CN104713969B - One kind of esophageal cancer primary screening method for constructing a model of serum metabolomics - Google Patents

One kind of esophageal cancer primary screening method for constructing a model of serum metabolomics Download PDF

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CN104713969B
CN104713969B CN201510149599.XA CN201510149599A CN104713969B CN 104713969 B CN104713969 B CN 104713969B CN 201510149599 A CN201510149599 A CN 201510149599A CN 104713969 B CN104713969 B CN 104713969B
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serum
analysis
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serum samples
esophageal cancer
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CN104713969A (en
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王家林
张涛
薛付忠
赵德利
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山东省肿瘤医院
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Abstract

本发明公开了一种血清代谢组学分析模型,构建方法包括:收集健康血清样本和患病血清样本;对样本进行LC‑MS检测,得原始代谢指纹图谱;将图谱进行预处理,所得二维矩阵依次进行主成分分析和偏最小二乘判别分析,得PLS‑DA模型,对得到的PLS‑DA模型进行验证,无过拟合危险,则模型构建完成。 The present invention discloses a serum metabonomics analysis model construction method comprising: collecting serum samples healthy and diseased serum samples; LC-MS of samples detected to obtain the original metabolic fingerprint; preprocessing the pattern, the resulting two-dimensional sequentially principal component analysis and partial least squares discriminant analysis, PLS-DA model obtained, for PLS-DA model was subjected to verification overfitting without danger, the matrix model building is completed. 本发明首次将血清代谢组学分析技术用于食管癌早期筛查中,利用本发明模型可以快速、便捷的筛选出食管癌高发人群,缩小食管癌筛查的范围,有效提高了食管癌高发区全人群筛查的效率,大大降低了筛查成本,有效避免了部分人群有创胃镜造成的痛苦,具有重要的经济和社会效益,便于推广应用。 The present invention first serum metabolomic analysis techniques for early diagnosis of esophageal cancer, using the model of the present invention can be quickly and easily screen out high risk of esophageal cancer, esophageal cancer screening narrow, effectively improve the high incidence of esophageal population-wide screening efficiency and greatly reduce the cost of screening, effectively avoid the part of the population suffering caused by invasive endoscopy, has important economic and social benefits, ease of application.

Description

一种食管癌初步筛查用血清代谢组学分析模型的构建方法 One kind of esophageal cancer primary screening method for constructing a model of serum metabolomics

技术领域 FIELD

[0001] 本发明涉及一种血清代谢组学分析模型,通过该模型可以方便、快捷对食管癌进行早期初步筛查,属于分析技术领域。 [0001] The present invention relates to a serum metabolomic analysis model, this model can be easily, fast and early esophageal preliminary screening, technical field belongs to analysis.

背景技术 Background technique

[0002] 食管癌(esophageal cancer)是由食管鳞状上皮或腺上皮的异常增生所形成的恶性病变,是由不典型增生到癌的逐渐演变的过程。 [0002] esophageal malignancy (esophageal cancer) is esophageal squamous epithelium or glandular epithelium formed by abnormal proliferation is cancer evolved from dysplasia to the process. 据世界卫生组织最新数据表明:全世界每年约有40万人死于食管癌,我国是食管癌发病率和死亡率最高的国家,且90%患者的组织类型为鳞状细胞癌。 According to the latest World Health Organization data show that: there are around 40 million people each year die from esophageal cancer, esophageal cancer of morbidity and mortality in countries with the highest and 90% of patients with tissue type is squamous cell carcinoma. 山东省汶河流域为食管癌高发区,以肥城市、宁阳县和汶上县最高,发病率分别为93.95/10万、88.68/10万和62.26/10万,远高于全国一般水平(16.7/10万),尤其是肥城市,其发病率为山东省平均水平的3.7倍,占到全县肿瘤死因的50%。 Wen River Basin in Shandong Province for the high incidence of esophageal, to fat city, Ningyang County Wenshang County and the highest incidence rate of 93.95 / 10 million and 88.68 / 100,000 and 62.26 / 100,000, respectively, well above the national level in general ( 16.7 / 100,000), especially in fat city, the incidence rate was 3.7 times the average level of Shandong province, the county accounted for 50% of the tumors cause of death. 食管癌的高发病率和高死亡率给我国尤其是山东省汶河流域造成了巨大的疾病负担和经济负担,已经成为严重的公共卫生问题,亟待解决。 High incidence of esophageal cancer and high mortality to China, especially in the Wen River Basin in Shandong Province caused a huge burden of disease and economic burden, has become a serious public health problem, to be solved.

[0003] 食管癌的病因复杂,多数学者认为是基因与环境共同作用的结果,食管癌发病的地域聚集性提示其与环境因素及不良生活习惯相关,如膳食成分中维生素与微量元素缺乏、进食含亚硝胺类较多的食物、如喜欢腌制酸菜或霉变食品、长期喜进烫食、吸烟、饮酒不良嗜好等。 [0003] complex etiology of esophageal cancer, most scholars believe is the result of the interaction of genes and environment, geographical aggregation of esophageal cancer associated with environmental factors that prompt and bad habits, such as dietary ingredients in vitamins and micronutrient deficiencies, eating contain nitrosamines more foods such as sauerkraut or pickled like moldy food, hot food into the long-term joy, smoking, drinking and other bad habits. 分子学研究表明食管癌的发生是多因素、多阶段、多基因变异的积累以及各因素与环境因素相互作用的结果,涉及众多原癌基因、抑癌基因以及蛋白质的改变,以及细胞周期。 Molecular studies have shown that esophageal cancer is a multi-factor, multi-stage, multi-gene mutations accumulate and the result of various factors interact with environmental factors, involving many genes, tumor suppressor genes and proteins change, as well as the original cancer cell cycle. 从癌前病变到食管癌的发生往往会经历漫长的过程,食管癌的重要癌前病变为食管鳞状上皮轻、中、重度不典型增生,由轻度不典型增生到癌变一般需要几年甚至十几年。 From precancerous lesions to esophageal cancer tend to go through a lengthy process, it is important precancerous lesions of esophageal cancer esophageal squamous epithelium mild, moderate and severe dysplasia from mild dysplasia to cancer usually takes years or even Over ten years. 如果在此期间,癌前病变人群改变不良生活习惯、进行预防性服药,那么将大大降低其癌变的几率。 If during this period, precancerous lesions population change bad habits, preventive medication, it will greatly reduce the chance of their cancer. 因此,食管癌癌前病变的早期识别和干预对降低其癌变率显得尤为重要。 Therefore, early identification and intervention esophageal precancerous lesions is particularly important to reduce the cancer rate.

[0004] 为筛查处于轻度、中度和重度不典型增生的癌前病变状态或早期食管癌的病例, 国家自2008年起在山东省肥城市(全国食管癌早诊早治示范基地),针对示范基地内的所有40~69岁的人群,借助胃镜下碘染色指示性活检技术,开展了食管癌早诊早治项目。 [0004] is screening in mild, moderate and severe cases of dysplasia or early esophageal precancerous lesions state, the state since 2008 in Shandong Province fat city (country esophageal cancer early detection and treatment demonstration base) for all 40 to 69 year-olds in the base model, with iodine staining indicative endoscopic biopsy techniques, carried out esophageal cancer early detection and treatment programs. 食管内镜碘染色检查后对可疑粘膜活检并进行组织病理学检查,是目前食管癌高发区普查、高危人群筛检和早期诊断中的金标准方法。 Esophageal iodine staining of endoscopic mucosal biopsies of suspicious histopathology, is the high incidence of esophageal screening, high-risk population screening and early diagnosis of the gold standard. 由于其直观,图像淸晰且特异性高,目前还没有一种方法能替代其地位。 Due to its intuitive Qing image clarity and high specificity, there is no substitute for a method for its position. 虽然该方法准确度高,但仍具有一定的局限性:胃镜为有创检查,且受检者感觉痛苦,在执行过程中有不依从现象;胃镜下碘染色指示性活检技术操作复杂、成本较高,如果在高发的示范区之外推广的可行性及效率仍有待商榷;食管癌高发区的碘染色阳性率不到10%,高达90%的待筛查人群要承受有创胃镜检查的痛苦,还给国家早诊早治项目带来了不必要的经济负担。 Although this method is accurate, but still has some limitations: gastroscopy is an invasive and painful subjects sensation, there is the phenomenon of non-compliance in the implementation process; iodine complex staining indicative endoscopic biopsy operation costs than high, if in addition to the high incidence of demonstration area to promote the feasibility and efficiency is still questionable; high incidence of esophageal iodine staining positive rate of less than 10%, up to 90% of the population to be screened to bear the pain of invasive gastroscopy , returned to the country early detection and treatment project brings unnecessary financial burden. 因此,急需开发一种新的更简便的方法,探寻在食管癌发生发展阶段机体内环境的变化,为食管癌的金标准筛检方法(即胃镜下碘染色指示性活检技术) 提供初筛的科学依据和转化医学支持,以区分碘染色阴性和碘染色阳性人群,从而避免碘染色阴性人群承受有创胃镜的痛苦并减少早诊早治项目的财政支出。 Therefore, an urgent need to develop a new and more convenient way to explore the changes in the development stage of internal environment in esophageal cancer, screening for providing the gold standard screening method (ie, iodine staining indicative endoscopic biopsy technique) esophageal cancer Translational Medicine scientific basis and support, in order to distinguish iodine and iodine-negative staining positive people to avoid iodine-negative invasive endoscopic people bear the pain and reduce fiscal spending early detection and treatment programs. 此外,在食管癌早诊早治项目早期曾试行使用哈佛癌症风险预测模型(问卷涉及的内容包括生活环境、饮食方式和习惯、心情和情绪、既往病史及恶性肿瘤家族史等五大方面)初步筛查食管癌高危个体,然后针对高危个体再施行胃镜下碘染色指示性活检技术。 In addition, early detection and treatment of esophageal cancer had earlier pilot project using the Harvard cancer risk prediction model (the contents of the questionnaire covered include five aspects of the living environment, diet and habits, moods and emotions, past medical history and family history of cancer, etc.) preliminary screening check esophageal risk individuals, and for the purposes of high-risk individuals and then iodine staining indicative endoscopic biopsy technique. 但在实际执行中发现其具有较高的假阴性率(即漏诊),R〇C曲线下面积AUC为0.70 (95%CI,0.66-0.74)(文献来源: Thrift AP, Kendall BJ, Pandeya N, Vaughan TL, Whiteman DC. A clinical risk prediction model for Barrett esophagus. Cancer Prev Res (Phila) , 2012,5(9): 1115-23.)。 Found in the actual implementation but it has a higher false negative rate (i.e., missed), the area under the AUC curve R〇C 0.70 (95% CI, 0.66-0.74) (literature sources: Thrift AP, Kendall BJ, Pandeya N, . Vaughan TL, Whiteman DC A clinical risk prediction model for Barrett esophagus Cancer Prev Res (Phila), 2012,5 (9):. 1115-23).. 由于该传统初筛方法效果不理想,目前食管癌筛查范围仅作40-69岁的年龄限定。 Since the traditional screening method is not satisfactory, the current range of esophageal cancer screening only for 40-69 year-old age limit.

