Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Nov 4:11:729512.
doi: 10.3389/fonc.2021.729512. eCollection 2021.

Untargeted GC-MS-Based Metabolomics for Early Detection of Colorectal Cancer

Guoxue Zhu  1 , Yi Wang  2 , Wang Wang  3 , Fang Shang  2 , Bin Pei  2 , Yang Zhao  1 , Desong Kong  4 , Zhimin Fan  2
Affiliations

Untargeted GC-MS-Based Metabolomics for Early Detection of Colorectal Cancer

Guoxue Zhu et al. Front Oncol. .

Abstract

Background: Colorectal cancer (CRC) is one of the most common malignant gastrointestinal cancers in the world with a 5-year survival rate of approximately 68%. Although researchers accumulated many scientific studies, its pathogenesis remains unclear yet. Detecting and removing these malignant polyps promptly is the most effective method in CRC prevention. Therefore, the analysis and disposal of malignant polyps is conducive to preventing CRC.

Methods: In the study, metabolic profiling as well as diagnostic biomarkers for CRC was investigated using untargeted GC-MS-based metabolomics methods to explore the intervention approaches. In order to better characterize the variations of tissue and serum metabolic profiles, orthogonal partial least-square discriminant analysis was carried out to further identify significant features. The key differences in tR-m/z pairs were screened by the S-plot and VIP value from OPLS-DA. Identified potential biomarkers were leading in the KEGG in finding interactions, which show the relationships among these signal pathways.

Results: Finally, 17 tissue and 13 serum candidate ions were selected based on their corresponding retention time, p-value, m/z, and VIP value. Simultaneously, the most influential pathways contributing to CRC were inositol phosphate metabolism, primary bile acid biosynthesis, phosphatidylinositol signaling system, and linoleic acid metabolism.

Conclusions: The preliminary results suggest that the GC-MS-based method coupled with the pattern recognition method and understanding these cancer-specific alterations could make it possible to detect CRC early and aid in the development of additional treatments for the disease, leading to improvements in CRC patients' quality of life.

Keywords: GC-MS; cancer tissue and paracarcinoma tissue; colorectal cancer; metabolomics; preoperative and postoperative serum.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The schematic diagram of the experimental design.
Figure 2
Figure 2
Total ion chromatogram of cancer tissue (A) and paracarcinoma tissue (B) and preoperative (C) and postoperative (D) serum of 2 weeks in positive-ion mode.
Figure 3
Figure 3
(A) PCA score plot of cancer tissue and paracarcinoma tissue samples in positive-ion mode with the statistical parameters (R2X = 0.964, Q2 = 0.897). (B) S-plot of OPLS-DA with the statistical parameters in positive-ion mode (R2X = 0.940, R2Y = 0.756, Q2 = 0.743). (C) VIP value plot between cancer tissue and paracarcinoma tissue samples in positive-ion mode. (D) Validation plot of the cancer tissue and paracarcinoma tissue samples in positive-ion mode obtained from 200 permutation tests.
Figure 4
Figure 4
(A) PCA score plot of preoperative and postoperative serum of 2-week samples in positive-ion mode with the statistical parameters (R2X = 0.965, Q2 = 0.823). (B) S-plot of OPLS-DA with the statistical parameters in positive-ion mode (R2X = 0.939, R2Y = 0.639, Q2 = 0.844). (C) VIP value plot between preoperative and postoperative serum of 2-week samples in positive-ion mode. (D) Validation plot of the preoperative and postoperative serum of 2-week samples in positive-ion mode obtained from 200 permutation tests.
Figure 5
Figure 5
Heatmap of differential metabolites between cancer tissue and paracarcinoma tissue samples (A) and preoperative and postoperative serum of 2-week samples (B).
Figure 6
Figure 6
Pathway enrichment analysis of CRC in cancer tissue and paracarcinoma tissue samples (A, B) and preoperative and postoperative serum of 2-week sample (C, D) levels.
Figure 7
Figure 7
Schematic diagram of the disturbed metabolic pathway related to CRC.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Asante I, Pei H, Zhou E, Liu S, Chui D, Yoo E, et al. . Exploratory Metabolomic Study to Identify Blood-Based Biomarkers as a Potential Screen for Colorectal Cancer. Mol Omics (2019) 15(1):21–9. doi: 10.1039/c8mo00158h - DOI - PMC - PubMed
    1. Jing Y, Wu X, Gao P, Fang Z, Wu J, Wang Q, et al. . Rapid Differentiating Colorectal Cancer and Colorectal Polyp Using Dried Blood Spot Mass Spectrometry Metabolomic Approach. IUBMB Life (2017) 69(5):347–54. doi: 10.1002/iub.1617 - DOI - PubMed
    1. Viswanath B, Kim S, Lee K. Recent Insights Into Nanotechnology Development for Detection and Treatment of Colorectal Cancer. Int J Nanomedicine (2016) 11:2491–504. doi: 10.2147/IJN.S108715 - DOI - PMC - PubMed
    1. Winawer S, Fletcher R, Rex D, Bond J, Burt R, Ferrucci J, et al. . Colorectal Cancer Screening and Surveillance: Clinical Guidelines and Rationale-Update Based on New Evidence. Gastroenterology (2003) 124:544–60. doi: 10.1053/gast.2003.50044 - DOI - PubMed
    1. Simon K. Colorectal Cancer Development and Advances in Screening. Clin. Interv. Aging (2016) 11:967–76. doi: 10.2147/CIA.S109285 - DOI - PMC - PubMed