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Ferroptosis and triple-negative breast cancer: Potential therapeutic targets

PURPOSE: Triple-negative breast cancer (TNBC) is an aggressive tumor with poor prognosis, it has higher recurrence and metastatic rates than other breast cancer subtypes. This study aims to investigate biomarkers and potential targets for TNBC related to ferroptosis through data mining and bioinform...

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Autores principales: Xu, Na, Li, Baohong, Liu, Yong, Yang, Cui, Tang, Siqi, Cho, William C., Huang, Zunnan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780505/
https://www.ncbi.nlm.nih.gov/pubmed/36568247
http://dx.doi.org/10.3389/fonc.2022.1017041
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author Xu, Na
Li, Baohong
Liu, Yong
Yang, Cui
Tang, Siqi
Cho, William C.
Huang, Zunnan
author_facet Xu, Na
Li, Baohong
Liu, Yong
Yang, Cui
Tang, Siqi
Cho, William C.
Huang, Zunnan
author_sort Xu, Na
collection PubMed
description PURPOSE: Triple-negative breast cancer (TNBC) is an aggressive tumor with poor prognosis, it has higher recurrence and metastatic rates than other breast cancer subtypes. This study aims to investigate biomarkers and potential targets for TNBC related to ferroptosis through data mining and bioinformatics analysis. The findings may provide new insights for treating TNBC. METHODS: The TNBC patients’ data from the Cancer Genome Atlas (TCGA) database were extracted for differential expression and prognosis analysis. Consensus genes obtained by intersecting differential expressed and ferroptosis-related genes was used to establish the prognostic model by the univariate and multivariate Cox analyses. Besides, TNBC data from the Gene Expression Omnibus (GEO) database was used to confirm the reliability of the prognosis model. Moreover, clinical information was analyzed by multifactorial independent analysis to identify independent prognostic factors. The expression of genes constituting the prognostic model was further validated using the Human Protein Atlas (HPA) database. Finally, the Comparative Toxicogenomic Data (CTD) database was used to explore possible treatment drugs for TNBC. RESULTS: We obtained 13,245 differential expressed genes, and 177 consensus genes. 98 genes with prognostic implication were obtained by univariable Cox. Then, a prognostic model including 12 ferroptosis-related genes was constructed by multivariable Cox. The area under curve (AUC) value of the prognostic model for TNBC was 0.82. The GEO database validated that the model (AUC = 0.77) could predict the patient outcomes. The staining results of 10 out of 12 prognostic model genes in HPA database showed that their expression was consistent with our predictions. Clinical risk analysis indicated that risk score of patients could act as an independent prognostic factor. Finally, six drugs that may have interaction with 12 ferroptosis-related genes were obtained using the CTD database. CONCLUSION: The prognostic model composed of 12 ferroptosis-related genes could predict the prognosis of TNBC patients, and seven genes (ASNS, LAMP2, CAV1, DPP4, HELLS, TF, ZFP69B) could be potential new therapeutic targets for TNBC, and two drugs (1-methyl-3-isobutylxanthine, rosiglitazone) could act as potential therapeutic drugs for the treatment of TNBC.
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spelling pubmed-97805052022-12-24 Ferroptosis and triple-negative breast cancer: Potential therapeutic targets Xu, Na Li, Baohong Liu, Yong Yang, Cui Tang, Siqi Cho, William C. Huang, Zunnan Front Oncol Oncology PURPOSE: Triple-negative breast cancer (TNBC) is an aggressive tumor with poor prognosis, it has higher recurrence and metastatic rates than other breast cancer subtypes. This study aims to investigate biomarkers and potential targets for TNBC related to ferroptosis through data mining and bioinformatics analysis. The findings may provide new insights for treating TNBC. METHODS: The TNBC patients’ data from the Cancer Genome Atlas (TCGA) database were extracted for differential expression and prognosis analysis. Consensus genes obtained by intersecting differential expressed and ferroptosis-related genes was used to establish the prognostic model by the univariate and multivariate Cox analyses. Besides, TNBC data from the Gene Expression Omnibus (GEO) database was used to confirm the reliability of the prognosis model. Moreover, clinical information was analyzed by multifactorial independent analysis to identify independent prognostic factors. The expression of genes constituting the prognostic model was further validated using the Human Protein Atlas (HPA) database. Finally, the Comparative Toxicogenomic Data (CTD) database was used to explore possible treatment drugs for TNBC. RESULTS: We obtained 13,245 differential expressed genes, and 177 consensus genes. 98 genes with prognostic implication were obtained by univariable Cox. Then, a prognostic model including 12 ferroptosis-related genes was constructed by multivariable Cox. The area under curve (AUC) value of the prognostic model for TNBC was 0.82. The GEO database validated that the model (AUC = 0.77) could predict the patient outcomes. The staining results of 10 out of 12 prognostic model genes in HPA database showed that their expression was consistent with our predictions. Clinical risk analysis indicated that risk score of patients could act as an independent prognostic factor. Finally, six drugs that may have interaction with 12 ferroptosis-related genes were obtained using the CTD database. CONCLUSION: The prognostic model composed of 12 ferroptosis-related genes could predict the prognosis of TNBC patients, and seven genes (ASNS, LAMP2, CAV1, DPP4, HELLS, TF, ZFP69B) could be potential new therapeutic targets for TNBC, and two drugs (1-methyl-3-isobutylxanthine, rosiglitazone) could act as potential therapeutic drugs for the treatment of TNBC. Frontiers Media S.A. 2022-12-09 /pmc/articles/PMC9780505/ /pubmed/36568247 http://dx.doi.org/10.3389/fonc.2022.1017041 Text en Copyright © 2022 Xu, Li, Liu, Yang, Tang, Cho and Huang 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 Oncology
Xu, Na
Li, Baohong
Liu, Yong
Yang, Cui
Tang, Siqi
Cho, William C.
Huang, Zunnan
Ferroptosis and triple-negative breast cancer: Potential therapeutic targets
title Ferroptosis and triple-negative breast cancer: Potential therapeutic targets
title_full Ferroptosis and triple-negative breast cancer: Potential therapeutic targets
title_fullStr Ferroptosis and triple-negative breast cancer: Potential therapeutic targets
title_full_unstemmed Ferroptosis and triple-negative breast cancer: Potential therapeutic targets
title_short Ferroptosis and triple-negative breast cancer: Potential therapeutic targets
title_sort ferroptosis and triple-negative breast cancer: potential therapeutic targets
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780505/
https://www.ncbi.nlm.nih.gov/pubmed/36568247
http://dx.doi.org/10.3389/fonc.2022.1017041
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