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

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 betwee...

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Autores principales: Teng, Xu, Yang, Tianshu, Huang, Wei, Li, Weishi, Zhou, Lin, Wang, Zihang, Feng, Yajuan, Zhang, Jingyao, Yin, Xin, Wang, Pei, Li, Gen, Yu, Hefeng, Chen, Zhongqiang, Fan, Dongwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312419/
https://www.ncbi.nlm.nih.gov/pubmed/34226298
http://dx.doi.org/10.18632/aging.203211
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author Teng, Xu
Yang, Tianshu
Huang, Wei
Li, Weishi
Zhou, Lin
Wang, Zihang
Feng, Yajuan
Zhang, Jingyao
Yin, Xin
Wang, Pei
Li, Gen
Yu, Hefeng
Chen, Zhongqiang
Fan, Dongwei
author_facet Teng, Xu
Yang, Tianshu
Huang, Wei
Li, Weishi
Zhou, Lin
Wang, Zihang
Feng, Yajuan
Zhang, Jingyao
Yin, Xin
Wang, Pei
Li, Gen
Yu, Hefeng
Chen, Zhongqiang
Fan, Dongwei
author_sort Teng, Xu
collection PubMed
description 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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spelling pubmed-83124192021-07-27 Bioinformatics analysis for the identification of key genes and long non-coding RNAs related to bone metastasis in breast cancer Teng, Xu Yang, Tianshu Huang, Wei Li, Weishi Zhou, Lin Wang, Zihang Feng, Yajuan Zhang, Jingyao Yin, Xin Wang, Pei Li, Gen Yu, Hefeng Chen, Zhongqiang Fan, Dongwei Aging (Albany NY) Research Paper 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. Impact Journals 2021-07-05 /pmc/articles/PMC8312419/ /pubmed/34226298 http://dx.doi.org/10.18632/aging.203211 Text en Copyright: © 2021 Teng et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Teng, Xu
Yang, Tianshu
Huang, Wei
Li, Weishi
Zhou, Lin
Wang, Zihang
Feng, Yajuan
Zhang, Jingyao
Yin, Xin
Wang, Pei
Li, Gen
Yu, Hefeng
Chen, Zhongqiang
Fan, Dongwei
Bioinformatics analysis for the identification of key genes and long non-coding RNAs related to bone metastasis in breast cancer
title Bioinformatics analysis for the identification of key genes and long non-coding RNAs related to bone metastasis in breast cancer
title_full Bioinformatics analysis for the identification of key genes and long non-coding RNAs related to bone metastasis in breast cancer
title_fullStr Bioinformatics analysis for the identification of key genes and long non-coding RNAs related to bone metastasis in breast cancer
title_full_unstemmed Bioinformatics analysis for the identification of key genes and long non-coding RNAs related to bone metastasis in breast cancer
title_short Bioinformatics analysis for the identification of key genes and long non-coding RNAs related to bone metastasis in breast cancer
title_sort bioinformatics analysis for the identification of key genes and long non-coding rnas related to bone metastasis in breast cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8312419/
https://www.ncbi.nlm.nih.gov/pubmed/34226298
http://dx.doi.org/10.18632/aging.203211
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