Non-coding RNAs regulate tumor cell plasticity

Tumor metastasis is one of the most serious challenges for human cancers as the majority of deaths caused by cancer are associated with metastasis, rather than the primary tumor. Recent studies have demonstrated that tumor cell plasticity plays a critical role in tumor metastasis by giving rise to various cell types which is necessary for tumor to invade adjacent tissues and form distant metastasis. These include differentiation of cancer stem cells (CSCs), or epithelial-mesenchymal transition (EMT) and its reverse process, mesenchymal-epithelial transition (MET). A growing body of evidence has demonstrated that the biology of tumor cell plasticity is tightly linked to functions of non-coding RNAs (ncRNAs), especially microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). Therefore, understanding the mechanisms how non-coding RNAs regulate tumor cell plasticity is essential for discovery of new diagnostic markers and therapeutic targets to overcome metastasis.     

Clinical significance of the interaction between non-coding RNAs and the epigenetics machinery

Non-coding RNAs and epigenetics are remarkable mechanisms of cellular control. In this review we underline the processes by which non-coding RNAs (ncRNAs), shown to be involved in various diseases, are capable of modifying and being modified by the epigenetic machinery, emphasizing the clinical importance of this network in cancer. Many ncRNAs have been described that play important roles in the establishment and maintenance of the epigenome. However, only a few studies deeply take into account the role of ncRNAs from a clinicopathological standpoint. The wide range of interactions between the non-coding RNome and the epigenome, and the roles of these networks in the pathogenesis, prognosis and early diagnosis of many diseases, present new challenges and opportunities for future studies regarding therapeutic strategies in oncology.     

Informatics challenges in structured RNA

The world of regulatory RNAs is fast expanding into mainstream molecular biology as both a subject of intense mechanistic study and as a tool for functional characterization. The RNA world is one of complex structures that carry out catalysis, sense metabolites and synthesize proteins. The dynamic and structural nature of RNAs presents a whole new set of informatics challenges to the computational community. The ability to relate structure and dynamics to function will be key to understanding this complex world. I review several important classes of structured RNAs that present our community with a series of biologically novel informatics challenges. I also review available informatics tools that have been recently developed in the field.     

Unlocking the potential of non-coding RNAs in cancer research and therapy

Non-coding RNAs (ncRNAs) have emerged as key regulators of gene expression, with growing evidence implicating their involvement in cancer development and progression. The potential of ncRNAs as diagnostic and prognostic biomarkers for cancer is promising, with emphasis on their use in liquid biopsy and tissue-based diagnostics. In a nutshell, the review comprehensively summarizes the diverse classes of ncRNAs implicated in cancer, including microRNAs, long non-coding RNAs, and circular RNAs, and their functions and mechanisms of action. Furthermore, we describe the potential therapeutic applications of ncRNAs, including anti-miRNA oligonucleotides, siRNAs, and other RNA-based therapeutics in cancer treatment. However, significant challenges remain in developing effective ncRNA-based diagnostics and therapeutics, including the lack of specificity, limited understanding of mechanisms, and delivery challenges. This review also covers the current state-of-the-art non-coding RNA research technologies and bioinformatic analysis tools. Lastly, we outline future research directions in non-coding RNA research in cancer, including developing novel biomarkers, therapeutic targets, and modalities. In summary, this review provides a comprehensive understanding of non-coding RNAs in cancer and their potential clinical applications, highlighting both the opportunities and challenges in this rapidly evolving field.     

cfRNAs as biomarkers in oncology – still experimental or applied tool for personalized medicine already?

Currently, the challenges of contemporary oncology are focused mainly on the development of personalized medicine and precise treatment, which could be achieved through the use of molecular biomarkers. One of the biological molecules with great potential are circulating free RNAs (cfRNAs) which are present in various types of body fluids, such as blood, serum, plasma, and saliva. Also, different types of cfRNA particles can be distinguished depending on their length and function: microRNA (miRNA), PIWI-interacting RNA (piRNA), tRNA-derived RNA fragments (tRFs), circular RNA (circRNA), long non-coding RNA (lncRNA), and messenger RNA (mRNA). Moreover, cfRNAs occur in various forms: as a free molecule alone, in membrane vesicles, such as exosomes, or in complexes with proteins and lipids. One of the modern approaches for monitoring patient's condition is a "liquid biopsy" that provides a non-invasive and easily available source of circulating RNAs. Both the presence of specific cfRNA types as well as their concentration are dependent on many factors including cancer type or even reaction to treatment. Despite the possibility of using circulating free RNAs as biomarkers, there is still a lack of validated diagnostic panels, defined protocols for sampling, storing as well as detection methods.In this work we examine different types of cfRNAs, evaluate them as possible biomarkers, and analyze methods of their detection. We believe that further research on cfRNA and defining diagnostic panels could lead to better and faster cancer identification and improve treatment monitoring.     

