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A novel gene signature to predict immune infiltration and outcome in patients with prostate cancer

Prostate cancer (PCa) is one of the most common malignancies in male. We aim to establish a novel gene signature for immune infiltration and outcome (biochemical recurrence (BCR) and overall survival (OS)) of patients with prostate cancer (PCa) to augment Gleason patterns for evaluating prognosis an...

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Autores principales: Shao, Ning, Tang, Hong, Mi, Yuanyuan, Zhu, Yao, Wan, Fangning, Ye, Dingwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7458664/
https://www.ncbi.nlm.nih.gov/pubmed/32923125
http://dx.doi.org/10.1080/2162402X.2020.1762473
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author Shao, Ning
Tang, Hong
Mi, Yuanyuan
Zhu, Yao
Wan, Fangning
Ye, Dingwei
author_facet Shao, Ning
Tang, Hong
Mi, Yuanyuan
Zhu, Yao
Wan, Fangning
Ye, Dingwei
author_sort Shao, Ning
collection PubMed
description Prostate cancer (PCa) is one of the most common malignancies in male. We aim to establish a novel gene signature for immune infiltration and outcome (biochemical recurrence (BCR) and overall survival (OS)) of patients with prostate cancer (PCa) to augment Gleason patterns for evaluating prognosis and managing patients undergoing radical prostatectomy (RP). Combined with our microarray data and the Cancer Genome Atlas Project (TCGA) database (discovery set), we identified a six-gene signature. The Gene Expression Omnibus (GEO) database served as the test set. The databases of Fudan University Shanghai Cancer Center (FUSCC) and Third Affiliated Hospital of Nantong University (TAHNU) served as an external validation set. Immunohistochemistry was used to investigate the relationship between risk groups and the immune infiltrate. We identified a six-gene signature to predict immune cell infiltration and outcome of PCa patients. The AUC values used to predict early BCR in the discovery, test, FUSCC, and TAHNU sets were 0.73, 0.76, 0.72, and 0.81, respectively. Low-risk score patients in each dataset experienced significantly longer OS (P = .01, 0.04, 0.02, respectively). The signature also predicted high regulatory T cells (Tregs) and M2-polarized macrophages infiltration in high-risk score patients with PCa. Additionally, high mutation load, related signal pathways, and sensitivity to anticancer drugs that correlated with high-risk score of cancer progression and death were also identified. The six-gene signature may improve prognostic information, serve as a prognostic tool to manage patients after RP, and advance basic studies of PCa.
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spelling pubmed-74586642020-09-11 A novel gene signature to predict immune infiltration and outcome in patients with prostate cancer Shao, Ning Tang, Hong Mi, Yuanyuan Zhu, Yao Wan, Fangning Ye, Dingwei Oncoimmunology Original Research Prostate cancer (PCa) is one of the most common malignancies in male. We aim to establish a novel gene signature for immune infiltration and outcome (biochemical recurrence (BCR) and overall survival (OS)) of patients with prostate cancer (PCa) to augment Gleason patterns for evaluating prognosis and managing patients undergoing radical prostatectomy (RP). Combined with our microarray data and the Cancer Genome Atlas Project (TCGA) database (discovery set), we identified a six-gene signature. The Gene Expression Omnibus (GEO) database served as the test set. The databases of Fudan University Shanghai Cancer Center (FUSCC) and Third Affiliated Hospital of Nantong University (TAHNU) served as an external validation set. Immunohistochemistry was used to investigate the relationship between risk groups and the immune infiltrate. We identified a six-gene signature to predict immune cell infiltration and outcome of PCa patients. The AUC values used to predict early BCR in the discovery, test, FUSCC, and TAHNU sets were 0.73, 0.76, 0.72, and 0.81, respectively. Low-risk score patients in each dataset experienced significantly longer OS (P = .01, 0.04, 0.02, respectively). The signature also predicted high regulatory T cells (Tregs) and M2-polarized macrophages infiltration in high-risk score patients with PCa. Additionally, high mutation load, related signal pathways, and sensitivity to anticancer drugs that correlated with high-risk score of cancer progression and death were also identified. The six-gene signature may improve prognostic information, serve as a prognostic tool to manage patients after RP, and advance basic studies of PCa. Taylor & Francis 2020-06-01 /pmc/articles/PMC7458664/ /pubmed/32923125 http://dx.doi.org/10.1080/2162402X.2020.1762473 Text en © 2020 The Author(s). Published with license by Taylor & Francis Group, LLC. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Shao, Ning
Tang, Hong
Mi, Yuanyuan
Zhu, Yao
Wan, Fangning
Ye, Dingwei
A novel gene signature to predict immune infiltration and outcome in patients with prostate cancer
title A novel gene signature to predict immune infiltration and outcome in patients with prostate cancer
title_full A novel gene signature to predict immune infiltration and outcome in patients with prostate cancer
title_fullStr A novel gene signature to predict immune infiltration and outcome in patients with prostate cancer
title_full_unstemmed A novel gene signature to predict immune infiltration and outcome in patients with prostate cancer
title_short A novel gene signature to predict immune infiltration and outcome in patients with prostate cancer
title_sort novel gene signature to predict immune infiltration and outcome in patients with prostate cancer
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7458664/
https://www.ncbi.nlm.nih.gov/pubmed/32923125
http://dx.doi.org/10.1080/2162402X.2020.1762473
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