated eRNAs in OC based on TCGA datasets. The levels of ZFHX4-AS1 were examined using TCGA datasets. Further exploration was carried out based on the following assays: clinical and survival assays, GO terms, and KEGG assays. TIMER was applied to delve into the relationships between ZFHX4-AS1 and tumor immune infiltration. In this research, we observed 71 survival-related eRNAs in OC patients. ZFHX4-AS1 was highly expressed in OC specimens and predicted a poor prognosis of OC patients. In addition, high ZFHX4-AS1 expression was positively related to the advanced stages of OC specimens. Multivariate assays revealed that ZFHX4-AS1 was an independent prognostic factor for overall survival of OC patients. KEGG analysis indicated that ZFHX4-AS1 may play a regulatory effect on TGF-beta signaling, PI3K-Akt signaling, and proteoglycans in cancer. The pan-cancer validation indicated that ZFHX4-AS1 was related to survival in eight tumors, namely, UCEC, STAD, SARC, OV, ACC, KICH, KIRC, and BLCA. The expression of ZFHX4-AS1 was correlated with the levels of B cells, T cell CD8+, neutrophil, macrophage, and myeloid dendritic cells. Simultaneously, ZFHX4-AS1 may be a prognostic biomarker and a distinctly immunotherapy-related eRNA in OC.

A Novel and Robust Prognostic Model for Hepatocellular Carcinoma Based on Enhancer RNAs-Regulated Genes

Evidence has demonstrated that enhancer RNAs (eRNAs) play a vital role in the progression and prognosis of cancers, but few studies have focused on the prognostic ability of eRNA-regulated genes (eRGs) for hepatocellular carcinoma (HCC). Using gene expression profiles of HCC patients from the TCGA-LIHC and eRNA expression profiles from the enhancer RNA in cancers (eRic) data portal, we developed a novel and robust prognostic signature composed of 10 eRGs based on Lasso-penalized Cox regression analysis. According to the signature, HCC patients were stratified into high- and low-risk groups, which have been shown to have significant differences in tumor immune microenvironment, immune checkpoints, HLA-related genes, DNA damage repair-related genes, Gene-set variation analysis (GSVA), and the lower half-maximal inhibitory concentration (IC50) of Sorafenib. The prognostic nomogram combining the signature, age, and TNM stage had good predictive ability in the training set (TCGA-LIHC) with the concordance index (C-index) of 0.73 and the AUCs for 1-, 3-, and 5-year OS of 0.82, 0.77, 0.74, respectively. In external validation set (GSE14520), the nomogram also performed well with the C-index of 0.71 and the AUCs for 1-, 3-, and 5-year OS of 0.74, 0.77, 0.74, respectively. In addition, an important eRG (AKR1C3) was validated using two HCC cell lines (Huh7 and MHCC-LM3) in vitro, and the results demonstrated the overexpression of AKR1C3 is related to cell proliferation, migration, and invasion in HCC. Altogether, our eRGs signature and nomogram can predict prognosis accurately and conveniently, facilitate individualized treatment, and improve prognosis for HCC patients.

A Two-eRNA-Based Signature Can Impact the Immune Status and Predict the Prognosis and Drug Sensitivity of Lung Adenocarcinoma

