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基于MB-WCX及MALDI-TOF/TOF MS技术的胃癌及结直肠癌血清肽组学初步研究

The Preliminary Study of Serum Peptidome of Gastric and Colorectal Carcinoma Based on MB-WCX and MALDI-TOF/TOF MS Technology

【作者】 赵莲

【导师】 沈守荣;

【作者基本信息】 中南大学 , 内科学, 2010, 博士

【摘要】 胃癌(Gastric Carcinoma, GC)与结直肠癌(Colorectal Carcinoma,CRC)是威胁人类健康的几大常见恶性肿瘤之一,在我国有着较高的发病率与死亡率。防治癌症措施中关键的一点在于防癌普查,以其尽早发现肿瘤,治疗癌症。但是目前临床缺乏效果明确的无创性检查手段,要确证肿瘤仍依赖内镜下病理活检。由于消化道肿瘤往往在癌症初期缺乏典型症状,上述侵入性检查难以作为常规筛查手段进行普及。因此,临床急需兼具灵敏度、特异性的非侵入性检查手段来弥补这一欠缺。血液来源广泛,获取容易,血液检查对于民众而言耐受度高,是最为理想的标本来源。血液肿瘤标志物的研究一直是肿瘤研究领域的热点。但经过数十年的研究,目前仍只有甲胎蛋白(alpha fetoprotein, AFP)、前列腺特异性抗原(prostate-specific antigen, PSA)等寥寥数种血清肿瘤标志物取得较为肯定的效果,而在消化道肿瘤方面,癌胚抗原(Carcinoembryonic antigen, CEA)、糖原19-9(carbohydrate antigen 19-9, CA19-9)等均缺乏足够的灵敏度和特异性。基于质谱技术的血清肽组学相关研究的发展为寻找新的消化道肿瘤血清标志物开辟了新的道路。1血清肽组学研究的方法学优化及偏倚研究血清肽组包含大量的生理与疾病相关的信息,吸引着研究人员从中寻找疾病相关多肽标记。高质量且表达稳定的血清多肽谱是血清肽组学研究的基础。血清成分却极其复杂,会对其质谱分析产生负面影响。因此选取合适的血清肽分离提纯方法很重要。此外,广泛的观点认为血清肽组的组成和含量会在体外发生改变,这种改变其与外部环境密切相关。这就涉及到与临床及分析化学、质谱仪,样本处理和质谱分析有关的偏差,例如:血液采集管,凝血时间和温度,冻融次数以及表面化学成分、质谱样本结晶以及激光强度都十分关键。此外,谱对齐被认为是信号处理中最大的挑战。如果恰当的对齐,则所产生的数据与那些基因表达分析所获得的数据就有了可比性,就可以运用现有的软件包进行分析。另外,我们想弄清楚,如性别、年龄等人口统计学参数差异到底对那些用我们的质谱平台绘制的血清多肽谱有些什么影响。