Calcific aortic valve disease (CAVD) is becoming an increasingly important global medical problem, but effective pharmacological treatments are lacking. Noncoding RNAs play a pivotal role in the progression of cardiovascular diseases, but their relationship with CAVD remains unclear. Sequencing data revealed differential expression of many noncoding RNAs in normal and calcified aortic valves, with significant differences in circHIPK3 and miR-182-5p expression. Overexpression of circHIPK3 ameliorated aortic valve lesions in a CAVD mouse model. In vitro experiments demonstrated that circHIPK3 inhibits the osteogenic response of aortic valve interstitial cells. Mechanistically, DEAD-box helicase 5 (DDX5) recruits methyltransferase 3 (METTL3) to promote the N6-methyladenosine (m6A) modification of circHIPK3. Furthermore, m6A-modified circHIPK3 increases the stability of Kremen1 (Krm1) mRNA, and Krm1 is a negative regulator of the Wnt/β-catenin pathway. Additionally, miR-182-5p suppresses the expression of Dickkopf2 (Dkk2), the ligand of Krm1, and attenuates the Krm1-mediated inhibition of Wnt signaling. Activation of the Wnt signaling pathway significantly contributes to the promotion of aortic valve calcification. Our study describes the role of the Krm1-Dkk2 axis in inhibiting Wnt signaling in aortic valves and suggests that noncoding RNAs are upstream regulators of this process. Calcific aortic valve disease (CAVD, a common heart condition) currently has no effective treatments. This research aimed to examine the role of non-coding RNAs (molecules that control gene activity) in CAVD, particularly circHIPK3 and miR-182-5p. Experiments were conducted on human heart valve cells and mice, showing that circHIPK3 can prevent heart valve hardening, while miR-182-5p can trigger a process that encourages hardening. The research also discovered a protein, Krm1, that can stop this hardening process. These results suggest that focusing on these non-coding RNAs and proteins could offer a new way to treat CAVD. However, more research is needed to fully comprehend these processes and their potential treatment implications. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.
{"title":"Noncoding RNA regulates the expression of Krm1 and Dkk2 to synergistically affect aortic valve lesions","authors":"Gaopeng Xian, Rong Huang, Minhui Xu, Hengli Zhao, Xingbo Xu, Yangchao Chen, Hao Ren, Dingli Xu, Qingchun Zeng","doi":"10.1038/s12276-024-01256-5","DOIUrl":"10.1038/s12276-024-01256-5","url":null,"abstract":"Calcific aortic valve disease (CAVD) is becoming an increasingly important global medical problem, but effective pharmacological treatments are lacking. Noncoding RNAs play a pivotal role in the progression of cardiovascular diseases, but their relationship with CAVD remains unclear. Sequencing data revealed differential expression of many noncoding RNAs in normal and calcified aortic valves, with significant differences in circHIPK3 and miR-182-5p expression. Overexpression of circHIPK3 ameliorated aortic valve lesions in a CAVD mouse model. In vitro experiments demonstrated that circHIPK3 inhibits the osteogenic response of aortic valve interstitial cells. Mechanistically, DEAD-box helicase 5 (DDX5) recruits methyltransferase 3 (METTL3) to promote the N6-methyladenosine (m6A) modification of circHIPK3. Furthermore, m6A-modified circHIPK3 increases the stability of Kremen1 (Krm1) mRNA, and Krm1 is a negative regulator of the Wnt/β-catenin pathway. Additionally, miR-182-5p suppresses the expression of Dickkopf2 (Dkk2), the ligand of Krm1, and attenuates the Krm1-mediated inhibition of Wnt signaling. Activation of the Wnt signaling pathway significantly contributes to the promotion of aortic valve calcification. Our study describes the role of the Krm1-Dkk2 axis in inhibiting Wnt signaling in aortic valves and suggests that noncoding RNAs are upstream regulators of this process. Calcific aortic valve disease (CAVD, a common heart condition) currently has no effective treatments. This research aimed to examine the role of non-coding RNAs (molecules that control gene activity) in CAVD, particularly circHIPK3 and miR-182-5p. Experiments were conducted on human heart valve cells and mice, showing that circHIPK3 can prevent heart valve hardening, while miR-182-5p can trigger a process that encourages hardening. The research also discovered a protein, Krm1, that can stop this hardening process. These results suggest that focusing on these non-coding RNAs and proteins could offer a new way to treat CAVD. However, more research is needed to fully comprehend these processes and their potential treatment implications. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.","PeriodicalId":50466,"journal":{"name":"Experimental and Molecular Medicine","volume":null,"pages":null},"PeriodicalIF":9.5,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11297286/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141472202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.1038/s12276-024-01220-3
Hyun Jung Hwang, Yoon Ki Kim
