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Identification of characteristic metabolic panels for different stages of prostate cancer by (1)H NMR-based metabolomics analysis

BACKGROUND: Prostate cancer (PCa) is the second most prevalent cancer in males worldwide, yet detecting PCa and its metastases remains a major challenging task in clinical research setups. The present study aimed to characterize the metabolic changes underlying the PCa progression and investigate th...

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Autores principales: Zhang, Xi, Xia, Binbin, Zheng, Hong, Ning, Jie, Zhu, Yinjie, Shao, Xiaoguang, Liu, Binrui, Dong, Baijun, Gao, Hongchang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205125/
https://www.ncbi.nlm.nih.gov/pubmed/35715864
http://dx.doi.org/10.1186/s12967-022-03478-5
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author Zhang, Xi
Xia, Binbin
Zheng, Hong
Ning, Jie
Zhu, Yinjie
Shao, Xiaoguang
Liu, Binrui
Dong, Baijun
Gao, Hongchang
author_facet Zhang, Xi
Xia, Binbin
Zheng, Hong
Ning, Jie
Zhu, Yinjie
Shao, Xiaoguang
Liu, Binrui
Dong, Baijun
Gao, Hongchang
author_sort Zhang, Xi
collection PubMed
description BACKGROUND: Prostate cancer (PCa) is the second most prevalent cancer in males worldwide, yet detecting PCa and its metastases remains a major challenging task in clinical research setups. The present study aimed to characterize the metabolic changes underlying the PCa progression and investigate the efficacy of related metabolic panels for an accurate PCa assessment. METHODS: In the present study, 75 PCa subjects, 62 PCa patients with bone metastasis (PCaB), and 50 benign prostatic hyperplasia (BPH) patients were enrolled, and we performed a cross-sectional metabolomics analysis of serum samples collected from these subjects using a (1)H nuclear magnetic resonance (NMR)-based metabolomics approach. RESULTS: Multivariate analysis revealed that BPH, PCa, and PCaB groups showed distinct metabolic divisions, while univariate statistics integrated with variable importance in the projection (VIP) scores identified a differential metabolite series, which included energy, amino acid, and ketone body metabolism. Herein, we identified a series of characteristic serum metabolic changes, including decreased trends of 3-HB and acetone as well as elevated trends of alanine in PCa patients compared with BPH subjects, while increased levels of 3-HB and acetone as well as decreased levels of alanine in PCaB patients compared with PCa. Additionally, our results also revealed the metabolic panels of discriminant metabolites coupled with the clinical parameters (age and body mass index) for discrimination between PCa and BPH, PCaB and BPH, PCaB and PCa achieved the AUC values of 0.828, 0.917, and 0.872, respectively. CONCLUSIONS: Overall, our study gave successful discrimination of BPH, PCa and PCaB, and we characterized the potential metabolic alterations involved in the PCa progression and its metastases, including 3-HB, acetone and alanine. The defined biomarker panels could be employed to aid in the diagnosis and classification of PCa in clinical practice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03478-5.
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spelling pubmed-92051252022-06-18 Identification of characteristic metabolic panels for different stages of prostate cancer by (1)H NMR-based metabolomics analysis Zhang, Xi Xia, Binbin Zheng, Hong Ning, Jie Zhu, Yinjie Shao, Xiaoguang Liu, Binrui Dong, Baijun Gao, Hongchang J Transl Med Research BACKGROUND: Prostate cancer (PCa) is the second most prevalent cancer in males worldwide, yet detecting PCa and its metastases remains a major challenging task in clinical research setups. The present study aimed to characterize the metabolic changes underlying the PCa progression and investigate the efficacy of related metabolic panels for an accurate PCa assessment. METHODS: In the present study, 75 PCa subjects, 62 PCa patients with bone metastasis (PCaB), and 50 benign prostatic hyperplasia (BPH) patients were enrolled, and we performed a cross-sectional metabolomics analysis of serum samples collected from these subjects using a (1)H nuclear magnetic resonance (NMR)-based metabolomics approach. RESULTS: Multivariate analysis revealed that BPH, PCa, and PCaB groups showed distinct metabolic divisions, while univariate statistics integrated with variable importance in the projection (VIP) scores identified a differential metabolite series, which included energy, amino acid, and ketone body metabolism. Herein, we identified a series of characteristic serum metabolic changes, including decreased trends of 3-HB and acetone as well as elevated trends of alanine in PCa patients compared with BPH subjects, while increased levels of 3-HB and acetone as well as decreased levels of alanine in PCaB patients compared with PCa. Additionally, our results also revealed the metabolic panels of discriminant metabolites coupled with the clinical parameters (age and body mass index) for discrimination between PCa and BPH, PCaB and BPH, PCaB and PCa achieved the AUC values of 0.828, 0.917, and 0.872, respectively. CONCLUSIONS: Overall, our study gave successful discrimination of BPH, PCa and PCaB, and we characterized the potential metabolic alterations involved in the PCa progression and its metastases, including 3-HB, acetone and alanine. The defined biomarker panels could be employed to aid in the diagnosis and classification of PCa in clinical practice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03478-5. BioMed Central 2022-06-17 /pmc/articles/PMC9205125/ /pubmed/35715864 http://dx.doi.org/10.1186/s12967-022-03478-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhang, Xi
Xia, Binbin
Zheng, Hong
Ning, Jie
Zhu, Yinjie
Shao, Xiaoguang
Liu, Binrui
Dong, Baijun
Gao, Hongchang
Identification of characteristic metabolic panels for different stages of prostate cancer by (1)H NMR-based metabolomics analysis
title Identification of characteristic metabolic panels for different stages of prostate cancer by (1)H NMR-based metabolomics analysis
title_full Identification of characteristic metabolic panels for different stages of prostate cancer by (1)H NMR-based metabolomics analysis
title_fullStr Identification of characteristic metabolic panels for different stages of prostate cancer by (1)H NMR-based metabolomics analysis
title_full_unstemmed Identification of characteristic metabolic panels for different stages of prostate cancer by (1)H NMR-based metabolomics analysis
title_short Identification of characteristic metabolic panels for different stages of prostate cancer by (1)H NMR-based metabolomics analysis
title_sort identification of characteristic metabolic panels for different stages of prostate cancer by (1)h nmr-based metabolomics analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9205125/
https://www.ncbi.nlm.nih.gov/pubmed/35715864
http://dx.doi.org/10.1186/s12967-022-03478-5
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