Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer

The complexity of breast cancer includes many interacting biological processes, and proteasome alpha (PSMA) subunits are reported to be involved in many cancerous diseases, although the transcriptomic expression of this gene family in breast cancer still needs to be more thoroughly investigated. Con...

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Autores principales: Chiao, Chung-Chieh, Liu, Yen-Hsi, Phan, Nam Nhut, An Ton, Nu Thuy, Ta, Hoang Dang Khoa, Anuraga, Gangga, Minh Xuan, Do Thi, Fitriani, Fenny, Putri Hermanto, Elvira Mustikawati, Athoillah, Muhammad, Andriani, Vivin, Ajiningrum, Purity Sabila, Wu, Yung-Fu, Lee, Kuen-Haur, Chuang, Jian-Ying, Wang, Chih-Yang, Kao, Tzu-Jen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8699889/
https://www.ncbi.nlm.nih.gov/pubmed/34943457
http://dx.doi.org/10.3390/diagnostics11122220
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author Chiao, Chung-Chieh
Liu, Yen-Hsi
Phan, Nam Nhut
An Ton, Nu Thuy
Ta, Hoang Dang Khoa
Anuraga, Gangga
Minh Xuan, Do Thi
Fitriani, Fenny
Putri Hermanto, Elvira Mustikawati
Athoillah, Muhammad
Andriani, Vivin
Ajiningrum, Purity Sabila
Wu, Yung-Fu
Lee, Kuen-Haur
Chuang, Jian-Ying
Wang, Chih-Yang
Kao, Tzu-Jen
author_facet Chiao, Chung-Chieh
Liu, Yen-Hsi
Phan, Nam Nhut
An Ton, Nu Thuy
Ta, Hoang Dang Khoa
Anuraga, Gangga
Minh Xuan, Do Thi
Fitriani, Fenny
Putri Hermanto, Elvira Mustikawati
Athoillah, Muhammad
Andriani, Vivin
Ajiningrum, Purity Sabila
Wu, Yung-Fu
Lee, Kuen-Haur
Chuang, Jian-Ying
Wang, Chih-Yang
Kao, Tzu-Jen
author_sort Chiao, Chung-Chieh
collection PubMed
description The complexity of breast cancer includes many interacting biological processes, and proteasome alpha (PSMA) subunits are reported to be involved in many cancerous diseases, although the transcriptomic expression of this gene family in breast cancer still needs to be more thoroughly investigated. Consequently, we used a holistic bioinformatics approach to study the PSMA genes involved in breast cancer by integrating several well-established high-throughput databases and tools, such as cBioPortal, Oncomine, and the Kaplan–Meier plotter. Additionally, correlations of breast cancer patient survival and PSMA messenger RNA expressions were also studied. The results demonstrated that breast cancer tissues had higher expression levels of PSMA genes compared to normal breast tissues. Furthermore, PSMA2, PSMA3, PSMA4, PSMA6, and PSMA7 showed high expression levels, which were correlated with poor survival of breast cancer patients. In contrast, PSMA5 and PSMA8 had high expression levels, which were associated with good prognoses. We also found that PSMA family genes were positively correlated with the cell cycle, ubiquinone metabolism, oxidative stress, and immune response signaling, including antigen presentation by major histocompatibility class, interferon-gamma, and the cluster of differentiation signaling. Collectively, these findings suggest that PSMA genes have the potential to serve as novel biomarkers and therapeutic targets for breast cancer. Nevertheless, the bioinformatic results from the present study would be strengthened with experimental validation in the future by prospective studies on the underlying biological mechanisms of PSMA genes and breast cancer.
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spelling pubmed-86998892021-12-24 Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer Chiao, Chung-Chieh Liu, Yen-Hsi Phan, Nam Nhut An Ton, Nu Thuy Ta, Hoang Dang Khoa Anuraga, Gangga Minh Xuan, Do Thi Fitriani, Fenny Putri Hermanto, Elvira Mustikawati Athoillah, Muhammad Andriani, Vivin Ajiningrum, Purity Sabila Wu, Yung-Fu Lee, Kuen-Haur Chuang, Jian-Ying Wang, Chih-Yang Kao, Tzu-Jen Diagnostics (Basel) Article The complexity of breast cancer includes many interacting biological processes, and proteasome alpha (PSMA) subunits are reported to be involved in many cancerous diseases, although the transcriptomic expression of this gene family in breast cancer still needs to be more thoroughly investigated. Consequently, we used a holistic bioinformatics approach to study the PSMA genes involved in breast cancer by integrating several well-established high-throughput databases and tools, such as cBioPortal, Oncomine, and the Kaplan–Meier plotter. Additionally, correlations of breast cancer patient survival and PSMA messenger RNA expressions were also studied. The results demonstrated that breast cancer tissues had higher expression levels of PSMA genes compared to normal breast tissues. Furthermore, PSMA2, PSMA3, PSMA4, PSMA6, and PSMA7 showed high expression levels, which were correlated with poor survival of breast cancer patients. In contrast, PSMA5 and PSMA8 had high expression levels, which were associated with good prognoses. We also found that PSMA family genes were positively correlated with the cell cycle, ubiquinone metabolism, oxidative stress, and immune response signaling, including antigen presentation by major histocompatibility class, interferon-gamma, and the cluster of differentiation signaling. Collectively, these findings suggest that PSMA genes have the potential to serve as novel biomarkers and therapeutic targets for breast cancer. Nevertheless, the bioinformatic results from the present study would be strengthened with experimental validation in the future by prospective studies on the underlying biological mechanisms of PSMA genes and breast cancer. MDPI 2021-11-27 /pmc/articles/PMC8699889/ /pubmed/34943457 http://dx.doi.org/10.3390/diagnostics11122220 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chiao, Chung-Chieh
Liu, Yen-Hsi
Phan, Nam Nhut
An Ton, Nu Thuy
Ta, Hoang Dang Khoa
Anuraga, Gangga
Minh Xuan, Do Thi
Fitriani, Fenny
Putri Hermanto, Elvira Mustikawati
Athoillah, Muhammad
Andriani, Vivin
Ajiningrum, Purity Sabila
Wu, Yung-Fu
Lee, Kuen-Haur
Chuang, Jian-Ying
Wang, Chih-Yang
Kao, Tzu-Jen
Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer
title Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer
title_full Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer
title_fullStr Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer
title_full_unstemmed Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer
title_short Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer
title_sort prognostic and genomic analysis of proteasome 20s subunit alpha (psma) family members in breast cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8699889/
https://www.ncbi.nlm.nih.gov/pubmed/34943457
http://dx.doi.org/10.3390/diagnostics11122220
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