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Identification of novel drug targets for diamond-blackfan anemia based on RPS19 gene mutation using protein-protein interaction network

BACKGROUND: Diamond-Blackfan anemia (DBA) is a congenital erythroid aplasia that usually presents in infancy. In order to explore the molecular mechanisms of wild and mutated samples from DBA patients were exposed to bioinformatics investigation. Biological network of differentially expressed genes...

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Autores principales: Khan, Abbas, Ali, Arif, Junaid, Muhammad, Liu, Chang, Kaushik, Aman Chandra, Cho, William C. S., Wei, Dong-Qing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998885/
https://www.ncbi.nlm.nih.gov/pubmed/29745857
http://dx.doi.org/10.1186/s12918-018-0563-0
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author Khan, Abbas
Ali, Arif
Junaid, Muhammad
Liu, Chang
Kaushik, Aman Chandra
Cho, William C. S.
Wei, Dong-Qing
author_facet Khan, Abbas
Ali, Arif
Junaid, Muhammad
Liu, Chang
Kaushik, Aman Chandra
Cho, William C. S.
Wei, Dong-Qing
author_sort Khan, Abbas
collection PubMed
description BACKGROUND: Diamond-Blackfan anemia (DBA) is a congenital erythroid aplasia that usually presents in infancy. In order to explore the molecular mechanisms of wild and mutated samples from DBA patients were exposed to bioinformatics investigation. Biological network of differentially expressed genes was constructed. This study aimed to identify novel therapeutic signatures in DBA and uncovered their mechanisms. The gene expression dataset of GSE14335 was used, which consists of 6 normal and 4 diseased cases. The gene ontology (GO), as well as Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and then protein–protein interaction (PPI) network of the identified differentially expressed genes (DEGs) was constructed by Cytoscape software. RESULTS: A total of 607 DEGs were identified in DBA, including 433 upregulated genes and 174 downregulated genes. GO analysis results showed that upregulated DEGs were significantly enriched in biological processes, negative regulation of transcription from RNA polymerase II promoter, chemotaxis, inflammatory response, immune response, positive regulation of cell proliferation, negative regulation of cell proliferation, response to mechanical stimulus, positive regulation of cell migration, response to lipopolysaccharide, and defence response. KEGG pathway analysis revealed the TNF signalling pathway, Osteoclast differentiation, Chemokine signalling pathway, Cytokine -cytokine receptor interaction, Rheumatoid arthritis, Biosynthesis of amino acids, Biosynthesis of antibiotics and Glycine, serine and threonine metabolism. The top 10 hub genes, AKT1, IL6, NFKB1, STAT3, STAT1, RAC1, EGR1, IL8, RELA, RAC3, mTOR and CCR2 were identified from the PPI network and sub-networks. CONCLUSION: The present study flagged that the identified DEGs and hub genes enrich our understanding of the molecular mechanisms underlying the development of DBA, and might shine some lights on identifying molecular targets and diagnostic biomarkers for DBA. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-018-0563-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-59988852018-06-25 Identification of novel drug targets for diamond-blackfan anemia based on RPS19 gene mutation using protein-protein interaction network Khan, Abbas Ali, Arif Junaid, Muhammad Liu, Chang Kaushik, Aman Chandra Cho, William C. S. Wei, Dong-Qing BMC Syst Biol Research BACKGROUND: Diamond-Blackfan anemia (DBA) is a congenital erythroid aplasia that usually presents in infancy. In order to explore the molecular mechanisms of wild and mutated samples from DBA patients were exposed to bioinformatics investigation. Biological network of differentially expressed genes was constructed. This study aimed to identify novel therapeutic signatures in DBA and uncovered their mechanisms. The gene expression dataset of GSE14335 was used, which consists of 6 normal and 4 diseased cases. The gene ontology (GO), as well as Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and then protein–protein interaction (PPI) network of the identified differentially expressed genes (DEGs) was constructed by Cytoscape software. RESULTS: A total of 607 DEGs were identified in DBA, including 433 upregulated genes and 174 downregulated genes. GO analysis results showed that upregulated DEGs were significantly enriched in biological processes, negative regulation of transcription from RNA polymerase II promoter, chemotaxis, inflammatory response, immune response, positive regulation of cell proliferation, negative regulation of cell proliferation, response to mechanical stimulus, positive regulation of cell migration, response to lipopolysaccharide, and defence response. KEGG pathway analysis revealed the TNF signalling pathway, Osteoclast differentiation, Chemokine signalling pathway, Cytokine -cytokine receptor interaction, Rheumatoid arthritis, Biosynthesis of amino acids, Biosynthesis of antibiotics and Glycine, serine and threonine metabolism. The top 10 hub genes, AKT1, IL6, NFKB1, STAT3, STAT1, RAC1, EGR1, IL8, RELA, RAC3, mTOR and CCR2 were identified from the PPI network and sub-networks. CONCLUSION: The present study flagged that the identified DEGs and hub genes enrich our understanding of the molecular mechanisms underlying the development of DBA, and might shine some lights on identifying molecular targets and diagnostic biomarkers for DBA. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-018-0563-0) contains supplementary material, which is available to authorized users. BioMed Central 2018-04-24 /pmc/articles/PMC5998885/ /pubmed/29745857 http://dx.doi.org/10.1186/s12918-018-0563-0 Text en © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Khan, Abbas
Ali, Arif
Junaid, Muhammad
Liu, Chang
Kaushik, Aman Chandra
Cho, William C. S.
Wei, Dong-Qing
Identification of novel drug targets for diamond-blackfan anemia based on RPS19 gene mutation using protein-protein interaction network
title Identification of novel drug targets for diamond-blackfan anemia based on RPS19 gene mutation using protein-protein interaction network
title_full Identification of novel drug targets for diamond-blackfan anemia based on RPS19 gene mutation using protein-protein interaction network
title_fullStr Identification of novel drug targets for diamond-blackfan anemia based on RPS19 gene mutation using protein-protein interaction network
title_full_unstemmed Identification of novel drug targets for diamond-blackfan anemia based on RPS19 gene mutation using protein-protein interaction network
title_short Identification of novel drug targets for diamond-blackfan anemia based on RPS19 gene mutation using protein-protein interaction network
title_sort identification of novel drug targets for diamond-blackfan anemia based on rps19 gene mutation using protein-protein interaction network
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998885/
https://www.ncbi.nlm.nih.gov/pubmed/29745857
http://dx.doi.org/10.1186/s12918-018-0563-0
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