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Characterizing the tumor RBP-ncRNA circuits by integrating transcriptomics, interactomics and clinical data
The interactions among non-coding RNA (ncRNA) and RNA binding protein (RBP) are increasingly recognized as one of basic mechanisms in gene regulation, and play a crucial role in cancer progressions. However, the current understanding of this regulation network, especially its dynamic spectrum accord...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479238/ https://www.ncbi.nlm.nih.gov/pubmed/34630941 http://dx.doi.org/10.1016/j.csbj.2021.09.019 |
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author | Jiang, Leiming Chen, Qiuyang Bei, Mingrong Shao, Mengting Xu, Jianzhen |
author_facet | Jiang, Leiming Chen, Qiuyang Bei, Mingrong Shao, Mengting Xu, Jianzhen |
author_sort | Jiang, Leiming |
collection | PubMed |
description | The interactions among non-coding RNA (ncRNA) and RNA binding protein (RBP) are increasingly recognized as one of basic mechanisms in gene regulation, and play a crucial role in cancer progressions. However, the current understanding of this regulation network, especially its dynamic spectrum according to the differentially expressed nodes (i.e. ncRNAs and RBP) is limited. Utilizing transcriptomics and interactomics resources, dysregulated RBP-ncRNA circuits (RNCs) are systematically dissected across 14 tumor types. We found these aberrant RNCs are robust and enriched with cancer-associated ncRNAs, RBPs and drug targets. Notably, the nodes in altered RNCs can jointly predict the clinical outcome while the individual node can’t, underscoring RNCs can serve as prognostic biomarkers. We identified 30 pan-cancer RNCs dysregulated at least in six tumor types. Pan-cancer RNC analysis can reveal novel mechanism of action (MOA) and repurpose for existing drugs. Importantly, our experiments elucidated the novel role of hsa-miR-224-5p, a member of the pan-cancer RNC hsa-miR-224-5p_MAGI2-AS3_MBNL2, in EMT program. Our analysis highlights the potential utilities of RNCs in elucidating ncRNA function in cancer, associating with clinical outcomes and discovering novel drug targets or MOA. |
format | Online Article Text |
id | pubmed-8479238 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-84792382021-10-07 Characterizing the tumor RBP-ncRNA circuits by integrating transcriptomics, interactomics and clinical data Jiang, Leiming Chen, Qiuyang Bei, Mingrong Shao, Mengting Xu, Jianzhen Comput Struct Biotechnol J Research Article The interactions among non-coding RNA (ncRNA) and RNA binding protein (RBP) are increasingly recognized as one of basic mechanisms in gene regulation, and play a crucial role in cancer progressions. However, the current understanding of this regulation network, especially its dynamic spectrum according to the differentially expressed nodes (i.e. ncRNAs and RBP) is limited. Utilizing transcriptomics and interactomics resources, dysregulated RBP-ncRNA circuits (RNCs) are systematically dissected across 14 tumor types. We found these aberrant RNCs are robust and enriched with cancer-associated ncRNAs, RBPs and drug targets. Notably, the nodes in altered RNCs can jointly predict the clinical outcome while the individual node can’t, underscoring RNCs can serve as prognostic biomarkers. We identified 30 pan-cancer RNCs dysregulated at least in six tumor types. Pan-cancer RNC analysis can reveal novel mechanism of action (MOA) and repurpose for existing drugs. Importantly, our experiments elucidated the novel role of hsa-miR-224-5p, a member of the pan-cancer RNC hsa-miR-224-5p_MAGI2-AS3_MBNL2, in EMT program. Our analysis highlights the potential utilities of RNCs in elucidating ncRNA function in cancer, associating with clinical outcomes and discovering novel drug targets or MOA. Research Network of Computational and Structural Biotechnology 2021-09-17 /pmc/articles/PMC8479238/ /pubmed/34630941 http://dx.doi.org/10.1016/j.csbj.2021.09.019 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Jiang, Leiming Chen, Qiuyang Bei, Mingrong Shao, Mengting Xu, Jianzhen Characterizing the tumor RBP-ncRNA circuits by integrating transcriptomics, interactomics and clinical data |
title | Characterizing the tumor RBP-ncRNA circuits by integrating transcriptomics, interactomics and clinical data |
title_full | Characterizing the tumor RBP-ncRNA circuits by integrating transcriptomics, interactomics and clinical data |
title_fullStr | Characterizing the tumor RBP-ncRNA circuits by integrating transcriptomics, interactomics and clinical data |
title_full_unstemmed | Characterizing the tumor RBP-ncRNA circuits by integrating transcriptomics, interactomics and clinical data |
title_short | Characterizing the tumor RBP-ncRNA circuits by integrating transcriptomics, interactomics and clinical data |
title_sort | characterizing the tumor rbp-ncrna circuits by integrating transcriptomics, interactomics and clinical data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479238/ https://www.ncbi.nlm.nih.gov/pubmed/34630941 http://dx.doi.org/10.1016/j.csbj.2021.09.019 |
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