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Using publicly available datasets to identify population-based transcriptomic landscape contributing to the aggressiveness of breast cancer in young women
Introduction: Although the risk of breast cancer increases with advancing age, some regions have larger number of young breast cancer patients (≤45 years-old), such as the Middle East, Eastern Asia, and North Africa, with more aggressive and poorly differentiated tumors. We aimed to conduct an in-si...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9845274/ https://www.ncbi.nlm.nih.gov/pubmed/36685821 http://dx.doi.org/10.3389/fgene.2022.1039037 |
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author | Tabbal, Marah Hachim, Mahmood Y. Jan, Reem Kais Adrian, Thomas E. |
author_facet | Tabbal, Marah Hachim, Mahmood Y. Jan, Reem Kais Adrian, Thomas E. |
author_sort | Tabbal, Marah |
collection | PubMed |
description | Introduction: Although the risk of breast cancer increases with advancing age, some regions have larger number of young breast cancer patients (≤45 years-old), such as the Middle East, Eastern Asia, and North Africa, with more aggressive and poorly differentiated tumors. We aimed to conduct an in-silico analysis in an attempt to understand the aggressive nature of early-onset breast cancer, and to identify potential drivers of early-onset breast cancer using gene expression profiling datasets in a population-dependent manner. Methods: Functional genomics experiments data were acquired from cBioPortal database for cancer genomics, followed by the stratification of patients based on the age at representation of breast cancer and race. Differential gene expression analysis and gene amplification status analysis were carried out, followed by hub gene, transcription factor, and signalling pathway identification. Results: PAM50 subtype analysis revealed that young patients (≤45 years-old) had four-fold more basal tumors and worst progression-free survival (median of 101 months), compared with the 45–65 years group (median of 168 months). Fourteen genes were amplified in more than 14% of patients with an early-onset breast cancer. Interestingly, FREM2, LINC00332, and LINC00366 were exclusively amplified in younger patients. Gene expression data from three different populations (Asian, White, and African) revealed a unique transcriptomic profile of young patients, which was also reflected on the PAM50 subtype analysis. Our data indicates a higher tendency of young African patients to develop basal tumors, while young Asian patients are more prone to developing Luminal A tumors. Most genes that were found to be upregulated in younger patients are involved in important signaling pathways that promote cancer progression and metastasis, such as MAPK pathway, Reelin pathway and the PI3K/Akt pathway. Conclusion: This study provides strong evidence that the molecular profile of tumors derived from young breast cancer patients of different populations is unique and may explain the aggressiveness of these tumors, stressing the need to conduct population- based multi-omic analyses to identify the potential drivers for tumorigenesis and molecular profiles of young breast cancer patients. |
format | Online Article Text |
id | pubmed-9845274 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98452742023-01-19 Using publicly available datasets to identify population-based transcriptomic landscape contributing to the aggressiveness of breast cancer in young women Tabbal, Marah Hachim, Mahmood Y. Jan, Reem Kais Adrian, Thomas E. Front Genet Genetics Introduction: Although the risk of breast cancer increases with advancing age, some regions have larger number of young breast cancer patients (≤45 years-old), such as the Middle East, Eastern Asia, and North Africa, with more aggressive and poorly differentiated tumors. We aimed to conduct an in-silico analysis in an attempt to understand the aggressive nature of early-onset breast cancer, and to identify potential drivers of early-onset breast cancer using gene expression profiling datasets in a population-dependent manner. Methods: Functional genomics experiments data were acquired from cBioPortal database for cancer genomics, followed by the stratification of patients based on the age at representation of breast cancer and race. Differential gene expression analysis and gene amplification status analysis were carried out, followed by hub gene, transcription factor, and signalling pathway identification. Results: PAM50 subtype analysis revealed that young patients (≤45 years-old) had four-fold more basal tumors and worst progression-free survival (median of 101 months), compared with the 45–65 years group (median of 168 months). Fourteen genes were amplified in more than 14% of patients with an early-onset breast cancer. Interestingly, FREM2, LINC00332, and LINC00366 were exclusively amplified in younger patients. Gene expression data from three different populations (Asian, White, and African) revealed a unique transcriptomic profile of young patients, which was also reflected on the PAM50 subtype analysis. Our data indicates a higher tendency of young African patients to develop basal tumors, while young Asian patients are more prone to developing Luminal A tumors. Most genes that were found to be upregulated in younger patients are involved in important signaling pathways that promote cancer progression and metastasis, such as MAPK pathway, Reelin pathway and the PI3K/Akt pathway. Conclusion: This study provides strong evidence that the molecular profile of tumors derived from young breast cancer patients of different populations is unique and may explain the aggressiveness of these tumors, stressing the need to conduct population- based multi-omic analyses to identify the potential drivers for tumorigenesis and molecular profiles of young breast cancer patients. Frontiers Media S.A. 2023-01-04 /pmc/articles/PMC9845274/ /pubmed/36685821 http://dx.doi.org/10.3389/fgene.2022.1039037 Text en Copyright © 2023 Tabbal, Hachim, Jan and Adrian. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Tabbal, Marah Hachim, Mahmood Y. Jan, Reem Kais Adrian, Thomas E. Using publicly available datasets to identify population-based transcriptomic landscape contributing to the aggressiveness of breast cancer in young women |
title | Using publicly available datasets to identify population-based transcriptomic landscape contributing to the aggressiveness of breast cancer in young women |
title_full | Using publicly available datasets to identify population-based transcriptomic landscape contributing to the aggressiveness of breast cancer in young women |
title_fullStr | Using publicly available datasets to identify population-based transcriptomic landscape contributing to the aggressiveness of breast cancer in young women |
title_full_unstemmed | Using publicly available datasets to identify population-based transcriptomic landscape contributing to the aggressiveness of breast cancer in young women |
title_short | Using publicly available datasets to identify population-based transcriptomic landscape contributing to the aggressiveness of breast cancer in young women |
title_sort | using publicly available datasets to identify population-based transcriptomic landscape contributing to the aggressiveness of breast cancer in young women |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9845274/ https://www.ncbi.nlm.nih.gov/pubmed/36685821 http://dx.doi.org/10.3389/fgene.2022.1039037 |
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