scholarly journals ceRNAs in Cancer: Mechanism and Functions in a Comprehensive Regulatory Network

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ni Yang ◽  
Kuo Liu ◽  
Mengxuan Yang ◽  
Xiang Gao
Keyword(s):  
Regulatory Network ◽  
Noncoding Rnas ◽  
Transcription Profile ◽  
Intracellular Communication ◽  
Competing Endogenous Rnas ◽  
Diagnostic Values ◽  
Correlated Factors ◽  
Post Transcriptional Regulation ◽  
Analytical Approaches ◽  
Prognosis Evaluation

Noncoding RNAs have been shown with powerful ability in post-transcriptional regulation, enabling intertwined RNA crosstalk and global molecular interaction in a large amount of dysfunctional conditions including cancer. Competing endogenous RNAs (ceRNAs) are those competitively binding with shared microRNAs (miRNAs), freeing their counterparts from miRNA-induced degradation, thus actively influencing and connecting with each other. Constantly updated analytical approaches boost outstanding advancement achieved in this burgeoning hotspot in multilayered intracellular communication, providing new insights into pathogenesis and clinical treatment. Here, we summarize the mechanisms and correlated factors under this RNA interplay and deregulated transcription profile in neoplasm and tumor progression, underscoring the great significance of ceRNAs for diagnostic values, monitoring biomarkers, and prognosis evaluation in cancer.

scholarly journals Competing Endogenous RNAs in Cervical Carcinogenesis: A New Layer of Complexity

Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 991
Author(s):  
Fernanda Costa Brandão Berti ◽  
Sara Cristina Lobo-Alves ◽  
Camila de Freitas Oliveira-Toré ◽  
Amanda Salviano-Silva ◽  
Karen Brajão de Oliveira ◽  
...  
Keyword(s):  
Gene Expression ◽  
Fine Tuning ◽  
Molecular Networks ◽  
Cervical Carcinogenesis ◽  
Molecular Changes ◽  
Cellular Processes ◽  
Target Mrnas ◽  
Competing Endogenous Rnas ◽  
Cervical Cells ◽  
Post Transcriptional Regulation

MicroRNAs (miRNAs) regulate gene expression by binding to complementary sequences within target mRNAs. Apart from working ‘solo’, miRNAs may interact in important molecular networks such as competing endogenous RNA (ceRNA) axes. By competing for a limited pool of miRNAs, transcripts such as long noncoding RNAs (lncRNAs) and mRNAs can regulate each other, fine-tuning gene expression. Several ceRNA networks led by different lncRNAs—described here as lncRNA-mediated ceRNAs—seem to play essential roles in cervical cancer (CC). By conducting an extensive search, we summarized networks involved in CC, highlighting the major impacts of such dynamic molecular changes over multiple cellular processes. Through the sponging of distinct miRNAs, some lncRNAs as HOTAIR, MALAT1, NEAT1, OIP5-AS1, and XIST trigger crucial molecular changes, ultimately increasing cell proliferation, migration, invasion, and inhibiting apoptosis. Likewise, several lncRNAs seem to be a sponge for important tumor-suppressive miRNAs (as miR-140-5p, miR-143-3p, miR-148a-3p, and miR-206), impairing such molecules from exerting a negative post-transcriptional regulation over target mRNAs. Curiously, some of the involved mRNAs code for important proteins such as PTEN, ROCK1, and MAPK1, known to modulate cell growth, proliferation, apoptosis, and adhesion in CC. Overall, we highlight important lncRNA-mediated functional interactions occurring in cervical cells and their closely related impact on cervical carcinogenesis.

scholarly journals Study on the Relationship between the miRNA-centered ceRNA Regulatory Network and Fatigue

2021 ◽  
Author(s):  
Xingzhe Yang ◽  
Feng Li ◽  
Jie Ma ◽  
Yan Liu ◽  
Xuejiao Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Hot Spot ◽  
Genetic Research ◽  
Noncoding Rnas ◽  
Messenger Rnas ◽  
Effective Prevention ◽  
Gene Regulatory ◽  
The Relationship

