Abstract
Abstract Background: Colorectal adenoma detection using non-invasive faecal-based biomarkers is not yet feasible. Our primary aim was to identify differential metabolomic signatures of colorectal adenomas in faecal samples using a Liquid Chromatography Mass Spectrometry (LCMS) assay. The secondary aim was to translate this assay to an Ambient Mass ionization-based technique, DESI, for high throughput, point of care diagnostics. Methods: Patients were prospectively recruited from the colorectal cancer clinic at Imperial College NHS Trust, UK. Patients provided fresh stool samples, prior to taking bowel preparation for colonoscopy. Specimens were collected in Fecotainer (AT Medical BV) and cooled before immediate manual homogenization, aliquoting and storage at -80oC. LCMS untargeted metabolomics was performed using Reversed Phase chromatography (Acquity UPLC, Xevo G2-XS QToF, Waters) in both ElectroSpray Ionization (ESI) modes. Deactivated faecal samples applied to swabs were analysed using DESI-MS (Xevo G2-XS QToF). Multivariate Statistical Analysis was performed using Python. Logistic regression (LR) classification with Leave One patient Out Cross Validation (LOOCV) was applied. Recursive Feature Elimination and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms were used for feature elimination. Results: 36 subjects (17 females, mean age 63.5, range 42-85) were included: 17 controls, 8 adenoma, and 11 cancer patients. Principal Component Analysis of LCMS data from both ESI modes separated the three groups. LR with LOOCV for the adenoma group showed 97% sensitivity and 100% specificity. Receiver Operator Characteristic curve based on a multivariate model of the top 5 significant features showed a diagnostic ability of binary classifiers of adenoma vs cancer 0.997 (Area under the curve (AUC), 95% CI=0.944-1), adenoma v healthy 0.981 (AUC, 95% CI=0.984-1), and healthy v cancer & adenoma 0.995 (AUC, 95% CI=0.931-1). LR with LOOCV after LASSO on the DESI-MS data revealed sensitivity, 84%, and specificity, 95%, for the adenoma group. Specifically, these data suggest increased abundances of N-acyl amino acids, polyunsaturated chain fatty acids (n-3 PUFAs), in the adenoma group. Both species participate in arachidonic and linoleic acid pathways, where upregulation causes prostaglandin overproduction. Glycerophosphoserines, important in cell apoptosis, were significantly increased in cancer vs adenoma/controls (p < 0.01). Conclusion: DESI-MS analysis of faecal samples can detect the presence of colorectal adenomas and distinguish them from cancer. A prospective trial is now under way to validate these findings. Citation Format: Maria Sani, Lauren Ford, Daniel Simon, Yuchen Xiang, James McKenzie, Stefania Manetta Stavrakaki, Petra Paizs, Tausif Huq, Jim Higginson, James Alexander, Zoltan Takats, James Kinross. A prospective pilot study of desorption electrospray ionisation mass spectrometry (DESI-MS) for the early detection of colorectal adenoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3905.
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