| Literature DB >> 30618123 |
Jie Li1, Chundi Gao1, Cun Liu2, Chao Zhou3,4, Xiaoran Ma1, Huayao Li1, Jia Li5, Xue Wang6, Lingyu Qi1, Yan Yao5, Xiaoming Zhang2, Jing Zhuang3,4, Lijuan Liu3,4, Kejia Wang6, Changgang Sun3,4.
Abstract
Previous studies on long noncoding RNA (lncRNA) have made breakthroughs in the treatment of several tumors, and these findings have brought attention to the lncRNA signature of breast cancer. Increased understanding of genomic architecture and achievement of innovative therapeutic strategies has prompted creation of a novel oncological model for the treatment of solid cancers. In this study, we systematically analyzed the transcriptome of breast cancer tissues to gain more in-depth knowledge of tumor biology. Gene coexpression relationships were studied in 206 samples from The Cancer Genome Atlas database, and nine coexpression modules were identified. After screening and analysis, we identified four important prognosis-related lncRNAs (HOTAIR, SNHG16, HCP5, and TINCR), and constructed a prognostic model, one (HCP5) of which has not previously been identified in the context of breast cancer. Importantly, an understanding of prognosis facilitates precise disease risk assessment and advances the selection of strategies for risk-adaptive management. These findings broaden the landscape of carcinogenic lncRNAs in breast cancer, providing insights into the biological significance and clinical application of lncRNAs in breast cancer.Entities:
Keywords: breast cancer; gene coexpression; lncRNA
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Year: 2019 PMID: 30618123 DOI: 10.1002/jcp.28089
Source DB: PubMed Journal: J Cell Physiol ISSN: 0021-9541 Impact factor: 6.384