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A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis

BACKGROUND: Gastric cancer (GC) ranks among the most common malignancies worldwide. This study aimed to find critical genes/pathways in GC pathogenesis. METHODS: Gene interactions were analyzed, and the protein–protein interaction network was drawn. Then enrichment analysis of the hub genes was perf...

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Autores principales: Mottaghi-Dastjerdi, Negar, Ghorbani, Abozar, Montazeri, Hamed, Guzzi, Pietro Hiram
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10364406/
https://www.ncbi.nlm.nih.gov/pubmed/37482618
http://dx.doi.org/10.1186/s12876-023-02891-4
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author Mottaghi-Dastjerdi, Negar
Ghorbani, Abozar
Montazeri, Hamed
Guzzi, Pietro Hiram
author_facet Mottaghi-Dastjerdi, Negar
Ghorbani, Abozar
Montazeri, Hamed
Guzzi, Pietro Hiram
author_sort Mottaghi-Dastjerdi, Negar
collection PubMed
description BACKGROUND: Gastric cancer (GC) ranks among the most common malignancies worldwide. This study aimed to find critical genes/pathways in GC pathogenesis. METHODS: Gene interactions were analyzed, and the protein–protein interaction network was drawn. Then enrichment analysis of the hub genes was performed and network cluster analysis and promoter analysis of the hub genes were done. Age/sex analysis was done on the identified genes. RESULTS: Eleven hub genes in GC were identified in the current study (ATP5A1, ATP5B, ATP5D, MT-ATP8, COX7A2, COX6C, ND4, ND6, NDUFS3, RPL8, and RPS16), mostly involved in mitochondrial functions. There was no report on the ATP5D, ND6, NDUFS3, RPL8, and RPS16 in GC. Our results showed that the most affected processes in GC are the metabolic processes, and the oxidative phosphorylation pathway was considerably enriched which showed the significance of mitochondria in GC pathogenesis. Most of the affected pathways in GC were also involved in neurodegenerative diseases. Promoter analysis showed that negative regulation of signal transduction might play an important role in GC pathogenesis. In the analysis of the basal expression pattern of the selected genes whose basal expression presented a change during the age, we found that a change in age may be an indicator of changes in disease insurgence and/or progression at different ages. CONCLUSIONS: These results might open up new insights into GC pathogenesis. The identified genes might be novel diagnostic/prognostic biomarkers or potential therapeutic targets for GC. This work, being based on bioinformatics analysis act as a hypothesis generator that requires further clinical validation.
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spelling pubmed-103644062023-07-25 A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis Mottaghi-Dastjerdi, Negar Ghorbani, Abozar Montazeri, Hamed Guzzi, Pietro Hiram BMC Gastroenterol Research BACKGROUND: Gastric cancer (GC) ranks among the most common malignancies worldwide. This study aimed to find critical genes/pathways in GC pathogenesis. METHODS: Gene interactions were analyzed, and the protein–protein interaction network was drawn. Then enrichment analysis of the hub genes was performed and network cluster analysis and promoter analysis of the hub genes were done. Age/sex analysis was done on the identified genes. RESULTS: Eleven hub genes in GC were identified in the current study (ATP5A1, ATP5B, ATP5D, MT-ATP8, COX7A2, COX6C, ND4, ND6, NDUFS3, RPL8, and RPS16), mostly involved in mitochondrial functions. There was no report on the ATP5D, ND6, NDUFS3, RPL8, and RPS16 in GC. Our results showed that the most affected processes in GC are the metabolic processes, and the oxidative phosphorylation pathway was considerably enriched which showed the significance of mitochondria in GC pathogenesis. Most of the affected pathways in GC were also involved in neurodegenerative diseases. Promoter analysis showed that negative regulation of signal transduction might play an important role in GC pathogenesis. In the analysis of the basal expression pattern of the selected genes whose basal expression presented a change during the age, we found that a change in age may be an indicator of changes in disease insurgence and/or progression at different ages. CONCLUSIONS: These results might open up new insights into GC pathogenesis. The identified genes might be novel diagnostic/prognostic biomarkers or potential therapeutic targets for GC. This work, being based on bioinformatics analysis act as a hypothesis generator that requires further clinical validation. BioMed Central 2023-07-24 /pmc/articles/PMC10364406/ /pubmed/37482618 http://dx.doi.org/10.1186/s12876-023-02891-4 Text en © The Author(s) 2023 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Mottaghi-Dastjerdi, Negar
Ghorbani, Abozar
Montazeri, Hamed
Guzzi, Pietro Hiram
A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis
title A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis
title_full A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis
title_fullStr A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis
title_full_unstemmed A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis
title_short A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis
title_sort systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10364406/
https://www.ncbi.nlm.nih.gov/pubmed/37482618
http://dx.doi.org/10.1186/s12876-023-02891-4
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