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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.
Affiliation
  • Zhu W; State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
  • Huang H; State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
  • Ming W; State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
  • Zhang R; State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
  • Gu Y; State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
  • Bai Y; State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
  • Liu X; Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Liu H; State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
  • Liu Y; Department of Information, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Gu W; State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
  • Sun X; Collaborative Innovation Center of Jiangsu Province of Cancer Prevention and Treatment of Chinese Medicine, School of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, Nanjing, China.
Comput Struct Biotechnol J ; 21: 4432-4445, 2023.
Article in En | MEDLINE | ID: mdl-37731598
ABSTRACT
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Comput Struct Biotechnol J Year: 2023 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Comput Struct Biotechnol J Year: 2023 Document type: Article