A Review of GC-Based Analysis of Non-Invasive Biomarkers of Colorectal Cancer and Related Pathways

Abstract

Colorectal cancer (CRC) is the third most commonly diagnosed cancer in the world. In Europe, it is the second most common cause of cancer-related deaths. With the advent of metabolomics approaches, studies regarding the investigation of metabolite profiles related to CRC have been conducted, aiming to serve as a tool for early diagnosis. In order to provide further information about the current status of this field of research, 21 studies were systematically reviewed, regarding their main findings and analytical aspects. A special focus was given to the employment of matrices obtained non-invasively and the use of gas chromatography as the analytical platform. The relationship between the reported volatile and non-volatile biomarkers and CRC-related metabolic alterations was also explored, demonstrating that many of these metabolites are connected with biochemical pathways proven to be involved in carcinogenesis. The most commonly reported CRC indicators were hydrocarbons, aldehydes, amino acids and short-chain fatty acids. These potential biomarkers can be associated with both human and bacterial pathways and the analysis based on such species has the potential to be applied in the clinical practice as a low-cost screening method.

Keywords: VOCs; biomarker; breath; colorectal cancer; feces; gas chromatography; pathways; profiling; urine.

Figure 1

Incidence distribution of potential CRC biomarkers, according to functional group.

Figure 2

Connected main pathways possibly altered in CRC (related to the reported metabolic biomarkers), involved in energy production and the generation of functional biomolecules, where: TCA—tricarboxylic acid, ATP—adenosine triphosphate, ADP—adenosine diphosphate, GDP—guanosine diphosphate, GTP—guanosine triphosphate, LPA—lysophosphatidic acid, PA—phosphatidic acids, MAG—monoacylglycerol, DAG—diacylglycerol, TAG—triacylglycerol. Based on Anderson et al., 2018 [79], Icard et al., 2012 [81] and Prentki et al., 2008 [87].

Figure 3

Lipid peroxidation mechanisms potentially involved in the formation of main classes of metabolic biomarkers. Based on Miekisch et al., 2004 [94] and Schaich et al., 2013 [95].

Figure 4

Bacterial fermentation pathways in the human gut. Based on Commane et al., 2005 [102] and Koh et al., 2016 [105].

Figure 5

Amino acid metabolism addressed to bacteria: (A) threonine degradation; (B) aldoxime-nitrile pathway and (C) methionine catabolism. Based on Portune et al., 2016 [115], Bhalla et al., 2018 [116] and Furne et al., 2001 [117].