Circular RNAs (circRNAs) are covalently closed single-stranded RNAs without a 5′ cap structure and a 3′ poly(A) tail typically present in linear mRNAs of eukaryotic cells. CircRNAs are predominantly generated through a back-splicing process within the nucleus. CircRNAs have long been considered non-coding RNAs seemingly devoid of protein-coding potential. However, many recent studies have challenged this idea and have provided substantial evidence that a subset of circRNAs can associate with polysomes and indeed be translated. Therefore, in this review, we primarily highlight the 5’ cap-independent internal initiation of translation that occurs on circular RNAs. Several molecular features of circRNAs, including the internal ribosome entry site, N6-methyladenosine modification, and the exon junction complex deposited around the back-splicing junction after back-splicing event, play pivotal roles in their efficient internal translation. We also propose a possible relationship between the translatability of circRNAs and their stability, with a focus on nonsense-mediated mRNA decay and nonstop decay, both of which are well-characterized mRNA surveillance mechanisms. An in-depth understanding of circRNA translation will reshape and expand our current knowledge of proteomics. This research delves into the intricate realm of circular RNAs (circRNAs), a kind of RNA molecule that forms a covalently closed circular structure, making it more stable than its linear counterparts. Despite being plentiful in cells, the role of circRNAs is largely a mystery. The researchers provide a summary of the various ways circRNAs are created and outline the different functions they can have. They also explore the molecular specifics of how circRNAs are translated and consider the potential interaction between this translation and their stability. The research is a review, summarizing and analyzing existing studies on the subject and highlighting the role and potential impact of circRNAs in the regulation of gene expression. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.
{"title":"Molecular mechanisms of circular RNA translation","authors":"Hyun Jung Hwang, Yoon Ki Kim","doi":"10.1038/s12276-024-01220-3","DOIUrl":"10.1038/s12276-024-01220-3","url":null,"abstract":"Circular RNAs (circRNAs) are covalently closed single-stranded RNAs without a 5′ cap structure and a 3′ poly(A) tail typically present in linear mRNAs of eukaryotic cells. CircRNAs are predominantly generated through a back-splicing process within the nucleus. CircRNAs have long been considered non-coding RNAs seemingly devoid of protein-coding potential. However, many recent studies have challenged this idea and have provided substantial evidence that a subset of circRNAs can associate with polysomes and indeed be translated. Therefore, in this review, we primarily highlight the 5’ cap-independent internal initiation of translation that occurs on circular RNAs. Several molecular features of circRNAs, including the internal ribosome entry site, N6-methyladenosine modification, and the exon junction complex deposited around the back-splicing junction after back-splicing event, play pivotal roles in their efficient internal translation. We also propose a possible relationship between the translatability of circRNAs and their stability, with a focus on nonsense-mediated mRNA decay and nonstop decay, both of which are well-characterized mRNA surveillance mechanisms. An in-depth understanding of circRNA translation will reshape and expand our current knowledge of proteomics. This research delves into the intricate realm of circular RNAs (circRNAs), a kind of RNA molecule that forms a covalently closed circular structure, making it more stable than its linear counterparts. Despite being plentiful in cells, the role of circRNAs is largely a mystery. The researchers provide a summary of the various ways circRNAs are created and outline the different functions they can have. They also explore the molecular specifics of how circRNAs are translated and consider the potential interaction between this translation and their stability. The research is a review, summarizing and analyzing existing studies on the subject and highlighting the role and potential impact of circRNAs in the regulation of gene expression. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.","PeriodicalId":50466,"journal":{"name":"Experimental and Molecular Medicine","volume":null,"pages":null},"PeriodicalIF":9.5,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11263353/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141318884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.1038/s12276-024-01267-2
TaeSoo Kim, Tae-Kyung Kim
{"title":"Regulatory RNA: from molecular insights to therapeutic frontiers","authors":"TaeSoo Kim, Tae-Kyung Kim","doi":"10.1038/s12276-024-01267-2","DOIUrl":"10.1038/s12276-024-01267-2","url":null,"abstract":"","PeriodicalId":50466,"journal":{"name":"Experimental and Molecular Medicine","volume":null,"pages":null},"PeriodicalIF":9.5,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11263535/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141318886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.1038/s12276-024-01177-3
