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Serum Metabolic Profiling Identifies a Biomarker Panel for Improvement of Prostate Cancer Diagnosis

OBJECTIVES: To identify and validate a biomarker panel by serum metabolic profiling for improvement of PCa diagnosis. MATERIALS AND METHODS: Totally, 134 individuals were included in this study. Among them, 39 PCa patients and 45 control patients (negative prostate biopsy) were involved in the disco...

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Autores principales: Xu, Huan, Chen, Junyi, He, Jingyi, Ji, Jin, Cao, Zhi, Chen, Xi, Xu, Yalong, He, Xing, Xu, Guowang, Zhou, Lina, Wei, Xuedong, Hou, Jianquan, Wang, Zhong, Yang, Bo, Wang, Fubo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138432/
https://www.ncbi.nlm.nih.gov/pubmed/34026644
http://dx.doi.org/10.3389/fonc.2021.666320
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author Xu, Huan
Chen, Junyi
He, Jingyi
Ji, Jin
Cao, Zhi
Chen, Xi
Xu, Yalong
He, Xing
Xu, Guowang
Zhou, Lina
Wei, Xuedong
Hou, Jianquan
Wang, Zhong
Yang, Bo
Wang, Fubo
author_facet Xu, Huan
Chen, Junyi
He, Jingyi
Ji, Jin
Cao, Zhi
Chen, Xi
Xu, Yalong
He, Xing
Xu, Guowang
Zhou, Lina
Wei, Xuedong
Hou, Jianquan
Wang, Zhong
Yang, Bo
Wang, Fubo
author_sort Xu, Huan
collection PubMed
description OBJECTIVES: To identify and validate a biomarker panel by serum metabolic profiling for improvement of PCa diagnosis. MATERIALS AND METHODS: Totally, 134 individuals were included in this study. Among them, 39 PCa patients and 45 control patients (negative prostate biopsy) were involved in the discovery phase and 50 healthy controls were enrolled for validation phase of metabolomics study. LC-MS Analysis was used for the identification of the serum metabolites of patients. RESULTS: Logistics regression analysis shows that 5 metabolites [dMePE(18:0/18:2), PC(16:0/20:2), PS(15:0/18:2), SM(d16:0/24:1], Carnitine C14:0) were significantly changed in PCa patients compared with control patients. A metabolic panel (MET) was calculated, showing a significantly higher diagnostic performance than PSA in differentiating PCa from control patients [AUC (MET vs. PSA): 0.823 ± 0.046 vs. 0.712 ± 0.057, p<0.001]. Moreover, this panel was superior to PSA in distinguishing PCa from negative prostate biopsies when PSA levels were less than 20 ng/ml [AUC (MET vs. PSA]: 0.836 ± 0.050 vs. 0.656 ± 0.067, p<0.001]. In the validation set, the MET panel yielded an AUC of 0.823 in distinguishing PCa patients from healthy controls, showing a significant improvement of PCa detection. CONCLUSIONS: The metabolite biomarker panel discovered in this study presents a good diagnostic performance for the detection of PCa.
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spelling pubmed-81384322021-05-22 Serum Metabolic Profiling Identifies a Biomarker Panel for Improvement of Prostate Cancer Diagnosis Xu, Huan Chen, Junyi He, Jingyi Ji, Jin Cao, Zhi Chen, Xi Xu, Yalong He, Xing Xu, Guowang Zhou, Lina Wei, Xuedong Hou, Jianquan Wang, Zhong Yang, Bo Wang, Fubo Front Oncol Oncology OBJECTIVES: To identify and validate a biomarker panel by serum metabolic profiling for improvement of PCa diagnosis. MATERIALS AND METHODS: Totally, 134 individuals were included in this study. Among them, 39 PCa patients and 45 control patients (negative prostate biopsy) were involved in the discovery phase and 50 healthy controls were enrolled for validation phase of metabolomics study. LC-MS Analysis was used for the identification of the serum metabolites of patients. RESULTS: Logistics regression analysis shows that 5 metabolites [dMePE(18:0/18:2), PC(16:0/20:2), PS(15:0/18:2), SM(d16:0/24:1], Carnitine C14:0) were significantly changed in PCa patients compared with control patients. A metabolic panel (MET) was calculated, showing a significantly higher diagnostic performance than PSA in differentiating PCa from control patients [AUC (MET vs. PSA): 0.823 ± 0.046 vs. 0.712 ± 0.057, p<0.001]. Moreover, this panel was superior to PSA in distinguishing PCa from negative prostate biopsies when PSA levels were less than 20 ng/ml [AUC (MET vs. PSA]: 0.836 ± 0.050 vs. 0.656 ± 0.067, p<0.001]. In the validation set, the MET panel yielded an AUC of 0.823 in distinguishing PCa patients from healthy controls, showing a significant improvement of PCa detection. CONCLUSIONS: The metabolite biomarker panel discovered in this study presents a good diagnostic performance for the detection of PCa. Frontiers Media S.A. 2021-05-07 /pmc/articles/PMC8138432/ /pubmed/34026644 http://dx.doi.org/10.3389/fonc.2021.666320 Text en Copyright © 2021 Xu, Chen, He, Ji, Cao, Chen, Xu, He, Xu, Zhou, Wei, Hou, Wang, Yang and Wang 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, Huan
Chen, Junyi
He, Jingyi
Ji, Jin
Cao, Zhi
Chen, Xi
Xu, Yalong
He, Xing
Xu, Guowang
Zhou, Lina
Wei, Xuedong
Hou, Jianquan
Wang, Zhong
Yang, Bo
Wang, Fubo
Serum Metabolic Profiling Identifies a Biomarker Panel for Improvement of Prostate Cancer Diagnosis
title Serum Metabolic Profiling Identifies a Biomarker Panel for Improvement of Prostate Cancer Diagnosis
title_full Serum Metabolic Profiling Identifies a Biomarker Panel for Improvement of Prostate Cancer Diagnosis
title_fullStr Serum Metabolic Profiling Identifies a Biomarker Panel for Improvement of Prostate Cancer Diagnosis
title_full_unstemmed Serum Metabolic Profiling Identifies a Biomarker Panel for Improvement of Prostate Cancer Diagnosis
title_short Serum Metabolic Profiling Identifies a Biomarker Panel for Improvement of Prostate Cancer Diagnosis
title_sort serum metabolic profiling identifies a biomarker panel for improvement of prostate cancer diagnosis
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138432/
https://www.ncbi.nlm.nih.gov/pubmed/34026644
http://dx.doi.org/10.3389/fonc.2021.666320
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