Enhancer RNAs (eRNAs) are intergenic long noncoding RNAs (lncRNAs) participating in the development of malignant cancers via targeting cancer-associated genes and immune checkpoints. Immune infiltration of the tumor microenvironment was positively associated with overall survival (OS) in lung adenocarcinoma (LUAD). In this study, we aimed to explore the clinical significance of PCBP1-AS1 in LUAD and developed a novel prognostic signature based on two eRNAs. Our team discovered that the expression of PCBP1-AS1 was distinctly downregulated in LUAD specimens compared with nontumor specimens. Lower PCBP1-AS1 expression was related to advanced clinical stages and poor prognosis. KEGG analysis unveiled that the coexpression genes of PCBP1-AS1 were involved in the regulation of several tumor-related pathways. In addition, remarkable associations were observed between the expression of PCBP1-AS1 and the levels of several immune cells. Then, we used PCBP1-AS1 and TBX5-AS1 to develop a prognostic model. Survival assays unveiled that patients with higher risk scores exhibited a shorter OS in contrast to patients with lower risk scores. In addition, multivariable Cox regressive analysis indicated that the risk score was an independent prediction factor in LUAD sufferers. The anticancer drug sensitivity analysis indicated that risk score had a positive relationship with several anticancer drugs. Taken together, our findings indicated PCBP1-AS1 as a function modulator in LUAD development. In addition, we constructed a robust immune-related eRNA signature which might be a clinical prognosis factor for LUAD patients.

Inflammatory Immune-Associated eRNA: Mechanisms, Functions and Therapeutic Prospects

The rapid development of multiple high-throughput sequencing technologies has made it possible to explore the critical roles and mechanisms of functional enhancers and enhancer RNAs (eRNAs). The inflammatory immune response, as a fundamental pathological process in infectious diseases, cancers and immune disorders, coordinates the balance between the internal and external environment of the organism. It has been shown that both active enhancers and intranuclear eRNAs are preferentially expressed over inflammation-related genes in response to inflammatory stimuli, suggesting that enhancer transcription events and their products influence the expression and function of inflammatory genes. Therefore, in this review, we summarize and discuss the relevant inflammatory roles and regulatory mechanisms of eRNAs in inflammatory immune cells, non-inflammatory immune cells, inflammatory immune diseases and tumors, and explore the potential therapeutic effects of enhancer inhibitors affecting eRNA production for diseases with inflammatory immune responses.

Enhancer RNAs (eRNAs) in Cancer: The Jacks of All Trades

Simple Summary

This review focuses on eRNAs and the several mechanisms by which they can regulate gene expression. In particular we describe here the most recent examples of eRNAs dysregulated in cancer or involved in the immune escape of tumor cells.

Abstract

Enhancer RNAs (eRNAs) are non-coding RNAs (ncRNAs) transcribed in enhancer regions. They play an important role in transcriptional regulation, mainly during cellular differentiation. eRNAs are tightly tissue- and cell-type specific and are induced by specific stimuli, activating promoters of target genes in turn. eRNAs usually have a very short half-life but in some cases, once activated, they can be stably expressed and acquire additional functions. Due to their critical role, eRNAs are often dysregulated in cancer and growing number of interactions with chromatin modifiers, transcription factors, and splicing machinery have been described. Enhancer activation and eRNA transcription have particular relevance also in inflammatory response, placing the eRNAs at the interplay between cancer and immune cells. Here, we summarize all the possible molecular mechanisms recently reported in association with eRNAs activity.

ELOVL2-AS1 inhibits migration of triple negative breast cancer

In this study, we identified a key enhancer RNA (eRNA) region in breast cancer (BRCA) by applying an integrated analysis method. Reported eRNA region and genes affected by them were selected as presumed target pairs. Kaplan-Meier (KM) survival and correlation analyses were performed to screen valuable eRNA region. Based on the KM value and its correlation with the paired target genes, we carefully selected ELOVL2-AS1 as a potential key eRNA region in BRCA. Subsequently, we analyzed the expression of ELOVL2-AS1 and ELOVL2 in four BRCA subtypes and in different BRCA cell lines. The expression of ELOVL2-AS1 and ELOVL2 in triple negative breast cancer (TNBC) was significantly lower than those in Luminal A. After that, we analyzed the function of genes that are positively correlated with ELOVL2-AS1. We found that the co-expression gene mainly related to cilia and cilia characteristics of TNBC is significantly weaker than that of Luminal A. Considering the stronger invasion and metastasis of TNBC (compared with Luminal A) and the close relationship between decreased cilia and metastasis, we overexpressed ELOVL2-AS1 in TNBC and observed its effect on cell migration. The results show that it can inhibit the migration of TNBC. Finally, we analyzed the assay for transposase-accessible chromatin sequencing data, chromatin interaction analysis with paired-end tag sequencing data, and chromatin immunoprecipitation sequencing data and identified the chromatin interaction between ELOVL2-AS1 and ELOVL2, suggesting a direct regulatory interaction.