[0005] 代谢组学是对生物样品(如血清、尿液、唾液等)中所有分子量低于lOOODa小分子代谢物(如脂肪酸、氨基酸、核苷及留体等生物小分子)进行定性定量检测,从而监测机体受疾病或危险因素累积等干扰后内源性物质做出的代谢响应。 [0005] Metabolomics is a biological sample (e.g., serum, urine, saliva, etc.) in all molecular weights below lOOODa small molecule metabolites (e.g., fatty acids, amino acids, nucleosides and the like leaving biomicromolecules) qualitative and quantitative detection of , to monitor the body disease or other metabolic risk factors in response to accumulation of endogenous substances made after the disturbance. 体内的生物信息由基因经转录传递给蛋白质,最终体现为小分子代谢物。 Vivo biological information transmitted from gene to protein transcribed, ultimately embodied as a small molecule metabolites. 不同于基因组学和蛋白组学反映的生物体内在差异,代谢组学的研究领域扩展到了机体与环境之间的相互影响和作用。 Unlike genomics and proteomics vivo expanded to reflect the action and the interaction between the body and the difference in the environment, metabolomics research. 小分子代谢物不仅是机体生命活动、生化代谢的物质基础,还体现了某些外来因素对体内代谢环境的改变, 因而某些独特代谢物的浓度在不同个体间的差异事实上反映了疾病内在的表现和外在病因。 Small molecule metabolites not only is the body's life activities, the material basis of biochemical metabolism, but also reflects some changes in external factors in vivo metabolism of the environment, and thus the concentration of some unique differences in metabolites between different individuals in fact reflect the inherent disease performance and external causes. 近年来研究发现,诸如代谢性疾病和恶性肿瘤(卵巢癌)等疾病发生发展过程中,机体基础生化代谢均发生了明显变化,对人类理解复杂疾病的代谢机制将发挥重要作用,同时为复杂疾病的筛检和早期诊断提供崭新的技术方法。 Recent studies found that diseases such as metabolic diseases and malignant tumors (ovarian cancer) and so the development process, the body's basal metabolic biochemistry have undergone significant changes, human understanding metabolic mechanisms of complex diseases will play an important role, as well as complex disease screening and early diagnosis to provide new technical methods.

[0006] 食管癌是一种典型的代谢性疾病,在我国90%以上患者为食管鳞状细胞癌(ESCC), 其通常表现为机体整体的代谢紊乱,因此代谢组学技术和方法非常适合于食管癌的研究。 [0006] Esophageal cancer is a typical metabolic diseases, more than 90% of patients with esophageal squamous cell carcinoma (of ESCC), which usually presents the whole body metabolism, techniques and methods thus is very suitable for metabolome study of esophageal cancer. 目前,已经有人利用代谢组学对食管癌进行研究,例如Wu等(Wu H,Xue R,Lu C,et al. Metabolomic study for diagnostic model of oesophageal cancer using gas chromatography/mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci,2009,877 (27) :3111_7.)、Zhang等(Zhang J,Bowers J,Liu L,et al· Esophageal cancer metabolite biomarkers detected by LC-MS and NMR methods. PLoS One,2012,7(1) :e30181.)、Xu等(Xu J,Chen Y,Zhang R,et al· Global and targeted metabolomics of esophageal squamous cell carcinoma discovers potential diagnostic and therapeutic biomarkers. Mol Cell Proteomics,2013,12 (5) :1306-18.)都利用代谢组学技术对食管癌进行了研究,但总体来说这些研究大多集中于病理学和发病机制的研究,为疾病的发生机理提供了新的线索,所使用的样本也是基于医院采集的食管癌晚期患者的样本,所得的研究结果仅能发现食管癌发病晚期同健康对照相比的代 At present, it has been the use of esophageal metabonomics study, for example, Wu et al. (Wu H, Xue R, Lu C, et al. Metabolomic study for diagnostic model of oesophageal cancer using gas chromatography / mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci, 2009,877 (27):.. 3111_7), Zhang et (Zhang J, Bowers J, Liu L, et al · Esophageal cancer metabolite biomarkers detected by LC-MS and NMR methods PLoS One, 2012,7 ( 1):. e30181), Xu et (Xu J, Chen Y, Zhang R, et al · Global and targeted metabolomics of esophageal squamous cell carcinoma discovers potential diagnostic and therapeutic biomarkers Mol Cell Proteomics, 2013,12 (5):. 1306 -18.) make use of metabolomics technology for esophageal cancer has been studied, but research in general, most of these studies focus on pathology and pathogenesis, provides new clues for the mechanism of the disease, the sample is used based on a sample of patients with advanced esophageal cancer hospital collected, the results obtained can only be found with advanced esophageal cancer compared with healthy controls on behalf of the 谢轮廓差异,而癌症晚期的血清代谢情况与癌前病变的血清代谢差异巨大,并不能对于食管癌的早期筛检和早期诊断带来帮助。 Xie outline differences, and serum metabolic differences with advanced cancer and precancerous lesions serum metabolism huge, and can not bring help for early screening and early diagnosis of esophageal cancer. 并且,目前上述研究方法在健康对照选取上容易受到选择性偏倚影响,造成评价结果的推广性较差。 Further, the above-described research methods currently vulnerable to the influence on the selectivity bias select healthy controls, resulting in promotion of poor evaluation results.

发明内容 SUMMARY

[0007] 针对现有技术中食管癌早期筛查方法繁琐、费用高、对检测人群造成痛苦等不足, 还没有一种简便快捷、适合大范围的缺陷,本发明提供了一种血清代谢组学分析模型,该分析模型构建方法简单,能够代替胃镜下碘染色指示性活检技术对人群进行食管癌早期、初步筛查,既经济实惠、方便快捷,又能避免待检测人群的痛苦,便于推广应用。 [0007] esophageal cancer early screening method for the cumbersome prior art, high cost, and other pain caused by lack of detection of the crowd, there is not a quick and easy, suitable for a wide range of defects, the present invention provides a serum metabolomics analysis model, the analysis model construction method is simple, can replace iodine staining under endoscopy biopsy indicative of early esophageal cancer populations, preliminary screening, not only affordable, convenient, and can avoid the pain to be detected crowd, easy application .