在本研究中,我们比较分析了数种磁珠以及离心超滤管对血清肽分离提纯的效力,以及在血清采集、预处理、质谱处理和数据处理过程中的许多细节的影响,并对性别和年龄差异对血清肽组的影响加以分析,揭示了基于弱阳离子磁珠多肽固相分离技术(weak cation exchange magnetic beads, MB-WCX)和基质辅助激光解吸电离飞行时间质谱(Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry, MALDI-TOF MS)的血清肽组学研究中各种非疾病变量对研究结果的影响。获得了研究所需的最佳的变量设置,为血清肽组学研究提供依据。本研究结果证明血清肽组学研究的每一个步骤都需要进行严格规范。2胃癌及结直肠癌的特异性血清肽组表达及诊断模型建立近年来血清肽组学方面的研究表明肿瘤状态下异常细胞的生长、侵袭以及免疫系统的改变伴随着酶和蛋白水解过程的变化,可引起机体血清肽组特异性的表达变化。对乳腺癌、前列腺癌、甲状腺癌、口腔癌等肿瘤的前期研究显示,构建特异性血清肽组合诊断模型,可以获得良好的诊断效能。本研究利用前期建立的以MB-WCX和高通量的MALDI-TOF MS技术为基础的标准化血清肽组学研究平台,对40例GC患者,40例CRC患者和40例正常人血清进行血清肽组学分析,利用flexAnalysisTM,和ClinProtTM生物信息学软件对质谱数据进行采集,获得173个标准化的血清肽谱峰数据。利用Wilcoxon test比较CRC组与正常组数据,发现其中81个峰具有显著差异(p<0.00001),约占血清肽谱的46.82%;GC组与正常组数据比较,发现有79个峰具有显著差异(p<0.00001),约占血清肽谱的45.7%。通过一种新型的统计学方法CARS,我们优化筛选出10个血清肽峰,并通过偏最小二乘判别分析法(partial leastsquares discriminant analysis, PLS-DA)利用其中5个峰(X13217.07m/z,X23890.71 m/z,X33972.74 m/z,X44963.99m/z和X55864.13m/z)构建了CRC判别方程:Z=0.5733X1+0.4129X2+0.5388X3-0.4420X4-0.4899X5。此方程的判别能力评估显示其十折交叉验证准确度达95.1%,双盲法对test group进行判别的灵敏度达89.9%,特异度达98%。用同样的统计学方法,我们使用另外5个峰构建了GC判别方程:Z=0.4835Y1+0.5390Y2+0.5189Y3-0.4614Y4-0.4317Y5(其中Y12311.37m/z,Y24210.40 m/z,Y35539.74m/z,Y46005.97 m/z,Y56666.69m/z),用十折交叉检验评估GC血清肽判别方程预测能力,提示其准确性高达96.6%,特异度为95.9%,灵敏度为95.3%。上述研究结果表明,GC患者以及CRC患者的血清肽表达谱与正常人血清肽表达谱存在显著差异,其肿瘤特异性的血清肽表达模式具有潜在的消化道肿瘤血清标志物的意义。本研究在严格标准化及优化的血清肽组学实验平台的基础上,利用新型的统计学手段筛选出一个优化的变量子集,大大提高了模型的预测能力,所建立的判别方程能够较为准确地区分癌症患者血清与正常人血清,显著提高胃癌和结直肠癌的诊断效能,为寻找新的肿瘤特异性血清标志物和开发简便易行的非侵入性癌症检查方法提供了新思路。

