4.7 Article

Uveal Melanoma Patients Have a Distinct Metabolic Phenotype in Peripheral Blood

Journal

Publisher

MDPI
DOI: 10.3390/ijms24065077

Keywords

noninvasive; prognostication; biomarker; metabolomics; liquid biopsy

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Using untargeted metabolomics, we identified differential metabolite patterns in UM patients compared to controls. The random forest classifier and leave-one-out cross-validation confirmed the discriminatory ability of these metabolite patterns in distinguishing UM patients from controls, but not in differentiating high-risk and low-risk UM patients. Dysregulation of metabolite patterns may be associated with processes related to malignancies.
Uveal melanomas (UM) are detected earlier. Consequently, tumors are smaller, allowing for novel eye-preserving treatments. This reduces tumor tissue available for genomic profiling. Additionally, these small tumors can be hard to differentiate from nevi, creating the need for minimally invasive detection and prognostication. Metabolites show promise as minimally invasive detection by resembling the biological phenotype. In this pilot study, we determined metabolite patterns in the peripheral blood of UM patients (n = 113) and controls (n = 46) using untargeted metabolomics. Using a random forest classifier (RFC) and leave-one-out cross-validation, we confirmed discriminatory metabolite patterns in UM patients compared to controls with an area under the curve of the receiver operating characteristic of 0.99 in both positive and negative ion modes. The RFC and leave-one-out cross-validation did not reveal discriminatory metabolite patterns in high-risk versus low-risk of metastasizing in UM patients. Ten-time repeated analyses of the RFC and LOOCV using 50% randomly distributed samples showed similar results for UM patients versus controls and prognostic groups. Pathway analysis using annotated metabolites indicated dysregulation of several processes associated with malignancies. Consequently, minimally invasive metabolomics could potentially allow for screening as it distinguishes metabolite patterns that are putatively associated with oncogenic processes in the peripheral blood plasma of UM patients from controls at the time of diagnosis.

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