Cargando…

Identifying the key genes and microRNAs in prostate cancer bone metastasis by bioinformatics analysis

Prostate adenocarcinoma (PCa) is the most common cause of death due to malignancy among men, and bone metastasis is the leading cause of mortality in patients with PCa. Therefore, identifying the causes and molecular mechanism of bone metastasis is important for early detection, diagnosis and person...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhu, Zhiguo, Wen, Yaoan, Xuan, Chunxiang, Chen, Qingping, Xiang, Qian, Wang, Jiamin, Liu, Yangzhou, Luo, Lianmin, Zhao, Shankun, Deng, Yihan, Zhao, Zhigang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7137804/
https://www.ncbi.nlm.nih.gov/pubmed/32027093
http://dx.doi.org/10.1002/2211-5463.12805
_version_ 1783518477501333504
author Zhu, Zhiguo
Wen, Yaoan
Xuan, Chunxiang
Chen, Qingping
Xiang, Qian
Wang, Jiamin
Liu, Yangzhou
Luo, Lianmin
Zhao, Shankun
Deng, Yihan
Zhao, Zhigang
author_facet Zhu, Zhiguo
Wen, Yaoan
Xuan, Chunxiang
Chen, Qingping
Xiang, Qian
Wang, Jiamin
Liu, Yangzhou
Luo, Lianmin
Zhao, Shankun
Deng, Yihan
Zhao, Zhigang
author_sort Zhu, Zhiguo
collection PubMed
description Prostate adenocarcinoma (PCa) is the most common cause of death due to malignancy among men, and bone metastasis is the leading cause of mortality in patients with PCa. Therefore, identifying the causes and molecular mechanism of bone metastasis is important for early detection, diagnosis and personalized therapy. In this study, we systematically analyzed molecular correlates of bone metastasis by bioinformatics analysis. A total of 12 differentially expressed microRNAs (miRNAs) and 102 differentially expressed genes were identified. Five miRNAs had prognostic significance in biochemical recurrence‐free survival (miR‐636, miR‐491‐5p, miR‐199b‐5p, miR‐199b‐3p, miR‐28‐3p). The differentially expressed genes were significantly enriched in extracellular matrix, cell‐substrate adhesion, collagen and integrin. Seven hub genes (VCAN, COL3A1, COL1A1, APOE, COL1A2, SDC1, THY1) with worse biochemical recurrence‐free survival and one hub gene (MMP9) with worse overall survival were detected. miR‐636, a novel oncogene, was found to be up‐regulated in bone metastatic PCa tissues and also predominately up‐regulated in human PCa cell lines. miR‐636 promoted cellular invasion and migration, and may promote bone metastasis via targeting MBNL2, TNS1 and STAB1. In conclusion, we have successfully defined molecular signatures of bone metastasis in PCa.
format Online
Article
Text
id pubmed-7137804
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-71378042020-04-08 Identifying the key genes and microRNAs in prostate cancer bone metastasis by bioinformatics analysis Zhu, Zhiguo Wen, Yaoan Xuan, Chunxiang Chen, Qingping Xiang, Qian Wang, Jiamin Liu, Yangzhou Luo, Lianmin Zhao, Shankun Deng, Yihan Zhao, Zhigang FEBS Open Bio Research Articles Prostate adenocarcinoma (PCa) is the most common cause of death due to malignancy among men, and bone metastasis is the leading cause of mortality in patients with PCa. Therefore, identifying the causes and molecular mechanism of bone metastasis is important for early detection, diagnosis and personalized therapy. In this study, we systematically analyzed molecular correlates of bone metastasis by bioinformatics analysis. A total of 12 differentially expressed microRNAs (miRNAs) and 102 differentially expressed genes were identified. Five miRNAs had prognostic significance in biochemical recurrence‐free survival (miR‐636, miR‐491‐5p, miR‐199b‐5p, miR‐199b‐3p, miR‐28‐3p). The differentially expressed genes were significantly enriched in extracellular matrix, cell‐substrate adhesion, collagen and integrin. Seven hub genes (VCAN, COL3A1, COL1A1, APOE, COL1A2, SDC1, THY1) with worse biochemical recurrence‐free survival and one hub gene (MMP9) with worse overall survival were detected. miR‐636, a novel oncogene, was found to be up‐regulated in bone metastatic PCa tissues and also predominately up‐regulated in human PCa cell lines. miR‐636 promoted cellular invasion and migration, and may promote bone metastasis via targeting MBNL2, TNS1 and STAB1. In conclusion, we have successfully defined molecular signatures of bone metastasis in PCa. John Wiley and Sons Inc. 2020-03-19 /pmc/articles/PMC7137804/ /pubmed/32027093 http://dx.doi.org/10.1002/2211-5463.12805 Text en © 2020 The Authors. Published by FEBS Press and John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Zhu, Zhiguo
Wen, Yaoan
Xuan, Chunxiang
Chen, Qingping
Xiang, Qian
Wang, Jiamin
Liu, Yangzhou
Luo, Lianmin
Zhao, Shankun
Deng, Yihan
Zhao, Zhigang
Identifying the key genes and microRNAs in prostate cancer bone metastasis by bioinformatics analysis
title Identifying the key genes and microRNAs in prostate cancer bone metastasis by bioinformatics analysis
title_full Identifying the key genes and microRNAs in prostate cancer bone metastasis by bioinformatics analysis
title_fullStr Identifying the key genes and microRNAs in prostate cancer bone metastasis by bioinformatics analysis
title_full_unstemmed Identifying the key genes and microRNAs in prostate cancer bone metastasis by bioinformatics analysis
title_short Identifying the key genes and microRNAs in prostate cancer bone metastasis by bioinformatics analysis
title_sort identifying the key genes and micrornas in prostate cancer bone metastasis by bioinformatics analysis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7137804/
https://www.ncbi.nlm.nih.gov/pubmed/32027093
http://dx.doi.org/10.1002/2211-5463.12805
work_keys_str_mv AT zhuzhiguo identifyingthekeygenesandmicrornasinprostatecancerbonemetastasisbybioinformaticsanalysis
AT wenyaoan identifyingthekeygenesandmicrornasinprostatecancerbonemetastasisbybioinformaticsanalysis
AT xuanchunxiang identifyingthekeygenesandmicrornasinprostatecancerbonemetastasisbybioinformaticsanalysis
AT chenqingping identifyingthekeygenesandmicrornasinprostatecancerbonemetastasisbybioinformaticsanalysis
AT xiangqian identifyingthekeygenesandmicrornasinprostatecancerbonemetastasisbybioinformaticsanalysis
AT wangjiamin identifyingthekeygenesandmicrornasinprostatecancerbonemetastasisbybioinformaticsanalysis
AT liuyangzhou identifyingthekeygenesandmicrornasinprostatecancerbonemetastasisbybioinformaticsanalysis
AT luolianmin identifyingthekeygenesandmicrornasinprostatecancerbonemetastasisbybioinformaticsanalysis
AT zhaoshankun identifyingthekeygenesandmicrornasinprostatecancerbonemetastasisbybioinformaticsanalysis
AT dengyihan identifyingthekeygenesandmicrornasinprostatecancerbonemetastasisbybioinformaticsanalysis
AT zhaozhigang identifyingthekeygenesandmicrornasinprostatecancerbonemetastasisbybioinformaticsanalysis