基于MRM质谱技术的代谢重编程靶向的肝癌早期诊断标志物发现

Hepatocellular carcinoma (HCC) is a malignant tumor that is common China. It is the second most common cause of cancer-re¬lated deaths after lung cancer, with the 5-year survival rate of less than 5%. The key factor of high mortality is shortage of high effective early diagnostic biomarker for HCC. Therefore, it is of great importance to find optimal diagnostic biomarkers which are of high sensitivity, high specific and easy to be applied in clinical test. Metabolic reprogramming is a hallmark of cancer, which contribute to the establishment and maintenance of the tumorigenic state. Our quantitative proteomics and kinomic studies of HCC revealed the metabolic reprogramming in the development and progression of HCC. Proteins and kinases involved in glycolysis, serine/glycine metabolism and lipid metabolism altered significantly in HCC tissues compared with pare-wised non-HCC tissues. The changes of proteins and kinases will lead to changes of small molecular metabolites in these pathways. MRM-based targeted analysis is intrinsically more sensitive, selective, and quantitative, and has a broader dynamic range of 5–6 orders of magnitude than MS based on untargeted analysis in complex biological samples using TOF or QTOF instruments. Serum is the best sample for biomarker discovery due to the richest metabolites and the feasibility to access. Thus, we plan to choose about one hundred metabolites which involved in the significantly changed metabolic pathway based on our previous proteomic and kinomic studies and monitor their changes in the serum from healthy control, HBV-infected patients, liver cirrhosis and HCC patients using MRM-based targeted mass spectrometry technology. In this way, high sensitive, high specific early diagnostic biomarkers can be discovered and validated for clinical use. Moreover, the biological mechanism of key metabolites will be explored and new HCC treatment ideas through metabolic intervention will be provided.

肝癌是世界范围内常见恶性肿瘤，在我国居癌症死因第二位。缺乏有效早期诊断标志物是高死亡率重要因素。因此，探寻灵敏度高、特异性强、检测方便的早期诊断标志物具有重要意义。我们前期的蛋白质组及激酶组学结果表明肝癌发生发展过程中发生代谢重编程，多个蛋白质和激酶显著变化，涉及糖酵解、甘氨酸/丝氨酸代谢、脂肪代谢等多个通路。代谢通路变化会导致某些小分子代谢物变化而具有疾病指示作用。基于高性能质谱的多反应监测（MRM）技术能够靶向精确定量多个目标化合物，具有灵敏度高、特异性强、抗干扰能力强等优点。由于血液中代谢物丰富且临床样本易得，因此，本项目拟根据我们前期的研究结果，选取显著变化代谢通路相关小分子约100个，采用高灵敏、高特异的基于质谱的MRM技术对肝癌、肝硬化、肝炎患者及健康对照者血液中的小分子物质进行靶向检测，有望找肝癌早期诊断标志物并将该方法推向临床应用提供依据，并为肝癌抗代谢治疗提供思路。

肝癌是世界范围内常见恶性肿瘤，在我国居癌症死因第二位。缺乏有效早期诊断标志物是高死亡率重要因素。因此，探寻灵敏度高、特异性强、监测方便的早期诊断标志物具有重要意义。从代谢通路变化切入，以血液为研究对象，检测特定代谢物的变化不仅可以发现用于快速诊断的小分子标志物，还可研究癌驱动基因促进肿瘤发生发展的代谢机制，从而为伴有特定基因突变的肿瘤患者提供新的治疗思路。. 本项目选择了31个涉及丝氨酸、丝氨酸代谢通路、三羧酸循环（TCA）及糖酵解的重要代谢物，建立了基于超高效液相色谱分离结合多反应离子监测（UPLC-MRM）的非靶向代谢组方法，具有灵敏度高、重复性好的优点。优化了血清中小分子代谢物提取方法；通过比较五种不同提取方法，确定了最佳提取方法。应用建立的UPLC-MRM方法，对来自临床的健康对照84例、肝硬化及肝癌患者76例和132例血清样本进行了代谢物的提取和靶向代谢组研究，对其中28个代谢物进行了定量分析。根据p˂0.05，比较肝硬化组和正常组、肝癌和和正常组及肝癌和肝硬化组，分别筛选出了10、13及5个差异代谢物。结合差异倍数FC≥1.5或FC≤0.67和ROC曲线分析，在这三组比较中筛选出了1个、4个和3 个标志物，肝硬化组和正常组之间的标志物是L-Glutamic acid; 肝癌和和正常组之间的标志物是DL-Glyceric acid, L-Glutamic acid, succinic acid和Cysteine，这几个标志物的ROC曲线下面积均在0.90左右，表明他们在区分疾病和健康对照时具有较高的灵敏度和特异性。 肝癌和肝硬化组之间的标志物是Cysteine, L-Threonine, succinic acid，这三个标志物的ROC曲线下面积均在0.63左右。这几个代谢物需要进一步验证。综上所述，本研究建立了UPLC-MRM方法，并应用该方法进行了肝癌、肝硬化患者血清的靶向代谢组研究，找到了几个具有肝癌早期诊断价值的潜在生物标志物，具有一定的临床应用价值和学术意义。.