[0008] 本发明针对目前采用胃镜下碘染色指示性活检技术对食管癌进行初步筛查的不足,首次提出采用血清代谢组学技术代替胃镜下碘染色指示性活检技术对食管癌进行初步筛查的思路。 [0008] The present invention is directed to insufficient iodine staining indicative currently used endoscopic biopsy technique esophageal preliminary screening, the first time using in place of serum metabonomics iodine staining indicative of esophageal endoscopic biopsy technique for initial screening ideas. 本发明依托"国家食管癌早诊早治示范基地(山东省肥城市)"的食管癌筛检与随访人群队列,针对项目中所有胃镜下碘染色指示性活检对象,采集初次发现的上消化道病变、食管癌癌前病变和食管癌早期患者的血清标本,并随机抽取筛检中无上消化道病变的健康对象作为对照组,使用快速分离液相色谱和质谱仪(LC/MS)的高通量检测获得相应的代谢指纹图谱,并通过对图谱的进一步分析构建得到了模型,该模型能够分析辨别血清代谢物情况,通过血清代谢物情况能够初步判断是否具有食管癌患病危险。 The present invention relies on "State of esophageal cancer early detection and treatment demonstration base (Shandong Province fat city)," the esophageal cancer screening and follow-up cohort, the project for all endoscopic biopsy iodine staining indicative target, collecting initial discovery of the digestive tract disease, esophageal cancer and precancerous lesions in patients with early esophageal cancer serum samples and random screening of healthy subjects supreme gastrointestinal lesions as a control group, the use of liquid chromatography and mass spectrometry rapid Resolution (LC / MS) high detecting metabolic flux to obtain the corresponding fingerprint, and further analysis of the map has been constructed model, which can be analyzed to identify serum metabolite case, where the serum metabolites can be determined whether the initial illness risk of esophageal cancer. 利用本发明模型可以用于高发病区的全人群食管癌早期筛检,筛除没有患病危险的人群,然后再针对高危个体进行常规内镜检查,判断是否患有食管癌。 With the present invention may be used to model the whole region of the high incidence of esophageal cancer population early screening, screening unaffected populations at risk, then the routine endoscopy for high risk individuals, it is determined whether or not having esophageal cancer. 本发明缩小了内镜检查的范围,对于食管癌筛检的实施和推广有着重要的经济和社会效益。 The present invention reduces the scope of endoscopy, for the implementation and promotion of esophageal cancer screening has important economic and social benefits.

[0009] 本发明具体技术方案如下: [0009] In particular aspect of the invention as follows:

[0010] -种血清代谢组学分析模型,构建方法包括以下步骤: (1)收集健康血清样本和患病血清样本,作为分析样本; [0010] - sera metabolomic analysis model construction method comprising the steps of: (1) collecting serum samples healthy and diseased serum samples, a sample for analysis;

[0012] (2)将每个分析样本采用LC-MS血清代谢组学技术进行分析,得健康血清样本和患病血清样本的原始代谢指纹图谱; [0012] (2) Each sample using LC-MS analysis of serum metabonomics analysis, serum samples obtained health and diseased metabolic fingerprint original serum samples;

[0013] (3)将健康血清样本和患病血清样本的原始代谢指纹图谱进行图谱预处理,得到每行为分析样本,每列为代谢物信息的二维矩阵,用于进一步的统计分析; [0013] (3) serum samples of healthy and diseased serum samples of the original pattern for pretreatment metabolic fingerprint, to give each behavior analysis of samples, each as a two dimensional matrix metabolite information for further statistical analysis;

[0014] (4)将步骤(3)的二维矩阵依次进行主成分分析(PCA)和偏最小二乘判别分析(PLS-DA),得PLS-DA模型,对得到的PLS-DA模型进行验证,无过拟合危险,则所得PLS-DA模型即为血清代谢组学分析模型。 Sequentially [0014] (4) The step (3) a two-dimensional matrix of principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), to give PLS-DA model, PLS-DA model was subjected to verification, overfitting without danger, the resulting serum is the PLS-DA model metabolomic analysis model.

[0015] 上述构建方法中,所述LC-MS血清代谢组学技术是采用液相色谱-质谱联用系统检测血清的代谢指纹图谱的方法,本发明的优选实施方式中,所用的液相色谱-质谱联用系统为超高效液相色谱-高分辨质谱联用系统(UPLC-QT0F/MS)。 [0015] In the above construction method, the LC-MS serum metabonomics is the use of liquid chromatography - mass spectrometry system serum metabolite fingerprinting method, a preferred embodiment of the present invention, used in liquid chromatography - MS system performance liquid chromatography - high resolution mass spectrometry system (UPLC-QT0F / MS). 优选的,液相色谱所用色谱柱为Waters ACQUITY UPLC ® HSS Τ3(1·8 μπι; 100 mm (length) X 2.1 mm)色谱柱,进样量为6yL,进样温度为4°C,流速为0.5 ml/min。 Preferably, the HPLC column was used Waters ACQUITY UPLC ® HSS Τ3 (1 · 8 μπι; 100 mm (length) X 2.1 mm) column, the injection volume 6YL, injection temperature of 4 ° C, flow rate 0.5 ml / min. 色谱流动相包含两种溶剂:A为0. lwt%甲酸水溶液(正离子ESI+)或0.5mmol/L氟化铵水溶液(负离子ESI-),B为0. lwt%甲酸的乙腈溶液(正离子ESI+)或纯乙腈(负离子ESI-)。 Chromatography flow phase comprises two solvents: A is 0. lwt% aqueous formic acid solution (positive ion ESI +) or 0.5mmol / L aqueous ammonium fluoride solution (negative ESI -), B is 0. lwt% formic acid in acetonitrile (positive ion ESI + ) or pure acetonitrile (negative ESI-). 色谱梯度洗脱条件为:〇-lmin为l%B,l-8min为1%B-100% B逐渐递增,然后10-10.1min为100%B迅速减为1%B,然后1%B持续1.9min。 Gradient elution chromatographic conditions were: square-lmin of l% B, l-8min to 1% B-100% B gradually increasing, then 10-10.1min was quickly reduced to 100% B 1% B, then 1% B Length 1.9min. 优选的,质谱检测使用四极杆时间飞行质谱仪Q-T0F,并采用电喷雾离子源的正离子模式(ESI+)和负离子模式(ESI-)。 Preferably, the mass spectrometry using quadrupole time of flight mass spectrometer Q-T0F, and using positive mode electrospray ion source (ESI +) and negative mode (ESI-). 离子源温度设定为400°C,锥孔气流量为12L/min。 The ion source temperature was set at 400 ° C, cone gas flow rate of 12L / min. 同时,脱溶剂气温设定为250 °C,脱溶剂气流量16L/min。 Meanwhile, the desolvation temperature was set to 250 ° C, desolvation gas flow rate of 16L / min. 在正离子和负离子模式下毛细管电压分别为+3kV和-3kV,锥孔电压均为0V。 In the positive and negative ion mode, the capillary voltage of + 3kV and were -3kV, are cone voltage 0V. 锥孔压力为20psi (正离子)和40psi(负离子)。 Cone pressure of 20psi (positive) and 40 psi for (negative). 图谱数据采集的质荷比范围为50~1200 m/z,采集的扫描频率为0.25s。 Mass spectral data collected charge ratios of 50 ~ 1200 m / z, the scanning frequency is acquired 0.25s.

[0016] 上述构建方法中,所述患病血清样本选自食管炎患者、轻度不典型增生患者、重度不典型增生患者、中度不典型增生患者、食管癌癌前病变患者、食管癌早期患者和原位癌患者的血清。 [0016] In the above construction method, the prevalence of serum samples selected esophagitis, patients with mild dysplasia, severe dysplasia patients, patients with moderate dysplasia, precancerous lesions esophageal cancer, esophageal cancer early and serum of patients with carcinoma in situ. 所述患者血清样本可以是患有上述一种病症的患者的血清,也可以是患有上述两种或两种以上的病症的患者的血清(例如患病血清为食管炎患者血清和轻度不典型增生患者的血清,或者是重度不典型增生患者血清、中度不典型增生患者血清和食管癌早期患者血清),优选的,患病血清样本含有患有上述每种病症的患者的血清(即患病血清样本中同时含有食管炎、轻度不典型增生、重度不典型增生、中度不典型增生、食管癌癌前病变、食管癌早期和原位癌患者的血清),预测准确度更高。 The serum may be serum sample of the patient suffering from a condition described above, or may be a patient suffering from the above-described serum two or more conditions (e.g., diseased patient serum and serum mild oesophagitis dysplasia patient serum or serum severe atypical hyperplasia, moderate atypical hyperplasia serum and serum early esophageal cancer), preferably, diseased serum samples containing each of the above serum of patients suffering from a condition (i.e. serum samples containing both diseased esophagitis, mild dysplasia, severe dysplasia, moderate dysplasia, precancerous lesions serum esophageal cancer, esophageal cancer patients with early and carcinoma in situ), a higher prediction accuracy .

[0017] 上述构建方法中,所述健康血清样本为没有患病血清样本所对应疾病或者与所对应疾病类似的疾病的人群的血清,也可以说是健康血清样本为没有上消化道病变的人群的血清。 [0017] In the above construction method, the health of a serum sample and the absence of disease or serum disease groups like disease prevalence corresponding serum samples corresponding to, it can be said that there is no healthy people serum samples on gastrointestinal lesions serum.

[0018] 上述构建方法中,所得PLS-DA模型的R2X=0.231, R2Y=0.749, Q2cum=0.638。 [0018] In the above construction method, R2X resulting model PLS-DA = 0.231, R2Y = 0.749, Q2cum = 0.638. 在此情况下模型灵敏度高,特异性好,具有很好的外推效果。 In this case, the model has high sensitivity, specificity and extrapolation with good effect.

