通过高效液相色谱-四极杆飞行时间质谱(HPLC-Q-TOF/MS)分别对肺癌细胞与正常细胞的极性与非极性代谢物进行指纹图谱分析,进一步应用偏最小二乘判别分析(PLS-DA)对代谢组学数据进行多维统计分析.研究结果显示,与正常细胞相比,肿瘤细胞存在异常的蛋白质、脂肪酸、磷脂代谢,并发现31种对分类有显著贡献的代谢小分子物质.通过本研究,建立了基于液相色谱-质谱联用技术的肺癌细胞代谢组学分析方法,发现了肺癌潜在疾病标记物,可为肺癌分子标记物的发现及其早期诊断提供新思路和新方法.
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