Four lncRNAs associated with breast cancer prognosis identified by coexpression network analysis.
Jie LiChundi GaoCun LiuChao ZhouXiaoran MaHuayao LiJia LiXue WangLingyu QiYan YaoXiaoming ZhangJing ZhuangLijuan LiuKejia WangChanggang SunPublished in: Journal of cellular physiology (2019)
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.
Keyphrases
- network analysis
- long noncoding rna
- risk assessment
- healthcare
- gene expression
- genome wide
- squamous cell carcinoma
- long non coding rna
- copy number
- heavy metals
- working memory
- breast cancer risk
- climate change
- rectal cancer
- childhood cancer
- optical coherence tomography
- transcription factor
- data analysis
- replacement therapy
- drug induced