Identification of internal control genes for circular RNAs

Verification of nucleotide sequence reagent identities in original publications in high impact factor cancer research journals

Human gene research studies that describe wrongly identified nucleotide sequence reagents have been mostly identified in journals of low to moderate impact factor, where unreliable findings could be considered to have limited influence on future research. This study examined whether papers describing wrongly identified nucleotide sequences are also published in high-impact-factor cancer research journals. We manually verified nucleotide sequence identities in original Molecular Cancer articles published in 2014, 2016, 2018, and 2020, including nucleotide sequence reagents that were claimed to target circRNAs. Using keywords identified in some 2018 and 2020 Molecular Cancer papers, we also verified nucleotide sequence identities in 2020 Oncogene papers that studied miRNA(s) and/or circRNA(s). Overall, 3.8% (251/6647) and 4.0% (47/1165) nucleotide sequences that were verified in Molecular Cancer and Oncogene papers, respectively, were found to be wrongly identified. Wrongly identified nucleotide sequences were distributed across 18% (91/500) original Molecular Cancer papers, including 38% (31/82) Molecular Cancer papers from 2020, and 40% (21/52) selected Oncogene papers from 2020. Original papers with wrongly identified nucleotide sequences were therefore unexpectedly frequent in two high-impact-factor cancer research journals, highlighting the risks of employing journal impact factors or citations as proxies for research quality.

Small Extracellular Vesicle-Derived Circular RNA hsa_circ_0007386 as a Biomarker for the Diagnosis of Pleural Mesothelioma

Pleural mesothelioma (PM) is a highly aggressive tumor that is caused by asbestos exposure and lacks effective therapeutic regimens. Current procedures for PM diagnosis are invasive and can take a long time to reach a definitive result. Small extracellular vesicles (sEVs) have been identified as important communicators between tumor cells and their microenvironment via their cargo including circular RNAs (circRNAs). CircRNAs are thermodynamically stable, highly conserved, and have been found to be dysregulated in cancer. This study aimed to identify potential biomarkers for PM diagnosis by investigating the expression of specific circRNA gene pattern (hsa_circ_0007386) in cells and sEVs using digital polymerase chain reaction (dPCR). For this reason, 5 PM, 14 non-PM, and one normal mesothelial cell line were cultured. The sEV was isolated from the cells using the gold standard ultracentrifuge method. The RNA was extracted from both cells and sEVs, cDNA was synthesized, and dPCR was run. Results showed that hsa_circ_0007386 was significantly overexpressed in PM cell lines and sEVs compared to non-PM and normal mesothelial cell lines (p < 0.0001). The upregulation of hsa_circ_0007386 in PM highlights its potential as a diagnostic biomarker. This study underscores the importance and potential of circRNAs and sEVs as cancer diagnostic tools.

Current advances in circular RNA detection and investigation methods: Are we running in circles?

Circular RNAs (circRNAs), characterized by their closed-loop structure, have emerged as significant transcriptomic regulators, with roles spanning from microRNA sponging to modulation of gene expression and potential peptide coding. The discovery and functional analysis of circRNAs have been propelled by advancements in both experimental and bioinformatics tools, yet the field grapples with challenges related to their detection, isoform diversity, and accurate quantification. This review navigates through the evolution of circRNA research methodologies, from early detection techniques to current state-of-the-art approaches that offer comprehensive insights into circRNA biology. We examine the limitations of existing methods, particularly the difficulty in differentiating circRNA isoforms and distinguishing circRNAs from their linear counterparts. A critical evaluation of various bioinformatics tools and novel experimental strategies is presented, emphasizing the need for integrated approaches to enhance our understanding and interpretation of circRNA functions. Our insights underscore the dynamic and rapidly advancing nature of circRNA research, highlighting the ongoing development of analytical frameworks designed to address the complexity of circRNAs and facilitate the assessment of their clinical utility. As such, this comprehensive overview aims to catalyze further advancements in circRNA study, fostering a deeper understanding of their roles in cellular processes and potential implications in disease. This article is categorized under: RNA Methods > RNA Nanotechnology RNA Methods > RNA Analyses in Cells RNA Methods > RNA Analyses In Vitro and In Silico.

