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Comprehensive evaluation of cell death-related genes as novel diagnostic biomarkers for breast cancer

BACKGROUND: Breast cancer (BRCA) ranks first among cancers in terms of incidence and mortality rates in women, primarily owing to metastasis, chemo-resistance, and heterogeneity. To predict long-term prognosis and design novel therapies for BRCA, more sensitive markers need to be explored. METHODS:...

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Autores principales: Shi, Xiaoyue, Ding, Hao, Tao, Jing, Zhu, Yanhui, Zhang, Xiaoqiang, He, Gao, Yang, Junzhe, Wu, Xian, Liu, Xiaoan, Yu, Xiafei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10643282/
https://www.ncbi.nlm.nih.gov/pubmed/38027811
http://dx.doi.org/10.1016/j.heliyon.2023.e21341
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author Shi, Xiaoyue
Ding, Hao
Tao, Jing
Zhu, Yanhui
Zhang, Xiaoqiang
He, Gao
Yang, Junzhe
Wu, Xian
Liu, Xiaoan
Yu, Xiafei
author_facet Shi, Xiaoyue
Ding, Hao
Tao, Jing
Zhu, Yanhui
Zhang, Xiaoqiang
He, Gao
Yang, Junzhe
Wu, Xian
Liu, Xiaoan
Yu, Xiafei
author_sort Shi, Xiaoyue
collection PubMed
description BACKGROUND: Breast cancer (BRCA) ranks first among cancers in terms of incidence and mortality rates in women, primarily owing to metastasis, chemo-resistance, and heterogeneity. To predict long-term prognosis and design novel therapies for BRCA, more sensitive markers need to be explored. METHODS: Data from 1089 BRCA patients were downloaded from TCGA database. Pearson's correlation analysis and univariate and multivariate Cox regression analyses were performed to assess the role of cell death-related genes (CDGs) in predicting BRCA prognosis. Kaplan–Meier survival curves were generated to compare the overall survival in the two subgroups. A nomogram was constructed using risk scores based on the five CDGs and other clinicopathological features. CCK-8, EdU incorporation, and colony formation assays were performed to verify the inhibitory effect of NFKBIA on BRCA cell proliferation. Transwell assay, flow cytometry, and immunohistochemistry analyses were performed to ascertain the biological function of NFKBIA. RESULTS: Five differentially expressed CDGs were detected among 156 CDGs. The risk score for each patient was then calculated based on the expression levels of the five CDGs. Distinct differences in immune infiltration, expression of immune-oncological targets, mutation status, and half-maximal inhibitory concentration values of some targeted drugs were observed between the high- and low-risk groups. Finally, in vitro cell experiments verified that NFKBIA overexpression suppresses the proliferation and migration of BRCA cells. CONCLUSIONS: Our study revealed that some CDGs, especially NFKBIA, could serve as sensitive markers for predicting the prognosis of patients with BRCA and designing more personalized clinical therapies.
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spelling pubmed-106432822023-10-28 Comprehensive evaluation of cell death-related genes as novel diagnostic biomarkers for breast cancer Shi, Xiaoyue Ding, Hao Tao, Jing Zhu, Yanhui Zhang, Xiaoqiang He, Gao Yang, Junzhe Wu, Xian Liu, Xiaoan Yu, Xiafei Heliyon Research Article BACKGROUND: Breast cancer (BRCA) ranks first among cancers in terms of incidence and mortality rates in women, primarily owing to metastasis, chemo-resistance, and heterogeneity. To predict long-term prognosis and design novel therapies for BRCA, more sensitive markers need to be explored. METHODS: Data from 1089 BRCA patients were downloaded from TCGA database. Pearson's correlation analysis and univariate and multivariate Cox regression analyses were performed to assess the role of cell death-related genes (CDGs) in predicting BRCA prognosis. Kaplan–Meier survival curves were generated to compare the overall survival in the two subgroups. A nomogram was constructed using risk scores based on the five CDGs and other clinicopathological features. CCK-8, EdU incorporation, and colony formation assays were performed to verify the inhibitory effect of NFKBIA on BRCA cell proliferation. Transwell assay, flow cytometry, and immunohistochemistry analyses were performed to ascertain the biological function of NFKBIA. RESULTS: Five differentially expressed CDGs were detected among 156 CDGs. The risk score for each patient was then calculated based on the expression levels of the five CDGs. Distinct differences in immune infiltration, expression of immune-oncological targets, mutation status, and half-maximal inhibitory concentration values of some targeted drugs were observed between the high- and low-risk groups. Finally, in vitro cell experiments verified that NFKBIA overexpression suppresses the proliferation and migration of BRCA cells. CONCLUSIONS: Our study revealed that some CDGs, especially NFKBIA, could serve as sensitive markers for predicting the prognosis of patients with BRCA and designing more personalized clinical therapies. Elsevier 2023-10-28 /pmc/articles/PMC10643282/ /pubmed/38027811 http://dx.doi.org/10.1016/j.heliyon.2023.e21341 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Shi, Xiaoyue
Ding, Hao
Tao, Jing
Zhu, Yanhui
Zhang, Xiaoqiang
He, Gao
Yang, Junzhe
Wu, Xian
Liu, Xiaoan
Yu, Xiafei
Comprehensive evaluation of cell death-related genes as novel diagnostic biomarkers for breast cancer
title Comprehensive evaluation of cell death-related genes as novel diagnostic biomarkers for breast cancer
title_full Comprehensive evaluation of cell death-related genes as novel diagnostic biomarkers for breast cancer
title_fullStr Comprehensive evaluation of cell death-related genes as novel diagnostic biomarkers for breast cancer
title_full_unstemmed Comprehensive evaluation of cell death-related genes as novel diagnostic biomarkers for breast cancer
title_short Comprehensive evaluation of cell death-related genes as novel diagnostic biomarkers for breast cancer
title_sort comprehensive evaluation of cell death-related genes as novel diagnostic biomarkers for breast cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10643282/
https://www.ncbi.nlm.nih.gov/pubmed/38027811
http://dx.doi.org/10.1016/j.heliyon.2023.e21341
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