基于拟靶向代谢组学的胃癌化疗敏感性预测模型的研究

The chemsensitivity prediction of the cancer is a research hotspot and difficulty in clinical oncology. Considering the relationship between chemosensitivity and small molecular metabolites, the research for chemosensitivity prediction model of gastric cancer will be developed using the pseudotargeted metabolomics strategy based on the mass spectrometric technique. The pseudotargeted metabolomics is an analytical strategy which combines the targeted and untargeted method organically based on the principle of complementary. Firstly, non-targeted analytical method will be performed to analyze the mixed plasma samples of patients from different groups and the information about the parent ions and the fragment ions of all the metabolites will be achieved. Then the LC-MRM method will be developed and applied to the detection of the patient plasma after screening the characteristic MRM ion pairs using the targeted analysis. The multivariable statistical analysis and Information mining will be applied to discover potential biomarkers which have strong predictive power and are relevant to the chemosensitivity in gastric cancer. Furthermore, the structures of the biomarkers will be identified and the metabolic pathways of these biomarkers will be elucidated. The quantitation method of the potential biomarkers will be developed and the quantitation index will be identified. At the end, a prediction model with the small molecular biomarker used as the main index will be set up for the chemosentivity in gastric cancer, aim to explore a new research strategy for individual therapy of the gastric cancer patients.

肿瘤化疗敏感性预测一直是临床肿瘤学研究的热点和难点。本研究针对胃癌化疗敏感性与体内小分子代谢物之间的相关性，采用基于质谱技术的拟靶向代谢组学分析策略，开展胃癌化疗敏感性预测模型的研究。拟靶向代谢组学是采取优势互补的原则，将靶向分析和非靶向分析有机结合的一种分析策略。首先用非靶向分析方法得到不同分组患者血浆样本中所有代谢物的母、子离子信息，在此基础上，利用靶向分析思路，通过筛选、整合所有未知代谢物的特征MRM离子对并优化质谱参数，建立基于LC-MRM技术的靶向分析方法。用该方法对胃癌患者的血浆样本进行系统检测，结合多变量数据分析、信息挖掘方法等手段筛选与胃癌化疗敏感性密切相关且有较强预测能力的生物标志物。此外，对生物标志物的结构进行鉴定，并分析其代谢通路、建立定量分析方法和定量指标。最终构建以小分子生物标志物为主要指标的胃癌化疗敏感性预测模型，旨在从代谢水平探索胃癌个体化治疗策略。

我国胃癌的发病率和死亡率仅次于肺癌位居第二。 手术、化疗和放疗是治疗胃癌的三大主要手段。其中，化疗是治疗晚期胃癌的重要手段，但目前化疗药物的总体有效率比较差，肿瘤化疗敏感性预测一直是临床肿瘤学研究的热点和难点。本研究针对胃癌化疗敏感性与体内小分子代谢物之间的相关性，采用基于质谱技术的拟靶向代谢组学分析策略，开展胃癌化疗敏感性预测模型的研究。拟靶向代谢组学是采取优势互补的原则，将靶向分析和非靶向分析有机结合的一种分析策略。首先用非靶向分析方法得到不同分组患者血浆样本中所有代谢物的母、子离子信息，在此基础上，利用靶向分析思路，通过筛选、整合所有未知代谢物的特征MRM离子对并优化质谱参数，建立基于LC-MRM技术的靶向分析方法。用该方法对胃癌患者的血浆样本进行系统检测，结合多变量数据分析、信息挖掘方法等手段筛选与胃癌化疗敏感性密切相关且有较强预测能力的生物标志物，旨在从代谢水平探索胃癌个体化治疗策略。本研究通过上述方法找到了能预测胃癌患者化疗后不同疗效的差异代谢物32个，目前正在进行结构鉴定和代谢通路分析，有望用于临床中。在胃癌化疗前，用来预测患者对化疗方案是否敏感，有针对性的选择化疗药物，无疑将大幅度提高胃癌化疗的有效率，改善胃癌患者的预后，真正实现个体化治疗。