An Unanticipated Modulation of Cyclin-Dependent Kinase Inhibitors: The Role of Long Non-Coding RNAs

It is now definitively established that a large part of the human genome is transcribed. However, only a scarce percentage of the transcriptome (about 1.2%) consists of RNAs that are translated into proteins, while the large majority of transcripts include a variety of RNA families with different dimensions and functions. Within this heterogeneous RNA world, a significant fraction consists of sequences with a length of more than 200 bases that form the so-called long non-coding RNA family. The functions of long non-coding RNAs range from the regulation of gene transcription to the changes in DNA topology and nucleosome modification and structural organization, to paraspeckle formation and cellular organelles maturation. This review is focused on the role of long non-coding RNAs as regulators of cyclin-dependent kinase inhibitors’ (CDKIs) levels and activities. Cyclin-dependent kinases are enzymes necessary for the tuned progression of the cell division cycle. The control of their activity takes place at various levels. Among these, interaction with CDKIs is a vital mechanism. Through CDKI modulation, long non-coding RNAs implement control over cellular physiology and are associated with numerous pathologies. However, although there are robust data in the literature, the role of long non-coding RNAs in the modulation of CDKIs appears to still be underestimated, as well as their importance in cell proliferation control.

Development and Validation of a Novel Prognostic Model for Lower-Grade Glioma Based on Enhancer RNA-Regulated Prognostic Genes

Enhancer RNAs (eRNAs) are present specifically in tumors, where they affect the expression of eRNA-regulated genes (ERGs). Owing to this characteristic, ERGs were hypothesized to improve prognosis of overall survival in heterogeneous low-grade and intermediate-grade gliomas. This study aimed to construct and validate an ERG prognostic tool to facilitate clinical management, and offer more effective diagnostic and therapeutic biomarkers for glioma. Survival-related eRNAs were identified, and their ERGs were selected based on eRNA and target gene information. The ERG prognostic model was constructed and validated using internal and external validation cohorts. Finally, biological differences related to the ERG signature were analysed to explore the potential mechanisms influencing survival outcomes. Thirteen ERGs were identified and used to build an ERG risk signature, which included five super-enhancer RNA (seRNA)-regulated genes and five LGG-specific eRNA-regulated genes. The prognostic nomogram established based on combining the ERG score, age, and sex was evaluated by calibration curves, clinical utility, Harrell’s concordance index (0.86; 95% CI: 0.83-0.90), and time-dependent receiver operator characteristic curves. We also explored potential immune-related mechanisms that might cause variation in survival. The established prognostic model displayed high validity and robustness. Several immune-related genes regulated by seRNAs or specific eRNAs were identified, indicating that these transcripts or their genes were potential targets for improving immunotherapeutic/therapeutic outcomes. The functions of an important specific eRNA-regulated gene (USP28) were validated in robust vitro experiments. In addition, the ERG risk signature was significantly associated with the immune microenvironment and other immune-related features.