AbstractIn recent years, the incidence of fatigue has been increasing, and the effective prevention and treatment of fatigue has become an urgent problem. As a result, the genetic research of fatigue has become a hot spot. Transcriptome-level regulation is the key link in the gene regulatory network. The transcriptome includes messenger RNAs (mRNAs) and noncoding RNAs (ncRNAs). MRNAs are common research targets in gene expression profiling. Noncoding RNAs, including miRNAs, lncRNAs, circRNAs and so on, have been developed rapidly. Studies have shown that miRNAs are closely related to the occurrence and development of fatigue. MiRNAs can regulate the immune inflammatory reaction in the central nervous system (CNS), regulate the transmission of nerve impulses and gene expression, regulate brain development and brain function, and participate in the occurrence and development of fatigue by regulating mitochondrial function and energy metabolism. LncRNAs can regulate dopaminergic neurons to participate in the occurrence and development of fatigue. This has certain value in the diagnosis of chronic fatigue syndrome (CFS). CircRNAs can participate in the occurrence and development of fatigue by regulating the NF-κB pathway, TNF-α and IL-1β. The ceRNA hypothesis posits that in addition to the function of miRNAs in unidirectional regulation, mRNAs, lncRNAs and circRNAs can regulate gene expression by competitive binding with miRNAs, forming a ceRNA regulatory network with miRNAs. Therefore, we suggest that the miRNA-centered ceRNA regulatory network is closely related to fatigue. At present, there are few studies on fatigue-related ncRNA genes, and most of these limited studies are on miRNAs in ncRNAs. However, there are a few studies on the relationship between lncRNAs, cirRNAs and fatigue. Less research is available on the pathogenesis of fatigue based on the ceRNA regulatory network. Therefore, exploring the complex mechanism of fatigue based on the ceRNA regulatory network is of great significance. In this review, we summarize the relationship between miRNAs, lncRNAs and circRNAs in ncRNAs and fatigue, and focus on exploring the regulatory role of the miRNA-centered ceRNA regulatory network in the occurrence and development of fatigue, in order to gain a comprehensive, in-depth and new understanding of the essence of the fatigue gene regulatory network.

Construction of an lncRNA–mRNA Co-Expression Regulatory Network Mediating Inflammation and Regeneration Following Acute Pancreatitis Injury

2021 ◽  
Author(s):  
Jing Wang ◽  
Tianjie Chen ◽  
Xiaohua Zhang ◽  
Shulei Zhao
Keyword(s):  
Acute Pancreatitis ◽  
Mrna Expression ◽  
Regulatory Network ◽  
Noncoding Rnas ◽  
Pancreatic Injury ◽  
Control Group ◽  
Rna Seq ◽  
Damage Repair ◽  
Injury And Repair ◽  
And Function

Abstract Long noncoding RNAs (lncRNAs) play important roles in the occurrence and development of many diseases and can be used as targets for diagnosis and treatment. However, the expression and function of lncRNAs in the injury and repair of acute pancreatitis (AP) are unclear. To decipher lncRNAs’ regulatory roles in AP, we reanalyzed an RNA-seq dataset of 24 pancreatic tissues, including those of normal control mice (BL), those 7 days after mild AP (D7), and those 14 days after mild AP (D14). The results showed significant differences in lncRNA and mRNA expression of D7/D14 groups compared with the control group. Co-expression analysis showed that differentially expressed (DE) lncRNAs were closely related to immunity- and inflammation-related pathways by trans-regulating mRNA expression. The lncRNA–mRNA network showed that the lncRNAs Dancer, Gmm20488, Terc, Snhg3, and Snhg20 were significantly correlated with AP pathogenesis. WGCNA and cis regulation analysis also showed that AP repair-associated lncRNAs were correlated with extracellular and inflammation-related genes, which affect the repair and regeneration of pancreatic injury after AP. In conclusion, the systemic dysregulation of lncRNAs is strongly involved in remodeling AP’s gene expression regulatory network, and the lncRNA–mRNA expression network could identify targets for AP treatment and damage repair.

scholarly journals BP Neural Network Could Help Improve Pre-miRNA Identification in Various Species

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Limin Jiang ◽  
Jingjun Zhang ◽  
Ping Xuan ◽  
Quan Zou
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Regulatory Network ◽  
Bioinformatics Analysis ◽  
Biological Function ◽  
State Of The Art ◽  
Biological Evolution ◽  
Noncoding Rnas ◽  
The Past ◽  
Mirna Identification