Keonyong Lee, Jayoung Ku, Doyeong Ku, Yoosik Kim
Alu elements are highly abundant primate-specific short interspersed nuclear elements that account for ~10% of the human genome. Due to their preferential location in gene-rich regions, especially in introns and 3′ UTRs, Alu elements can exert regulatory effects on the expression of both host and neighboring genes. When two Alu elements with inverse orientations are positioned in close proximity, their transcription results in the generation of distinct double-stranded RNAs (dsRNAs), known as inverted Alu repeats (IRAlus). IRAlus are key immunogenic self-dsRNAs and post-transcriptional cis-regulatory elements that play a role in circular RNA biogenesis, as well as RNA transport and stability. Recently, IRAlus dsRNAs have emerged as regulators of transcription and activators of Z-DNA-binding proteins. The formation and activity of IRAlus can be modulated through RNA editing and interactions with RNA-binding proteins, and misregulation of IRAlus has been implicated in several immune-associated disorders. In this review, we summarize the emerging functions of IRAlus dsRNAs, the regulatory mechanisms governing IRAlus activity, and their relevance in the pathogenesis of human diseases. Understanding the role of Alu elements—short DNA sequences scattered throughout our genome—is crucial for grasping human genetics. These elements can affect how our genes function, and sometimes, their misregulation causes diseases. However, there’s still much we don’t know about their impact on gene regulation and cell signaling, including innate immune responses. Lee et al. summarized how Alu elements interact with our immune system by generating specific structures similar to ones from viruses. The authors suggest that further understanding of biological processes regulated by Alu elements could lead to advancements in the development of potential treatment for diseases linked to immune system dysfunction. Future research could explore how to manipulate these elements to benefit human health. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.
{"title":"Inverted Alu repeats: friends or foes in the human transcriptome","authors":"Keonyong Lee, Jayoung Ku, Doyeong Ku, Yoosik Kim","doi":"10.1038/s12276-024-01177-3","DOIUrl":"10.1038/s12276-024-01177-3","url":null,"abstract":"Alu elements are highly abundant primate-specific short interspersed nuclear elements that account for ~10% of the human genome. Due to their preferential location in gene-rich regions, especially in introns and 3′ UTRs, Alu elements can exert regulatory effects on the expression of both host and neighboring genes. When two Alu elements with inverse orientations are positioned in close proximity, their transcription results in the generation of distinct double-stranded RNAs (dsRNAs), known as inverted Alu repeats (IRAlus). IRAlus are key immunogenic self-dsRNAs and post-transcriptional cis-regulatory elements that play a role in circular RNA biogenesis, as well as RNA transport and stability. Recently, IRAlus dsRNAs have emerged as regulators of transcription and activators of Z-DNA-binding proteins. The formation and activity of IRAlus can be modulated through RNA editing and interactions with RNA-binding proteins, and misregulation of IRAlus has been implicated in several immune-associated disorders. In this review, we summarize the emerging functions of IRAlus dsRNAs, the regulatory mechanisms governing IRAlus activity, and their relevance in the pathogenesis of human diseases. Understanding the role of Alu elements—short DNA sequences scattered throughout our genome—is crucial for grasping human genetics. These elements can affect how our genes function, and sometimes, their misregulation causes diseases. However, there’s still much we don’t know about their impact on gene regulation and cell signaling, including innate immune responses. Lee et al. summarized how Alu elements interact with our immune system by generating specific structures similar to ones from viruses. The authors suggest that further understanding of biological processes regulated by Alu elements could lead to advancements in the development of potential treatment for diseases linked to immune system dysfunction. Future research could explore how to manipulate these elements to benefit human health. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.","PeriodicalId":50466,"journal":{"name":"Experimental and Molecular Medicine","volume":null,"pages":null},"PeriodicalIF":9.5,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11263572/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141318882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.1038/s12276-024-01266-3
Xin Le Yap, Jun-An Chen