RNomics: identification and function of small,non-messenger RNAs

In the past few years, our knowledge about small non-mRNAs (snmRNAs) has grown exponentially. Approaches including computational and experimental RNomics have led to a plethora of novel snmRNAs, especially small nucleolar RNAs (snoRNAs). Members of this RNA class guide modification of ribosomal and spliceosomal RNAs. Novel targets for snoRNAs were identified such as tRNAs and potentially mRNAs, and several snoRNAs were shown to be tissue-specifically expressed. In addition, previously unknown classes of snmRNAs have been discovered. MicroRNAs and small interfering RNAs of about 21-23 nt, were shown to regulate gene expression by binding to mRNAs via antisense elements. Regulation of gene expression is exerted by degradation of mRNAs or translational regulation. snmRNAs play a variety of roles during regulation of gene expression. Moreover, the function of some snmRNAs known for decades, has been finally elucidated. Many other RNAs were identified by RNomics studies lacking known sequence and structure motifs. Future challenges in the field of RNomics include identification of the novel snmRNA's biological roles in the cell.     

Quantitative aspects of RNA silencing in metazoans

Small regulatory RNAs (microRNAs, siRNAs, and piRNAs) exhibit several unique features that clearly distinguish them from other known gene regulators. Their genomic organization, mode of action, and proposed biological functions raise specific questions. In this review, we focus on the quantitative aspect of small regulatory RNA biology. The original nature of these small RNAs accelerated the development of novel detection techniques and improved statistical methods and promoted new concepts that may unexpectedly generalize to other gene regulators. Quantification of natural phenomena is at the core of scientific practice, and the unique challenges raised by small regulatory RNAs have prompted many creative innovations by the scientific community.     

Reconstruction of natural RNA sequences from RNA shape, thermodynamic stability, mutational robustness, and linguistic complexity by evolutionary computation

The process of designing novel RNA sequences by inverse RNA folding, available in tools such as RNAinverse and InfoRNA, can be thought of as a reconstruction of RNAs from secondary structure. In this reconstruction problem, no physical measures are considered as additional constraints that are independent of structure, aside of the goal to reach the same secondary structure as the input using energy minimization methods. An extension of the reconstruction problem can be formulated since in many cases of natural RNAs, it is desired to analyze the sequence and structure of RNA molecules using various physical quantifiable measures. In prior works that used secondary structure predictions, it has been shown that natural RNAs differ significantly from random RNAs in some of these measures. Thus, we relax the problem of reconstructing RNAs from secondary structure into reconstructing RNAs from shapes, and in turn incorporate physical quantities as constraints. This allows for the design of novel RNA sequences by inverse folding while considering various physical quantities of interest such as thermodynamic stability, mutational robustness, and linguistic complexity. At the expense of altering the number of nucleotides in stems and loops, for example, physical measures can be taken into account. We use evolutionary computation for the new reconstruction problem and illustrate the procedure on various natural RNAs.     

非编码RNA与基因表达调控

近年来,随着对基因组的深入研究,发现真核生物中存在许多形态和功能各异的非编码RNA分子,这类RNA分子并不表达蛋白质,但它们在基因转录水平、转录后水平及翻译水平起了重要的调控作用。具有调控作用的RNA分子种类非常丰富,如长链非编码RNA(long non-coding RNA,lncRNA)、miRNA、PIWI相互作用RNA(PIWI-interacting RNA,piRNA)、内源性小干扰RNA(endogenous small interfering RNA,endo-siRNA)、竞争性内源RNA(competitive endogenous RNA,ceRNA)等,它们使基因表达过程更为丰富、严谨和有序。本文综述几类典型的非编码RNA对基因表达的调节作用,以助于理解细胞中RNA分子调节网络的功能和机制。     

Reconstruction of Natural RNA Sequences from RNA Shape,Thermodynamic Stability,Mutational Robustness,and Linguistic Complexity by Evolutionary Computation

Abstract

The process of designing novel RNA sequences by inverse RNA folding, available in tools such as RNAinverse and InfoRNA, can be thought of as a reconstruction of RNAs from secondary structure. In this reconstruction problem, no physical measures are considered as additional constraints that are independent of structure, aside of the goal to reach the same secondary structure as the input using energy minimization methods. An extension of the reconstruction problem can be formulated since in many cases of natural RNAs, it is desired to analyze the sequence and structure of RNA molecules using various physical quantifiable measures. In prior works that used secondary structure predictions, it has been shown that natural RNAs differ significantly from random RNAs in some of these measures. Thus, we relax the problem of reconstructing RNAs from secondary structure into reconstructing RNAs from shapes, and in turn incorporate physical quantities as constraints. This allows for the design of novel RNA sequences by inverse folding while considering various physical quantities of interest such as thermodynamic stability, mutational robustness, and linguistic complexity. At the expense of altering the number of nucleotides in stems and loops, for example, physical measures can be taken into account. We use evolutionary computation for the new reconstruction problem and illustrate the procedure on various natural RNAs.     

Non-cell Autonomous RNA Trafficking and Long-Distance Signaling

A wide range of proteins and RNA molecules in plants have been recently identified as non-cell autonomous, phloem-mobile molecules and suggested to play important roles in physiological and developmental processes. Systemic movement of both protein-coding mRNAs and non-coding small RNAs is shown to correlate with the epigenetic changes brought about across grafting junctions, supporting their potential roles as long-distance signaling molecules. Plants appear to have evolved this unique RNA-based signaling mechanism to control systemic regulation of various responses to environmental stimuli and challenges such as photoperiods, nutrient availabilities, and pathogen attacks. This mechanism may have been exploited by viroids, non-coding RNA pathogens, to spread infection cell to cell and through phloem. A model describing potential molecular mechanisms by which the systemic RNA trafficking occurs will be presented.