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Identification of molecular subtypes and a prognostic signature based on chromatin regulators related genes in prostate cancer
The clinical and molecular phenotypes of prostate cancer (PCa) exhibit substantial heterogeneity, ranging from indolent to metastatic disease. In this study, we aimed to identify PCa subtypes and construct a gene signature that can predict the recurrence-free survival (RFS) of PCa patients based on...
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/PMC9871366/ https://www.ncbi.nlm.nih.gov/pubmed/36704352 http://dx.doi.org/10.3389/fgene.2022.1110723 |
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author | Ma, Hangbin Zhou, Cheng Ge, Jianchao Yu, Wandong Zhou, Yinghao Wang, Pengyu Zhang, Xuehu Zhang, Jun Shi, Guowei |
author_facet | Ma, Hangbin Zhou, Cheng Ge, Jianchao Yu, Wandong Zhou, Yinghao Wang, Pengyu Zhang, Xuehu Zhang, Jun Shi, Guowei |
author_sort | Ma, Hangbin |
collection | PubMed |
description | The clinical and molecular phenotypes of prostate cancer (PCa) exhibit substantial heterogeneity, ranging from indolent to metastatic disease. In this study, we aimed to identify PCa subtypes and construct a gene signature that can predict the recurrence-free survival (RFS) of PCa patients based on chromatin regulators genes (CRGs). Strikingly, we identified two heterogeneous subtypes with distinct clinical and molecular characteristics. Furthermore, by performing differential analysis between the two CRGs subtypes, we successfully constructed a gene signature to predict PCa prognosis. The signature, comprising four genes (MXD3, SSTR1, AMH and PPFIA2), was utilized to classify PCa patients into two risk groups; the high-risk group was characterized by poor prognosis and more aggressive clinical features. Moreover, we investigated the immune profile, mutation landscape and molecular pathways in each of the groups. Additionally, drug-susceptibility testing was performed to explore sensitive drugs for high-risk patients. Furthermore, we found that MXD3 downregulation suppressed the proliferation of PCa cell lines in vitro. Overall, our results highlight the signature based on CRGs as a powerful tool for predicting RFS of PCa patients, as well as an indicator for personalized treatment of those patients. |
format | Online Article Text |
id | pubmed-9871366 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98713662023-01-25 Identification of molecular subtypes and a prognostic signature based on chromatin regulators related genes in prostate cancer Ma, Hangbin Zhou, Cheng Ge, Jianchao Yu, Wandong Zhou, Yinghao Wang, Pengyu Zhang, Xuehu Zhang, Jun Shi, Guowei Front Genet Genetics The clinical and molecular phenotypes of prostate cancer (PCa) exhibit substantial heterogeneity, ranging from indolent to metastatic disease. In this study, we aimed to identify PCa subtypes and construct a gene signature that can predict the recurrence-free survival (RFS) of PCa patients based on chromatin regulators genes (CRGs). Strikingly, we identified two heterogeneous subtypes with distinct clinical and molecular characteristics. Furthermore, by performing differential analysis between the two CRGs subtypes, we successfully constructed a gene signature to predict PCa prognosis. The signature, comprising four genes (MXD3, SSTR1, AMH and PPFIA2), was utilized to classify PCa patients into two risk groups; the high-risk group was characterized by poor prognosis and more aggressive clinical features. Moreover, we investigated the immune profile, mutation landscape and molecular pathways in each of the groups. Additionally, drug-susceptibility testing was performed to explore sensitive drugs for high-risk patients. Furthermore, we found that MXD3 downregulation suppressed the proliferation of PCa cell lines in vitro. Overall, our results highlight the signature based on CRGs as a powerful tool for predicting RFS of PCa patients, as well as an indicator for personalized treatment of those patients. Frontiers Media S.A. 2023-01-10 /pmc/articles/PMC9871366/ /pubmed/36704352 http://dx.doi.org/10.3389/fgene.2022.1110723 Text en Copyright © 2023 Ma, Zhou, Ge, Yu, Zhou, Wang, Zhang, Zhang and Shi. 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 Ma, Hangbin Zhou, Cheng Ge, Jianchao Yu, Wandong Zhou, Yinghao Wang, Pengyu Zhang, Xuehu Zhang, Jun Shi, Guowei Identification of molecular subtypes and a prognostic signature based on chromatin regulators related genes in prostate cancer |
title | Identification of molecular subtypes and a prognostic signature based on chromatin regulators related genes in prostate cancer |
title_full | Identification of molecular subtypes and a prognostic signature based on chromatin regulators related genes in prostate cancer |
title_fullStr | Identification of molecular subtypes and a prognostic signature based on chromatin regulators related genes in prostate cancer |
title_full_unstemmed | Identification of molecular subtypes and a prognostic signature based on chromatin regulators related genes in prostate cancer |
title_short | Identification of molecular subtypes and a prognostic signature based on chromatin regulators related genes in prostate cancer |
title_sort | identification of molecular subtypes and a prognostic signature based on chromatin regulators related genes in prostate cancer |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871366/ https://www.ncbi.nlm.nih.gov/pubmed/36704352 http://dx.doi.org/10.3389/fgene.2022.1110723 |
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