Journal of Southern Medical University ›› 2023, Vol. 43 ›› Issue (3): 443-453.doi: 10.12122/j.issn.1673-4254.2023.03.15

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Integrated analysis of serum untargeted metabolomics and targeted bile acid metabolomics for identification of diagnostic biomarkers for colorectal cancer

WANG Xuancheng, ZHU Yifan, ZHOU Hailin, HUANG Zongsheng, CHEN Hongwei, ZHANG Jiahao, YANG Shanyi, CHEN Guanghui, ZHANG Qisong   

  1. Medical College of Guangxi University, Nanning 530004, China; Department of Rehabilitation Medicine, First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530023, China; Department of Gastroenterology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, China
  • Online:2023-03-20 Published:2023-03-20

Abstract: Objective To identify potential diagnostic biomarkers of colorectal cancer (CRC) using serum metabolomic technology for minimally invasive and efficient screening for CRC. Methods Serum samples from 79 healthy individuals and 82 CRC patients were analyzed by metabolomics using ultra-high-performance liquid chromatography-tandem high-resolution mass spectrometry (UHPLC-HRMS). The differential metabolites between the two groups were analyzed using principal component analysis and orthogonal partial least squares discriminant analysis (OPLS- DA). Receiver operating characteristic curve (ROC) analysis was performed to identify the differential metabolites with good diagnostic performance (AUC>0.80) for CRC, and targeted bile acid metabolomics was used to verify the selected bile acids as biomarkers. Results Serum metabolic profiles differed significantly between the healthy individuals and CRC patients, and a total of 82 differential metabolites (mostly fatty acids and glycerophospholipids) were selected. ROC analysis identified 10 differential metabolites, including adenine, bilirubin, ACar 12:0, ACar 10:1, ACar 9:0, PC 18:2e, deoxycholic acid, chenodeoxycholic acid, ACar 14:1 and palmitoylcarnitine. One of these metabolites was significantly up-regulated and 9 were down-regulated in the serum of CRC patients (P<0.05). Multivariate ROC analysis with support vector machine algorithm showed that the biomarker panel consisting of 7 differential metabolites had an AUC of 0.94 for CRC diagnosis. The results of targeted bile acid metabolomics were consistent with those of untargeted metabolomics. The serum levels of deoxycholic acid and chenodeoxycholic acid were significantly down-regulated in patients with CRC as compared with the healthy individuals (P<0.05). Conclusion Metabolic disorders of fatty acids and glycerophospholipids are closely related wigh tumorigenesis of CRC. Ten differential metabolites show good performance for CRC diagnosis, and the panel consisting 7 of these metabolites has important diagnostic value for CRC. Deoxycholic acid and chenodeoxycholic acid may serve as potential diagnostic biomarkers of CRC.

Key words: colorectal cancer; serum untargeted metabolomics; targeted bile acid metabolomics; biomarkers