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Tumor senescence leads to poor survival and therapeutic resistance in human breast cancer

BACKGROUND: Breast cancer (BRCA) is the most common malignant tumor that seriously threatens the health of women worldwide. Senescence has been suggested as a pivotal player in the onset and progression of tumors as well as the process of treatment resistance. However, the role of senescence in BRCA...

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Autores principales: Zhai, Jingtong, Han, Jiashu, Li, Cong, Lv, Dan, Ma, Fei, Xu, Binghe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019818/
https://www.ncbi.nlm.nih.gov/pubmed/36937388
http://dx.doi.org/10.3389/fonc.2023.1097513
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author Zhai, Jingtong
Han, Jiashu
Li, Cong
Lv, Dan
Ma, Fei
Xu, Binghe
author_facet Zhai, Jingtong
Han, Jiashu
Li, Cong
Lv, Dan
Ma, Fei
Xu, Binghe
author_sort Zhai, Jingtong
collection PubMed
description BACKGROUND: Breast cancer (BRCA) is the most common malignant tumor that seriously threatens the health of women worldwide. Senescence has been suggested as a pivotal player in the onset and progression of tumors as well as the process of treatment resistance. However, the role of senescence in BRCA remains unelucidated. METHODS: The clinical and transcriptomic data of 2994 patients with BRCA were obtained from The Cancer Genome Atlas and the METABRIC databases. Consensus clustering revealed senescence-associated subtypes of BRCA patients. Functional enrichment analysis explored biological effect of senescence. We then applied weighted gene co-expression network analysis (WGCNA) and LASSO regression to construct a senescence scoring model, Sindex. Survival analysis validated the effectiveness of Sindex to predict the overall survival (OS) of patients with BRCA. A nomogram was constructed by multivariate Cox regression. We used Oncopredict algorithm and real-world data from clinical trials to explore the value of Sindex in predicting response to cancer therapy. RESULTS: We identified two distinct senescence-associated subtypes, noted low senescence CC1 and high senescence CC2. Survival analysis revealed worse OS associated with high senescence, which was also validated with patient samples from the National Cancer Center in China. Further analysis revealed extensively cell division and suppression of extracellular matrix process, along with lower stromal and immune scores in the high senescence CC2. We then constructed a 37 signature gene scoring model, Sindex, with robust predictive capability in patients with BRCA, especially for long time OS beyond 10 years. We demonstrated that the Sene-high subtype was resistant to CDK inhibitors but sensitive to proteosome inhibitors, and there was no significant difference in paclitaxel chemotherapy and immunotherapy between patients with different senescence statuses. CONCLUSIONS: We reported senescence as a previously uncharacterized hallmark of BRCA that impacts patient outcomes and therapeutic response. Our analysis demonstrated that the Sindex can be used to identify not only patients at different risk levels for the OS but also patients who would benefit from some cancer therapeutic drugs.
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spelling pubmed-100198182023-03-17 Tumor senescence leads to poor survival and therapeutic resistance in human breast cancer Zhai, Jingtong Han, Jiashu Li, Cong Lv, Dan Ma, Fei Xu, Binghe Front Oncol Oncology BACKGROUND: Breast cancer (BRCA) is the most common malignant tumor that seriously threatens the health of women worldwide. Senescence has been suggested as a pivotal player in the onset and progression of tumors as well as the process of treatment resistance. However, the role of senescence in BRCA remains unelucidated. METHODS: The clinical and transcriptomic data of 2994 patients with BRCA were obtained from The Cancer Genome Atlas and the METABRIC databases. Consensus clustering revealed senescence-associated subtypes of BRCA patients. Functional enrichment analysis explored biological effect of senescence. We then applied weighted gene co-expression network analysis (WGCNA) and LASSO regression to construct a senescence scoring model, Sindex. Survival analysis validated the effectiveness of Sindex to predict the overall survival (OS) of patients with BRCA. A nomogram was constructed by multivariate Cox regression. We used Oncopredict algorithm and real-world data from clinical trials to explore the value of Sindex in predicting response to cancer therapy. RESULTS: We identified two distinct senescence-associated subtypes, noted low senescence CC1 and high senescence CC2. Survival analysis revealed worse OS associated with high senescence, which was also validated with patient samples from the National Cancer Center in China. Further analysis revealed extensively cell division and suppression of extracellular matrix process, along with lower stromal and immune scores in the high senescence CC2. We then constructed a 37 signature gene scoring model, Sindex, with robust predictive capability in patients with BRCA, especially for long time OS beyond 10 years. We demonstrated that the Sene-high subtype was resistant to CDK inhibitors but sensitive to proteosome inhibitors, and there was no significant difference in paclitaxel chemotherapy and immunotherapy between patients with different senescence statuses. CONCLUSIONS: We reported senescence as a previously uncharacterized hallmark of BRCA that impacts patient outcomes and therapeutic response. Our analysis demonstrated that the Sindex can be used to identify not only patients at different risk levels for the OS but also patients who would benefit from some cancer therapeutic drugs. Frontiers Media S.A. 2023-03-02 /pmc/articles/PMC10019818/ /pubmed/36937388 http://dx.doi.org/10.3389/fonc.2023.1097513 Text en Copyright © 2023 Zhai, Han, Li, Lv, Ma and Xu 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
Zhai, Jingtong
Han, Jiashu
Li, Cong
Lv, Dan
Ma, Fei
Xu, Binghe
Tumor senescence leads to poor survival and therapeutic resistance in human breast cancer
title Tumor senescence leads to poor survival and therapeutic resistance in human breast cancer
title_full Tumor senescence leads to poor survival and therapeutic resistance in human breast cancer
title_fullStr Tumor senescence leads to poor survival and therapeutic resistance in human breast cancer
title_full_unstemmed Tumor senescence leads to poor survival and therapeutic resistance in human breast cancer
title_short Tumor senescence leads to poor survival and therapeutic resistance in human breast cancer
title_sort tumor senescence leads to poor survival and therapeutic resistance in human breast cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019818/
https://www.ncbi.nlm.nih.gov/pubmed/36937388
http://dx.doi.org/10.3389/fonc.2023.1097513
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