Abstract
Oesophageal cancer (OC) is associated with high morbidity and mortality, and surgery is the most effective approach to treat it. In order to reduce surgical risks and duration of surgery, we explored a new strategy to determine tumour margins in surgery. In this study, we included 128 cancerous and 128 noncancerous database entries obtained from 32 human patients. Using internal extractive electrospray ionization-MS, in positive ion detection mode, the relative abundances of m/z 104.13, m/z 116.10, m/z 132.13, and m/z 175.13 were higher in cancer tissue while the relative abundances of m/z 82.99, m/z 133.11, m/z 147.08, m/z 154.06, and m/z 188.05 were higher in normal tissue. Using partial least squares analysis, the mass spectra of cancer samples was discriminated from those of normal tissues, and the discriminatory ions were obtained from loading plots. Dimethylglycine(m/z 104), proline(m/z 116), isoleucine(m/z 132), asparagine(m/z 133), glutamine(m/z 147), and arginine(m/z 175) were identified by collision-induced dissociation experiments. Using the ROC curve analysis, we verified the validity of six amino acids for the identification of tumour tissue. Further investigations of tissue amino acids may allow us to better understand the underlying mechanisms involved in OC and develop novel means to identify tumour tissue during operation.
Highlights
Oesophageal cancer (OC) is one of the most common types of cancer and the sixth leading cause of cancer-related mortality[1]
Tumour margins are accurately determined intraoperatively by frozen-section histology, which is the gold standard method at present[7]; it is associated with many drawbacks: its time-consuming (30–40 min) nature considerably lengthens the exposure of the patient to the general anaesthetic and operative risk, and the diagnosis with this procedure is subjective
Amino acids and small molecules play an important role in cancer metabolic pathways, but traditional methods focus on protein and nucleic acids rather than amino acids and small molecules
Summary
Oesophageal cancer (OC) is one of the most common types of cancer and the sixth leading cause of cancer-related mortality[1]. We analysed trace differences in the metabolism of amino acids and small molecules to distinguish between OC tissue and adjacent matched normal tissue samples obtained by iEESI-MS. Key amino acids and small molecules with the most influence on the separation between sample classes were identified, and their chemical structures were studied by collision-induced dissociation (CID). This novel technique to intraoperatively predict tumour margins was associated with reduced operation risk and time
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