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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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Detalles Bibliográficos
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
Descripción
Sumario: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.