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Delineating highly transcribed noncoding elements landscape in breast cancer

Highly transcribed noncoding elements (HTNEs) are critical noncoding elements with high levels of transcriptional capacity in particular cohorts involved in multiple cellular biological processes. Investigation of HTNEs with persistent aberrant expression in abnormal tissues could be of benefit in e...

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Autores principales: Zhu, Wenyong, Huang, Hao, Ming, Wenlong, Zhang, Rongxin, Gu, Yu, Bai, Yunfei, Liu, Xiaoan, Liu, Hongde, Liu, Yun, Gu, Wanjun, Sun, Xiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507584/
https://www.ncbi.nlm.nih.gov/pubmed/37731598
http://dx.doi.org/10.1016/j.csbj.2023.09.009
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author Zhu, Wenyong
Huang, Hao
Ming, Wenlong
Zhang, Rongxin
Gu, Yu
Bai, Yunfei
Liu, Xiaoan
Liu, Hongde
Liu, Yun
Gu, Wanjun
Sun, Xiao
author_facet Zhu, Wenyong
Huang, Hao
Ming, Wenlong
Zhang, Rongxin
Gu, Yu
Bai, Yunfei
Liu, Xiaoan
Liu, Hongde
Liu, Yun
Gu, Wanjun
Sun, Xiao
author_sort Zhu, Wenyong
collection PubMed
description Highly transcribed noncoding elements (HTNEs) are critical noncoding elements with high levels of transcriptional capacity in particular cohorts involved in multiple cellular biological processes. Investigation of HTNEs with persistent aberrant expression in abnormal tissues could be of benefit in exploring their roles in disease occurrence and progression. Breast cancer is a highly heterogeneous disease for which early screening and prognosis are exceedingly crucial. In this study, we developed a HTNE identification framework to systematically investigate HTNE landscapes in breast cancer patients and identified over ten thousand HTNEs. The robustness and rationality of our framework were demonstrated via public datasets. We revealed that HTNEs had significant chromatin characteristics of enhancers and long noncoding RNAs (lncRNAs) and were significantly enriched with RNA-binding proteins as well as targeted by miRNAs. Further, HTNE-associated genes were significantly overexpressed and exhibited strong correlations with breast cancer. Ultimately, we explored the subtype-specific transcriptional processes associated with HTNEs and uncovered the HTNE signatures that could classify breast cancer subtypes based on the properties of hormone receptors. Our results highlight that the identified HTNEs as well as their associated genes play crucial roles in breast cancer progression and correlate with subtype-specific transcriptional processes of breast cancer.
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spelling pubmed-105075842023-09-20 Delineating highly transcribed noncoding elements landscape in breast cancer Zhu, Wenyong Huang, Hao Ming, Wenlong Zhang, Rongxin Gu, Yu Bai, Yunfei Liu, Xiaoan Liu, Hongde Liu, Yun Gu, Wanjun Sun, Xiao Comput Struct Biotechnol J Research Article Highly transcribed noncoding elements (HTNEs) are critical noncoding elements with high levels of transcriptional capacity in particular cohorts involved in multiple cellular biological processes. Investigation of HTNEs with persistent aberrant expression in abnormal tissues could be of benefit in exploring their roles in disease occurrence and progression. Breast cancer is a highly heterogeneous disease for which early screening and prognosis are exceedingly crucial. In this study, we developed a HTNE identification framework to systematically investigate HTNE landscapes in breast cancer patients and identified over ten thousand HTNEs. The robustness and rationality of our framework were demonstrated via public datasets. We revealed that HTNEs had significant chromatin characteristics of enhancers and long noncoding RNAs (lncRNAs) and were significantly enriched with RNA-binding proteins as well as targeted by miRNAs. Further, HTNE-associated genes were significantly overexpressed and exhibited strong correlations with breast cancer. Ultimately, we explored the subtype-specific transcriptional processes associated with HTNEs and uncovered the HTNE signatures that could classify breast cancer subtypes based on the properties of hormone receptors. Our results highlight that the identified HTNEs as well as their associated genes play crucial roles in breast cancer progression and correlate with subtype-specific transcriptional processes of breast cancer. Research Network of Computational and Structural Biotechnology 2023-09-14 /pmc/articles/PMC10507584/ /pubmed/37731598 http://dx.doi.org/10.1016/j.csbj.2023.09.009 Text en © 2023 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
Zhu, Wenyong
Huang, Hao
Ming, Wenlong
Zhang, Rongxin
Gu, Yu
Bai, Yunfei
Liu, Xiaoan
Liu, Hongde
Liu, Yun
Gu, Wanjun
Sun, Xiao
Delineating highly transcribed noncoding elements landscape in breast cancer
title Delineating highly transcribed noncoding elements landscape in breast cancer
title_full Delineating highly transcribed noncoding elements landscape in breast cancer
title_fullStr Delineating highly transcribed noncoding elements landscape in breast cancer
title_full_unstemmed Delineating highly transcribed noncoding elements landscape in breast cancer
title_short Delineating highly transcribed noncoding elements landscape in breast cancer
title_sort delineating highly transcribed noncoding elements landscape in breast cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507584/
https://www.ncbi.nlm.nih.gov/pubmed/37731598
http://dx.doi.org/10.1016/j.csbj.2023.09.009
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