Pan-Cancer Analysis of Canonical and Modified miRNAs Enhances the Resolution of the Functional miRNAome in Cancer

ncRNA Editing: Functional Characterization and Computational Resources

Non-coding RNAs (ncRNAs) play crucial roles in gene expression regulation, translation, and disease development, including cancer. They are classified by size in short and long non-coding RNAs. This chapter focuses on the functional implications of adenosine-to-inosine (A-to-I) RNA editing in both short (e.g., miRNAs) and long ncRNAs. RNA editing dynamically alters the sequence and structure of primary transcripts, impacting ncRNA biogenesis and function. Notable findings include the role of miRNA editing in promoting glioblastoma invasiveness, characterizing RNA editing hotspots across cancers, and its implications in thyroid cancer and ischemia. This chapter also highlights bioinformatics resources and next-generation sequencing (NGS) technologies that enable comprehensive ncRNAome studies and genome-wide RNA editing detection. Dysregulation of RNA editing machinery has been linked to various human diseases, emphasizing the potential of RNA editing as a biomarker and therapeutic target. This overview integrates current knowledge and computational tools for studying ncRNA editing, providing insights into its biological significance and clinical applications.

Advances in A-to-I RNA editing in cancer

RNA modifications are widespread throughout the mammalian transcriptome and play pivotal roles in regulating various cellular processes. These modifications are strongly linked to the development of many cancers. One of the most prevalent forms of RNA modifications in humans is adenosine-to-inosine (A-to-I) editing, catalyzed by the enzyme adenosine deaminase acting on RNA (ADAR) in double-stranded RNA (dsRNA). With advancements in RNA sequencing technologies, the role of A-to-I modification in cancer has garnered increasing attention. Research indicates that the levels and specific sites of A-to-I editing are significantly altered in many malignant tumors, correlating closely with tumor progression. This editing occurs in both coding and noncoding regions of RNA, influencing signaling pathways involved in cancer development. These modifications can either promote or suppress cancer progression through several mechanisms, including inducing non-synonymous amino acid mutations, altering the immunogenicity of dsRNAs, modulating mRNA interactions with microRNAs (miRNAs), and affecting the splicing of circular RNAs (circRNAs) as well as the function of long non-coding RNAs (lncRNAs). A comprehensive understanding of A-to-I RNA editing is crucial for advancing the diagnosis, treatment, and prognosis of human cancers. This review explores the regulatory mechanisms of A-to-I editing in cancers and examines their potential clinical applications. It also summarizes current research, identifies future directions, and highlights potential therapeutic implications.

Improved lung cancer classification by employing diverse molecular features of microRNAs

MiRNAs are edited or modified in multiple ways during their biogenesis pathways. It was reported that miRNA editing was deregulated in tumors, suggesting the potential value of miRNA editing in cancer classification. Here we extracted three types of miRNA features from 395 LUAD and control samples, including the abundances of original miRNAs, the abundances of edited miRNAs, and the editing levels of miRNA editing sites. Our results show that eight classification algorithms selected generally had better performances on combined features than on the abundances of miRNAs or editing features of miRNAs alone. One feature selection algorithm, i.e., the DFL algorithm, selected only three features, i.e., the frequencies of hsa-miR-135b-5p, hsa-miR-210-3p and hsa-mir-182_48u (an edited miRNA), from 316 training samples. Seven classification algorithms achieved 100% accuracies on these three features for 79 independent testing samples. These results indicate that the additional information of miRNA editing is useful in improving the classification of LUAD samples.

tRFUniverse: A comprehensive resource for the interactive analyses of tRNA-derived ncRNAs in human cancer

tRNA-derived ncRNAs are a heterogeneous class of non-coding RNAs recently proposed to be active regulators of gene expression and be involved in many diseases, including cancer. Consequently, several online resources on tRNA-derived ncRNAs have been released. Although interesting, such resources present only basic features and do not adequately exploit the wealth of knowledge available about tRNA-derived ncRNAs. Therefore, we introduce tRFUniverse, a novel online resource for the analysis of tRNA-derived ncRNAs in human cancer. tRFUniverse presents an extensive collection of classes of tRNA-derived ncRNAs analyzed across all the TCGA and TARGET tumor cohorts, NCI-60 cell lines, and biological fluids. Moreover, public AGO CLASH/CLIP-Seq data were analyzed to identify the molecular interactions between tRNA-derived ncRNAs and other transcripts. Importantly, tRFUniverse combines in a single resource a comprehensive set of features that we believe may be helpful to investigate the involvement of tRNA-derived ncRNAs in cancer biology.

miRNA dosage control in development and human disease

In mammals, miRNAs recognize target mRNAs via base pairing, which leads to a complex 'multiple-to-multiple' regulatory network. Previous studies have focused on the regulatory mechanisms and functions of individual miRNAs, but alterations of many individual miRNAs do not strongly disturb the miRNA regulatory network. Recent studies revealed the important roles of global miRNA dosage control events in physiological processes and pathogenesis, suggesting that miRNAs can be considered as a 'cellular buffer' that controls cell fate. Here, we review the current state of research on how global miRNA dosage is tightly controlled to regulate development, tumorigenesis, neurophysiology, and immunity. We propose that methods of controlling global miRNA dosage may serve as effective therapeutic tools to cure human diseases.

Functional and Potential Therapeutic Implication of MicroRNAs in Pancreatic Cancer

The alarmingly low five-year survival rate for pancreatic cancer presents a global health challenge, contributing to about 7% of all cancer-related deaths. Late-stage diagnosis and high heterogeneity are the biggest hurdles in treating pancreatic cancer. Thus, there is a pressing need to discover novel biomarkers that could help in early detection as well as improve therapeutic strategies. MicroRNAs (miRNAs), a class of short non-coding RNA, have emerged as promising candidates with regard to both diagnostics and therapeutics. Dysregulated miRNAs play pivotal roles in accelerating tumor growth and metastasis, orchestrating tumor microenvironment, and conferring chemoresistance in pancreatic cancer. The differential expression profiles of miRNAs in pancreatic cancer could be utilized to explore novel therapeutic strategies. In this review, we also covered studies on recent advancements in various miRNA-based therapeutics such as restoring miRNAs with a tumor-suppressive function, suppressing miRNA with an oncogenic function, and combination with chemotherapeutic drugs. Despite several challenges in terms of specificity and targeted delivery, miRNA-based therapies hold the potential to revolutionize the treatment of pancreatic cancer by simultaneously targeting multiple signaling pathways.

Reassessment of miRNA variant (isomiRs) composition by small RNA sequencing

IsomiRs, sequence variants of mature microRNAs, are usually detected and quantified using high-throughput sequencing. Many examples of their biological relevance have been reported, but sequencing artifacts identified as artificial variants might bias biological inference and therefore need to be ideally avoided. We conducted a comprehensive evaluation of 10 different small RNA sequencing protocols, exploring both a theoretically isomiR-free pool of synthetic miRNAs and HEK293T cells. We calculated that, with the exception of two protocols, less than 5% of miRNA reads can be attributed to library preparation artifacts. Randomized-end adapter protocols showed superior accuracy, with 40% of true biological isomiRs. Nevertheless, we demonstrate concordance across protocols for selected miRNAs in non-templated uridyl additions. Notably, NTA-U calling and isomiR target prediction can be inaccurate when using protocols with poor single-nucleotide resolution. Our results highlight the relevance of protocol choice for biological isomiRs detection and annotation, which has key potential implications for biomedical applications.