MicroRNAs (miRNAs) are pivotal regulators of gene expression and are involved in biological processes spanning from early developmental stages to the intricate process of aging. Extensive research has underscored the fundamental role of miRNAs in orchestrating eukaryotic development, with disruptions in miRNA biogenesis resulting in early lethality. Moreover, perturbations in miRNA function have been implicated in the aging process, particularly in model organisms such as nematodes and flies. miRNAs tend to be clustered in vertebrate genomes, finely modulating an array of biological pathways through clustering within a single transcript. Although extensive research of their developmental roles has been conducted, the potential implications of miRNA clusters in regulating aging remain largely unclear. In this review, we use the Mir-23-27-24 cluster as a paradigm, shedding light on the nuanced physiological functions of miRNA clusters during embryonic development and exploring their potential involvement in the aging process. Moreover, we advocate further research into the intricate interplay among miRNA clusters, particularly the Mir-23-27-24 cluster, in shaping the regulatory landscape of aging. MicroRNAs significantly influence everything from growth to aging. However, the specific roles of certain miRNA clusters, like Mir-23-27-24, in aging are less understood. This review investigates the Mir-23-27-24 cluster’s function in embryonic growth and possible aging regulation. It’s a comprehensive review of how the Mir-23-27-24 cluster affects vital biological processes and aging, combining existing research to fill knowledge gaps. The Mir-23-27-24 cluster includes miRNAs vital in development stages and linked to various diseases, including cancer. Researchers underline the cluster’s role in embryonic development and its overlooked role in aging. They explore how these miRNAs control gene expression and contribute to the complexity of biological functions. This study implies that miRNA clusters like Mir-23-27-24 could be crucial in aging, opening new paths for aging research and potential treatments for age-related diseases. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.
{"title":"Elucidation of how the Mir-23-27-24 cluster regulates development and aging","authors":"Xin Le Yap, Jun-An Chen","doi":"10.1038/s12276-024-01266-3","DOIUrl":"10.1038/s12276-024-01266-3","url":null,"abstract":"MicroRNAs (miRNAs) are pivotal regulators of gene expression and are involved in biological processes spanning from early developmental stages to the intricate process of aging. Extensive research has underscored the fundamental role of miRNAs in orchestrating eukaryotic development, with disruptions in miRNA biogenesis resulting in early lethality. Moreover, perturbations in miRNA function have been implicated in the aging process, particularly in model organisms such as nematodes and flies. miRNAs tend to be clustered in vertebrate genomes, finely modulating an array of biological pathways through clustering within a single transcript. Although extensive research of their developmental roles has been conducted, the potential implications of miRNA clusters in regulating aging remain largely unclear. In this review, we use the Mir-23-27-24 cluster as a paradigm, shedding light on the nuanced physiological functions of miRNA clusters during embryonic development and exploring their potential involvement in the aging process. Moreover, we advocate further research into the intricate interplay among miRNA clusters, particularly the Mir-23-27-24 cluster, in shaping the regulatory landscape of aging. MicroRNAs significantly influence everything from growth to aging. However, the specific roles of certain miRNA clusters, like Mir-23-27-24, in aging are less understood. This review investigates the Mir-23-27-24 cluster’s function in embryonic growth and possible aging regulation. It’s a comprehensive review of how the Mir-23-27-24 cluster affects vital biological processes and aging, combining existing research to fill knowledge gaps. The Mir-23-27-24 cluster includes miRNAs vital in development stages and linked to various diseases, including cancer. Researchers underline the cluster’s role in embryonic development and its overlooked role in aging. They explore how these miRNAs control gene expression and contribute to the complexity of biological functions. This study implies that miRNA clusters like Mir-23-27-24 could be crucial in aging, opening new paths for aging research and potential treatments for age-related diseases. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.","PeriodicalId":50466,"journal":{"name":"Experimental and Molecular Medicine","volume":null,"pages":null},"PeriodicalIF":9.5,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11263685/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141318881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.1038/s12276-024-01239-6
Sumin Yang, Sung-Hyun Kim, Eunjeong Yang, Mingon Kang, Jae-Yeol Joo