Age-Invariant Genes: Multi-Tissue Identification and Characterization of Murine Reference Genes

Studies of the aging transcriptome focus on genes that change with age. But what can we learn from age-invariant genes-those that remain unchanged throughout the aging process? These genes also have a practical application: they serve as reference genes (often called housekeeping genes) in expression studies. Reference genes have mostly been identified and validated in young organisms, and no systematic investigation has been done across the lifespan. Here, we build upon a common pipeline for identifying reference genes in RNA-seq datasets to identify age-invariant genes across seventeen C57BL/6 mouse tissues (brain, lung, bone marrow, muscle, white blood cells, heart, small intestine, kidney, liver, pancreas, skin, brown, gonadal, marrow, and subcutaneous adipose tissue) spanning 1 to 21+ months of age. We identify 9 pan-tissue age-invariant genes and many tissue-specific age-invariant genes. These genes are stable across the lifespan and are validated in independent bulk RNA-seq datasets and RT-qPCR. We find age-invariant genes have shorter transcripts on average and are enriched for CpG islands. Interestingly, pathway enrichment analysis for age-invariant genes identifies an overrepresentation of molecular functions associated with some, but not all, hallmarks of aging. Thus, though hallmarks of aging typically involve changes in cell maintenance mechanisms, select genes associated with these hallmarks resist fluctuations in expression with age. Finally, our analysis concludes no classical reference gene is appropriate for aging studies in all tissues. Instead, we provide tissue-specific and pan-tissue genes for assays utilizing reference gene normalization (i.e., RT-qPCR) that can be applied to animals across the lifespan.

Differences of circular RNA expression profiles between monozygotic twins' blood, with the forensic application in bloodstain and saliva

Monozygotic twins (MZTs) possess identical genomic DNA sequences and are usually indistinguishable through routine forensic DNA typing methods, which can be relevant in criminal and paternity cases. Recently, novel epigenetic methods involving DNA methylation and microRNA analysis have been introduced to differentiate MZTs. In this study, we explore the potential of using epigenetic markers, specifically circular RNAs (circRNAs), a type of non-coding RNA (ncRNA), to identify MZTs, and investigate the unique expression patterns of circRNAs within pairs of MZTs, enabling effective differentiation. Epigenetics regulates gene expression at the post-transcriptional level and plays a crucial role in cell growth and aging. CircRNAs, a recently characterized subclass of ncRNA, have a distinct covalent loop structure without the typical 5' cap or 3' tail. They have been reported to modulate various cellular processes and play roles in embryogenesis and eukaryotic development. To achieve this, we conducted a comprehensive circRNA sequencing analysis (circRNA-seq) using total RNA extracted from the blood samples of five pairs of MZTs. We identified a total of 15,257 circRNAs in all MZTs using circRNA-seq. Among them, 3, 21, 338, and 2967 differentially expressed circRNAs (DEcircRNAs) were shared among five, four, three, and two pairs of MZTs, respectively. Subsequently, we validated twelve selected DEcircRNAs using real-time quantitative polymerase chain reaction (RT-qPCR) assays, which included hsa_circ_0004724, hsa_circ_0054196, hsa_circ_004964, hsa_circ_0000591, hsa_circ_0005077, hsa_circ_0054853, hsa_circ_0054716, hsa_circ_0002302, hsa_circ_0004482, hsa_circ_0001103, novel_circ_0030288 and novel_circ_0056831. Among them, hsa_circ_0005077 and hsa_circ_0004482 exhibited the best performance, showing differences in 7 out of 10 pairs of MZTs. These twelve differentially expressed circRNAs also demonstrated strong discriminative power when tested on saliva samples from 10 pairs of MZTs. Notably, hsa_circ_0004724 displayed differential expression in 8 out of 10 pairs of MZTs in their saliva. Additionally, we evaluated the detection sensitivity, longitudinal temporal stability, and suitability for aged bloodstains of these twelve DEcircRNAs in forensic scenarios. Our findings highlight the potential of circRNAs as molecular markers for distinguishing MZTs, emphasizing their suitability for forensic application.

circNFIB decreases synthesis of arachidonic acid and inhibits breast tumor growth and metastasis

