代谢组学
生物标志物
通路分析
接收机工作特性
肺癌
生物标志物发现
代谢物
转录组
曲线下面积
癌症
代谢组
生物
生物信息学
癌症研究
肿瘤科
计算生物学
化学
医学
内科学
蛋白质组学
生物化学
基因表达
基因
作者
Jianan Zheng,Zheng Yuan,Wenjing Li,Jinxiu Zhi,Xinjie Huang,Wei Zhu,Zhongqiu Liu,Lingzhi Gong
标识
DOI:10.1016/j.cca.2022.02.018
摘要
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.
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