Guansheng Zhong1, Weiyang Lou2, Minya Yao1, Chengyong Du1, Haiyan Wei1, Peifen Fu1. 1. Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, 79 Qingchun Road, Hangzhou, Zhejiang 310003, PR China. 2. Program of Innovative Cancer Therapeutics, Division of Hepatobiliary & Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, College of Medicine, Key Laboratory of Organ Transplantation, Zhejiang University, 79 Qingchun Road, Zhejiang Province, Hangzhou 310003, PR China.
Abstract
Aim: To identify novel competing endogenous RNA (ceRNA) network related to patients prognosis in breast cancer. Materials & methods: Dysregulated mRNA based on intersection of three Gene Expression Omnibus and The Cancer Genome Atlas datasets were analyzed by bioinformatics. Results: In total 72 upregulated and 208 downregulated genes were identified. Functional analysis showed that some pathways related to cancer were significantly enriched. By means of stepwise reverse prediction and validation from mRNA to lncRNA, 19 hub genes, nine key miRNA and four key lncRNAs were identified by expression and survival analysis. Ultimately, the coexpression analysis identified RRM2-let-7a-5p-SNHG16/MAL2 as key ceRNA subnetwork associated with prognosis of breast cancer. Conclusion: We successfully constructed a novel ceRNA network, among which each component was significantly associated with breast cancer prognosis.
Aim: To identify novel competing endogenous RNA (ceRNA) network related to patients prognosis in breast cancer. Materials & methods: Dysregulated mRNA based on intersection of three Gene Expression Omnibus and The Cancer Genome Atlas datasets were analyzed by bioinformatics. Results: In total 72 upregulated and 208 downregulated genes were identified. Functional analysis showed that some pathways related to cancer were significantly enriched. By means of stepwise reverse prediction and validation from mRNA to lncRNA, 19 hub genes, nine key miRNA and four key lncRNAs were identified by expression and survival analysis. Ultimately, the coexpression analysis identified RRM2-let-7a-5p-SNHG16/MAL2 as key ceRNA subnetwork associated with prognosis of breast cancer. Conclusion: We successfully constructed a novel ceRNA network, among which each component was significantly associated with breast cancer prognosis.
Entities:
Keywords:
bioinformatic analysis; breast cancer; competing endogenous RNA; long noncoding RNA; miRNA
Authors: Elena A Filippova; Marina V Fridman; Alexey M Burdennyy; Vitaly I Loginov; Irina V Pronina; Svetlana S Lukina; Alexey A Dmitriev; Eleonora A Braga Journal: Int J Mol Sci Date: 2021-06-24 Impact factor: 5.923
Authors: Teng Ma; Huaidong Liu; Yan Liu; Tingting Liu; Hui Wang; Fulu Qiao; Lu Song; Lin Zhang Journal: BMC Cancer Date: 2020-10-14 Impact factor: 4.430