[0019] 上述构建方法中,所述健康血清样本和患病血清样本均来自40-69岁人群。 [0019] In the above construction method, the serum samples of healthy and diseased serum samples were from 40-69 years of age.

[0020] 上述构建方法中,所选择的血清样本数量大,所述患病血清样本453个,健康血清样本187个,预测效果更高。 [0020] In the above construction method, a large number of selected serum samples, the prevalence of serum samples 453, 187 healthy serum samples, higher prediction.

[0021] 上述构建方法中,为了实时监测模型构建时的质量控制情况,加入质量控制样品进行质量控制。 [0021] In the above construction method, the mass model building for control of real-time monitoring, addition of quality control samples for quality control. 加入方式为:每10个分析样本加入一个质量控制样品,该质量控制样品可以用于实时监测分析样本从进样前处理到分析过程中的质量控制情况。 Add way: every 10 samples analyzed was added a quality control samples, the quality control samples can be used for real-time monitoring and analysis of quality control samples from the process prior to injection into the analysis process. 所述质量控制样品组成相同,均为同一健康血清样本和同一患病血清样本按照1:1的体积比混合得到的样品。 Quality control samples consisting of the same, the same serum samples were healthy and diseased serum samples according to the same 1: 1 ratio of sample volume obtained. [0022] 上述构建方法中,在取得分析样本和质量控制样品后,要对他们进行预处理,预处理后再加入液相色谱-质谱联用系统进行检测。 [0022] In the above construction method, after obtaining the samples and quality control samples analyzed, pretreatment to them, then added pretreatment liquid chromatography - mass spectrometry detection system. 进样前的预处理包括以下步骤: Pretreatment of the sample comprising the steps of:

[0023] (1)用移液器抽取50μ1分析样本或质量控制样品,置于Bravo自动标本处理系统(Agilent,USA)的96孔板上; [0023] (1) analyzing a sample by pipette or extraction 50μ1 quality control samples, placed on Bravo automatic sample processing system (Agilent, USA) in 96 well plates;

[0024] (2)加入150μ1甲醇提取,涡旋30s,并在-20°C下孵化以沉淀蛋白。 [0024] (2) the methanol extract was added 150μ1, vortexed 30s, and incubation at -20 ° C to precipitate the proteins.

[0025] (3)然后于高速离心机中在4°C下以4000转/分离心20min; [0025] (3) and in a high speed centrifuge at 4 ° C for 4000 revolutions / 20min isolated heart;

[0026] ⑷将步骤⑶的上清液倒入LC-MS进样瓶中,保存在-80°C下以备LC-MS检测。 [0026] ⑷ ⑶ Step supernatant was poured into vials LC-MS, LC-MS saved for detecting at -80 ° C.

[0027] 上述Bravo自动标本处理系统,也叫Bravo自动化液体处理平台。 [0027] The automatic sample processing system Bravo, Bravo Automated liquid handling also called internet.

[0028] 上述分析样本和质量控制样品预处理过程中,如果分析样本和质量控制样品取样时间较长,可以将它们放入_80°C冰箱内保存,预处理时将装有已冷冻的0.4ml分析样本或质量控制样品的〇.5ml离心管置于水中,水平面以没过冰冻表面为宜,放入冰箱冷藏室中进行解冻;完全解冻后,涡旋30s。 [0028] The analysis of samples and quality control samples pretreatment process, if the analysis of samples and quality control samples long sampling time, they can be stored into the refrigerator _80 ° C, the pretreatment with the frozen 0.4 analysis ml samples or quality control samples 〇.5ml centrifuge tube was placed in water, not over the horizontal plane surface preferably frozen, thawed in the refrigerator freezer; after completely thawed, vortexed 30s. 经过以上解冻处理后再用上述预处理步骤进行预处理。 After the above pretreatment with thawing treatment after the above-described pretreatment step.

[0029] 上述构建方法中,对原始代谢指纹图谱进行图谱预处理是指:用Masshunter软件将获得的原始代谢指纹图谱转换为MZdata数据文件,然后将Mzdata数据文件使用XCMS软件包进行包括保留时间校正、峰识别、峰匹配和峰对齐的预处理操作,得到可用于统计分析的二维矩阵,矩阵中的每行为分析样本或质量控制样品,每列为代谢物信息。 [0029] In the above construction method, the original pattern preprocessing fingerprints metabolic means: converting original Masshunter metabolic fingerprint obtained for MZdata software data file and the data file using the Mzdata XCMS software package including a time correction , peak identification and peak matching alignment and peak preprocessing operations, two-dimensional matrix can be used to give statistical analysis, the behavior of each matrix sample analysis or quality control samples, each of the information as metabolites.

[0030] 在上述血清代谢组学分析模型中,健康血清样本和患病血清样本的代谢物信息分别位于模型的不同位置,且各自无重叠,可以记为健康血清样本组区域为阴性区域,患病血清样本组区域为阳性区域。 [0030] In the serum model metabolomic analysis, serum samples healthy and diseased serum samples metabolite information are located at different positions of the model, without overlap and each may be referred to as serum sample set region healthy negative region, suffering from serum sickness sample set region is positive region.

[0031] 使用上述血清代谢组学分析模型,可以用于血清样本的代谢组学分析。 [0031] Using the above serum metabolomic analysis model can be used to set the metabolic analysis of serum samples.

[0032] 本发明的分析血清代谢组学的方法,包括以下步骤:将待检血清样本进行预处理, 达到进样要求;将预处理的待检血清样本采用LC-MS血清代谢组学技术进行分析,得该待检血清样本的原始代谢指纹图谱;将该原始代谢指纹图谱进行图谱预处理,得到可以用于统计分析的代谢物信息;将该代谢物信息导入血清代谢组学分析模型中,用于分析待检血清样本的代谢组学情况。 [0032] A method for analysis of serum metabolomics present invention, comprising the steps of: serum samples subject to be pretreated to achieve the required injection; pretreated serum samples to be tested using LC-MS techniques serum metabonomics analysis, serum samples have to be the subject of the original metabolic fingerprint; the original pattern for the pretreatment metabolic fingerprint, may be used to obtain information metabolites statistical analysis; this information into serum metabolite metabolomic analysis model, analysis for metabolomics case of serum samples to be tested. 通过分析可以获得食管癌早期筛查风险的预测概率(大于50%即为阳性),从而通过人体代谢情况判定食管癌筛查风险。 By analyzing the predicted probability of screening for early esophageal cancer risk may be obtained (that is, greater than 50% positive), thereby determining the risk of esophageal cancer by screening for the human metabolism. 在实际应用中,如果待检血清样本的代谢物信息位于模型的患病血清样本组区域(即阳性区域,即预测概率大于50%),则表示该人具有食管癌的患病危险,需要进行进一步的内镜下指示性活检;如果待检血清样本的代谢物信息位于模型的健康血清样本组区域(即阴性区域,预测概率小于50%),则表示该人不具有食管癌的患病危险,不需要进行进一步的检查。 In practice, if the information to be metabolites in serum samples from the subject positioned diseased area of ​​the model group serum samples (i.e. positive areas, i.e., the predicted probability is greater than 50%), it indicates that the sick person having a risk of esophageal cancer, the need for further indicative endoscopic biopsy; if metabolite serum samples to be tested serum samples from healthy group information is located in areas of the model (i.e., a negative region, the predicted probability is less than 50%), it indicates that the person does not have the risk of esophageal cancer diseased , does not require further examination.

[0033] 上述分析血清代谢组学的方法中,对待检血清样本进行预处理的步骤、将待检血清样本的原始代谢指纹图谱进行图谱预处理的步骤都和上述构建血清代谢组学分析模型时的预处理步骤、图谱预处理步骤相同。 [0033] The method for analyzing serum metabolomics, the subject treated serum samples preprocessing step, the original metabolic fingerprint to be the subject of serum samples are pretreatment step and said map constructing serum metabolomic analysis model when the pretreatment step, the same pattern preprocessing step.

[0034] 本发明依托"国家食管癌早诊早治示范基地(肥城市)"筛检平台,采集食管炎、不典型增生(又叫非典型增生、异型增生)、癌前病变及早期食管癌阶段的血清标本,所选血清标本高达640例,范围广,数量多,真实性更加可靠。 [0034] The present invention relies on "State of esophageal cancer early detection and treatment demonstration base (fat city)," screening platform, collecting esophagitis, atypical hyperplasia (also known as atypical hyperplasia, dysplasia), precancerous lesions and early esophageal cancer phase serum samples, serum samples were selected up to 640 patients a wide range, quantity, authenticity is more reliable. 通过UPLC-QT0F/MS和统计模式识别方法获得血清代谢物分析模型,该模型可以作为食管癌高发地区人群食管癌早期筛检的模型, 达到对食管癌的早期筛查的目的。 Serum metabolite analysis model obtained by UPLC-QT0F / MS methods and statistical pattern recognition, the model can be used as areas of high population of esophageal cancer of esophageal cancer model early screening, early screening for the purpose of esophageal cancer.