We identified circNFIB (hsa_circ_0086376) as a down-regulated circRNA in breast cancer but its effect is unclear. We aimed to explore the roles of circNFIB in breast cancer. The expression levels of circNFIB in breast cancer tissues and cells were detected. Both in vitro and in vivo experiments were used to assess the effects and mechanisms of circNFIB. circNFIB was down-regulated in 29 breast cancer tissues compared to adjacent normal tissues. circNFIB is a highly conserved circRNA and mainly located in cytoplasm of breast cancer cells. In vitro experiments showed that overexpression of circNFIB inhibited proliferation and invasion of breast cancer cells, whereas knockdown of circNFIB induced proliferation and invasion. Animal experiments indicated that circNFIB inhibited tumor growth and metastasis in vivo. Bioinformatics analysis showed that circNFIB contained an open reading frame (ORF) spanning its spliced junction, an internal ribosome entry site (IRES) and a N6-methyladenosine (m6A) site, suggesting circNFIB had the potential to encode a 56 amino acid (aa) protein, which was then confirmed by experiments. Metabonomics analysis results indicated that circNFIB may inhibit synthesis of arachidonic acid (AA) by regulating phospholipase. EIF4A3 and U2AF65 may regulate circNFIB expression by binding to the flanking sequence of circNFIB. In conclusion, circNFIB is a down-regulated circRNA in breast cancer tissues and encodes a 56 aa protein. circNFIB down-regulates AA in breast cancer cells, thus decreasing AA metabolites. Based on reported evidences of AA metabolites on cancer, we speculated that circNFIB may inhibit breast tumor growth and metastasis partly by inhibiting AA.

Identification of circRNAs linked to Alzheimer's disease and related dementias

INTRODUCTION

Circular RNAs (circRNAs) exhibit selective expression in the brain and differential regulation in Alzheimer's disease (AD). To explore the role of circRNAs in AD, we investigated how circRNA expression varies between brain regions and with AD-related stress in human neuronal precursor cells (NPCs).

METHODS

Ribosomal RNA-depleted hippocampus RNA-sequencing data were generated. Differentially regulated circRNAs in AD and related dementias were detected using CIRCexplorer3 and limma. circRNA results were validated using quantitative real-time PCR of cDNA from the brain and NPCs.

RESULTS

We identified 48 circRNAs that were significantly associated with AD. We observed that circRNA expression differed by dementia subtype. Using NPCs, we demonstrated that exposure to oligomeric tau elicits downregulation of circRNA similar to that observed in the AD brain.

DISCUSSION

Our study shows that differential expression of circRNA can vary by dementia subtype and brain region. We also demonstrated that circRNAs can be regulated by AD-linked neuronal stress independently from their cognate linear messenger RNAs (mRNAs).

CAFs-secreted exosomal cricN4BP2L2 promoted colorectal cancer stemness and chemoresistance by interacting with EIF4A3

Cancer-associated fibroblasts secreted exosomes (CAFs-exo) are important for tumor carcinogenesis and chemoresistance, but its underlying mechanism in colorectal cancer (CRC) has not yet been clarified. In this study, we investigated the regulatory mechanism of CAFs-exo cricN4BP2L2 on the proliferation, apoptosis, stemness and chemoresistance of LoVo cells. We found that CAFs-exo promoted the oxaliplatin resistance and stemness of LoVo cells, while inhibited the LoVo cell apoptosis. Moreover, knockdown of cricN4BP2L2 in CAFs-exo inhibited the oxaliplatin resistance and stemness characteristics of LoVo cells. Mechanistically, cricN4BP2L2 regulated PI3K/AKT/mTOR axis by binding to EIF4A3. Rescue experiments proved that CAFs-derived exosomal cricN4BP2L2 promoted CRC cells stemness and oxaliplatin resistance by upregulating EIF4A3. Moreover, in vivo experiments showed that depletion of cricN4BP2L2 suppressed CRC tumorigenesis growth. In conclusion, CAFs-exo cricN4BP2L2 promoted the CRC cells stemness and oxaliplatin resistance through EIF4A3/PI3K/AKT/mTOR pathway.

CircPrimer 2.0: a software for annotating circRNAs and predicting translation potential of circRNAs

Background

Some circular RNAs (circRNAs) can be translated into functional peptides by small open reading frames (ORFs) in a cap-independent manner. Internal ribosomal entry site (IRES) and N⁶-methyladenosine (m⁶A) were reported to drive translation of circRNAs. Experimental methods confirming the presence of IRES and m⁶A site are time consuming and labor intensive. Lacking computational tools to predict ORFs, IRESs and m⁶A sites for circRNAs makes it harder.

Results

In this report, we present circPrimer 2.0, a Java based software for annotating circRNAs and predicting ORFs, IRESs, and m6A sites of circRNAs. circPrimer 2.0 has a graphical and a command-line interface that enables the tool to be embed into an analysis pipeline.

Conclusions

circprimer 2.0 is an easy-to-use software for annotating circRNAs and predicting translation potential of circRNAs, and freely available at www.bio-inf.cn.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04705-y.

