Establishing essential quality criteria for the validation of circular RNAs as biomarkers

Computational approaches for circRNAs prediction and in silico characterization

Circular RNAs (circRNAs) are single-stranded and covalently closed non-coding RNA molecules originated from RNA splicing. Their functions include regulatory potential over other RNA species, such as microRNAs, messenger RNAs and RNA binding proteins. For circRNA identification, several algorithms are available and can be classified in two major types: pseudo-reference-based and split-alignment-based approaches. In general, the data generated from circRNA transcriptome initiatives is deposited on public specific databases, which provide a large amount of information on different species and functional annotations. In this review, we describe the main computational resources for the identification and characterization of circRNAs, covering the algorithms and predictive tools to evaluate its potential role in a particular transcriptomics project, including the public repositories containing relevant data and information for circRNAs, recapitulating their characteristics, reliability and amount of data reported.

Preanalytic and Analytic Quality System Considerations in Noncoding RNA Biomarker Development for Clinical Diagnostics

A frequent topic of biomedical research is the potential clinical use of non-coding (nc) RNAs as quantitative biomarkers for a broad spectrum of health and disease. However, ncRNA analyses have not been pressed into widespread diagnostic use. Strong preclinical evidence suggests obstacles in the translation and reproducibility of this type of biomarker which may result from preanalytical and analytical variation in the non-standardized processes used to collect, process, and store samples, as well as the substantive differences between small and long ncRNA. We performed a narrative review of selected literature, through the lens of key laboratory-developed test (LDT) regulations under the Clinical Laboratory Improvement Amendments (CLIA) in the United States, to study critical gaps in ncRNA validation studies. This review describes the leading candidate ncRNA subclasses, their biogenesis and cellular function, and identifies specific pre-analytical variables with disproportionate impact on testing performance. We summarize these findings with strategic recommendations to clinicians and biomedical scientists involved in the design, conduct, and translation of ncRNA biomarker development.

Epigenetic modifications in spinal ligament aging

Spinal stenosis is a common degenerative spine disorder in the aged population and the spinal ligament aging is a main contributor to this chronic disease. However, the underlying mechanisms of spinal ligament aging remain unclear. Epigenetics is the study of heritable and reversible changes in the function of a gene or genome that occur without any alteration in the primary DNA sequence. Epigenetic alterations have been demonstrated to play crucial roles in age-related diseases and conditions, and they are recently studied as biomarkers and therapeutic targets in the field of cancer research. The main epigenetic modifications, including DNA methylation alteration, histone modifications as well as dysregulated noncoding RNA modulation, have all been implicated in spinal ligament aging diseases. DNA methylation modulates the expression of critical genes including WNT5A, GDNF, ACSM5, miR-497 and miR-195 during spinal ligament degeneration. Histone modifications widely affect gene expression and obvious histone modification abnormalities have been found in spinal ligament aging. MicroRNAs (miRNAs), long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) exert crucial regulating effects on spinal ligament aging conditions via targeting various osteogenic or fibrogenic differentiation related genes. To our knowledge, there is no systematic review yet to summarize the involvement of epigenetic mechanisms of spinal ligament aging in degenerative spinal diseases. In this study, we systematically discussed the different epigenetic modifications and their potential functions in spinal ligament aging process.

CIRCprimerXL: Convenient and High-Throughput PCR Primer Design for Circular RNA Quantification

Circular RNA (circRNA) is a class of endogenous non-coding RNA characterized by a back-splice junction (BSJ). In general, large-scale circRNA BSJ detection is performed based on RNA sequencing data, followed by the selection and validation of circRNAs of interest using RT-qPCR with circRNA-specific PCR primers. Such a primer pair is convergent and functional on the circRNA template but divergent and non-functional on the linear host gene. Although a few circRNA primer design pipelines have been published, none of them offer large-scale, easy-to-use circRNA primer design. Other limitations are that these tools generally do not take into account assay specificity, secondary structures, and SNPs in the primer annealing regions. Furthermore, these tools are limited to circRNA primer design for humans (no other organisms possible), and no wet-lab validation is demonstrated. Here, we present CIRCprimerXL, a circRNA RT-qPCR assay design pipeline based on the primer design framework primerXL. CIRCprimerXL takes a circRNA BSJ position as input, and designs BSJ-spanning primers using Primer3. The user can choose to use the unspliced or spliced circRNA sequence as template. Prior to primer design, sequence regions with secondary structures and common SNPs are flagged. Next, the primers are filtered based on predicted specificity and the absence of secondary structures of the amplicon to select a suitable primer pair. Our tool is both available as a user-friendly web tool and as a stand-alone pipeline based on Docker and Nextflow, allowing users to run the pipeline on a wide range of computer infrastructures. The CIRCprimerXL Nextflow pipeline can be used to design circRNA primers for any species by providing the appropriate reference genome. The CIRCprimerXL web tool supports circRNA primer design for human, mouse, rat, zebrafish, Xenopus tropicalis, and C. elegans. The design process can easily be scaled up for the qPCR assay design of tens of thousands of circRNAs within a couple of hours. We show how CIRCprimerXL has been successfully used to design qPCR assays for over 15,000 human circRNAs of which 20 were empirically validated. CIRCprimerXL software, documentation, and test data can be found at: https://github.com/OncoRNALab/CIRCprimerXL. CIRCprimerXL is also implemented as a webtool at: https://circprimerxl.cmgg.be.

