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A Motif-Based Network Analysis of Regulatory Patterns in Doxorubicin Effects on Treating Breast Cancer, a Systems Biology Study
BACKGROUND: Breast cancer is the most common malignancy worldwide. Doxorubicin is an anthracycline used to treat breast cancer as the first treatment choice. Nevertheless, the molecular mechanisms underlying the response to Doxorubicin and its side effects are not comprehensively understood so far....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Avicenna Research Institute
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9077660/ https://www.ncbi.nlm.nih.gov/pubmed/35633986 http://dx.doi.org/10.18502/ajmb.v14i2.8889 |
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author | Dehghan, Zeinab Mirmotalebisohi, Seyed Amir Sameni, Marzieh Bazgiri, Maryam Zali, Hakimeh |
author_facet | Dehghan, Zeinab Mirmotalebisohi, Seyed Amir Sameni, Marzieh Bazgiri, Maryam Zali, Hakimeh |
author_sort | Dehghan, Zeinab |
collection | PubMed |
description | BACKGROUND: Breast cancer is the most common malignancy worldwide. Doxorubicin is an anthracycline used to treat breast cancer as the first treatment choice. Nevertheless, the molecular mechanisms underlying the response to Doxorubicin and its side effects are not comprehensively understood so far. We used systems biology and bioinformatics methods to identify essential genes and molecular mechanisms behind the body response to Doxorubicin and its side effects in breast cancer patients. METHODS: Omics data were extracted and analyzed to construct the protein-protein interaction and gene regulatory networks. Network analysis was performed to identify hubs, bottlenecks, clusters, and regulatory motifs to evaluate crucial genes and molecular mechanisms behind the body response to Doxorubicin and its side effects. RESULTS: Analyzing the constructed PPI and gene-TF-miRNA regulatory network showed that MCM3, MCM10, and TP53 are key hub-bottlenecks and seed proteins. Enrichment analysis also revealed cell cycle, TP53 signaling, Forkhead box O (FoxO) signaling, and viral carcinogenesis as essential pathways in response to this drug. Besides, SNARE interactions in vesicular transport and neurotrophin signaling were identified as pathways related to the side effects of Doxorubicin. The apoptosis induction, DNA repair, invasion inhibition, metastasis, and DNA replication are suggested as critical molecular mechanisms underlying Doxorubicin anti-cancer effect. SNARE interactions in vesicular transport and neurotrophin signaling and FoxO signaling pathways in glucose metabolism are probably the mechanisms responsible for side effects of Doxorubicin. CONCLUSION: Following our model validation using the existing experimental data, we recommend our other newly predicted biomarkers and pathways as possible molecular mechanisms and side effects underlying the response to Doxorubicin in breast cancer requiring further investigations. |
format | Online Article Text |
id | pubmed-9077660 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Avicenna Research Institute |
record_format | MEDLINE/PubMed |
spelling | pubmed-90776602022-05-26 A Motif-Based Network Analysis of Regulatory Patterns in Doxorubicin Effects on Treating Breast Cancer, a Systems Biology Study Dehghan, Zeinab Mirmotalebisohi, Seyed Amir Sameni, Marzieh Bazgiri, Maryam Zali, Hakimeh Avicenna J Med Biotechnol Original Article BACKGROUND: Breast cancer is the most common malignancy worldwide. Doxorubicin is an anthracycline used to treat breast cancer as the first treatment choice. Nevertheless, the molecular mechanisms underlying the response to Doxorubicin and its side effects are not comprehensively understood so far. We used systems biology and bioinformatics methods to identify essential genes and molecular mechanisms behind the body response to Doxorubicin and its side effects in breast cancer patients. METHODS: Omics data were extracted and analyzed to construct the protein-protein interaction and gene regulatory networks. Network analysis was performed to identify hubs, bottlenecks, clusters, and regulatory motifs to evaluate crucial genes and molecular mechanisms behind the body response to Doxorubicin and its side effects. RESULTS: Analyzing the constructed PPI and gene-TF-miRNA regulatory network showed that MCM3, MCM10, and TP53 are key hub-bottlenecks and seed proteins. Enrichment analysis also revealed cell cycle, TP53 signaling, Forkhead box O (FoxO) signaling, and viral carcinogenesis as essential pathways in response to this drug. Besides, SNARE interactions in vesicular transport and neurotrophin signaling were identified as pathways related to the side effects of Doxorubicin. The apoptosis induction, DNA repair, invasion inhibition, metastasis, and DNA replication are suggested as critical molecular mechanisms underlying Doxorubicin anti-cancer effect. SNARE interactions in vesicular transport and neurotrophin signaling and FoxO signaling pathways in glucose metabolism are probably the mechanisms responsible for side effects of Doxorubicin. CONCLUSION: Following our model validation using the existing experimental data, we recommend our other newly predicted biomarkers and pathways as possible molecular mechanisms and side effects underlying the response to Doxorubicin in breast cancer requiring further investigations. Avicenna Research Institute 2022 /pmc/articles/PMC9077660/ /pubmed/35633986 http://dx.doi.org/10.18502/ajmb.v14i2.8889 Text en Copyright© 2022 Avicenna Research Institute https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) |
spellingShingle | Original Article Dehghan, Zeinab Mirmotalebisohi, Seyed Amir Sameni, Marzieh Bazgiri, Maryam Zali, Hakimeh A Motif-Based Network Analysis of Regulatory Patterns in Doxorubicin Effects on Treating Breast Cancer, a Systems Biology Study |
title | A Motif-Based Network Analysis of Regulatory Patterns in Doxorubicin Effects on Treating Breast Cancer, a Systems Biology Study |
title_full | A Motif-Based Network Analysis of Regulatory Patterns in Doxorubicin Effects on Treating Breast Cancer, a Systems Biology Study |
title_fullStr | A Motif-Based Network Analysis of Regulatory Patterns in Doxorubicin Effects on Treating Breast Cancer, a Systems Biology Study |
title_full_unstemmed | A Motif-Based Network Analysis of Regulatory Patterns in Doxorubicin Effects on Treating Breast Cancer, a Systems Biology Study |
title_short | A Motif-Based Network Analysis of Regulatory Patterns in Doxorubicin Effects on Treating Breast Cancer, a Systems Biology Study |
title_sort | motif-based network analysis of regulatory patterns in doxorubicin effects on treating breast cancer, a systems biology study |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9077660/ https://www.ncbi.nlm.nih.gov/pubmed/35633986 http://dx.doi.org/10.18502/ajmb.v14i2.8889 |
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