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A comprehensive bioinformatics analysis to identify potential prognostic biomarkers among CC and CXC chemokines in breast cancer
Breast cancer (BC) is a major human health problem due to its increasing incidence and mortality rate. CC and CXC chemokines are associated with tumorigenesis and the progression of many cancers. Since the prognostic values of CC and CXC families' expression in various types of cancers are beco...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209453/ https://www.ncbi.nlm.nih.gov/pubmed/35725915 http://dx.doi.org/10.1038/s41598-022-14610-2 |
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author | Hozhabri, Hossein Moghaddam, Marziyeh Mazaheri Moghaddam, Madiheh Mazaheri Mohammadian, Ali |
author_facet | Hozhabri, Hossein Moghaddam, Marziyeh Mazaheri Moghaddam, Madiheh Mazaheri Mohammadian, Ali |
author_sort | Hozhabri, Hossein |
collection | PubMed |
description | Breast cancer (BC) is a major human health problem due to its increasing incidence and mortality rate. CC and CXC chemokines are associated with tumorigenesis and the progression of many cancers. Since the prognostic values of CC and CXC families' expression in various types of cancers are becoming increasingly evident, we aimed to conduct a comprehensive bioinformatics analysis elucidating the prognostic values of the CC and CXC families in BC. Therefore, TCGA, UALCAN, Kaplan–Meier plotter, bc-GenExMiner, cBioPortal, STRING, Enrichr, and TIMER were utilized for analysis. We found that high levels of CCL4/5/14/19/21/22 were associated with better OS and RFS, while elevated expression of CCL24 was correlated with shorter OS in BC patients. Also, high levels of CXCL9/13 indicated longer OS, and enhanced expression of CXCL12/14 was linked with better OS and RFS in BC patients. Meanwhile, increased transcription levels of CXCL8 were associated with worse OS and RFS in BC patients. In addition, our results showed that CCL5, CCL8, CCL14, CCL20, CCL27, CXCL4, and CXCL14 were notably correlated with the clinical outcomes of BC patients. Our findings provide a new point of view that may help the clinical application of CC and CXC chemokines as prognostic biomarkers in BC. |
format | Online Article Text |
id | pubmed-9209453 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92094532022-06-22 A comprehensive bioinformatics analysis to identify potential prognostic biomarkers among CC and CXC chemokines in breast cancer Hozhabri, Hossein Moghaddam, Marziyeh Mazaheri Moghaddam, Madiheh Mazaheri Mohammadian, Ali Sci Rep Article Breast cancer (BC) is a major human health problem due to its increasing incidence and mortality rate. CC and CXC chemokines are associated with tumorigenesis and the progression of many cancers. Since the prognostic values of CC and CXC families' expression in various types of cancers are becoming increasingly evident, we aimed to conduct a comprehensive bioinformatics analysis elucidating the prognostic values of the CC and CXC families in BC. Therefore, TCGA, UALCAN, Kaplan–Meier plotter, bc-GenExMiner, cBioPortal, STRING, Enrichr, and TIMER were utilized for analysis. We found that high levels of CCL4/5/14/19/21/22 were associated with better OS and RFS, while elevated expression of CCL24 was correlated with shorter OS in BC patients. Also, high levels of CXCL9/13 indicated longer OS, and enhanced expression of CXCL12/14 was linked with better OS and RFS in BC patients. Meanwhile, increased transcription levels of CXCL8 were associated with worse OS and RFS in BC patients. In addition, our results showed that CCL5, CCL8, CCL14, CCL20, CCL27, CXCL4, and CXCL14 were notably correlated with the clinical outcomes of BC patients. Our findings provide a new point of view that may help the clinical application of CC and CXC chemokines as prognostic biomarkers in BC. Nature Publishing Group UK 2022-06-20 /pmc/articles/PMC9209453/ /pubmed/35725915 http://dx.doi.org/10.1038/s41598-022-14610-2 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 Hozhabri, Hossein Moghaddam, Marziyeh Mazaheri Moghaddam, Madiheh Mazaheri Mohammadian, Ali A comprehensive bioinformatics analysis to identify potential prognostic biomarkers among CC and CXC chemokines in breast cancer |
title | A comprehensive bioinformatics analysis to identify potential prognostic biomarkers among CC and CXC chemokines in breast cancer |
title_full | A comprehensive bioinformatics analysis to identify potential prognostic biomarkers among CC and CXC chemokines in breast cancer |
title_fullStr | A comprehensive bioinformatics analysis to identify potential prognostic biomarkers among CC and CXC chemokines in breast cancer |
title_full_unstemmed | A comprehensive bioinformatics analysis to identify potential prognostic biomarkers among CC and CXC chemokines in breast cancer |
title_short | A comprehensive bioinformatics analysis to identify potential prognostic biomarkers among CC and CXC chemokines in breast cancer |
title_sort | comprehensive bioinformatics analysis to identify potential prognostic biomarkers among cc and cxc chemokines in breast cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209453/ https://www.ncbi.nlm.nih.gov/pubmed/35725915 http://dx.doi.org/10.1038/s41598-022-14610-2 |
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