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mRNA–miRNA bipartite networks reconstruction in different tissues of bladder cancer based on gene co-expression network analysis

Bladder cancer (BC) is one of the most important cancers worldwide, and if it is diagnosed early, its progression in humans can be prevented and long-term survival will be achieved accordingly. This study aimed to identify novel micro-RNA (miRNA) and gene-based biomarkers for diagnosing BC. The micr...

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Autores principales: Abedi, Zahra, MotieGhader, Habib, Hosseini, Sahar Sadat, Sheikh Beig Goharrizi, Mohammad Ali, Masoudi-Nejad, Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8991185/
https://www.ncbi.nlm.nih.gov/pubmed/35393513
http://dx.doi.org/10.1038/s41598-022-09920-4
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author Abedi, Zahra
MotieGhader, Habib
Hosseini, Sahar Sadat
Sheikh Beig Goharrizi, Mohammad Ali
Masoudi-Nejad, Ali
author_facet Abedi, Zahra
MotieGhader, Habib
Hosseini, Sahar Sadat
Sheikh Beig Goharrizi, Mohammad Ali
Masoudi-Nejad, Ali
author_sort Abedi, Zahra
collection PubMed
description Bladder cancer (BC) is one of the most important cancers worldwide, and if it is diagnosed early, its progression in humans can be prevented and long-term survival will be achieved accordingly. This study aimed to identify novel micro-RNA (miRNA) and gene-based biomarkers for diagnosing BC. The microarray dataset of BC tissues (GSE13507) listed in the GEO database was analyzed for this purpose. The gene expression data from three BC tissues including 165 primary bladder cancer (PBC), 58 normal looking-bladder mucosae surrounding cancer (NBMSC), and 23 recurrent non-muscle invasive tumor tissues (RNIT) were used to reconstruct gene co-expression networks. After preprocessing and normalization, deferentially expressed genes (DEGs) were obtained and used to construct the weighted gene co-expression network (WGCNA). Gene co-expression modules and low-preserved modules were extracted among BC tissues using network clustering. Next, the experimentally validated mRNA-miRNA interaction information were used to reconstruct three mRNA-miRNA bipartite networks. Reactome pathway database and Gene ontology (GO) was subsequently performed for the extracted genes of three bipartite networks and miRNAs, respectively. To further analyze the data, ten hub miRNAs (miRNAs with the highest degree) were selected in each bipartite network to reconstruct three bipartite subnetworks. Finally, the obtained biomarkers were comprehensively investigated and discussed in authentic studies. The obtained results from our study indicated a group of genes including PPARD, CST4, CSNK1E, PTPN14, ETV6, and ADRM1 as well as novel miRNAs (e.g., miR-16-5p, miR-335-5p, miR-124-3p, and let-7b-5p) which might be potentially associated with BC and could be a potential biomarker. Afterward, three drug-gene interaction networks were reconstructed to explore candidate drugs for the treatment of BC. The hub miRNAs in the mRNA-miRNA bipartite network played a fundamental role in BC progression; however, these findings need further investigation.
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spelling pubmed-89911852022-04-11 mRNA–miRNA bipartite networks reconstruction in different tissues of bladder cancer based on gene co-expression network analysis Abedi, Zahra MotieGhader, Habib Hosseini, Sahar Sadat Sheikh Beig Goharrizi, Mohammad Ali Masoudi-Nejad, Ali Sci Rep Article Bladder cancer (BC) is one of the most important cancers worldwide, and if it is diagnosed early, its progression in humans can be prevented and long-term survival will be achieved accordingly. This study aimed to identify novel micro-RNA (miRNA) and gene-based biomarkers for diagnosing BC. The microarray dataset of BC tissues (GSE13507) listed in the GEO database was analyzed for this purpose. The gene expression data from three BC tissues including 165 primary bladder cancer (PBC), 58 normal looking-bladder mucosae surrounding cancer (NBMSC), and 23 recurrent non-muscle invasive tumor tissues (RNIT) were used to reconstruct gene co-expression networks. After preprocessing and normalization, deferentially expressed genes (DEGs) were obtained and used to construct the weighted gene co-expression network (WGCNA). Gene co-expression modules and low-preserved modules were extracted among BC tissues using network clustering. Next, the experimentally validated mRNA-miRNA interaction information were used to reconstruct three mRNA-miRNA bipartite networks. Reactome pathway database and Gene ontology (GO) was subsequently performed for the extracted genes of three bipartite networks and miRNAs, respectively. To further analyze the data, ten hub miRNAs (miRNAs with the highest degree) were selected in each bipartite network to reconstruct three bipartite subnetworks. Finally, the obtained biomarkers were comprehensively investigated and discussed in authentic studies. The obtained results from our study indicated a group of genes including PPARD, CST4, CSNK1E, PTPN14, ETV6, and ADRM1 as well as novel miRNAs (e.g., miR-16-5p, miR-335-5p, miR-124-3p, and let-7b-5p) which might be potentially associated with BC and could be a potential biomarker. Afterward, three drug-gene interaction networks were reconstructed to explore candidate drugs for the treatment of BC. The hub miRNAs in the mRNA-miRNA bipartite network played a fundamental role in BC progression; however, these findings need further investigation. Nature Publishing Group UK 2022-04-07 /pmc/articles/PMC8991185/ /pubmed/35393513 http://dx.doi.org/10.1038/s41598-022-09920-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Abedi, Zahra
MotieGhader, Habib
Hosseini, Sahar Sadat
Sheikh Beig Goharrizi, Mohammad Ali
Masoudi-Nejad, Ali
mRNA–miRNA bipartite networks reconstruction in different tissues of bladder cancer based on gene co-expression network analysis
title mRNA–miRNA bipartite networks reconstruction in different tissues of bladder cancer based on gene co-expression network analysis
title_full mRNA–miRNA bipartite networks reconstruction in different tissues of bladder cancer based on gene co-expression network analysis
title_fullStr mRNA–miRNA bipartite networks reconstruction in different tissues of bladder cancer based on gene co-expression network analysis
title_full_unstemmed mRNA–miRNA bipartite networks reconstruction in different tissues of bladder cancer based on gene co-expression network analysis
title_short mRNA–miRNA bipartite networks reconstruction in different tissues of bladder cancer based on gene co-expression network analysis
title_sort mrna–mirna bipartite networks reconstruction in different tissues of bladder cancer based on gene co-expression network analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8991185/
https://www.ncbi.nlm.nih.gov/pubmed/35393513
http://dx.doi.org/10.1038/s41598-022-09920-4
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