CircATRNL1 and circZNF608 Inhibit Ovarian Cancer by Sequestering miR-152-5p and Encoding Protein

Background: CircRNAs have been found to be involved in the pathogenesis of various diseases. We aimed to explore the roles of circRNAs in ovarian cancer.

Methods: The expression levels of circRNAs in ovarian cancer and normal ovarian tissues were analyzed using RNA sequencing. Fluorescent in situ hybridization (FISH), proliferation assays and transwell assays were used to assess the effects of circRNAs on ovarian cancer.

Results: CircATRNL1 and circZNF608 were downregulated in 20 ovarian cancer tissues compared to normal tissues. CircATRNL1 and circZNF608 are mainly located in the cytoplasm of ovarian cancer cells, and circATRNL1 is a highly conserved circRNA. The overexpression of circATRNL1 and circZNF608 inhibits the proliferation and invasion of ovarian cancer cells. We predicted miRNA–circRNA interactions for circZNF608 and circATRNL1 and obtained 63 interactions. However, a luciferase reporter assay showed that only miR-152-5p was sequestered by circZNF608. Bioinformatics analysis and experiments indicated that circATRNL1 contains an internal ribosome entry site and an open reading frame encoding a 131 aa protein.

Conclusion: In conclusion, circATRNL1 and circZNF608 are two downregulated circRNAs in ovarian cancer and work as tumor suppressors. CircZNF608 may exert antitumor activity in ovarian cancer by binding miR-152-5p, and circATRNL1 may encode a 131 aa protein.

CircN4BP2L2 promotes colorectal cancer growth and metastasis through regulation of the miR-340-5p/CXCR4 axis

Colorectal cancer (CRC) is the third leading cause of cancer-related death worldwide. Dysregulation of circular RNAs (circRNAs) appears to be a critical factor in CRC progression. However, mechanistic studies delineating the role of circRNAs in CRC remain limited. In this study, qRT-PCR and western blot assays were used to measure the expression of genes and proteins. Migration, invasion, proliferation, and apoptosis were examined by wound-healing, transwell, CCK-8, colony formation, and flow cytometry assays, respectively. Molecular interactions were validated by a dual-luciferase report system. A xenograft animal model was established to examine in vivo tumor growth and lung metastasis. Our data indicated that circN4BP2L2 expression was increased in CRC tissues and cell lines. Notably, inhibition of circN4BP2L2 effectively inhibited proliferation, migration, and invasion of LoVo cells, and inhibited tumor growth and metastasis in vivo, whereas the forced expression of circN4BP2L2 facilitated the proliferation, migration, and invasion of HT-29 cells. Mechanistic studies revealed that circN4BP2L2 acted as a molecular sponge of miR-340-5p to competitively promote CXCR4 expression. Furthermore, inhibition of miR-340-5p reversed the anti-cancer effects of circN4BP2L2 or CXCR4 silencing. Our data indicated an oncogenic role of circN4BP2L2 in CRC via regulation of the miR-340-5p/CXCR4 axis, which may be a promising biomarker and target for CRC treatment.

The Use of circRNAs as Biomarkers of Cancer

CircRNAs are a subclass of lncRNAs that have been found to be abundantly present in a wide range of species, including humans. CircRNAs are generally produced by a noncanonical splicing event called backsplicing that is dependent on the canonical splicing machinery, giving rise to circRNAs classified into three main categories: exonic circRNA, circular intronic RNA, and exon-intron circular RNA. Notably, circRNAs possess functional importance and display their functions through different mechanisms of action including sponging miRNAs, or even being translated into functional proteins. In addition, circRNAs also have great potential as biomarkers, particularly in cancer, thanks to their high stability, tissue type and developmental stage specificity, and their presence in biological fluids, which make them promising candidates as noninvasive biomarkers. In this chapter, we describe the most commonly used techniques for the study of circRNAs as cancer biomarkers, including high-throughput techniques such as RNA-Seq and microarrays, and other methods to analyze the presence of specific circRNAs in patient samples.

