化学
色谱法
代谢组学
固相萃取
质谱法
串联质谱法
氨基酸
萃取(化学)
液相色谱-质谱法
肝细胞癌
生物化学
癌症研究
医学
作者
Piao Liu,Chang-Hong Li,Meixian Ou,Chang Jun Yin,Xinyue Kang,Jun Chen,Ran Liu,Jialang Zhuang
摘要
ABSTRACT A dispersive solid‐phase extraction process was established using UiO‐66‐NH 2 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‐NH 2 , 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.
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