UiO-66-NH2 Dispersed Solid-Phase Extraction Combined With Liquid Chromatography-Tandem Mass Spectrometry for Metabolomics Analysis in Cancer Patients and Healthy Individuals

Abstract

A dispersive solid-phase extraction process was established using UiO-66-NH₂ as an adsorbent, in combination with ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) technology, and the performance of this combination for the metabolomic analysis of biological specimens was assessed. Differential metabolites in plasma samples from oral squamous cell carcinoma and hepatocellular carcinoma patients and healthy volunteers were screened, and metabolic pathway enrichment analysis was performed via pseudo-targeted metabolomics. Based on the significantly enriched metabolic pathways and related literature, 20 amino acids were selected and targeted for quantitative analysis. The key parameters for extraction recovery, including the type of liquid in the adsorption system, pH of the eluent, amount of UiO-66-NH₂, and time of extraction and elution, were optimized based on the selected amino acids. The optimized method demonstrated a remarkable performance: correlation coefficients > 0.99, limits of detection ranging from 0.002 to 0.080 µg/mL (signal-to-noise ratio = 10), and recoveries of 63.9%-110.8% in plasma samples. Thus, via targeted metabolomics analysis, 10 amino acids (including lysine and 3-iodo-L-tyrosine) and 10 amino acids (including arginine and histidine) were determined as potential biomarkers for oral squamous cell carcinoma and hepatocellular carcinoma, respectively. Based on the above potential amino acid markers, discriminant equations for oral squamous cell carcinoma and hepatocellular carcinoma were established, respectively. Two biomarker combinations were successfully screened: lysine and 3-iodo-L-tyrosine (AUC = 0.998, sensitivity = 0.967, specificity = 1.0) for oral squamous cell carcinoma, and histidine and arginine (AUC = 0.944, sensitivity = 0.833, specificity = 0.933) for hepatocellular carcinoma. Our findings will provide new directions for cancer diagnosis.

Keywords: biomarkers; hepatocellular carcinoma; metabolomics; oral squamous cell carcinoma.