MicroRNAs (miRNAs) are a set of short (21–24 nt) noncoding RNAs that play significant regulatory roles in cells. In the past few years, research on miRNA-related problems has become a hot field of bioinformatics because of miRNAs’ essential biological function. miRNA-related bioinformatics analysis is beneficial in several aspects, including the functions of miRNAs and other genes, the regulatory network between miRNAs and their target mRNAs, and even biological evolution. Distinguishing miRNA precursors from other hairpin-like sequences is important and is an essential procedure in detecting novel microRNAs. In this study, we employed backpropagation (BP) neural network together with 98-dimensional novel features for microRNA precursor identification. Results show that the precision and recall of our method are 95.53% and 96.67%, respectively. Results further demonstrate that the total prediction accuracy of our method is nearly 13.17% greater than the state-of-the-art microRNA precursor prediction software tools.

scholarly journals Challenges and Strategies in Ascribing Functions to Long Noncoding RNAs

Cancers ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1458 ◽  
Author(s):  
Yang Zhao ◽  
Hongqi Teng ◽  
Fan Yao ◽  
Shannon Yap ◽  
Yutong Sun ◽  
...  
Keyword(s):  
Regulation Of Gene Expression ◽  
Noncoding Rnas ◽  
Genetically Engineered ◽  
Long Noncoding Rnas ◽  
Genetically Engineered Mouse Models ◽  
Genomic Location ◽  
Bona Fide ◽  
Underlying Mechanisms ◽  
Post Transcriptional Regulation ◽  
In Cis

Long noncoding RNAs (lncRNAs) are involved in many physiological and pathological processes, such as development, aging, immunity, and cancer. Mechanistically, lncRNAs exert their functions through interaction with proteins, genomic DNA, and other RNA, leading to transcriptional and post-transcriptional regulation of gene expression, either in cis or in trans; it is often difficult to distinguish between these two regulatory mechanisms. A variety of approaches, including RNA interference, antisense oligonucleotides, CRISPR-based methods, and genetically engineered mouse models, have yielded abundant information about lncRNA functions and underlying mechanisms, albeit with many discrepancies. In this review, we elaborate on the challenges in ascribing functions to lncRNAs based on the features of lncRNAs, including the genomic location, copy number, domain structure, subcellular localization, stability, evolution, and expression pattern. We also describe a framework for the investigation of lncRNA functions and mechanisms of action. Rigorous characterization of cancer-implicated lncRNAs is critical for the identification of bona fide anticancer targets.

Competing Endogenous RNAs in Hepatocellular Carcinoma—The Pinnacle of Rivalry

2019 ◽  
Vol 39 (04) ◽  
pp. 463-475 ◽  
Author(s):  
Abdelrahman Yousry Afify ◽  
Salma Abdulmaqsoud Ibrahim ◽  
Mennah Hisham Aldamsisi ◽  
Mai Saad Zaghloul ◽  
Nada El-Ekiaby ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Noncoding Rnas ◽  
Circular Rnas ◽  
Solo Performance ◽  
Regulatory Pathways ◽  
Small Noncoding Rnas ◽  
Posttranscriptional Gene Regulation ◽  
Competing Endogenous Rnas ◽  
Genomic Regulation

AbstractThe role of noncoding transcripts in gene expression is nowadays acknowledged to keep various diseases at bay—despite being referred to as “junk” DNA several years ago. Believed to be at the heart of multiple regulatory pathways, microRNAs (miRNAs) are small noncoding RNAs (ncRNAs) involved in posttranscriptional gene regulation. Recently, the discovery of ncRNAs that compete for shared miRNA pools has dimmed the light on the solo performance of miRNAs in genomic regulation. Indeed, several studies describe RNAs such as long noncoding RNAs, mRNAs, circular RNAs, pseudogenes, and viral RNAs as competing endogenous RNAs (ceRNAs) that sequester miRNAs, allowing for de-repression of downstream miRNA targets. Such integration between coding and noncoding transcripts forms complex ceRNA networks that when dysregulated lead to several diseases such as hepatocellular carcinoma. Here, the authors review perturbed ceRNA networks in hepatocellular carcinoma, describe the role of each in tumorigenesis, and discuss their various clinical implications.

