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描绘乳腺癌中高转录非编码元件图谱。

Delineating highly transcribed noncoding elements landscape in breast cancer.

作者信息

Zhu Wenyong, Huang Hao, Ming Wenlong, Zhang Rongxin, Gu Yu, Bai Yunfei, Liu Xiaoan, Liu Hongde, Liu Yun, Gu Wanjun, Sun Xiao

机构信息

State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.

Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.

出版信息

Comput Struct Biotechnol J. 2023 Sep 14;21:4432-4445. doi: 10.1016/j.csbj.2023.09.009. eCollection 2023.

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.

摘要

高转录非编码元件(HTNEs)是关键的非编码元件,在参与多种细胞生物学过程的特定群体中具有高水平的转录能力。研究在异常组织中持续异常表达的HTNEs,可能有助于探索它们在疾病发生和发展中的作用。乳腺癌是一种高度异质性疾病,早期筛查和预后极其关键。在本研究中,我们开发了一个HTNE识别框架,以系统地研究乳腺癌患者的HTNE图谱,并鉴定出一万多个HTNEs。我们通过公开数据集证明了我们框架的稳健性和合理性。我们发现HTNEs具有增强子和长链非编码RNA(lncRNAs)的显著染色质特征,并且富含RNA结合蛋白以及被miRNAs靶向。此外,HTNE相关基因显著过表达,并与乳腺癌表现出强烈相关性。最终,我们探索了与HTNEs相关的亚型特异性转录过程,并发现了能够根据激素受体特性对乳腺癌亚型进行分类的HTNE特征。我们的结果突出表明,鉴定出的HTNEs及其相关基因在乳腺癌进展中起关键作用,并与乳腺癌的亚型特异性转录过程相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d51/10507584/a09fdc9d44a7/ga1.jpg

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