Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Jiang, Leiming, Chen, Qiuyang, Bei, Mingrong, Shao, Mengting, Xu, Jianzhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
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
_version_ 1784576210038161408
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
work_keys_str_mv AT jiangleiming characterizingthetumorrbpncrnacircuitsbyintegratingtranscriptomicsinteractomicsandclinicaldata
AT chenqiuyang characterizingthetumorrbpncrnacircuitsbyintegratingtranscriptomicsinteractomicsandclinicaldata
AT beimingrong characterizingthetumorrbpncrnacircuitsbyintegratingtranscriptomicsinteractomicsandclinicaldata
AT shaomengting characterizingthetumorrbpncrnacircuitsbyintegratingtranscriptomicsinteractomicsandclinicaldata
AT xujianzhen characterizingthetumorrbpncrnacircuitsbyintegratingtranscriptomicsinteractomicsandclinicaldata