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Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer
Pancreatic cancer (PC) is burdened with a low 5-year survival rate and high mortality due to a severe lack of early diagnosis methods and slow progress in treatment options. To improve clinical diagnosis and enhance the treatment effects, we applied metabolomics using ultra-high-performance liquid c...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9479084/ https://www.ncbi.nlm.nih.gov/pubmed/36119530 http://dx.doi.org/10.3389/fonc.2022.991051 |
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author | Liu, Chang Qin, Henan Liu, Huiying Wei, Tianfu Wu, Zeming Shang, Mengxue Liu, Haihua Wang, Aman Liu, Jiwei Shang, Dong Yin, Peiyuan |
author_facet | Liu, Chang Qin, Henan Liu, Huiying Wei, Tianfu Wu, Zeming Shang, Mengxue Liu, Haihua Wang, Aman Liu, Jiwei Shang, Dong Yin, Peiyuan |
author_sort | Liu, Chang |
collection | PubMed |
description | Pancreatic cancer (PC) is burdened with a low 5-year survival rate and high mortality due to a severe lack of early diagnosis methods and slow progress in treatment options. To improve clinical diagnosis and enhance the treatment effects, we applied metabolomics using ultra-high-performance liquid chromatography with a high-resolution mass spectrometer (UHPLC-HRMS) to identify and validate metabolite biomarkers from paired tissue samples of PC patients. Results showed that the metabolic reprogramming of PC mainly featured enhanced amino acid metabolism and inhibited sphingolipid metabolism, which satisfied the energy and biomass requirements for tumorigenesis and progression. The altered metabolism results were confirmed by the significantly changed gene expressions in PC tissues from an online database. A metabolites biomarker panel (six metabolites) was identified for the differential diagnosis between PC tumors and normal pancreatic tissues. The panel biomarker distinguished tumors from normal pancreatic tissues in the discovery group with an area under the curve (AUC) of 1.0 (95%CI, 1.000−1.000). The biomarker panel cutoff was 0.776. In the validation group, an AUC of 0.9000 (95%CI = 0.782–1.000) using the same cutoff, successfully validated the biomarker signature. Moreover, this metabolites panel biomarker had a great capability to predict the overall survival (OS) of PC. Taken together, this metabolomics method identifies and validates metabolite biomarkers that can diagnose the onsite progression and prognosis of PC precisely and sensitively in a clinical setting. It may also help clinicians choose proper therapeutic interventions for different PC patients and improve the survival of PC patients. |
format | Online Article Text |
id | pubmed-9479084 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94790842022-09-17 Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer Liu, Chang Qin, Henan Liu, Huiying Wei, Tianfu Wu, Zeming Shang, Mengxue Liu, Haihua Wang, Aman Liu, Jiwei Shang, Dong Yin, Peiyuan Front Oncol Oncology Pancreatic cancer (PC) is burdened with a low 5-year survival rate and high mortality due to a severe lack of early diagnosis methods and slow progress in treatment options. To improve clinical diagnosis and enhance the treatment effects, we applied metabolomics using ultra-high-performance liquid chromatography with a high-resolution mass spectrometer (UHPLC-HRMS) to identify and validate metabolite biomarkers from paired tissue samples of PC patients. Results showed that the metabolic reprogramming of PC mainly featured enhanced amino acid metabolism and inhibited sphingolipid metabolism, which satisfied the energy and biomass requirements for tumorigenesis and progression. The altered metabolism results were confirmed by the significantly changed gene expressions in PC tissues from an online database. A metabolites biomarker panel (six metabolites) was identified for the differential diagnosis between PC tumors and normal pancreatic tissues. The panel biomarker distinguished tumors from normal pancreatic tissues in the discovery group with an area under the curve (AUC) of 1.0 (95%CI, 1.000−1.000). The biomarker panel cutoff was 0.776. In the validation group, an AUC of 0.9000 (95%CI = 0.782–1.000) using the same cutoff, successfully validated the biomarker signature. Moreover, this metabolites panel biomarker had a great capability to predict the overall survival (OS) of PC. Taken together, this metabolomics method identifies and validates metabolite biomarkers that can diagnose the onsite progression and prognosis of PC precisely and sensitively in a clinical setting. It may also help clinicians choose proper therapeutic interventions for different PC patients and improve the survival of PC patients. Frontiers Media S.A. 2022-09-02 /pmc/articles/PMC9479084/ /pubmed/36119530 http://dx.doi.org/10.3389/fonc.2022.991051 Text en Copyright © 2022 Liu, Qin, Liu, Wei, Wu, Shang, Liu, Wang, Liu, Shang and Yin 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 Liu, Chang Qin, Henan Liu, Huiying Wei, Tianfu Wu, Zeming Shang, Mengxue Liu, Haihua Wang, Aman Liu, Jiwei Shang, Dong Yin, Peiyuan Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer |
title | Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer |
title_full | Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer |
title_fullStr | Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer |
title_full_unstemmed | Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer |
title_short | Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer |
title_sort | tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9479084/ https://www.ncbi.nlm.nih.gov/pubmed/36119530 http://dx.doi.org/10.3389/fonc.2022.991051 |
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