International Institute for Translational Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510006, PR China.
Department of Cardiothoracic Surgery, The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510006, PR China.
Clin Chim Acta. 2022 May 1;530:66-73. doi: 10.1016/j.cca.2022.02.018. Epub 2022 Mar 1.
Non-small-cell lung cancer (NSCLC) is one of the main types of lung cancer. Due to lack of effective biomarkers for early detection of NSCLC, the therapeutic effect is not ideal. This study aims to reveal potential biomarkers for clinical diagnosis.
The plasma metabolic profiles of the patients were characterized by liquid chromatography-mass spectrometry (LC-MS). Differential metabolites were screened by p less than 0.05 and VIP greater than 1. Multivariate statistical analysis was used to search for potential biomarkers. Receiver operating characteristic (ROC) curve was used to evaluate the predictors of potential biomarkers. Pathway enrichment analysis was performed on metabolomics data by Ingenuity Pathway Analysis (IPA) and transcriptomics data from GEO were used for validation.
A plasma metabolite biomarker panel including 13(S)-hydroxyoctadecadienoic acid (13(S)-HODE) and arachidonic acid was chose. The area under the ROC curve were 0.917, 0.900 and 0.867 for the panel in the different algorithm like Partial Least Squares Discrimination Analysis (PLS-DA), Support Vector Machine (SVM), Random Forest (RF). The candidate biomarkers were associated with the Akt pathway. Genes involved in the biological pathway had significant changes in the expression levels.
13(S)-HODE and arachidonic acid may be potential biomarkers of NSCLC. The Akt pathway was associated with this biomarker panel in NSCLC. Further studies are needed to clarify the mechanisms of disruption in this pathway.
非小细胞肺癌(NSCLC)是肺癌的主要类型之一。由于缺乏用于 NSCLC 早期检测的有效生物标志物,因此治疗效果并不理想。本研究旨在揭示用于临床诊断的潜在生物标志物。
通过液相色谱-质谱(LC-MS)对患者的血浆代谢谱进行特征分析。通过 p 值小于 0.05 和 VIP 值大于 1 筛选差异代谢物。使用多元统计分析搜索潜在生物标志物。使用受试者工作特征(ROC)曲线评估潜在生物标志物的预测能力。通过 IPA 对代谢组学数据进行通路富集分析,并使用 GEO 的转录组学数据进行验证。
选择了一个包括 13(S)-羟基十八碳二烯酸(13(S)-HODE)和花生四烯酸的血浆代谢物生物标志物组合。在不同算法(如偏最小二乘判别分析(PLS-DA)、支持向量机(SVM)、随机森林(RF))中,该组合的 ROC 曲线下面积分别为 0.917、0.900 和 0.867。候选生物标志物与 Akt 通路相关。参与生物学通路的基因在表达水平上有显著变化。
13(S)-HODE 和花生四烯酸可能是非小细胞肺癌的潜在生物标志物。Akt 通路与 NSCLC 中的这个生物标志物组合有关。需要进一步研究来阐明该通路中断的机制。