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. 2022 Aug 25:9:913967.
doi: 10.3389/fsurg.2022.913967. eCollection 2022.

Metabolomic profiling identifies biomarkers and metabolic impacts of surgery for colorectal cancer

Feng Zhuang  1 , Xuesong Bai  2 , Yang Shi  1 , Le Chang  1 , Wanchao Ai  1 , Juan Du  1 , Wei Liu  2 , Humin Liu  1 , Xukun Zhou  1 , Zhong Wang  1 , Tao Hong  2
Affiliations

Metabolomic profiling identifies biomarkers and metabolic impacts of surgery for colorectal cancer

Feng Zhuang et al. Front Surg. .

Abstract

Background: Colorectal cancer (CRC) is one of the most common malignant tumors with recurrence and metastasis after surgical resection. This study aimed to identify the physiological changes after surgery and explore metabolites and metabolic pathways with potential prognostic value for CRC.

Methods: An ultra-high-performance liquid chromatography Q-exactive mass spectrometry was used to profile serum metabolites from 67 CRC patients and 50 healthy volunteers. Principal component analysis (PCA) and orthogonal projections to latent structures-discriminant analysis were used to distinguish the internal characteristics of data in different groups. Multivariate statistics were compiled to screen the significant metabolites and metabolic pathways.

Result: A total of 180 metabolites were detected. Under the conditions of variable importance in projection >1 and p-value <0.05, 46 differentially expressed metabolites were screened for further pathway enrichment analysis. Based on the Kyoto Encyclopedia of Genes and Genomes database and Small Molecule Pathway Database, three metabolic pathways-arginine and proline metabolism, ascorbate and aldarate metabolism, and phenylalanine metabolism-were significantly altered after surgical resection and identified as associated with the removal of CRC. Notably, gamma-linolenic acid was upregulated in the CRC preoperative patients compared with those in healthy volunteers but returned to healthy levels after surgery.

Conclusion: Through serum-based metabolomics, our study demonstrated the differential metabolic characteristics in CRC patients after surgery compared with those before surgery. Our results suggested that metabonomic analysis may be a powerful method for exploring physiological alterations in CRC patients after surgery as well as a useful tool for identifying candidate biomarkers and monitoring disease recurrence.

Keywords: ascorbate; colorectal cancer; gamma-linolenic acid (GLA); metabolomic profiling; phenylalanine; proline; tumorectomy.

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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
(A) PCA was conducted between the preoperation group (blue dots) and postoperation group (purple dots). (B) The OPLS-DA model was constructed using data from 67 CRC patients' serum metabonomics before (blue) and after (purple) surgery. (C) The permutation test plot of OPLS-DA (green, the value of R2Y; blue, the value of Q2; permutation test with 200 times, a p value of CV-ANOVA < 0.01). PCA, principal component analysis; OPLS-DA, orthogonal projections to latent structures-discriminant analysis; CRC, colorectal cancer.
Figure 2
Figure 2
(A) The heat map for the 46 critical metabolites between the pre- and postoperation groups, including 32 downregulated metabolites and 14 upregulated metabolites. (B) The correlation network of the 46 differentially expressed metabolites.
Figure 3
Figure 3
(A) Pathway analysis based on the KEGG database. (B) Enrichment analysis based on SMPDB. (C) Metabolic network of the crucial metabolites and significant metabolic pathways in the KEGG general metabolic pathway map. The following colored dots and lines denote the following: red dots, increased metabolites after surgery; blue dots, decreased metabolites after surgery; blue line, ascorbate and aldarate metabolism; yellow line, arginine and proline metabolism; green line, phenylalanine metabolism. KEGG, Kyoto Encyclopedia of Genes and Genomes; SMPDB, Small Molecule Pathway Database.
Figure 4
Figure 4
(A) Serum levels of GLA in healthy samples and preoperative and postoperative samples. (B) The expression levels of metabolites involved in the metabolic pathways associated with radical resection of CRC. GLA, gamma-linolenic acid. CRC, colorectal cancer. *p < 0.05. ns, not significant.
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