Yueting Xiong1, Chao Shi2, Fan Zhong3, Xiaohui Liu4, Pengyuan Yang5. 1. Institutes of Biomedical Sciences and The Fifth People's Hospital of Shanghai, Fudan University, Shanghai 200032, China. 2. Shanghai Dermatology Hospital, No. 1278th Baode Road, Jing'an District, Shanghai 200443, China. 3. Institutes of Biomedical Sciences and The Fifth People's Hospital of Shanghai, Fudan University, Shanghai 200032, China; Department of Systems Biology for Medicine, Shanghai Medical College, Fudan University, Shanghai 200032, China. 4. Institutes of Biomedical Sciences and The Fifth People's Hospital of Shanghai, Fudan University, Shanghai 200032, China. Electronic address: liuxiaohui@fudan.edu.cn. 5. Institutes of Biomedical Sciences and The Fifth People's Hospital of Shanghai, Fudan University, Shanghai 200032, China. Electronic address: pyyang@fudan.edu.cn.
Abstract
BACKGROUND: Pancreatic cancer (PC) is the fourth leading cause of cancer death because of its subtle clinical symptoms in the early stage. To discover particular serum metabolites as potential biomarkers to differentiate pancreatic carcinoma from benign disease (BD) is on urgent demand. METHOD: To comprehensively analyze serum metabolites obtained from 14 patients with PC, 10 patients with BD and 10 healthy individuals (normal control, NC), we separated the metabolites using both reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC). The data were acquired on a high-resolution quadrupole time-of-flight mass spectrometer operated in negative (ESI-) and positive (ESI+) ionization modes, respectively. Differential metabolites were selected by univariate (Student's t test) and multivariate (orthogonal partial least squares-discriminant analysis (OPLS-DA)) statistics. Sequential window acquisition of all theoretical spectra (SWATH) analysis was further utilized to validate the metabolites found in discovery stage. The receiver operator characteristics (ROC) curve analysis was performed to evaluate predictive clinical usefulness of 8 metabolites. RESULTS: A total of 8 metabolites including taurocholic acid, glycochenodexycholic acid, glycocholic acid, L-glutamine, glutamic acid, L-phenylalanine, L-tryptophan, and L-arginine were identified and relatively quantified as differential metabolites for discriminating PC, BD and NC. The 8 metabolites and their combination discriminated PC from BD and NC with well-performed area under the curve (AUC) values, sensitivity and specificity. CONCLUSION: Bile acids (especially taurocholic acid) performed to be potential biomarkers in PC diagnosis. Other amino acids (such as L-glutamine, glutamic acid, L-phenylalanine, L-tryptophan, and L-arginine) in serum samples from PC patients might provide a sensitive, blood-borne diagnostic signature for the presence of PC or its precursor lesions.
BACKGROUND:Pancreatic cancer (PC) is the fourth leading cause of cancer death because of its subtle clinical symptoms in the early stage. To discover particular serum metabolites as potential biomarkers to differentiate pancreatic carcinoma from benign disease (BD) is on urgent demand. METHOD: To comprehensively analyze serum metabolites obtained from 14 patients with PC, 10 patients with BD and 10 healthy individuals (normal control, NC), we separated the metabolites using both reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC). The data were acquired on a high-resolution quadrupole time-of-flight mass spectrometer operated in negative (ESI-) and positive (ESI+) ionization modes, respectively. Differential metabolites were selected by univariate (Student's t test) and multivariate (orthogonal partial least squares-discriminant analysis (OPLS-DA)) statistics. Sequential window acquisition of all theoretical spectra (SWATH) analysis was further utilized to validate the metabolites found in discovery stage. The receiver operator characteristics (ROC) curve analysis was performed to evaluate predictive clinical usefulness of 8 metabolites. RESULTS: A total of 8 metabolites including taurocholic acid, glycochenodexycholic acid, glycocholic acid, L-glutamine, glutamic acid, L-phenylalanine, L-tryptophan, and L-arginine were identified and relatively quantified as differential metabolites for discriminating PC, BD and NC. The 8 metabolites and their combination discriminated PC from BD and NC with well-performed area under the curve (AUC) values, sensitivity and specificity. CONCLUSION:Bile acids (especially taurocholic acid) performed to be potential biomarkers in PC diagnosis. Other amino acids (such as L-glutamine, glutamic acid, L-phenylalanine, L-tryptophan, and L-arginine) in serum samples from PCpatients might provide a sensitive, blood-borne diagnostic signature for the presence of PC or its precursor lesions.
Authors: Yanhui Wang; Jiawei Xiao; Wenna Jiang; Duo Zuo; Xia Wang; Yu Jin; Lu Qiao; Haohua An; Lexin Yang; Daphne W Dumoulin; Wolfram C M Dempke; Sarah A Best; Li Ren Journal: Transl Lung Cancer Res Date: 2021-12