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Research Paper|Volume 13, Issue 13|pp 17302—17315

Bioinformatics analysis for the identification of key genes and long non-coding RNAs related to bone metastasis in breast cancer

Xu Teng1, Tianshu Yang1, Wei Huang1, Weishi Li2, Lin Zhou3, Zihang Wang3, Yajuan Feng3, Jingyao Zhang4, Xin Yin1, Pei Wang1, Gen Li1, Hefeng Yu1, Zhongqiang Chen2, Dongwei Fan2
  • 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
  • 2Department of Orthopaedics, Peking University Third Hospital, Beijing 100191, P.R. China
  • 3School of Information Science and Technology, University of Science and Technology of China, Hefei 230026, Anhui, P.R. China
  • 4State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, P.R. China
Received: January 21, 2021Accepted: May 31, 2021Published: July 5, 2021

Copyright: © 2021 Teng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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.