[0035] 本发明血清代谢组学分析模型和分析血清代谢组学的方法是基于食管癌早期或者癌变前的血清样本得到的,相比于基于医院的食管癌中晚期患者的血清样本得到的模型,本发明血清代谢组学情况与要筛查的高危人群的血清代谢组学情况匹配度更高,更适合食管癌的早期筛查。 [0035] The model and method for analysis of serum Serum metabolomics Metabolomics present invention is based on early esophageal cancer or precancerous serum samples obtained, as compared to the model based on serum samples of esophageal cancer patients with advanced hospital obtained , where higher learning match serum metabolome serum metabolome of the present invention to learn where to be at high risk screening, early screening is more suitable for esophageal cancer. 并且通过对建模方法的优化,本发明模型灵敏度高,特异性好,能很好的分辨健康人群和高危患病人群,非常适合临床应用。 By modeling and optimization methods, high sensitivity model of the invention, specificity, can distinguish between good and healthy people at high risk patient population, very suitable for clinical application.

[0036] 本发明首次将血清代谢组学分析技术用于食管癌早期筛查中,通过本发明可以对食管癌高发区的全人群进行初步筛查,快速、便捷的筛选出食管癌高发人群,准确度高,缩小了食管癌筛查的范围。 [0036] The present invention firstly Sera metabolomic analysis techniques for early diagnosis of esophageal cancer, the initial screening may be the whole population of the present invention, high incidence of esophageal, fast, easy screening high risk of esophageal cancer, high accuracy, reduced the scope of esophageal cancer screening. 本发明将食管癌筛查方法由传统的直接胃镜下碘染色指示性活检筛查方法变为先经本发明分析血清代谢组学的方法筛查,筛查结果为阳性的个体再行胃镜下碘染色指示性活检技术进行筛查,分析血清代谢组学时仅需采集血清,无创、花费低,有效提高了食管癌高发区全人群筛查的效率,大大降低了筛查成本,有效避免了部分人群有创胃镜造成的痛苦,具有重要的经济和社会效益,便于推广应用。 The screening method of the present invention changed from esophageal iodine staining indicated the traditional method of biopsy screening gastroscopy direct analysis method of the present invention over prior serum metabolomics screening, individual positive screening results again iodo gastroscopy indicative staining biopsy technique for screening, analysis of serum collected serum metabolomics hours only, non-invasive, low-cost, improve the efficiency of the high incidence of esophageal screening the whole population, significantly reducing screening costs, avoid the part of the population there is pain caused by invasive endoscopy, has important economic and social benefits, ease of application. 此外,本发明方法的提出还有利于简便的发现食管癌疑似病患,有利于癌症的早发现、早治疗,具有很高的科研和医学价值。 In addition, the proposed method of the present invention also facilitates easy discovery suspected of esophageal cancer patients, help cancer early detection, early treatment with high scientific and medical value.

附图说明 BRIEF DESCRIPTION

[0037]图1为血清代谢组学检测的质量控制图,横轴为保留时间,纵轴为代谢物在QC样本中的RSD%值。 [0037] FIG. 1 is a quality control graphics serum metabolites detected, the horizontal axis represents retention time and the ordinate is the metabolite RSD% of the value QC sample.

[0038]图2为代谢轮廓预分析的PCA得分图,其中NEG为阴性,表示健康血清样本,P0S为阳性,表示患病血清样本,QC表示质量控制样品。 [0038] FIG. 2 is a PCA score plot metabolic profiling pre-analysis, in which NEG negative, serum samples indicate health, P0S is positive for the prevalence of serum samples, QC represents the quality control samples.

[0039] 图3为PLS-DA三维得分图,建模的R2X=0.231, R2Y=0.749, Q2cum=0.638,其中Screening NEG为筛查阴性,表示健康血清样本,Screening P0S为筛查阳性,表示患病血清样本。 [0039] FIG. 3 is a three-dimensional score map PLS-DA, modeled R2X = 0.231, R2Y = 0.749, Q2cum = 0.638, which is a negative screening Screening NEG, serum samples indicates health, Screening P0S is screened positive for the patient disease serum samples.

[0040] 图4为基于随机置换方法的PLS-DA建模验证图。 [0040] FIG. 4 is a PLS-DA model based on a random permutation authentication method of FIG.

[0041]图5为用于食管癌早期筛查的PLS-DA模型的外部验证得分图,其中Screening NEG 为筛查阴性,表示健康血清样本,Screening POS为筛查阳性,表示患病血清样本, Screening NEG-test表示外部测试样本的筛查阴性,Screening POS-test表示外部测试样本的筛查阳性。 [0041] FIG. 5 is an external PLS-DA model for early diagnosis of esophageal cancer verification score map, which is a negative screening Screening NEG, serum samples indicates health, Screening POS is screened positive for the prevalence of serum samples, screening NEG-test represents the external negative screening test sample, screening POS-test screening represents a positive external test sample.

[0042] 图6为PLS-DA模型外部测试样本的R0C曲线。 [0042] FIG. 6 is a graph R0C external test sample PLS-DA model.

具体实施方式 Detailed ways

[0043] 下面,通过以下具体实施方式对本发明进行进一步的解释,并对本发明优点进行进一步的证明。 [0043] Next, a further explanation of the invention by the following detailed description, and advantages of the present invention will be further demonstrated.

[0044] 本发明血清代谢物分析模型的构建方法以及效果验证如下: [0044] The method of constructing metabolites and serum effects model analysis to verify the present invention are as follows:

[0045] 1、研究对象 [0045] 1, subjects

[0046] 本研究依托"国家食管癌早诊早治示范基地(山东省肥城市)"的食管癌筛查与随访社区人群队列,针对山东省肥城市40-69岁胃镜下碘染色指示性活检对象(作为金标准确认),采集初次发现(未经过治疗或未服用过药物)的碘染色阳性受检者(包括食管炎、轻度不典型增生、重度不典型增生、中度不典型增生、食管癌癌前病变、食管癌早期患者、原位癌患者)的血清样本作为患病样本;并随机抽取筛检中胃镜下碘染色阴性受试者即无上消化道病变的健康对象作为健康样本。 [0046] In this study, based on "national esophageal cancer early detection and treatment demonstration base (Shandong Province fat city)," the esophageal cancer screening and follow-up of the community cohort, iodine staining under the indicative fat city in Shandong Province, 40-69 years old endoscopic biopsy Object (confirmed as the gold standard), iodine staining found that the initial acquisition of the subject (therapeutic or drugs had not been administered) (including esophagitis, mild dysplasia, severe dysplasia, moderate dysplasia, esophageal precancerous lesions, the patient, the patient carcinoma in situ) serum samples as early esophageal cancer diseased samples; and random screening of iodine-negative subjects i.e. supreme gastrointestinal lesions of endoscopic healthy subject sample as a health .

[0047] 本研究共检测640人,其中碘染色阳性受检者(即患病样本)共453例,碘染色阴性受检者(即健康样本)共187例;年龄、性别在两组间差异没有统计学意义,具有可比性。 [0047] 640 people were detected in this study, where the subject iodine staining (i.e., diseased sample) were 453 cases, iodine-negative subject (i.e., a healthy sample) 187; age, gender differences between the two groups not statistically significant, comparable.

[0048] 2、LC_MS的血清代谢组学检测 [0048] 2, LC_MS detected serum metabolomics

[0049] 分别采集患者样本和健康样本的血清,作为患者血清样本和健康血清样本,所有采集的血清样本离心后放于-80°C冰箱内保存,使用超高效液相色谱-质谱联用仪①?^:-QT0F/MS 6550,Agilent)和Bravo自动标本预处理系统(Agilent,USA)进行代谢组学检测(分3个大批次检测,并做好质量控制),获得样本的包含色谱和质谱信息的原始代谢指纹图谱。 [0049] Serum samples were collected and healthy samples, a sample of serum and serum samples of healthy patients, all the serum samples collected by centrifugation -80 ° C put in the refrigerator, using ultra performance liquid chromatography - mass spectrometry ① ^: -? QT0F / MS 6550, Agilent) and Bravo automatic sample pretreatment system (Agilent, USA) metabolomics detector (3 large batches of detection points, and make quality control), chromatography, and obtaining a sample comprising original metabolic fingerprint mass spectrometry information. 具体操作如下: Specific operation is as follows:

[0050] 2.1仪器和设备 [0050] 2.1 Instrument and Equipment

[0051] 实验设备包括:UPLC-QT0F/MS 6550系统(Agilent, USA)、Bravo系统(Agilent, USA)、高速低温离心机、振动涡旋机、氮气干燥装置、4°C冷藏冰箱(海尔)、纯水仪(西门子)。 [0051] The test apparatus comprises: UPLC-QT0F / MS 6550 system (Agilent, USA), Bravo system (Agilent, USA), low-speed centrifuges, vibrating scroll machine, a nitrogen gas drying apparatus, 4 ° C refrigerator freezer (Haier) , water meter (Siemens).