It is apparent that various functional units within the cellular machinery are derived from RNAs. The evolution of sequencing techniques has resulted in significant insights into approaches for transcriptome studies. Organisms utilize RNA to govern cellular systems, and a heterogeneous class of RNAs is involved in regulatory functions. In particular, regulatory RNAs are increasingly recognized to participate in intricately functioning machinery across almost all levels of biological systems. These systems include those mediating chromatin arrangement, transcription, suborganelle stabilization, and posttranscriptional modifications. Any class of RNA exhibiting regulatory activity can be termed a class of regulatory RNA and is typically represented by noncoding RNAs, which constitute a substantial portion of the genome. These RNAs function based on the principle of structural changes through cis and/or trans regulation to facilitate mutual RNA‒RNA, RNA‒DNA, and RNA‒protein interactions. It has not been clearly elucidated whether regulatory RNAs identified through deep sequencing actually function in the anticipated mechanisms. This review addresses the dominant properties of regulatory RNAs at various layers of the cellular machinery and covers regulatory activities, structural dynamics, modifications, associated molecules, and further challenges related to therapeutics and deep learning. Regulatory RNAs, such as long noncoding RNAs (lncRNAs, RNAs that do not code for proteins), microRNAs (miRNAs, small RNAs that regulate gene expression), and circular RNAs (circRNAs, RNAs that form a covalently closed continuous loop), are important in controlling gene expression. The exact ways and roles of these RNAs are not completely known. This study by Joo et al. reviews current knowledge on regulatory RNAs, focusing on their structure and function in cell parts. The authors talk about the different methods used to study these RNAs, including RNA-Chromatin, RNA-Protein, and RNA structure sequencing. They also emphasize the role of RNA modifications in controlling gene expression and the potential of deep learning (a type of machine learning) in predicting RNA functions. The study concludes that understanding regulatory RNAs better could lead to new treatment strategies for various diseases. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.
{"title":"Molecular insights into regulatory RNAs in the cellular machinery","authors":"Sumin Yang, Sung-Hyun Kim, Eunjeong Yang, Mingon Kang, Jae-Yeol Joo","doi":"10.1038/s12276-024-01239-6","DOIUrl":"10.1038/s12276-024-01239-6","url":null,"abstract":"It is apparent that various functional units within the cellular machinery are derived from RNAs. The evolution of sequencing techniques has resulted in significant insights into approaches for transcriptome studies. Organisms utilize RNA to govern cellular systems, and a heterogeneous class of RNAs is involved in regulatory functions. In particular, regulatory RNAs are increasingly recognized to participate in intricately functioning machinery across almost all levels of biological systems. These systems include those mediating chromatin arrangement, transcription, suborganelle stabilization, and posttranscriptional modifications. Any class of RNA exhibiting regulatory activity can be termed a class of regulatory RNA and is typically represented by noncoding RNAs, which constitute a substantial portion of the genome. These RNAs function based on the principle of structural changes through cis and/or trans regulation to facilitate mutual RNA‒RNA, RNA‒DNA, and RNA‒protein interactions. It has not been clearly elucidated whether regulatory RNAs identified through deep sequencing actually function in the anticipated mechanisms. This review addresses the dominant properties of regulatory RNAs at various layers of the cellular machinery and covers regulatory activities, structural dynamics, modifications, associated molecules, and further challenges related to therapeutics and deep learning. Regulatory RNAs, such as long noncoding RNAs (lncRNAs, RNAs that do not code for proteins), microRNAs (miRNAs, small RNAs that regulate gene expression), and circular RNAs (circRNAs, RNAs that form a covalently closed continuous loop), are important in controlling gene expression. The exact ways and roles of these RNAs are not completely known. This study by Joo et al. reviews current knowledge on regulatory RNAs, focusing on their structure and function in cell parts. The authors talk about the different methods used to study these RNAs, including RNA-Chromatin, RNA-Protein, and RNA structure sequencing. They also emphasize the role of RNA modifications in controlling gene expression and the potential of deep learning (a type of machine learning) in predicting RNA functions. The study concludes that understanding regulatory RNAs better could lead to new treatment strategies for various diseases. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.","PeriodicalId":50466,"journal":{"name":"Experimental and Molecular Medicine","volume":null,"pages":null},"PeriodicalIF":9.5,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11263585/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141318883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.1038/s12276-024-01251-w
Seo-Won Choi, Jin-Wu Nam