Comprehensive Analysis of Enhancer RNAs Identifies LINC00689 and ELFN1-AS1 as Novel Prognostic Biomarkers in Uveal Melanoma

Enhancer RNAs (eRNAs) have emerged as key players in the pathology of several tumors, including uveal melanoma. Here, we aimed to explore the prognostic values of eRNAs in uveal melanoma (UVM) patients. The expressing data and survival data of UVM patients were downloaded from TCGA and GSE22138 datasets. The Kaplan-Meier methods with the log-rank test were applied to screen survival-related eRNAs in UVM. GEPIA was applied to analyze the associations between expressions of eRNA and disease-free survival. KEGG assays were applied to explore the potential signaling pathways of the key eRNA. The prognostic values of eRNAs were further explored by multivariate assays by the R package survival. The eRNAs were validated in pan-cancer. In this study, we identified 89 survival-related eRNAs in UVM based on TCGA datasets. Based on GSE22138 datasets, we found 27 survival-related eRNAs in UVM. Only two eRNAs (LINC00689 and ELFN1-AS1) were overlapped in both two datasets. The results of multivariate analysis revealed that both LINC00689 and ELFN1-AS1 were independent prognostic factors in UVM patients. The pan-cancer validation results further confirmed the prognostic values of LINC00689 and ELFN1-AS1 in eight tumors. Overall, we identified two novel UVM-related eRNAs, LINC00689 and ELFN1-AS1 which may serve as prognostic and diagnostic biomarkers of UVM patients for clinical decision-making.

Enhancer RNA: What we know and what we can achieve

Enhancers are important cis-acting elements that can regulate gene transcription and cell fate alongside promoters. In fact, many human cancers and diseases are associated with the malfunction of enhancers. Recent studies have shown that enhancers can produce enhancer RNAs (eRNAs) by RNA polymerase II. In this review, we discuss eRNA production, characteristics, functions and mechanics. eRNAs can determine chromatin accessibility, histone modification and gene expression by constructing a 'chromatin loop', thereby bringing enhancers to their target gene. eRNA can also be involved in the phase separation with enhancers and other proteins. eRNAs are abundant, and importantly, tissue-specific in tumours, various diseases and stem cells; thus, eRNAs can be a potential target for disease diagnosis and treatment. As eRNA is produced from the active transcription of enhancers and is involved in the regulation of cell fate, its manipulation will influence cell function, and therefore, it can be a new target for biological therapy.

Enhancer RNA LINC00242-Induced Expression of PHF10 Drives a Better Prognosis in Pancreatic Adenocarcinoma

Enhancer RNA is a kind of non-coding RNA, which is transcribed from the enhancer region of gene and plays an important role in gene transcription regulation. However, the role of eRNA in pancreatic adenocarcinoma (PAAD) is still unclear. In this study, we identified the key eRNA and its target gene in PAAD. The transcriptome data and clinical information of pancreatic cancer were downloaded from the UCSC Xena platform. A total of 2,695 eRNAs and its target gene predicted by the PreSTIGE method were selected as candidate eRNA–target pairs. After survival analysis, we found that LINC00242 was the eRNA most related to patients’ survival, and correlation analysis further indicated that LINC00242 and its target gene PHF10 had a significant co-expression relationship. Downregulation of LINC00242 was significantly associated with unfavorable clinicopathological features. Based on pan-cancer analysis, we found that LINC00242 was associated with the survival of multiple cancers, and LINC00242 was co-expressed with its target genes in multiple cancer types. External experiments further demonstrated that PHF10 was the downstream target gene of LINC00242. After ssGSEA analysis, PAAD patients were classified as high, medium, and low immune cell infiltration clusters. Compared with the low and medium immune infiltration clusters, the expression level of PHF10 was significantly upregulated in the high immune infiltration clusters. After performing the CIBERSORT algorithm, we found that there was a significant difference in the abundance of immune infiltrating cells between the PHF10 high- and low-expression groups. Additionally, the web tool TIMER was used to detect the distribution and expression of PHF10 in pan-cancer.

A Novel Prognostic Tool for Glioma Based on Enhancer RNA-Regulated Immune Genes

Background: Gliomas are the most malignant tumors of the nervous system. Even though their survival outcome is closely affected by immune-related genes (IRGs) in the tumor microenvironment (TME), the corresponding regulatory mechanism remains poorly characterized.