scholarly journals MicroRNAs : An Emerging Player In Autophagy

2014 ◽  
Author(s):  
yongfei yang ◽  
CHENGYU LIANG
Keyword(s):  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Regulation Of Gene Expression ◽  
Substantial Effect ◽  
Digestion Process ◽  
The Past ◽  
Pathological Conditions ◽  
Cellular Autophagy ◽  
Evolutionarily Conserved ◽  
Post Transcriptional Regulation

Autophagy is an evolutionarily conserved self-digestion process for the quality control of intracellular entities in eukaryotes. In the past few years, mounting evidence indicates that microRNAs (miRNAs)-mediated post-transcriptional regulation of gene expression represents an integral part of the autophagy regulatory network and may have a substantial effect on autophagy-related physiological and pathological conditions including cancer. Herein, we examine some of the molecular mechanisms by which microRNAs manipulate the autophagic machinery to maintain cellular homeostasis and their biological outputs during cancer development. A better understanding of interaction between microRNAs and cellular autophagy may ultimately benefit future cancer diagnostic and anticancer therapeutics.

The Promise of miRNA Replacement Therapy for Hepatocellular Carcinoma

2019 ◽  
Vol 19 (5) ◽  
pp. 290-304 ◽  
Author(s):  
Mahmoud Elhefnawi ◽  
Zeinab Salah ◽  
Bangly Soliman
Keyword(s):  
Hepatocellular Carcinoma ◽  
Clinical Trials ◽  
Mortality Rate ◽  
Tumor Suppressor ◽  
Noncoding Rnas ◽  
Efficient Delivery ◽  
Post Transcriptional Regulation ◽  
Tumor Suppressor Mirnas

Hepatocellular carcinoma is a devastating tumor which accounts for death mortality rate 94% globally, and about 780,000 new cases each year. Tumor suppressor miRNAs represent a class of noncoding RNAs, which exhibit decreased or inhibited expression in the case of carcinogenesis. Therefore, the replacement of these molecules leads to post-transcriptional regulation of tens to hundreds of oncogenic targets and limiting the tumor. Interestingly, there is a group of tumor silencer miRNAs that have been highlighted in HCC and herein, our review will discuss the prominent examples of these miRs in terms of their efficient delivery using vectors, nano-delivery systems, their successful models either in vitro or in vivo and pre-clinical trials. Collectively, tumor suppressor miRNAs can act as novel therapeutics for HCC and more studies should be directed towards these promising therapeutics.

Detecting Co-Regulatory Modules from Human Regulatory Network by Randomly Walking Between Regulator and Gene Modules

2017 ◽  
Vol 14 (1) ◽  
pp. 384-388
Author(s):  
Jiawei Luo ◽  
Dan Song ◽  
Cheng Liang ◽  
Guanghui Li ◽  
Buwen Cao
Keyword(s):  
Transcriptional Regulation ◽  
Regulatory Network ◽  
Gene Interaction ◽  
Heterogeneous Data ◽  
Transcriptional Factors ◽  
Coordinate Regulation ◽  
Regulatory Modules ◽  
Gene Modules ◽  
Living Organisms ◽  
Post Transcriptional Regulation

Gene expression is jointly regulated by microRNAs and transcriptional factors. As such, constructing a regulatory network for microRNAs and transcriptional factors and analyzing their combinatorial effects are vital to understand living organisms. Co-regulatory modules, including functional homogeneous microRNAs, transcriptional factors, and genes, provide insights into coordinate regulation. In this paper, we propose a random walk with restart between regulator and gene modules (RWRRGM) method to detect co-regulatory modules from a human regulatory network. The network integrates large, heterogeneous data, including transcriptional regulation, post-transcriptional regulation, and gene-gene interaction. RWRRGM first identifies regulator and gene modules by greedily expanding seed nodes and then walks on the identified modules randomly. Finally, functional homogeneous regulator and gene modules are integrated to form co-regulatory modules. RWRRGM-based modules exhibit higher enrichment in gene ontology terms and known pathways than modules predicted by other methods.

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