Circular RNAs are an unusual class of single-stranded RNAs whose ends are covalently linked via back-splicing. Due to their versatility, the need to express circular RNAs in vivo and in vitro has increased. Efforts have been made to efficiently and precisely synthesize circular RNAs. However, a review on the optimization of the processes of circular RNA design, synthesis, and delivery is lacking. Our review highlights the multifaceted aspects considered when producing optimal circular RNAs and summarizes the available options for each step of exogenous circular RNA design and synthesis, including circularization strategies. Additionally, this review describes several potential applications of circular RNAs. Circular RNAs were once considered errors in splicing. However, we now understand that circRNAs are common and play roles in health and disease, including potential use in creating vaccines. This review examines ways to create and use circRNAs, with a focus on improving their creation and delivery for medical purposes. They discuss various methods, including using natural and synthetic elements to enhance circRNA formation and stability. The main findings suggest that improving the creation and delivery of circRNAs could greatly enhance their medical potential. Researchers conclude that with more development, circRNAs could become powerful tools in gene therapy and vaccine creation, offering new ways to treat diseases. The future implications of this research could transform how we approach disease treatment and vaccine creation, making therapies more effective and long-lasting. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.
{"title":"Optimal design of synthetic circular RNAs","authors":"Seo-Won Choi, Jin-Wu Nam","doi":"10.1038/s12276-024-01251-w","DOIUrl":"10.1038/s12276-024-01251-w","url":null,"abstract":"Circular RNAs are an unusual class of single-stranded RNAs whose ends are covalently linked via back-splicing. Due to their versatility, the need to express circular RNAs in vivo and in vitro has increased. Efforts have been made to efficiently and precisely synthesize circular RNAs. However, a review on the optimization of the processes of circular RNA design, synthesis, and delivery is lacking. Our review highlights the multifaceted aspects considered when producing optimal circular RNAs and summarizes the available options for each step of exogenous circular RNA design and synthesis, including circularization strategies. Additionally, this review describes several potential applications of circular RNAs. Circular RNAs were once considered errors in splicing. However, we now understand that circRNAs are common and play roles in health and disease, including potential use in creating vaccines. This review examines ways to create and use circRNAs, with a focus on improving their creation and delivery for medical purposes. They discuss various methods, including using natural and synthetic elements to enhance circRNA formation and stability. The main findings suggest that improving the creation and delivery of circRNAs could greatly enhance their medical potential. Researchers conclude that with more development, circRNAs could become powerful tools in gene therapy and vaccine creation, offering new ways to treat diseases. The future implications of this research could transform how we approach disease treatment and vaccine creation, making therapies more effective and long-lasting. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.","PeriodicalId":50466,"journal":{"name":"Experimental and Molecular Medicine","volume":null,"pages":null},"PeriodicalIF":9.5,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11263348/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141318885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL studies in other fields, the successful implementation of DL in RB depends heavily on the effective utilization of large-scale datasets from public databases. In achieving this goal, data encoding methods, learning algorithms, and techniques that align well with biological domain knowledge have played pivotal roles. In this review, we provide guiding principles for applying these DL concepts to various problems in RB by demonstrating successful examples and associated methodologies. We also discuss the remaining challenges in developing DL models for RB and suggest strategies to overcome these challenges. Overall, this review aims to illuminate the compelling potential of DL for RB and ways to apply this powerful technology to investigate the intriguing biology of RNA more effectively. This review spotlights the revolutionary role of deep learning (DL) in expanding the understanding of RNA. RNA is a fundamental biomolecule that shapes and regulates diverse phenotypes including human diseases. Understanding the principles governing the functions of RNA is a key objective of current biology. Recently, big data produced via high-throughput experiments have been utilized to develop DL models aimed at analyzing and predicting RNA-related biological processes. This review emphasizes the role of public databases in providing these big data for training DL models. The authors introduce core DL concepts necessary for training models from the biological data. By extensively examining DL studies in various fields of RNA biology, the authors suggest how to better leverage DL for revealing novel biological knowledge and demonstrate the potential of DL in deciphering the complex biology of RNA. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.
