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Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer

BACKGROUND: In today’s society, cancer has become a big concern. The most common cancers in women are breast cancer (BC), endometrial cancer (EC), ovarian cancer (OC), and cervical cancer (CC). CC is a type of cervix cancer that is the fourth most common cancer in women and the fourth major cause of...

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Autores principales: Hasan, Md. Tanvir, Islam, Md. Rakibul, Islam, Md. Rezwan, Altahan, Baraa Riyadh, Ahmed, Kawsar, Bui, Francis M., Azam, Sami, Moni, Mohammad Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9892376/
https://www.ncbi.nlm.nih.gov/pubmed/36723760
http://dx.doi.org/10.1186/s43141-023-00469-x
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author Hasan, Md. Tanvir
Islam, Md. Rakibul
Islam, Md. Rezwan
Altahan, Baraa Riyadh
Ahmed, Kawsar
Bui, Francis M.
Azam, Sami
Moni, Mohammad Ali
author_facet Hasan, Md. Tanvir
Islam, Md. Rakibul
Islam, Md. Rezwan
Altahan, Baraa Riyadh
Ahmed, Kawsar
Bui, Francis M.
Azam, Sami
Moni, Mohammad Ali
author_sort Hasan, Md. Tanvir
collection PubMed
description BACKGROUND: In today’s society, cancer has become a big concern. The most common cancers in women are breast cancer (BC), endometrial cancer (EC), ovarian cancer (OC), and cervical cancer (CC). CC is a type of cervix cancer that is the fourth most common cancer in women and the fourth major cause of death. RESULTS: This research uses a network approach to discover genetic connections, functional enrichment, pathways analysis, microRNAs transcription factors (miRNA-TF) co-regulatory network, gene-disease associations, and therapeutic targets for CC. Three datasets from the NCBI’s GEO collection were considered for this investigation. Then, using a comparison approach between the datasets, 315 common DEGs were discovered. The PPI network was built using a variety of combinatorial statistical approaches and bioinformatics tools, and the PPI network was then utilized to identify hub genes and critical modules. CONCLUSION: Furthermore, we discovered that CC has specific similar links with the progression of different tumors using Gene Ontology terminology and pathway analysis. Transcription factors-gene linkages, gene-disease correlations, and the miRNA-TF co-regulatory network were revealed to have functional enrichments. We believe the candidate drugs identified in this study could be effective for advanced CC treatment.
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spelling pubmed-98923762023-02-08 Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer Hasan, Md. Tanvir Islam, Md. Rakibul Islam, Md. Rezwan Altahan, Baraa Riyadh Ahmed, Kawsar Bui, Francis M. Azam, Sami Moni, Mohammad Ali J Genet Eng Biotechnol Research BACKGROUND: In today’s society, cancer has become a big concern. The most common cancers in women are breast cancer (BC), endometrial cancer (EC), ovarian cancer (OC), and cervical cancer (CC). CC is a type of cervix cancer that is the fourth most common cancer in women and the fourth major cause of death. RESULTS: This research uses a network approach to discover genetic connections, functional enrichment, pathways analysis, microRNAs transcription factors (miRNA-TF) co-regulatory network, gene-disease associations, and therapeutic targets for CC. Three datasets from the NCBI’s GEO collection were considered for this investigation. Then, using a comparison approach between the datasets, 315 common DEGs were discovered. The PPI network was built using a variety of combinatorial statistical approaches and bioinformatics tools, and the PPI network was then utilized to identify hub genes and critical modules. CONCLUSION: Furthermore, we discovered that CC has specific similar links with the progression of different tumors using Gene Ontology terminology and pathway analysis. Transcription factors-gene linkages, gene-disease correlations, and the miRNA-TF co-regulatory network were revealed to have functional enrichments. We believe the candidate drugs identified in this study could be effective for advanced CC treatment. Springer Berlin Heidelberg 2023-02-01 /pmc/articles/PMC9892376/ /pubmed/36723760 http://dx.doi.org/10.1186/s43141-023-00469-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Research
Hasan, Md. Tanvir
Islam, Md. Rakibul
Islam, Md. Rezwan
Altahan, Baraa Riyadh
Ahmed, Kawsar
Bui, Francis M.
Azam, Sami
Moni, Mohammad Ali
Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer
title Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer
title_full Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer
title_fullStr Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer
title_full_unstemmed Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer
title_short Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer
title_sort systematic approach to identify therapeutic targets and functional pathways for the cervical cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9892376/
https://www.ncbi.nlm.nih.gov/pubmed/36723760
http://dx.doi.org/10.1186/s43141-023-00469-x
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