Emerging roles of circRNAs in the pathological process of myocardial infarction

Myocardial infarction (MI) is defined as cardiomyocyte death in a clinical context consistent with ischemic insult. MI remains one of the leading causes of morbidity and mortality worldwide. Although there are a number of effective clinical methods for the diagnosis and treatment of MI, further investigation of novel biomarkers and molecular therapeutic targets is required. Circular RNAs (circRNAs), novel non-coding RNAs, have been reported to function mainly by acting as microRNA (miRNA) sponges or binding to RNA-binding proteins (RBPs). The circRNA-miRNA-mRNA (protein) regulatory pathway regulates gene expression and affects the pathological mechanisms of various diseases. Undoubtedly, a more comprehensive understanding of the relationship between MI and circRNA will lay the foundation for the development of circRNA-based diagnostic and therapeutic strategies for MI. Therefore, this review summarizes the pathophysiological process of MI and various approaches to measure circRNA levels in MI patients, tissues, and cells; highlights the significance of circRNAs in the regulation MI pathogenesis and development; and provides potential clinical insight for the diagnosis, prognosis, and treatment of MI.

Using Drosophila to uncover molecular and physiological functions of circRNAs

Circular RNAs (circRNAs) are a class of covalently closed RNA molecules generated by backsplicing. circRNAs are expressed in a tissue-specific manner, accumulate with age in neural tissues, and are highly stable. In many cases, circRNAs are generated at the expense of a linear transcript as back-splicing competes with linear splicing. Some circRNAs regulate gene expression in cis, and some circRNAs can be translated into protein. The advent of deep sequencing and new bioinformatic tools has allowed detection of thousands of circRNAs in eukaryotes. Studying the functions of circRNAs is done using a combination of molecular and genetic methods. The unique genetic tools that can be used in studies of Drosophila melanogaster are ideal for deciphering the functions of circRNAs in vivo. These tools include the GAL4-UAS system, which can be used to manipulate the levels of circRNAs with exquisite temporal and spatial control, and genetic interaction screening, which could be used to identify pathways regulated by circRNAs. Research performed in Drosophila has revealed circRNAs production mechanisms, details of their translation, and their physiological functions. Due to their short lifecycle and the existence of excellent neurodegeneration models, Drosophila can also be used to study the role of circRNAs in aging and age-related disorders. Here, we review molecular and genetic tools and methods for detecting, manipulating, and studying circRNAs in Drosophila.

Validation of Circular RNAs Using RT-qPCR After Effective Removal of Linear RNAs by Ribonuclease R

Circular RNAs (circRNAs) are a class of endogenous noncoding RNAs that have been shown to play a role in normal development, homeostasis, and disease, including cancer. CircRNAs are formed through a process called back-splicing, which results in a covalently closed loop with a nonlinear back-spliced junction (BSJ). In general, circRNA BSJs are predicted in RNA sequencing data using one of numerous circRNA detection algorithms. Selected circRNAs are then typically validated using an orthogonal method such as reverse transcription quantitative PCR (RT-qPCR) with circRNA-specific primers. However, linear transcripts originating from endogenous trans-splicing can lead to false-positive signals both in RNA sequencing and in RT-qPCR experiments. Therefore, it is essential to perform the RT-qPCR validation step only after linear RNAs have been degraded using an exonuclease such as ribonuclease R (RNase R). Several RNase R protocols are available for circRNA detection using RNA sequencing or RT-qPCR. These protocols-which vary in enzyme concentration, RNA input amount, incubation times, and cleanup steps-typically lack a detailed validated standard protocol and fail to provide a range of conditions that deliver accurate results. As such, some protocols use RNase R concentrations that are too high, resulting in partial degradation of the target circRNAs. Here, we describe an optimized workflow for circRNA validation, combining RNase R treatment and RT-qPCR. First, we outline the steps for circRNA primer design and qPCR assay validation. Then, we describe RNase R treatment of total RNA and, importantly, a subsequent essential buffer cleanup step. Lastly, we outline the steps to perform the RT-qPCR and discuss the downstream data analyses. © 2021 Wiley Periodicals LLC. Basic Protocol 1: CircRNA primer design and qPCR assay validation Basic Protocol 2: RNase R treatment, cleanup, and RT-qPCR.