{"title":"Big data and deep learning for RNA biology","authors":"Hyeonseo Hwang, Hyeonseong Jeon, Nagyeong Yeo, Daehyun Baek","doi":"10.1038/s12276-024-01243-w","DOIUrl":"10.1038/s12276-024-01243-w","url":null,"abstract":"The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL studies in other fields, the successful implementation of DL in RB depends heavily on the effective utilization of large-scale datasets from public databases. In achieving this goal, data encoding methods, learning algorithms, and techniques that align well with biological domain knowledge have played pivotal roles. In this review, we provide guiding principles for applying these DL concepts to various problems in RB by demonstrating successful examples and associated methodologies. We also discuss the remaining challenges in developing DL models for RB and suggest strategies to overcome these challenges. Overall, this review aims to illuminate the compelling potential of DL for RB and ways to apply this powerful technology to investigate the intriguing biology of RNA more effectively. This review spotlights the revolutionary role of deep learning (DL) in expanding the understanding of RNA. RNA is a fundamental biomolecule that shapes and regulates diverse phenotypes including human diseases. Understanding the principles governing the functions of RNA is a key objective of current biology. Recently, big data produced via high-throughput experiments have been utilized to develop DL models aimed at analyzing and predicting RNA-related biological processes. This review emphasizes the role of public databases in providing these big data for training DL models. The authors introduce core DL concepts necessary for training models from the biological data. By extensively examining DL studies in various fields of RNA biology, the authors suggest how to better leverage DL for revealing novel biological knowledge and demonstrate the potential of DL in deciphering the complex biology of RNA. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.","PeriodicalId":50466,"journal":{"name":"Experimental and Molecular Medicine","volume":null,"pages":null},"PeriodicalIF":9.5,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11263376/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141318827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12DOI: 10.1038/s12276-024-01259-2
Sang Hoon Kim, Bo Ryeong Lee, Sung-Min Kim, Sungsik Kim, Min-seok Kim, Jaehyun Kim, Inkyu Lee, Hee-Soo Kim, Gi-Hoon Nam, In-San Kim, Kyuyoung Song, Yoonjoo Choi, Dong-Sup Lee, Woong-Yang Park
Neoantigens are ideal targets for cancer immunotherapy because they are expressed de novo in tumor tissue but not in healthy tissue and are therefore recognized as foreign by the immune system. Advances in next-generation sequencing and bioinformatics technologies have enabled the quick identification and prediction of tumor-specific neoantigens; however, only a small fraction of predicted neoantigens are immunogenic. To improve the predictability of immunogenic neoantigens, we developed the in silico neoantigen prediction workflows VACINUSpMHC and VACINUSTCR: VACINUSpMHC incorporates physical binding between peptides and MHCs (pMHCs), and VACINUSTCR integrates T cell reactivity to the pMHC complex through deep learning-based pairing with T cell receptors (TCRs) of putative tumor-reactive CD8 tumor-infiltrating lymphocytes (TILs). We then validated our neoantigen prediction workflows both in vitro and in vivo in patients with hepatocellular carcinoma (HCC) and in a B16F10 mouse melanoma model. The predictive abilities of VACINUSpMHC and VACINUSTCR were confirmed in a validation cohort of 8 patients with HCC. Of a total of 118 neoantigen candidates predicted by VACINUSpMHC, 48 peptides were ultimately selected using VACINUSTCR. In vitro validation revealed that among the 48 predicted neoantigen candidates, 13 peptides were immunogenic. Assessment of the antitumor efficacy of the candidate neoepitopes using a VACINUSTCR in vivo mouse model suggested that vaccination with the predicted neoepitopes induced neoantigen-specific T cell responses and enabled the trafficking of neoantigen-specific CD8 + T cell clones into the tumor tissue, leading to tumor suppression. This study showed that the prediction of immunogenic neoantigens can be improved by integrating a tumor-reactive TIL TCR-pMHC ternary complex. Cancer scientists have created a new way to identify and choose neoantigens (new proteins on cancer cells) for use in cancer vaccines. The research, led by Woong-Yang Park, included 33 patients with different cancer types. The scientists used a mix of computer-based prediction techniques and lab-based tests to find the most effective neoantigens. The results showed that the new technique, named VACINUS, was better at predicting effective neoantigens than older methods. The scientists concluded that the VACINUS technique could improve the immune response of predicted neoantigens, making them better at activating an immune reaction against cancer cells. This could result in the creation of more effective cancer vaccines in the future. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.
