Metabolomics study reveals systematic metabolic dysregulation and early detection markers associated with incident pancreatic cancer

Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential biomarkers for pancreatic cancer in prospective Chinese cohorts, we conducted an untargeted metabolomics study in subjects with incident pancreatic c...

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Published inInternational journal of cancer Vol. 150; no. 7; pp. 1091 - 1100
Main Authors Wang, Shuangyuan, Li, Mian, Yan, Li, He, Meian, Lin, Hong, Xu, Yu, Wan, Qin, Qin, Guijun, Chen, Gang, Xu, Min, Wang, Guixia, Qin, Yingfen, Luo, Zuojie, Tang, Xulei, Wang, Tiange, Zhao, Zhiyun, Xu, Yiping, Chen, Yuhong, Huo, Yanan, Hu, Ruying, Ye, Zhen, Dai, Meng, Shi, Lixin, Gao, Zhengnan, Su, Qing, Mu, Yiming, Zhao, Jiajun, Chen, Lulu, Zeng, Tianshu, Yu, Xuefeng, Li, Qiang, Shen, Feixia, Chen, Li, Zhang, Yinfei, Wang, Youmin, Deng, Huacong, Liu, Chao, Wu, Shengli, Yang, Tao, Li, Donghui, Ning, Guang, Wu, Tangchun, Wang, Weiqing, Bi, Yufang, Lu, Jieli
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 01.04.2022
Wiley Subscription Services, Inc
Subjects
Aged
Alanine
Androstenediol
biomarker
Biomarkers
Biomarkers, Tumor - analysis
Cancer
Female
Humans
Lipid metabolism
Male
Medical research
Metabolic networks
Metabolic Networks and Pathways
Metabolism
Metabolites
Metabolomics
Metabolomics - methods
Middle Aged
Nucleotides
Pancreatic cancer
Pancreatic Neoplasms - diagnosis
Pancreatic Neoplasms - metabolism
prospective cohort
Prospective Studies
Steroid hormones
Vitamins
pancreatic cancer
prospective cohort
biomarker
metabolomics
Online AccessGet full text
ISSN0020-7136
1097-0215
1097-0215
DOI10.1002/ijc.33877

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Abstract Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential biomarkers for pancreatic cancer in prospective Chinese cohorts, we conducted an untargeted metabolomics study in subjects with incident pancreatic cancer and matched controls (n = 192) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We characterized 998 metabolites in baseline serum and calculated 156 product‐to‐precursor ratios based on the KEGG database. The identified metabolic profiling revealed systematic metabolic network disorders before pancreatic cancer diagnosis. Forty‐Five metabolites or product‐to‐precursor ratios showed significant associations with pancreatic cancer (P < .05 and FDR < 0.1), revealing abnormal metabolism of amino acids (especially alanine, aspartate and glutamate), lipids (especially steroid hormones), vitamins, nucleotides and peptides. A novel metabolite panel containing aspartate/alanine (OR [95% CI]: 1.97 [1.31‐2.94]), androstenediol monosulfate (0.69 [0.49‐0.97]) and glycylvaline (1.68 [1.04‐2.70]) was significantly associated with risk of pancreatic cancer. Area under the receiver operating characteristic curves (AUCs) was improved from 0.573 (reference model of CA 19‐9) to 0.721. The novel metabolite panel was validated in an independent cohort with AUC improved from 0.529 to 0.661. These biomarkers may have a potential value in early detection of pancreatic cancer. What's new? Comprehensive metabolite profiling provides new insight into metabolic network dysregulation and non‐invasive biomarkers. This is the first study exploring the associations between nearly 1000 metabolites and pancreatic cancer risk in a prospective multi‐center cohort from China. Our findings highlighted abnormal metabolism of amino acids, steroid hormones, vitamins, and inflammation‐related metabolites. A novel metabolite panel containing aspartate/alanine, androstenediol monosulfate and glycylvaline may have a potential value in early detection of pancreatic cancer.
AbstractList Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential biomarkers for pancreatic cancer in prospective Chinese cohorts, we conducted an untargeted metabolomics study in subjects with incident pancreatic cancer and matched controls (n = 192) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We characterized 998 metabolites in baseline serum and calculated 156 product-to-precursor ratios based on the KEGG database. The identified metabolic profiling revealed systematic metabolic network disorders before pancreatic cancer diagnosis. Forty-Five metabolites or product-to-precursor ratios showed significant associations with pancreatic cancer (P < .05 and FDR < 0.1), revealing abnormal metabolism of amino acids (especially alanine, aspartate and glutamate), lipids (especially steroid hormones), vitamins, nucleotides and peptides. A novel metabolite panel containing aspartate/alanine (OR [95% CI]: 1.97 [1.31-2.94]), androstenediol monosulfate (0.69 [0.49-0.97]) and glycylvaline (1.68 [1.04-2.70]) was significantly associated with risk of pancreatic cancer. Area under the receiver operating characteristic curves (AUCs) was improved from 0.573 (reference model of CA 19-9) to 0.721. The novel metabolite panel was validated in an independent cohort with AUC improved from 0.529 to 0.661. These biomarkers may have a potential value in early detection of pancreatic cancer.
Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential biomarkers for pancreatic cancer in prospective Chinese cohorts, we conducted an untargeted metabolomics study in subjects with incident pancreatic cancer and matched controls (n = 192) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We characterized 998 metabolites in baseline serum and calculated 156 product‐to‐precursor ratios based on the KEGG database. The identified metabolic profiling revealed systematic metabolic network disorders before pancreatic cancer diagnosis. Forty‐Five metabolites or product‐to‐precursor ratios showed significant associations with pancreatic cancer ( P  < .05 and FDR < 0.1), revealing abnormal metabolism of amino acids (especially alanine, aspartate and glutamate), lipids (especially steroid hormones), vitamins, nucleotides and peptides. A novel metabolite panel containing aspartate/alanine (OR [95% CI]: 1.97 [1.31‐2.94]), androstenediol monosulfate (0.69 [0.49‐0.97]) and glycylvaline (1.68 [1.04‐2.70]) was significantly associated with risk of pancreatic cancer. Area under the receiver operating characteristic curves (AUCs) was improved from 0.573 (reference model of CA 19‐9) to 0.721. The novel metabolite panel was validated in an independent cohort with AUC improved from 0.529 to 0.661. These biomarkers may have a potential value in early detection of pancreatic cancer.
Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential biomarkers for pancreatic cancer in prospective Chinese cohorts, we conducted an untargeted metabolomics study in subjects with incident pancreatic cancer and matched controls (n = 192) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We characterized 998 metabolites in baseline serum and calculated 156 product-to-precursor ratios based on the KEGG database. The identified metabolic profiling revealed systematic metabolic network disorders before pancreatic cancer diagnosis. Forty-Five metabolites or product-to-precursor ratios showed significant associations with pancreatic cancer (P < .05 and FDR < 0.1), revealing abnormal metabolism of amino acids (especially alanine, aspartate and glutamate), lipids (especially steroid hormones), vitamins, nucleotides and peptides. A novel metabolite panel containing aspartate/alanine (OR [95% CI]: 1.97 [1.31-2.94]), androstenediol monosulfate (0.69 [0.49-0.97]) and glycylvaline (1.68 [1.04-2.70]) was significantly associated with risk of pancreatic cancer. Area under the receiver operating characteristic curves (AUCs) was improved from 0.573 (reference model of CA 19-9) to 0.721. The novel metabolite panel was validated in an independent cohort with AUC improved from 0.529 to 0.661. These biomarkers may have a potential value in early detection of pancreatic cancer.Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential biomarkers for pancreatic cancer in prospective Chinese cohorts, we conducted an untargeted metabolomics study in subjects with incident pancreatic cancer and matched controls (n = 192) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We characterized 998 metabolites in baseline serum and calculated 156 product-to-precursor ratios based on the KEGG database. The identified metabolic profiling revealed systematic metabolic network disorders before pancreatic cancer diagnosis. Forty-Five metabolites or product-to-precursor ratios showed significant associations with pancreatic cancer (P < .05 and FDR < 0.1), revealing abnormal metabolism of amino acids (especially alanine, aspartate and glutamate), lipids (especially steroid hormones), vitamins, nucleotides and peptides. A novel metabolite panel containing aspartate/alanine (OR [95% CI]: 1.97 [1.31-2.94]), androstenediol monosulfate (0.69 [0.49-0.97]) and glycylvaline (1.68 [1.04-2.70]) was significantly associated with risk of pancreatic cancer. Area under the receiver operating characteristic curves (AUCs) was improved from 0.573 (reference model of CA 19-9) to 0.721. The novel metabolite panel was validated in an independent cohort with AUC improved from 0.529 to 0.661. These biomarkers may have a potential value in early detection of pancreatic cancer.
Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential biomarkers for pancreatic cancer in prospective Chinese cohorts, we conducted an untargeted metabolomics study in subjects with incident pancreatic cancer and matched controls (n = 192) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We characterized 998 metabolites in baseline serum and calculated 156 product‐to‐precursor ratios based on the KEGG database. The identified metabolic profiling revealed systematic metabolic network disorders before pancreatic cancer diagnosis. Forty‐Five metabolites or product‐to‐precursor ratios showed significant associations with pancreatic cancer (P < .05 and FDR < 0.1), revealing abnormal metabolism of amino acids (especially alanine, aspartate and glutamate), lipids (especially steroid hormones), vitamins, nucleotides and peptides. A novel metabolite panel containing aspartate/alanine (OR [95% CI]: 1.97 [1.31‐2.94]), androstenediol monosulfate (0.69 [0.49‐0.97]) and glycylvaline (1.68 [1.04‐2.70]) was significantly associated with risk of pancreatic cancer. Area under the receiver operating characteristic curves (AUCs) was improved from 0.573 (reference model of CA 19‐9) to 0.721. The novel metabolite panel was validated in an independent cohort with AUC improved from 0.529 to 0.661. These biomarkers may have a potential value in early detection of pancreatic cancer.
Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential biomarkers for pancreatic cancer in prospective Chinese cohorts, we conducted an untargeted metabolomics study in subjects with incident pancreatic cancer and matched controls (n = 192) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We characterized 998 metabolites in baseline serum and calculated 156 product‐to‐precursor ratios based on the KEGG database. The identified metabolic profiling revealed systematic metabolic network disorders before pancreatic cancer diagnosis. Forty‐Five metabolites or product‐to‐precursor ratios showed significant associations with pancreatic cancer (P < .05 and FDR < 0.1), revealing abnormal metabolism of amino acids (especially alanine, aspartate and glutamate), lipids (especially steroid hormones), vitamins, nucleotides and peptides. A novel metabolite panel containing aspartate/alanine (OR [95% CI]: 1.97 [1.31‐2.94]), androstenediol monosulfate (0.69 [0.49‐0.97]) and glycylvaline (1.68 [1.04‐2.70]) was significantly associated with risk of pancreatic cancer. Area under the receiver operating characteristic curves (AUCs) was improved from 0.573 (reference model of CA 19‐9) to 0.721. The novel metabolite panel was validated in an independent cohort with AUC improved from 0.529 to 0.661. These biomarkers may have a potential value in early detection of pancreatic cancer. What's new? Comprehensive metabolite profiling provides new insight into metabolic network dysregulation and non‐invasive biomarkers. This is the first study exploring the associations between nearly 1000 metabolites and pancreatic cancer risk in a prospective multi‐center cohort from China. Our findings highlighted abnormal metabolism of amino acids, steroid hormones, vitamins, and inflammation‐related metabolites. A novel metabolite panel containing aspartate/alanine, androstenediol monosulfate and glycylvaline may have a potential value in early detection of pancreatic cancer.
Author Wang, Youmin
He, Meian
Tang, Xulei
Zhao, Jiajun
Liu, Chao
Yang, Tao
Xu, Min
Wu, Shengli
Wan, Qin
Hu, Ruying
Chen, Li
Lu, Jieli
Wang, Guixia
Huo, Yanan
Zhao, Zhiyun
Lin, Hong
Wang, Tiange
Chen, Lulu
Chen, Gang
Qin, Guijun
Chen, Yuhong
Li, Donghui
Zhang, Yinfei
Shi, Lixin
Su, Qing
Ning, Guang
Deng, Huacong
Xu, Yu
Yan, Li
Zeng, Tianshu
Shen, Feixia
Wang, Shuangyuan
Xu, Yiping
Wang, Weiqing
Bi, Yufang
Li, Qiang
Qin, Yingfen
Gao, Zhengnan
Mu, Yiming
Yu, Xuefeng
Wu, Tangchun
Ye, Zhen
Luo, Zuojie
Dai, Meng
Li, Mian
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Thu Apr 24 23:05:37 EDT 2025
Wed Jan 22 16:25:51 EST 2025
IsPeerReviewed true
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Issue 7
Keywords pancreatic cancer
prospective cohort
biomarker
metabolomics
Language English
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Notes Funding information
This work was supported by the Ministry of Science and Technology of China under Award Number 2018YFC1311705 and 2018YFC1311800, the National Natural Science Foundation of China under Award Number 91857205, 82088102, 81930021, 81970728, 81970691, 81870560 and 21904084, Shanghai Outstanding Academic Leaders Plan under Award Number 20XD1422800, Science and Technology Committee of Shanghai under Award Number 20Y11905100, Clinical Research Plan of SHDC under Award Number SHDC2020CR3064B and SHDC2020CR1001A, Shanghai Medical and Health Development Foundation under Award Number DMRFP_I_01, Chinese Academy of Medical Sciences Foundation under Award Number 2018PT32017 and 2019PT330006, and the fund of Shanghai Municipal Health Commission under Award Number 20214Y0002
Shuangyuan Wang, Mian Li, Li Yan, Meian He, Hong Lin and Yu Xu contributed equally to this work.
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Snippet Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential...
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SubjectTerms Aged
Alanine
Androstenediol
biomarker
Biomarkers
Biomarkers, Tumor - analysis
Cancer
Female
Humans
Lipid metabolism
Male
Medical research
Metabolic networks
Metabolic Networks and Pathways
Metabolism
Metabolites
Metabolomics
Metabolomics - methods
Middle Aged
Nucleotides
Pancreatic cancer
Pancreatic Neoplasms - diagnosis
Pancreatic Neoplasms - metabolism
prospective cohort
Prospective Studies
Steroid hormones
Vitamins
Title Metabolomics study reveals systematic metabolic dysregulation and early detection markers associated with incident pancreatic cancer
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fijc.33877
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