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Serum metabolite signatures in normal individuals and patients with colorectal adenoma or colorectal cancer using UPLC-MS/MS method.

Authors :
Guo, Jiachi
Pan, Yuanming
Chen, Jigui
Jin, Peng
Tang, Shan
Wang, Haihong
Su, Hui
Wang, Qian
Chen, Chao
Xiong, Fei
Liu, Kejia
Li, Yansheng
Su, Mingliang
Tang, Tang
He, Yuqi
Sheng, Jianqiu
Source :
Journal of Proteomics. Jan2023, Vol. 270, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

Colorectal cancer (CRC) is one of the main causes of cancer-related deaths worldwide. Sporadic CRC develops from normal mucosa via adenoma to adenocarcinoma, which provides a long screening window for clinical detection. However, early diagnosis of sporadic colorectal adenoma (CRA) and CRC using serum metabolic screening remains unclear. The purpose of this study was to identify some promising signatures for distinguishing the different pathological metabolites of colorectal mucosal malignant transformation. A total of 238 endogenous metabolites were elected. We found that CRA and CRC patients had 72 and 73 different metabolites compared with healthy controls, respectively. There were 20 different metabolites between CRA and CRC patients. The potential metabolites of tumor growth (including patients with CRA and CRC) were found, such as A- d -glucose, D-mannose, N -acetyl-D-glucosamine, L-cystine, Sarcosine, TXB 2, 12-Hete, and chenodeoxycholic acid. Compared with CRA, 3,4,5-trimethoxybenzoic acid was significantly higher in CRC patients. There results prompt us to use the potential serum signatures to screen CRC as the novel strategy. Serum metabolite screening is useful for early detection of mucosal intestinal malignancy. We will further investigate the roles of these promising biomarkers during intestinal tumorigenesis in future. CRC is one of the main causes of cancer-related deaths worldwide. Sporadic CRC develops from normal mucosa via adenomas to adenocarcinoma, which provides a long screening window for about 5–10 years. We adopt the metabolic analysis of extensive targeted metabolic technology. The main purpose of the metabolic group analysis is to detect and screen the different metabolites, thereby performing related functional prediction and analysis of the differential metabolites. In our study, 30 samples are selected, divided into 3 groups for metabolic analysis, and 238 metabolites are elected. In 238 metabolites, we find that CRA patients have 72 different metabolites compared with health control. Compared with health control, CRC have 73 different metabolites. Compared with CRA and CRC patients, there are 20 different metabolites. The annotation results of the significantly different metabolites are classified according to the KEGG pathway type. The potential metabolites of tumor growth stage (including patients with CRA and CRC) are found, such as A- d -glucose, D-mannose, N -acetyl-D-glucosamine, L-cystine, sarcosine, TXB 2, 12-Hete and chenodeoxycholic acid. Compared with CRA patients, CRC patients had significantly higher 3,4,5-trimethoxybenzoic acid level. It is prompted to use serum different metabolites to screen CRC to provide new possibilities. • In this study, 30 samples were selected, divided into 3 groups (including CRA, CRC, and healthy control group) for metabolic studies, and 238 metabolites were elected. • We used the combination of UPLC-MS/MS detection platform, metwell databases and multiple statistical analysis to integrate and explore the potential different metabolites. • The method of combining fold change and VIP values of OPLS-DA model were used to screen the differential metabolites. • The annotation results of the significantly different metabolites were classified according to the KEGG pathway type. The potential metabolites of tumor growth stage (including patients with CRA and CRC) were found, such as A- d -glucose, D-mannose, N -acetyl-D-glucosamine, L-cystine, sarcosine, TXB 2, 12-Hete and chenodeoxycholic acid. • Compared with CRA patients, CRC patients had significantly higher 3,4,5-trimethoxybenzoic acid level. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18743919
Volume :
270
Database :
Academic Search Index
Journal :
Journal of Proteomics
Publication Type :
Academic Journal
Accession number :
159857915
Full Text :
https://doi.org/10.1016/j.jprot.2022.104741