Pamungkas Aryo D, Medriano Carl A, Sim Eunjung, Lee Sungyong, Park Youngja H
College of Pharmacy, Korea University, Jochiwon‑eup, Sejong 30029, Republic of Korea.
Department of Pulmonology, Korea University Guro Hospital, Guro‑gu, Seoul 08308, Republic of Korea.
Mol Med Rep. 2017 Jun;15(6):4155-4161. doi: 10.3892/mmr.2017.6530. Epub 2017 Apr 28.
The most common type of lung cancer is non‑small cell lung cancer (NSCLC), which is frequently characterized by a mutation in the epidermal growth factor receptor (EGFR). Determining the presence of an EGFR mutation in lung cancer is important, as it determines the type of treatment that a patients will receive. Therefore, the aim of the present study was to apply high‑resolution metabolomics (HRM) using liquid chromatography‑mass spectrometry to identify significant compounds in human plasma samples obtained from South Korean NSCLC patients, as potential biomarkers for providing early detection and diagnosis of minimally‑invasive NSCLC. The metabolic differences between lung cancer patients without EGFR mutations were compared with patients harboring EGFR mutations. Univariate analysis was performed, with a false discovery rate of q=0.05, in order to identify significant metabolites between the two groups. In addition, hierarchical clustering analysis was performed to discriminate between the metabolic profiles of the two groups. Furthermore, the significant metabolites were identified and mapped using Mummichog software, in order to generate a potential metabolic network model. Using metabolome‑wide association studies, metabolic alterations were identified. Linoleic acid [303.23 m/z, (M+Na)+], 5‑methyl tetrahydrofolate [231.10 m/z, (M+2H)+] and N‑succinyl‑L‑glutamate‑5 semialdehyde [254.06 m/z, (M+Na)+], were observed to be elevated in patients harboring EGFR mutations, whereas tetradecanoyl carnitine [394.29 m/z, (M+Na)+] was observed to be reduced. This suggests that these compounds may be affected by the EGFR mutation. In conclusion, the present study identified four potential biomarkers in patients with EGFR mutations, using HRM combined with pathway analysis. These results may facilitate the development of novel diagnostic tools for EGFR mutation detection in patients with lung cancer.
最常见的肺癌类型是非小细胞肺癌（NSCLC），其特征通常是表皮生长因子受体（EGFR）发生突变。确定肺癌中EGFR突变的存在很重要，因为这决定了患者将接受的治疗类型。因此，本研究的目的是应用液相色谱 - 质谱联用的高分辨率代谢组学（HRM）来鉴定从韩国NSCLC患者获得的人血浆样本中的重要化合物，作为提供早期检测和诊断微创NSCLC的潜在生物标志物。将无EGFR突变的肺癌患者与携带EGFR突变的患者的代谢差异进行比较。进行单变量分析，错误发现率q = 0.05，以识别两组之间的显著代谢物。此外，进行层次聚类分析以区分两组的代谢谱。此外，使用Mummichog软件识别并绘制显著代谢物，以生成潜在的代谢网络模型。通过代谢组全关联研究，确定了代谢改变。观察到携带EGFR突变的患者中，亚油酸[303.23 m/z，（M + Na）+]、5-甲基四氢叶酸[231.10 m/z，（M + 2H）+]和N-琥珀酰-L-谷氨酸-5-半醛[254.06 m/z，（M + Na）+]升高，而十四烷酰肉碱[394.29 m/z，（M + Na）+]降低。这表明这些化合物可能受EGFR突变影响。总之，本研究使用HRM结合通路分析，在EGFR突变患者中鉴定出四种潜在生物标志物。这些结果可能有助于开发用于检测肺癌患者EGFR突变的新型诊断工具。