Clinicopathological-Associated Regulatory Network of Deregulated circRNAs in Hepatocellular Carcinoma

Simple Summary

Here, we present a novel strategy to identify key signatures of clinically-relevant co-expressed circRNA-mRNA networks in pertinent cancer-pathways that modulate the prognosis of HCC patients, by integrating clinicopathological features, circRNA and mRNA expression profiles. Five master circRNAs were identified and experimentally demonstrated to upregulate proliferate and promote transformation. Through further integration with miRNA-expression profiles, clinically-relevant competing-endogenous-RNA (ceRNA) networks of circRNA-miRNA-mRNAs were constructed. The most up-regulated nodal-circRNA, circGPC3 was experimentally demonstrated to up-regulate cell-cycle, migration and invasion. circGPC3 was found to act as a sponge of miR-378a-3p to regulate ASPM expression and modulate cell transformation. These 5 nodal circRNAs has potential to be good prognostic biomarkers with good prognostic performance. circGPC3 has great potential to be a promising non-invasive prognostic biomarker for early HCC. We have thus demonstrated the robustness of bioinformatically-predicted master circRNAs in clinically-relevant, circRNA-mRNA networks, underscoring the important roles that these identified deregulated key/master circRNAs play in HCC.

Abstract

Hepatocellular carcinoma (HCC) is one of the most common and lethal cancers worldwide. Here, we present a novel strategy to identify key circRNA signatures of clinically relevant co-expressed circRNA-mRNA networks in pertinent cancer-pathways that modulate prognosis of HCC patients, by integrating clinic-pathological features, circRNA and mRNA expression profiles. Through further integration with miRNA expression profiles, clinically relevant competing-endogenous-RNA (ceRNA) networks of circRNA-miRNA-mRNAs were constructed. At least five clinically relevant nodal-circRNAs, co-expressed with numerous genes, were identified from the circRNA-mRNA networks. These nodal circRNAs upregulated proliferation (except circRaly) and transformation in cells. The most upregulated nodal-circRNA, circGPC3, associated with higher-grade tumors and co-expressed with 33 genes, competes with 11 mRNAs for two shared miRNAs. circGPC3 was experimentally demonstrated to upregulate cell-cycle and migration/invasion in both transformed and non-transformed liver cell-lines. circGPC3 was further shown to act as a sponge of miR-378a-3p to regulate APSM (Abnormal spindle-like microcephaly associated) expression and modulate cell transformation. This study identifies 5 key nodal master circRNAs in a clinically relevant circRNA-centric network that are significantly associated with poorer prognosis of HCC patients and promotes tumorigenesis in cell-lines. The identification and characterization of these key circRNAs in clinically relevant circRNA-mRNA and ceRNA networks may facilitate the design of novel strategies targeting these important regulators for better HCC prognosis.

Methods to study circRNA-protein interactions

Circular RNAs (circRNAs) have been studied extensively in the last few years, uncovering functional roles in a diverse range of cell types and organisms. As shown for a few cases, these functions may be mediated by trans-acting factors, in particular RNA-binding proteins (RBPs). However, the specific interaction partners for most circRNAs remain unknown. This is mainly due to technical difficulties in their identification and in differentiating between interactors of circRNAs and their linear counterparts. Here we review the currently used methodology to systematically study circRNA-protein complexes (circRNPs), focusing either on a specific RNA or protein, both on the gene-specific or global level, and discuss advantages and challenges of the available approaches.

Dual Effects of Non-Coding RNAs (ncRNAs) in Cancer Stem Cell Biology

The identification of cancer stem cells (CSCs) as initiators of carcinogenesis has revolutionized the era of cancer research and our perception for the disease treatment options. Additional CSC features, including self-renewal and migratory and invasive capabilities, have further justified these cells as putative diagnostic, prognostic, and therapeutic targets. Given the CSC plasticity, the identification of CSC-related biomarkers has been a serious burden in CSC characterization and therapeutic targeting. Over the past decades, a compelling amount of evidence has demonstrated critical regulatory functions of non-coding RNAs (ncRNAs) on the exclusive features of CSCs. We now know that ncRNAs may interfere with signaling pathways, vital for CSC phenotype maintenance, such as Notch, Wnt, and Hedgehog. Here, we discuss the multifaceted contribution of microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), as representative ncRNA classes, in sustaining the CSC-like traits, as well as the underlying molecular mechanisms of their action in various CSC types. We further discuss the use of CSC-related ncRNAs as putative biomarkers of high diagnostic, prognostic, and therapeutic value.