Identification of a Potentially Functional circRNA-miRNA-mRNA Regulatory Network in Melanocytes for Investigating Pathogenesis of Vitiligo

CircRNAs have been reported to play essential roles in regulating immunity and inflammation, which may be an important regulatory factor in the development of vitiligo. However, the expression profile of circRNAs and their potential biological functions in vitiligo have not been reported so far. In our study we found there are 64 dysregulated circRNAs and 14 dysregulated miRNAs in the patients with vitiligo. Through the correlation analysis, we obtained 12 dysregulated circRNAs and 5 dysregulated miRNAs, forming 48 relationships in the circRNA-miRNA-mRNA regulatory network. Gene Ontology analysis indicated dysregulated circRNAs in vitiligo is closely related to the disorder of the metabolic pathway. The KEGG pathway of dysregulation of circRNAs mainly enriched in the biological processes such as ubiquitin mediated proteolysis, endocytosis and RNA degradation, and in Jak-STAT signaling pathway. Therefore, we found the circRNA-miRNA-mRNA regulatory network are involved in the regulation of numerous melanocyte functions, and these dysregulated circRNAs may closely related to the melanocyte metabolism. Our study provides a theoretical basis for studying the vitiligo pathogenesis from the perspective of circRNA-miRNA-mRNA network.

Circular RNAs and Their Linear Transcripts as Diagnostic and Prognostic Tissue Biomarkers in Prostate Cancer after Prostatectomy in Combination with Clinicopathological Factors

As new biomarkers, circular RNAs (circRNAs) have been largely unexplored in prostate cancer (PCa). Using an integrative approach, we aimed to evaluate the potential of circRNAs and their linear transcripts (linRNAs) to act as (i) diagnostic biomarkers for differentiation between normal and tumor tissue and (ii) prognostic biomarkers for the prediction of biochemical recurrence (BCR) after radical prostatectomy. In a first step, eight circRNAs (circATXN10, circCRIM1, circCSNK1G3, circGUCY1A2, circLPP, circNEAT1, circRHOBTB3, and circSTIL) were identified as differentially expressed via a genome-wide circRNA-based microarray analysis of six PCa samples. Additional bioinformatics and literature data were applied for this selection process. In total, 115 malignant PCa and 79 adjacent normal tissue samples were examined using robust RT-qPCR assays specifically established for the circRNAs and their linear counterparts. Their diagnostic and prognostic potential was evaluated using receiver operating characteristic curves, Cox regressions, decision curve analyses, and C-statistic calculations of prognostic indices. The combination of circATXN10 and linSTIL showed a high discriminative ability between malignant and adjacent normal tissue PCa. The combination of linGUCY1A2, linNEAT1, and linSTIL proved to be the best predictive RNA-signature for BCR. The combination of this RNA signature with five established reference models based on only clinicopathological factors resulted in an improved predictive accuracy for BCR in these models. This is an encouraging study for PCa to evaluate circRNAs and their linRNAs in an integrative approach, and the results showed their clinical potential in combination with standard clinicopathological variables.

Instability of circular RNAs in clinical tissue samples impairs their reliable expression analysis using RT-qPCR: from the myth of their advantage as biomarkers to reality

Background: Circular RNAs (circRNAs) are a new class of RNAs with medical significance. Compared to that of linear mRNA transcripts, the stability of circRNAs against degradation owing to their circular structure is considered advantageous for their use as biomarkers. As systematic studies on the stability of circRNAs depending on the RNA integrity, determined as RNA integrity number (RIN), in clinical tissue samples are lacking, we have investigated this aspect in the present study under model and clinical conditions.

Methods: Total RNA isolated from kidney cancer tissue and cell lines (A-498 and HEK-293) with different RIN after thermal degradation was used in model experiments. Further, RNA isolated from kidney cancer and prostate cancer tissue collected under routine surgical conditions, representing clinical samples with RIN ranging from 2 to 9, were examined. Quantitative real-time reverse-transcription polymerase chain reaction (RT-qPCR) analysis of several circRNAs (circEGLN3, circRHOBTB3, circCSNK1G3, circRNA4, and circRNA9), their corresponding linear counterparts, tissue-specific reference genes, and three microRNAs (as controls) was performed. The quantification cycles were converted into relative quantities and normalized to the expression of specific reference genes for the corresponding tissue. The effect of RIN on the expression of different RNA entities was determined using linear regression analysis, and clinical samples were classified into two groups based on RIN greater or lesser than 6.

Results: The results of model experiments and clinical sample analyses showed that all relative circRNA expression gradually decreased with reduction in RIN values. The adverse effect of RIN was partially compensated after normalizing the data and limiting the samples to only those with RIN values > 6.

Conclusions: Our results suggested that circRNAs are not stable in clinical tissue samples, but are subjected to degradative processes similar to mRNAs. This has not been investigated extensively in circRNA expression studies, and hence must be considered in future for obtaining reliable circRNA expression data. This can be achieved by applying the principles commonly used in mRNA expression studies.