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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Bioinformatics analysis for the identification of key genes and long non-coding RNAs related to bone metastasis in
Xu Teng1, Tianshu Yang1, Wei Huang1
1Beijing Key Laboratory for Cancer Invasion and Metastasis Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, P.R. China.
Abstract:
The molecular mechanism of bone metastasis in breast cancer is largely unknown. Herein, we aimed to identify the key genes and long non-coding RNAs (lncRNAs) related to the bone metastasis of breast cancer using a bioinformatics approach. We screened differentially expressed genes and lncRNAs between normal breast and breast cancer bone metastasis samples using the GSE66206 dataset from the Gene Expression Omnibus. We also constructed a differentially expressed lncRNA-mRNA interaction network and analyzed the node degrees to identify the driving genes. After finding potential pathogenic modules of breast cancer bone metastasis, we identified breast cancer bone metastasis-related modules and functional enrichment analysis of the genes and lncRNAs in the modules. Based on the above analysis, we constructed a differentially expressed lncRNA-mRNA network related to bone metastasis in breast cancer and identified core driver genes, including BNIP3 and the lncRNA RP11-317-J19.1. The role of core driver genes and lncRNAs in the network implies their biological functions in regulating bone development and remodeling. Thus, targeting the core driver genes and lncRNAs in the network may be a promising therapeutic strategy to manage bone metastasis.
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