UHPLC-HRMS-Based Multiomics to Explore the Potential Mechanism and Biomarkers for Colorectal Cancer

Author:

Wang Xuancheng1,Guan Xuan1,Tong Ying1,Liang Yunxiao2,Huang Zongsheng2,Wen Mingsen1,Luo Jichu1,Chen Hongwei1,Yang Shanyi1,She Zhiyong1,Wei Zhijuan1,Zhou Yun1,Qi Yali1,Zhu Pingchuan1,Nong Yanying3,Zhang Qisong1

Affiliation:

1. Guangxi University

2. People's Hospital of Guangxi Zhuang Autonomous Region

3. The First Affiliated Hospital of Guangxi Medical University

Abstract

Abstract Background Understanding the metabolic changes in colorectal cancer (CRC) is crucial for elucidating its pathogenesis and early monitoring, thereby reducing mortality. However, there is a lack of systematic research on the metabolic changes and differences of CRC cells at different stages. Furthermore, studies validating multiomics findings in the serum of CRC patients using cell models have not yet been published. Methods Ultrahigh-performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS)-based metabolomics and lipidomics were employed to comprehensively measure metabolites and lipids in CRC cells at four different stages and serum samples from normal control (NR) and CRC subjects. Univariate and multivariate statistical analyses were applied to select the differential metabolites and lipids between groups. Biomarkers with good diagnostic efficacy for CRC that existed in both cells and serum were screened by the receiver operating characteristic curve (ROC) analysis. Furthermore, potential biomarkers were validated using metabolite standards. Results Metabolite and lipid profiles differed significantly among CRC cells at stages A, B, C, and D. Dysregulation of glycerophospholipid (GPL), fatty acid (FA), and amino acid (AA) metabolism played a crucial role in the CRC progression, particularly GPL metabolism dominated by phosphatidylcholine (PC). A total of 46 differential metabolites and 29 differential lipids common to the four stages of CRC cells were discovered. Eight metabolites showed the same trends in CRC cells and serum from CRC patients compared to the control groups. Among them, palmitoylcarnitine and sphingosine could serve as potential biomarkers with the values of area under the curve (AUC) more than 0.80 in the serum and cells. Their panel exhibited excellent performance in discriminating CRC cells at different stages from normal cells (AUC = 1.00). Conclusions To our knowledge, this is the first research to attempt to further validate the results of metabolism studies of serum from CRC patients using cell models. The metabolic disorders of PC, FA, and AA were closely related to the tumorigenesis of CRC, with PC being the more critical factor. The panel composed of palmitoylcarnitine and sphingosine may act as a potential biomarker for the diagnosis of CRC, aiding in its prevention.

Publisher

Research Square Platform LLC

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