【Abstract】 Gastric carcinoma (GC) and colorectal carcinoma (CRC) are two of the most commonly diagnosed and the leading cause of cancer death the world, as well as in China. The high incidence rates and mortality of both two cancers in China reflect the great risk to human healthy. The great majority of these cancers and deaths could be prevented by increasing the use of established screening tests. However, even more progress is possible by increasing access to and utilization of GC and CRC screening tests; currently, only half of people aged 50 or older, for whom screening is recommended, have received the recommended tests. Early colorectal cancer often has no symptoms, which is why screening is so important and also is why patients refuse the invasive examination, such as endoscope. Reasons cited by survey participants for not participating in gastroenterological cancer screening include lack of time, inconvenience, lack of interest, cost, fear of being diagnosed with cancer, embarrassment, and unpleasantness of the test.However, studies show that this method is the most sensitive for the detection of colorectal cancer or adenomatous polyps. Noninvasive examination with high sensitivity and specificity is required for gastroenterological cancer screening. Blood is the most ideal sample source as it can be collected easily with less reluctance. Detection of blood tumor biomarkers has been highlight for years. Although researchers have bent to these work, only few of tumor biomarkers used in clinic are of convinced efficiency, such as alpha fetoprotein(AFP) and prostate-specific antigen(PSA).Some biomarkers offer suggestion for gastroenterological carcinoma diagnosis is not powerful enough by themselves, such as carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9). Based on the mass technology advances in serum peptidome may indicate new direction of cancer biomarker detection.1 Methodology optimization and bias investigation of serum peptidome researchSerum peptidome contains a large number of physiologic and disease-related information and attracts researchers’eyeballs in finding disease-related polypeptide markers. Stable serum peptidome profiles with high quality are the cornerstone of serum peptidome research. However, the serum composition is extremely complex that can adversely affect its mass spectrometric profiling. Moreover, it has been widely believed that the composition and abundance of serum polypeptides would change ex vivo, which is closely related with the outside environment. It is related to biases of clinical and analytical chemistries, mass spectrometry, sample handling, and spectral analysis. For instance, blood collection tubes, clotting times and temperature, and the number of freeze-thaw cycles are all critically important as well as surface chemistries and MALDI sample crystallization and laser irradiation, which were all major sources of variation. In addition, spectral alignment appeared to be the most challenging in terms of signal processing. When aligned properly, however, the resulting datasets are comparable to those obtained by common gene expression analysis, enabling the use of existing software packages. Besides, we wanted to address whether parameters such as gender and age influence peptidome profiles as obtained using our mass spectrometry-based serum peptide profiling platform. In this paper, we studied comparatively in the numerous details of the process of the sampling and treatment of blood, the pretreatment of serum (magnetic beads and ultra filtrate centrifugal Filters), the mass spectrometry and the data handling, and analyzed the effectiveness of gender and age differences on the serum peptidome. Effectiveness of variables on serum peptidome research based on MB-WCX and MALDI-TOF mass spectrometry was unfolded. The optimal variables setting was obtained, which provide evidence for serum peptidome research. The results demonstrated that each step of the serum peptidome experiment should be standardized.2 Specific expression of serum peptidome and foundation of diagno -stic model on gastric cancer and colorectal cancerRecent years studies of serum peptidome show that the state of exception tumor cell growth, invasion, and the change of immune system along with the change of enzyme and protein hydrolysis process, can cause the body’s serum peptidome specific changes. The early studies of breast cancer, prostate cancer, thyroid cancer and oral cancer show that one can get good diagnosis efficiency by building model of combined specific serum peptides. In this study, we employed weak cation exchange magnetic beads (MB-WCX) to desalt samples and remove abundant proteins. Serum peptidomic profiles from 40 GC patients and 40 CRC patients without treatment and 40 healthy controls were obtained by using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. The serum peptidome research platform has been standardized and optimized in previous research. Comparing the CRC group and control group with Wilcoxon test, we discovered that 81 peaks were of significant differences (p<0.00001) between the two, about 46.82% of the total serum peptides; 79 peaks of marked difference were picked out by comparing GC group with control group (p<0.00001)。A novel strategy for selecting an optimal combination of key elements of multi-component spectral data, named competitive adaptive reweighted sampling (CARS), is adopted. Two optimal subsets of peaks were selects by using CARS method and pattern recognition equations were established through partial least squares-discriminant analysis (PLS-DA).One optimal subset of 5 peptide peaks (X1 3217.07m/z, X2 3890.71 m/z, X3 3972.74 m/z, X44963.99m/z和X5 5864.13m/z)selected by comparing CRC group and control group was used to set up a discriminant equation (Z=0.5733X1+0.4129X2+ 0.5388X3-0.4420X4-0.4899X5) to distinguish CRC from normal with a 10-fold cross validation accuracy of 95.1%,a sensitivity of 89.9% and specificity of 98% in double blind test on test group. Similarly, a GC discriminant equation was established to distinguish GC from normal: Z=0.4835Y1+0.5390Y2+0.5189Y3-0.4614Y4-0.4317Y5 (Y,2311.37m/z, Y24210.40 m/z, Y35539.74 m/z, Y46005.97 m/z, Y56666.69m/z) 10-fold cross validation shows the accuracy of this equation in GC diagnosis is 95.1%.Meanwhile, the equation was evaluated by double blind test on test group, a sensitivity of 89.9%and a specificity of 98% was acquired. The findings show that significant differences exist among serum peptide expression profiles of GC patients, CRC patients and normal controls.The tumor-specific expression patterns of serum peptide has the potential of gastrointestinal tumor markers. This study is based on strict standardized and optimized experimental platform, to take full advantage of new statistical means to filter out a subset variable. The discriminant equations can more accurately distinguish cancer patients with normal human; significantly improve the diagnostic efficiency of GC and CRC. This work provides researchers a new way to find novel tumor specific serum markers and to develop a simple but non-invasive cancers screening method.

  • 【网络出版投稿人】 中南大学
  • 【网络出版年期】2010年 11期
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