[0052] 实验耗材包括:Waters ACQUITY UPLC® HSS T3 (particle size, 1.8 μπι; 100 mm (length) Χ2.1 mm)色谱柱、液氮、高纯氮;锥底进样瓶、2ml离心转子、2ml离心管(圆底)、移液器、1〇〇〇μ1枪头、200μ1枪头、记号笔、乳胶手套、口罩。 [0052] The laboratory supplies comprising: Waters ACQUITY UPLC® HSS T3 (particle size, 1.8 μπι; 100 mm (length) Χ2.1 mm) column, liquid nitrogen, high purity nitrogen; conical bottom vials, 2ml centrifuge rotor, 2ml centrifuge tube (round), pipette tip 1〇〇〇μ1, 200μ1 tips, marker, latex gloves, masks.

[0053] 实验试剂包括:甲醇(迪马,HPLC级纯)、乙腈(迪马,HPLC级纯)、甲酸(光复精密化学研究所,天津)、纯水(T0C〈10ppb)。 [0053] Reagents comprising: methanol (Dumas, HPLC pure grade), acetonitrile (Dumas, HPLC grade pure), formic acid (Precision Recovery Institute of Chemistry, Tianjin), water (T0C <10ppb).

[0054] 2.2血清样本预处理 [0054] 2.2 Sample pretreatment serum

[0055] 血清样本预处理前,制备60份质量控制样品(QC),将所有患者血清样本、健康血清样本和质量控制样品进行随机编号,以患者血清样本和健康血清样本作为分析样本,每隔10个分析样本加入一个质量控制样品。 [0055] Serum sample preparation, quality control samples prepared 60 parts (the QC), the serum samples, healthy patients serum samples and quality control samples were all random numbers to serum samples and serum samples from healthy patients as an analytical sample, every analysis of a sample was added 10 quality control samples. 质量控制样品是将同一患者血清样本和同一健康血清样本进行混合,并均匀地分成60份。 The quality control samples are the same serum samples and serum samples from the same patient health were mixed uniformly and divided into 60 parts. 患者血清样本、健康血清样本和质量控制样品均进行预处理,预处理包括以下4个步骤: Patients with serum samples, serum samples health and quality control samples were pretreated, pre-processing includes the following four steps:

[0056] (1)用移液器抽取50μ1分析样本或质量控制样品,置于Bravo自动标本处理系统(Agilent,USA)的96孔板上; [0056] (1) analyzing a sample by pipette or extraction 50μ1 quality control samples, placed on Bravo automatic sample processing system (Agilent, USA) in 96 well plates;

[0057] (2)加入150μ1甲醇提取,涡旋30s,并在_20°C下孵化以沉淀蛋白。 [0057] (2) the methanol extract was added 150μ1, vortexed 30s, and incubation at _20 ° C to precipitate the proteins.

[0058] (3)然后于高速离心机中在4°C下以4000转/分离心20min; [0058] (3) and in a high speed centrifuge at 4 ° C for 4000 revolutions / 20min isolated heart;

[0059] (4)将步骤(3)的上清液倒入LC-MS进样瓶中,保存在-80°C下以备LC-MS检测; The supernatant [0059] (4) The step (3) is poured into the LC-MS vials and stored at -80 ° C in preparation for LC-MS detection;

[0060] 2 · 3血清UPLC-QT0F/MS检测 [0060] 2.3 Serum UPLC-QT0F / MS detection

[0061] UPLC系统(1290 series, Agilent)将6yL等份预处理后的样品注入ACQUITY UPLC HSS T3 (particle size, 1.8 μπι; 100 mm (length) X 2.1 mm)色谱柱(Waters,Milford,USA)。 [0061] UPLC system (1290 series, Agilent) aliquot of the sample after the pretreatment 6yL injection ACQUITY UPLC HSS T3 (particle size, 1.8 μπι; 100 mm (length) X 2.1 mm) column (Waters, Milford, USA) . 进样顺序为完全随机化进样,以排除进样顺序带来的偏倚。 Injection fully randomized order of injection to eliminate bias caused by the injection sequence. 色谱流动相包含两种溶剂:A为0. lwt%甲酸(水稀释,正离子ESI+)或0.5mM氟化铵(水稀释,负离子ESI-),B为0. lwt%甲酸(乙腈稀释,正离子ESI+)或100%乙腈(负离子ESI-)。 Chromatography flow phase comprises two solvents: A is 0. lwt% formic acid (diluted with water, the positive ion ESI +) or 0.5mM ammonium fluoride (diluted with water, anion ESI -), B is 0. lwt% formic acid (diluted with acetonitrile, n ion ESI +) or 100% acetonitrile (negative ESI-). 色谱梯度为: 0-lmin 为l%B,l-8min 为1%B-100%B 逐渐递增,然后10-10.1min 为100%B 迅速减为1%B,然后1% B持续1.9min。 Chromatography gradient: 0-lmin of l% B, l-8min to 1% B-100% B gradually increasing, then 10-10.1min was quickly reduced to 100% B 1% B, then 1% B Length 1.9min. 流速为0.5 ml/min。 Flow rate of 0.5 ml / min. 整个样品检测过程维持在4°C。 The entire sample detection process is maintained at 4 ° C. 其中,A和B的百分含量指的是体积百分含量。 Wherein the percentages of A and B refer to the volume percentage.

[0062] 质谱检测使用Agilent四极杆时间飞行质谱仪Q-TOF (6550,Agilent),并采用电喷雾离子源的正离子模式(ESI+)和负离子模式(ESI-)。 [0062] MS detection using an Agilent quadrupole time of flight mass spectrometer Q-TOF (6550, Agilent), using electrospray ionization and positive ion mode (ESI +) and negative mode (ESI-). 离子源温度设定为400°C,而锥孔气流量为12L/min。 The ion source temperature was set at 400 ° C, and cone gas flow of 12L / min. 同时,脱溶剂气温设定为250°C,而脱溶剂气流量16L/min。 Meanwhile, the desolvation temperature was set to 250 ° C, and desolvation gas flow rate of 16L / min. 在正离子和负离子模式下毛细管电压分别为+3kV和-3kV,且锥孔电压均为0V。 In the positive and negative ion mode, the capillary voltage of + 3kV and were -3kV, and are cone voltage 0V. 锥孔压力为20psi (正离子)和40psi(负离子)。 Cone pressure of 20psi (positive) and 40 psi for (negative). 图谱数据采集的质荷比范围为50~1200 m/z,采集的扫描频率为0.25s。 Mass spectral data collected charge ratios of 50 ~ 1200 m / z, the scanning frequency is acquired 0.25s. [0063] 3、XCMS图谱预处理 [0063] 3, XCMS map pretreatment

[0064] UPLC-QT0F/MS血清正离子ESI+和负离子ESI-检测获得原始代谢指纹图谱数据通过Agi lent公司的Masshunt软件转化为Mzdata数据文件,然后使用R语言的XCMS软件包进行XCMS图谱预处理,预处理包括保留时间校正、峰识别、峰匹配、峰对齐、滤噪、重叠峰解析、阈值选择、标准化等。 [0064] UPLC-QT0F / MS positive serum and negative ion ESI + detection ESI- metabolic fingerprint to obtain the original data by Agi lent into software companies Masshunt Mzdata data file, then the package XCMS R XCMS language pattern is pretreated, pretreatment including a time correction, peak identification and peak matching, peak alignment, noise filtering, resolve overlapping peaks, the threshold select and standardization. XCMS预处理的相关参数为:峰半腰峰宽为10 (fwhm=10),保留时间窗设置为10 (bw=10),而其他参数为默认值。 XCMS pretreatment parameters is: halfway the peak band width of 10 (fwhm = 10), the retention time window is set to 10 (bw = 10), while the other default parameters. XCMS图谱预处理后得到可用于统计分析的二维矩阵,其中每行为样本(观测),每列为代谢物(变量),矩阵中值为相应的代谢物浓度。 XCMS spectrum obtained two-dimensional matrix can be pretreated for statistical analysis, the behavior of each sample (observed), each as metabolites (variable), the value of the corresponding matrix metabolite concentrations. 并且每个代谢物峰使用保留时间(retention time,RT)和质荷比(mass-to-charge ratio,ffi/z)定性。 And each metabolite peak using the retention time (retention time, RT) and mass to charge ratio (mass-to-charge ratio, ffi / z) qualitatively. 然后该二维矩阵使用R软件包进行代谢物峰标识(包括同位素峰、加合物和碎片离子)。 Then the two-dimensional matrix using the R software package for identification of metabolites peak (including isotope peaks, adducts and fragment ions). 统计分析前对样本进行标准化处理,待分析保留时间范围设定为0.5~10 min。 The samples were normalized prior to statistical analysis, the retention time range is set to 0.5 ~ 10 min to be analyzed. 经XCMS图谱预处理,在正离子检测模式的UPLC-QT0F/MS谱生成的数据矩阵中包含522个代谢物峰,负离子检测模式为212个代谢物峰。 Pretreated by XCMS pattern, comprising 522 metabolite peaks in positive ion detection mode UPLC-QT0F / MS spectrum data matrix generated, negative ion detection mode 212 metabolite peaks.