Methods: Specific enhancer RNAs (eRNAs) can be found in tumors, where they control downstream genes. The present study aimed to identify eRNA-regulated IRGs, evaluate their influence on the TME, and use them to construct a novel prognostic model for gliomas.

Results: Thirteen target genes (ADCYAP1R1, BMP2, BMPR1A, CD4, DDX17, ELN, FGF13, MAPT, PDIA2, PSMB8, PTPN6, SEMA6C, and SSTR5) were identified and integrated into a comprehensive risk signature, which distinguished two risk subclasses. Discrepancies between these subclasses were compared to explore potential mechanisms attributed to eRNA-regulated genes, including immune cell infiltration, clinicopathological features, survival outcomes, and chemotherapeutic drug sensitivity. Furthermore, the risk signature was used to construct a prognostic tool that was evaluated by calibration curve, clinical utility, Harrell’s concordance index (0.87; 95% CI: 0.84–0.90), and time-dependent receiver operator characteristic curves (AUCs: 0.93 and 0.89 at 3 and 5 years, respectively). The strong reliability and robustness of the established prognostic tool were validated in another independent cohort. Finally, potential subtypes were explored in patients with grade III tumors.

Conclusion: Overall, eRNAs were associated with immune-related dysfunctions in the TME. Targeting of IRGs regulated by eRNAs could improve immunotherapeutic/therapeutic outcomes.

Targeting of noncoding RNAs encoded by a novel MYC enhancers inhibits the proliferation of human hepatic carcinoma cells in vitro

The proto-oncogene MYC is important for development and cell growth, however, its abnormal regulation causes cancer. Recent studies identified distinct enhancers of MYC in various cancers, but any MYC enhancer(s) in hepatocellular carcinoma (HCC) remain(s) elusive. By analyzing H3K27ac enrichment and enhancer RNA (eRNA) expression in cultured HCC cells, we identified six putative MYC enhancer regions. Amongst these, two highly active enhancers, located ~ 800 kb downstream of the MYC gene, were identified by qRT-PCR and reporter assays. We functionally confirmed these enhancers by demonstrating a significantly reduced MYC expression and cell proliferation upon CRISPR/Cas9-based deletion and/or antisense oligonucleotide (ASO)-mediated inhibition. In conclusion, we identified potential MYC enhancers of HCC and propose that the associated eRNAs may be suitable targets for HCC treatment.

A four-enhancer RNA-based prognostic signature for thyroid cancer

Enhancer RNAs (eRNAs) can serve as an independent prognostic factor for poor outcomes of cancer patients. The purpose of this study was to identify a vital eRNA signature that has prognostic value for thyroid cancer based on GTEx and TCGA screening. We downloaded gene expression data and clinical data of thyroid cancer included in the GTEx and TCGA databases and conducted data consolidation. eRNA expression data were extracted, and subjected to differential analysis and cluster analysis. Univariate Cox regression was used to screen the prognostic factors of thyroid cancer. Multivariate Cox regression was applied for prognostic risk assessment model construction, with the efficacy evaluated by receiver operating characteristic (ROC) curve. Downstream regulatory genes of candidate eRNAs were determined using correlation analysis. There were 79 differentially expressed eRNAs associated with thyroid cancer. These differentially expressed eRNAs could assign all thyroid cancer samples into three molecular subtypes, which showed a strong link to lymph node metastasis (N stage) of thyroid cancer patients. Additionally, four key eRNAs AC141930.1, NBDY, MEG3 and AP002358.1 closely related to the prognosis of thyroid cancer patients. The risk model based on the four eRNAs predicted the prognosis of thyroid cancer patients effectively. TPO, MGST2, THBS2 and SLC25A47P1 were potential downstream regulators of the four eRNAs involved in the development of thyroid cancer. Collectively, our data suggest that a four-eRNA signature consisting of AC141930.1, NBDY, MEG3 and AP002358.1 can accurately predict the prognosis of thyroid cancer patients.