| 摘要: |
| 目的 基于结直肠癌（CRC）患者化疗前血浆中的内源性代谢物，寻找潜在卡培他滨肝毒性易感标志物，建立预测模型。方法 收集50例接受卡培他滨化疗的CRC患者化疗前血浆样本及化疗肝毒性不良反应随访记录。采用超高效液相色谱结合四极杆飞行时间质谱（UHPLC-Q-TOF-MS）法进行非靶向代谢组学分析。基于生物信息学分析，采用差异分析、相关性分析、随机森林方法筛选肝毒性相关的内源性代谢物。将所有样本按照7∶3比例随机分成训练集和测试集，基于训练集数据建立预测卡培他滨化疗肝毒性的多因素logistic回归模型，通过ROC曲线分析评价模型在训练集、测试集及整个数据集中的预测效果。结果 CRC患者化疗前血浆中肝毒性相关内源性代谢物主要集中在脂质内源性代谢物，经筛选发现鞘氨醇-1-磷酸、神经酰胺、半乳糖、花生四烯酸、酪氨酸、胆绿素、肉豆蔻酸、磷脂酰胆碱（35∶1）、磷脂酰乙醇胺（36∶1）、棕榈酸等可能是潜在的重要肝毒性易感标志物。基于以上标志物建立的卡培他滨化疗肝毒性预测模型在训练集、测试集、整个数据集中的AUC分别为0.946（95% CI 0.842～1.000）、0.920（95% CI 0.720～1.000）、0.912（95% CI 0.810～0.982）。结论 利用CRC患者化疗前血浆中的内源性代谢物可以有效预测卡培他滨化疗肝毒性不良反应，这些肝毒性标志物指示易感患者具有脂质代谢紊乱相关的特征。 |
| 关键词: 结直肠肿瘤 卡培他滨 肝毒性 预测模型 代谢组学 生物学标志物 |
| DOI：10.16781/j.CN31-2187/R.20220286 |
| 投稿时间：2022-04-08修订日期：2022-05-23 |
| 基金项目: |
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| Establishment of a prediction model for capecitabine chemotherapy-related hepatotoxicity in colorectal cancer patients based on metabonomics |
| LIN Zeshuai1,2,CHEN Jiani3,YAO Houshan2,LI Mingming3,YAO Jia1* |
(1. Department of Biochemistry and Molecular Biology, Shanxi Medical University, Taiyuan 030001, Shanxi, China;
2. Department of Colorectal Surgery, The Second Affiliated Hospital of Naval Medical University (Second Military Medical University), Shanghai 200003, China;
3. Department of Pharmacy, The Second Affiliated Hospital of Naval Medical University (Second Military Medical University), Shanghai 200003, China
*Corresponding author) |
| Abstract: |
| Objective To identify potential biomarkers and establish a prediction model for chemotherapy-related hepatotoxicity susceptibility based on plasma endogenous metabolites of colorectal cancer (CRC) patients before chemotherapy. Methods The plasma samples of 50 CRC patients before capecitabine chemotherapy and the records of their chemotherapy-related hepatotoxicity during the follow-up were collected. An ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) was used to perform untargeted metabolomic analysis. Based on bioinformatics analysis, differential analysis, correlation analysis, and random forest were used to screen for hepatotoxicity-related plasma endogenous metabolites. All samples were randomly assigned (7∶3) to training set or test set. A multivariate logistic regression model was established to predict the hepatotoxicity of capecitabine chemotherapy based on the training set data. The prediction effects of the model in the training, test and entire sets were evaluated by receiver operating characteristic (ROC) curve analysis. Results The endogenous metabolites related to hepatotoxicity in the plasma of CRC patients before chemotherapy were mainly lipid endogenous metabolites. A series of potentially important predictive biomarkers for hepatotoxicity susceptibility were identified, including sphingamine-1-phosphate, ceramide, galactose, arachidonic acid, tyrosine, biliverdin, myristic acid, phosphatidylcholine (35∶1), phosphatidylethanolamine (36∶1), and hexadecanoic acid. The area under curve values of the prediction model based on the above biomarkers in the training, test and entire sets were 0.946 (95% confidence interval ［CI］ 0.842-1.000), 0.920 (95% CI 0.720-1.000), and 0.912 (95% CI 0.810-0.982), respectively. Conclusion The endogenous metabolites in the plasma of CRC patients before chemotherapy can effectively predict the hepatotoxicity of capecitabine chemotherapy. These hepatotoxicity biomarkers indicate that susceptible patients have characteristics related to lipid metabolism disorders |
| Key words: colorectal neoplasms capecitabine hepatotoxicity prediction model metabonomics biomarkers |