[0065] 4、LC_MS实验质量控制 [0065] 4, LC_MS quality control test

[0066] 在血清样品进行代谢组学检测时,将制备的QC样品按每10个分析样本安排1个QC 的顺序均匀地插入分析样本中,从而实时监测从样本前处理到样本检测过程中的质量控制情况。 [0066] When serum samples metabolomics Science detection, the QC sample was prepared for each of the 10 samples analyzed sequentially arranged a QC sample is uniformly inserted into the analysis, so that real-time monitoring process the sample from the sample prior to the detection process quality control of the situation. 所得原始代谢指纹图谱经XCMS图谱预处理后,计算每个代谢物在QC样本中的%RSD值(变异系数),并且以%RSD值为纵轴,以保留时间为横轴画图(见图1),图中的圆点代表代谢物。 The resulting raw metabolic fingerprint pattern by XCMS pretreated% RSD calculated value (coefficient of variation) of each metabolite in the QC sample and% RSD value at the vertical axis and the horizontal axis is retention time of the drawing (see FIG. 1 ), circles represent metabolites in FIG. 可以从图中看出绝大多数代谢物的%RSD值控制在30%以下,说明样本前处理到样本品检测过程中的质量控制情况良好,所获得的代谢组学数据真实可信。 As can be seen from the figure% RSD values ​​metabolites majority controlled at 30% or less, the sample processing to be described before a good quality control of the sample materials in the process of detecting, for metabolomic data obtained authentic.

[0067] 5、基于PCA的代谢轮廓预分析 [0067] 5, PCA-based metabolic profiling of pre-analysis

[0068] 将得到的二维矩阵数据随机分配成2/3作为训练样本training data (125 NEG: 303 POS),另外1/3作为外部测试样本test data(62NEG:151P0S)。 [0068] The two-dimensional matrix data obtained were randomly assigned to training samples 2/3 as training data (125 NEG: 303 POS), another third external test sample test data (62NEG: 151P0S). 对训练样本使用无监督分析方法即主成分分析(principal component analysis, PCA)来观察组间初步的分类趋势和离群点,见图2。 Unsupervised analysis using the method of training samples principal component analysis (principal component analysis, PCA) between the two groups to observe the initial classification trends and outliers, shown in Figure 2. 图中QC标本的重复性可表明LC-MS实验质量控制良好。 FIG QC samples LC-MS showed repeatability experiment good quality control. 从图中还可以看出,筛查阳性(即患病血清样本)和筛查阴性(即健康血清样本)间具有一定的分类趋势, 但仍有部分交叉,需要采用有监督学习方法实现进一步的分类。 Can also be seen from the figure, positive screening (ie, diseased serum samples) and negative screening (ie healthy serum samples) between a certain classification trend, but there are still some cross, we need a supervised learning method to achieve further classification.

[0069] 6、基于PLS-DA的代谢轮廓分析 [0069] 6, based on metabolic profile PLS-DA analysis

[0070] 为尽量消除组内差距引起的偏差,获得较为明显的分组趋势,进一步针对训练样本使用有监督分析方法即偏最小二乘判别分析(partial least squares-discriminant analysis,PLS-DA)显示碘染色阳性受检者和碘染色阴性受检者的代谢轮廓的差异和分类趋势。 [0070] In order to minimize the gap to eliminate bias caused by the group, group obtained obvious trend for further use of supervised training samples i.e., Partial Least Squares discriminant analysis method Analysis (partial least squares-discriminant analysis, PLS-DA) displays iodine differences in metabolic profile of subjects and iodine staining positive-negative subjects and classification of trends. 如图3所示,碘染色阳性组和阴性组间具有代谢模式差异和明显的组间分类趋势,其建模的R2X=0.231,R2Y=0.749,Q2cum=0.638。 3, between the positive and negative iodine staining with inter-group differences in metabolic pattern classification and obvious trend groups that modeled R2X = 0.231, R2Y = 0.749, Q2cum = 0.638. 从图3可以看出,相较于完全健康的碘染色阴性组,无论是食管炎、不典型增生还是更为严重的原位癌和早期食管癌(碘染色阳性组) 都出现了明显的代谢7、食管癌早期筛查的PLS-DA模型外部验证 As it can be seen from Figure 3, compared to the perfectly healthy iodine-negative group, whether it is esophagitis, dysplasia or carcinoma in situ more severe and early esophageal cancer (iodine staining group) has shown a significant metabolic 7, the external authentication early esophageal cancer screening PLS-DA model

[0071] 将外部测试样本二维矩阵数据(62NEG: 151P0S)代入上述建立的PLS-DA模型中,得到预测的因子1-3 (即t [1]、t [2]、t [3]值),将外部测试样本画入PLS得分图中,见图5。 [0071] The external test sample two-dimensional matrix data: PLS-DA model (62NEG 151P0S) built into the above to obtain the prediction factor 1-3 (i.e., t [1], t [2], t [3] value ), the external test sample drawn into the scoring FIG PLS, figure 5. 并根据PLS-DA模型中显示的外部测试样本的阴性和阳性,同实际分类标签(筛查阴性和阳性)做R0C曲线分析,见图6。 The positive and negative external test specimen and display PLS-DA model, with the actual classification label (positive and negative screening) do R0C curve analysis shown in Figure 6. 其中R0C曲线下面积AUC值为0.99 (95%CI: 0.978~1),灵敏度为95.4%,特异度为100%,该模型外部测试样本预测的争取率为94.8%。 Wherein AUC is the area under the curve R0C 0.99 (95% CI: 0.978 ~ 1), sensitivity of 95.4% and specificity of 100%, the model prediction for the external test sample was 94.8%. 这表明,按照本发明方法所建立的食管癌早期筛查的PLS-DA模型预测准确性高,具有不错的外推效果。 This indicates that high accuracy of the prediction model PLS-DA early esophageal cancer screening method according to the present invention established, extrapolation with good effect.

[0072] 本发明方法的食管癌早期筛查PLS-DA模型的最优预测界限值(cutoff)为0.50 (见图6),在实际应用中可使用该界限值作为判定筛查结果的标准,能够达到灵敏度和特异度的优化和权衡,而其他界限值均不是最优,会损失灵敏度或特异度。 [0072] The optimal prediction limit value PLS-DA model early screening method of the present invention, esophageal cancer (the cutoff) of 0.50 (see FIG. 6), may be used in practical applications the limit value as the determination result of the screening criteria, You can achieve the sensitivity and specificity of optimization and trade-offs, while the other limit values ​​are not optimal, lose sensitivity or specificity.

[0073] 8、对比实验 [0073] 8, Comparative Experiment

[0074] 在模型构建研究过程中,根据图谱预处理后的二维矩阵选择了10种差异最为显著的代谢物,并以每一种差异代谢物为判断标准,通过其含量差异来反应食管癌阳性情况。 [0074] In the research process model building, the two-dimensional matrix pattern of selected 10 kinds of pre-processing the most significant difference metabolites, and each of the differences in metabolite is a criterion to the reaction by the content difference esophageal positive situation. 结果显示,每一种单一代谢物的预测水平均不高,与实际情况的匹配度不足89%,不具有外推效果。 The results show that the level of each single prediction metabolites are not high, the actual degree of match is less than 89%, do not have the effect of extrapolation.

[0075] 9、结论 [0075] 9. Conclusion

[0076] 由以上验证可以看出,只有通过本发明方法构建的模型才能具有很好的预测效果。 [0076] As can be seen from the above verification, only by the process of the present invention is constructed in order to have a good predictive model results. 本发明所得PLS-DA模型无过拟合危险,且具有明显的组间分类趋势,通过血清代谢情况能够很好的将健康血清和疑似病变血清区分开来,灵敏度和特异度高,可以用于食管癌早期筛查。 The present invention is obtained PLS-DA model overfitting without danger, and has a significant inter-group classification tendency will be well separated by serum and serum metabolic health serum suspicious lesion areas, the high sensitivity and specificity, may be used esophageal cancer early screening.