{"title":"The identification of effective tumor-suppressing neoantigens using a tumor-reactive TIL TCR-pMHC ternary complex","authors":"Sang Hoon Kim, Bo Ryeong Lee, Sung-Min Kim, Sungsik Kim, Min-seok Kim, Jaehyun Kim, Inkyu Lee, Hee-Soo Kim, Gi-Hoon Nam, In-San Kim, Kyuyoung Song, Yoonjoo Choi, Dong-Sup Lee, Woong-Yang Park","doi":"10.1038/s12276-024-01259-2","DOIUrl":"10.1038/s12276-024-01259-2","url":null,"abstract":"Neoantigens are ideal targets for cancer immunotherapy because they are expressed de novo in tumor tissue but not in healthy tissue and are therefore recognized as foreign by the immune system. Advances in next-generation sequencing and bioinformatics technologies have enabled the quick identification and prediction of tumor-specific neoantigens; however, only a small fraction of predicted neoantigens are immunogenic. To improve the predictability of immunogenic neoantigens, we developed the in silico neoantigen prediction workflows VACINUSpMHC and VACINUSTCR: VACINUSpMHC incorporates physical binding between peptides and MHCs (pMHCs), and VACINUSTCR integrates T cell reactivity to the pMHC complex through deep learning-based pairing with T cell receptors (TCRs) of putative tumor-reactive CD8 tumor-infiltrating lymphocytes (TILs). We then validated our neoantigen prediction workflows both in vitro and in vivo in patients with hepatocellular carcinoma (HCC) and in a B16F10 mouse melanoma model. The predictive abilities of VACINUSpMHC and VACINUSTCR were confirmed in a validation cohort of 8 patients with HCC. Of a total of 118 neoantigen candidates predicted by VACINUSpMHC, 48 peptides were ultimately selected using VACINUSTCR. In vitro validation revealed that among the 48 predicted neoantigen candidates, 13 peptides were immunogenic. Assessment of the antitumor efficacy of the candidate neoepitopes using a VACINUSTCR in vivo mouse model suggested that vaccination with the predicted neoepitopes induced neoantigen-specific T cell responses and enabled the trafficking of neoantigen-specific CD8 + T cell clones into the tumor tissue, leading to tumor suppression. This study showed that the prediction of immunogenic neoantigens can be improved by integrating a tumor-reactive TIL TCR-pMHC ternary complex. Cancer scientists have created a new way to identify and choose neoantigens (new proteins on cancer cells) for use in cancer vaccines. The research, led by Woong-Yang Park, included 33 patients with different cancer types. The scientists used a mix of computer-based prediction techniques and lab-based tests to find the most effective neoantigens. The results showed that the new technique, named VACINUS, was better at predicting effective neoantigens than older methods. The scientists concluded that the VACINUS technique could improve the immune response of predicted neoantigens, making them better at activating an immune reaction against cancer cells. This could result in the creation of more effective cancer vaccines in the future. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.","PeriodicalId":50466,"journal":{"name":"Experimental and Molecular Medicine","volume":null,"pages":null},"PeriodicalIF":9.5,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11263684/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141312197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：