Browsing by Author "Fitzgerald, Liam Warren"

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    Targeted Serum Metabolomics for Noninvasive Detection of Colorectal Neoplasia
    (2023-08) Fitzgerald, Liam Warren; Bathe, Oliver; Orton, Dennis; Kopciuk, Karen; Vogel, Hans
    Background: Early detection of colorectal cancer (CRC) and its precursor lesions improves CRC-related mortality and reduces disease incidence. However, due to limitations of currently available screening modalities, patient adherence to screening is low. A reliable and inexpensive blood test represents a promising solution to this problem. Our group has previously demonstrated that there are distinct metabolic perturbations in CRC and adenomatous polyps which are measurable in the blood. However, a targeted metabolomic approach is needed to uncover reliable meta-biomarkers for CRC, adenomatous polyps, and serrated polyps. Methods: A targeted metabolomic assay (Biocrates MxP® Quant 500) was used to analyze our discovery set of sera from patients with CRC of all stage (N=111), adenoma (N=63), sessile serrated adenoma (SSA; N=62), and age- and sex-matched disease-free controls (DFC; N=154). Orthogonal partial least squares discriminant analysis (OPLS-DA) and machine learning (ML) were used to derive signatures comprised of metabolite concentration ratios which discriminate between CRC, adenoma, SSA, and DFCs. A large, representative validation cohort (N=838) was also analyzed to test our meta-biomarkers. Results: Two signatures for CRC were derived from OPLS-DA and ML and comprised of 21 and 16 metabolite ratios, respectively. OPLS-DA signatures for adenoma and SSA were comprised of 23 and 56 metabolite ratios, respectively. All models performed well based on 7-fold internal cross-validation, with receiver operating characteristic (ROC) analysis demonstrating areas under the curve (AUC) greater than 0.85. Importantly, external validation confirmed the reliability of our meta-biomarkers, with sensitivities as high as 92-100% for CRC and 80-85% for adenoma and SSA being possible. Conclusion: Our meta-biomarkers discovered using targeted metabolomics demonstrated excellent performance based on internal and external validation. Of significance, our signatures exhibit superior sensitivity compared to other readily available screening modalities such as stool tests.