[0077] 在采用本发明模型进行食管癌早期筛查应用时,步骤如下: [0077] When using the present model application in screening for early esophageal cancer, the following steps:

[0078] (1)采集待检血清,离心后采用上述2.2中的步骤(1)-⑷对血清进行预处理,以备进样检测; [0078] (1) collecting serum to be tested, after the centrifugation step above 2.2 using (1) -⑷ serum pretreatment, to prepare sample detection;

[0079] (2)将预处理后的待检血清样本按照上述2.3的步骤进行LC-MS检测,得原始代谢指纹图谱; [0079] (2) The serum samples to be tested after pretreatment according to the procedure described above is 2.3 LC-MS detection, metabolic fingerprint to obtain the original;

[0080] (3)将原始代谢指纹图谱按照上述步骤3的方法进行图谱预处理,得到该待检血清的代谢物信息; [0080] (3) The original spectra for metabolic fingerprint pretreatment method according to the above-described step 3, to give information of the metabolite to be tested serum;

[0081] (4)将该代谢物信息导入PLS-DA模型中,计算得到t[l]、t[2]、t[3]值,可以获得食管癌早期筛查风险的预测概率(大于50%即为阳性),从而通过人体代谢情况判定食管癌筛查风险。 [0081] (4) the information into a metabolite PLS-DA model, calculate t [l], t [2], t [3] value can be obtained early screening of esophageal cancer predicted probability of risk (greater than 50 % is positive), thereby determining the risk of esophageal cancer by screening for the human metabolism. 在实际应用中,如果待检血清样本的代谢物信息位于模型的患病血清样本组区域(即阳性区域,即预测概率大于50%),则表示该人具有食管癌的患病危险,需要进行进一步的内镜下指示性活检;如果待检血清样本的代谢物信息位于模型的健康血清样本组区域(即阴性区域,预测概率小于50%),则表示该人不具有食管癌的患病危险,不需要进行进一步的检查。 In practice, if the information to be metabolites in serum samples from the subject positioned diseased area of ​​the model group serum samples (i.e. positive areas, i.e., the predicted probability is greater than 50%), it indicates that the sick person having a risk of esophageal cancer, the need for further indicative endoscopic biopsy; if metabolite serum samples to be tested serum samples from healthy group information is located in areas of the model (i.e., a negative region, the predicted probability is less than 50%), it indicates that the person does not have the risk of esophageal cancer diseased , does not require further examination.

[0082] 除此之外,为了加快筛查效率,可以同时采集多人的血清样本,并进行编号,将多个样本一次性进行LC-MS检测、图谱预处理和数据导入。 [0082] In addition, in order to speed up the screening efficiency, serum samples collected at the same time many people, and are numbered, the plurality of samples one time for LC-MS detection, map preprocessing and data import.

[0083] 以上为对本发明专利的描述而非限定,基于本发明专利思想的其他实施方式,均在本发明保护范围之中。 [0083] The above is the description of the present invention without limiting the patent, the patent based on other embodiments of the inventive concept, are in the scope of the invention.

Claims (6)

1. 一种食管癌初步筛查用血清代谢组学分析模型的构建方法,其特征是:该分析模型的构建方法包括以下步骤: (1) 收集健康血清样本和患病血清样本,作为分析样本; (2) 将每个分析样本采用LC-MS血清代谢组学技术进行分析,得健康血清样本和患病血清样本的原始代谢指纹图谱; (3) 将健康血清样本和患病血清样本的原始代谢指纹图谱进行图谱预处理,得到每行为分析样本,每列为代谢物信息的二维矩阵,用于进一步的统计分析; (4) 将步骤(3)的二维矩阵依次进行主成分分析和偏最小二乘判别分析,得PLS-DA模型,对得到的PLS-DA模型进行验证,无过拟合危险,则所得PLS-DA模型即为食管癌初步筛查用血清代谢组学分析模型; 所述患病血清样本选自下列患者的血清:食管炎、食管癌癌前病变、食管癌早期和食管鳞状上皮原位癌患者的血清;所述健康血清样 An esophageal initial screening analysis model construction methods using serum metabolomics, characterized in that: the analysis model construction method comprising the steps of: (1) collecting serum samples from healthy and diseased serum samples, a sample for analysis ; (2) analysis of each serum sample using LC-MS metabonomics analysis, serum samples obtained health and diseased metabolic fingerprint original serum samples; (3) serum samples of healthy and diseased serum samples of the original metabolic fingerprint pattern for pretreatment, behavioral analysis for each sample to obtain, as a two dimensional matrix for each metabolite information for further statistical analysis; (4) the step (3) sequentially two-dimensional matrix and principal component analysis partial Least Squares discriminant analysis, PLS-DA model obtained, for PLS-DA model was subjected to verification overfitting without danger, the resulting model is the PLS-DA model esophageal initial screening with serum metabolomics; the serum sample is selected from the diseased patient serum following: esophagitis, esophageal precancerous lesion, early serum esophageal squamous cell carcinoma in situ and esophagus of a patient; a healthy serum sample 为没有患病血清所对应疾病或者类似疾病的人群的血清; 液相色谱所用色谱柱为Waters ACQUITY UPLC HSS T3色谱柱,规格为100 mmX 2.1 mm,1.8 μπι;进样量为6yL,进样温度为4°C,流速为0.5 ml/min;色谱流动相包含两种溶剂A 和B:正离子ESI+模式下的A为0. lwt%甲酸水溶液,负离子ESI-模型下的A为0.5mmol/L氟化铵水溶液,正离子ESI+模式下的B为O.lwt%甲酸的乙腈溶液,负离子ESI-模型下的B为纯乙腈;色谱梯度洗脱条件为:〇-lmin为1%B,l-8min为1%B-100%B逐渐递增,10-10 · lmin为100%B 迅速减为1%B,然后1%B持续1.9min; 质谱检测使用四极杆时间飞行质谱仪Q-T0F,并采用电喷雾离子源的正离子模式ESI + 和负离子模式ESI-,离子源温度为400°C,锥孔气流量为12L/min,脱溶剂气温为250°C,脱溶剂气流量为16L/min;在正离子和负离子模式下毛细管电压分别为+3kV和-3kV,锥孔电压均为0V;正离子模式下锥孔压力 Corresponding to no disease or illness serum Serum similar diseases population; HPLC column used was Waters ACQUITY UPLC HSS T3 columns, specification of 100 mmX 2.1 mm, 1.8 μπι; injection volume was 6YL, injection temperature to 4 ° C, flow rate of 0.5 ml / min; mobile phase chromatography comprising two solvents a and B: positive ion ESI + a in the mode 0. lwt% aqueous formic acid, a model under negative ESI- 0.5mmol / L aqueous ammonium fluoride solution, in the positive ion ESI + B mode O.lwt% formic acid in acetonitrile, under negative ESI- B model pure acetonitrile; gradient elution chromatographic conditions were: square-lmin to 1% B, l- 8min to 1% B-100% B incremental, 10-10 · lmin was quickly reduced to 100% B 1% B, then 1% B 1.9 min duration; mass spectrometry using quadrupole time of flight mass spectrometer Q-T0F, and using electrospray ion source in positive ion mode and negative mode ESI + ESI-, ion source temperature was 400 ° C, cone gas flow rate of 12L / min, the desolvation temperature of 250 ° C, desolvation gas flow rate of 16L / min; in positive and negative ion mode, the capillary voltage of + 3kV and were -3kV, are cone voltage 0V; cone pressure in positive ion mode 为20psi,负离子模式下锥孔压力为40psi ;图谱数据采集的质荷比范围为50~1200 m/z,采集的扫描频率为0.25s。 Is 20psi, the pressure cone is 40 psi for negative ion mode; mass spectrum data collected charge ratios of 50 ~ 1200 m / z, the scanning frequency is acquired 0.25s.
2. 根据权利要求1所述的构建方法,其特征是:所述食管癌癌前病变患者的血清包括食管鳞状上皮轻度不典型增生患者的血清、食管鳞状上皮重度不典型增生患者的血清和食管鳞状上皮中度不典型增生患者的血清。 2. The construction method according to claim 1, characterized in that: the serum of patients with esophageal precancerous lesions including serum esophageal squamous patients with mild dysplasia, severe esophageal squamous dysplasia patient sera sera of patients with dysplasia and esophageal squamous epithelium moderate.
3. 根据权利要求1所述的构建方法,其特征是:PLS-DA模型的R2X=0.231,R2Y=0.749, Q2cum=0.638〇 3. The construction method according to claim 1, characterized in that: R2X PLS-DA model = 0.231, R2Y = 0.749, Q2cum = 0.638〇
4. 根据权利要求1、2或3所述的构建方法,其特征是:所述健康血清样本和患病血清样本均来自4CK69岁人群。 4. Construction of the method according to claim 1, 2 or 3, characterized in that: the healthy and diseased serum samples are serum samples from 4CK69 years of age.
5. 根据权利要求1、2或3所述的构建方法,其特征是:所述患病血清样本453个,健康血清样本187个。 5. Construction method according to claim 2 or 3, characterized in that: said diseased serum samples 453, 187 healthy serum samples.
6. 根据权利要求1、2或3所述的构建方法,其特征是:对原始代谢指纹图谱进行图谱预处理是指:用Masshunter软件将获得的原始代谢指纹图谱转换为MZdata数据文件,然后将Mzdata数据文件使用XCMS软件包进行包括保留时间校正、峰识别、峰匹配和峰对齐的预处理操作,得到可用于统计分析的二维矩阵,矩阵中的每行为分析样本或质量控制样品,每列为代谢物信息。 The construction method of claim 1 or claim 3, characterized in that: the original map preprocessing fingerprints metabolic means: converting original Masshunter metabolic fingerprint obtained for MZdata software data file, and then Mzdata XCMS data files including a package for time correction, peak identification and peak matching alignment and peak preprocessing operations, a two-dimensional matrix can be used to give statistical analysis, the behavior of each matrix sample analysis or quality control samples, each column for the metabolite information.
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