摘要
盆腔子宫内膜异位症(endometriosis, EM)是一种常见的妇女良性疾病,指异位子宫内膜累及盆腔腹膜及(或)盆腔内生殖器的病变,即子宫内膜腺体及间质细胞生长在子宫腔以外的部位,这种组织学上完全良性的内膜组织可像恶性肿瘤一样增生、浸润、扩散与转移,引起相应的临床症状。其常见的症状包括：痛经,性交痛,不孕,肠道或泌尿道症状(排便困难、腹泻、便秘、甚至周期性便血、尿频、血尿等)等,严重影响育龄期女性的生活质量和健康。子宫内膜异位症的发病机制至今仍不清楚,目前尚无有效的早期筛查和特异的诊断方法。如何提高子宫内膜异位症的诊断率尤其是早期诊断率已被公认为是改善其疗效和预后的关键。若能提高早期子宫内膜异位症的诊断率,即可明显提高子宫内膜异位症的总体治疗效果。因此,在无症状人群中用非侵入性手段筛检子宫内膜异位症,达到早发现、早诊断、早治疗,是子宫内膜异位症的重要防治策略之一。由于是蛋白质并不是核酸方为生命活动具体的执行者和体现者,因此,深入研究子宫内膜异位症的发病机制,寻找特异性、灵敏性均佳的生物标志物用于诊断,尤其是早期诊断,客观上要求在蛋白质组的水平上进行深入的探索。表面加强激光解吸电离-飞行时间质谱(surface-enhanced laser desorption/ ionization time-of-flight mass spectrometry, SELDI-TOF-MS)是近年来发展起来的一种全新的蛋白质组学的研究手段,该方法相对其他传统的蛋白质组学研究方法而言,具有能直接对临床的标本进行检测,实现了高通量的质谱技术应用于临床样本检测的优点。生命科学的快速发展使人们从基因组学、蛋白质组学等研究领域中获得了大量的数据,仅依靠传统的统计手段是无法处理这些数据的,生物信息学的发展更是为收集、存储以及分析这些数据,并且从中获取有用的生物学信息提供了重要的手段。课题旨在应用SELDI蛋白质指纹图谱和生物信息学技术从血清、在位子宫内膜、腹水中筛选子宫内膜异位症的生物标志物并分别构建子宫内膜异位症的血清、在位子宫内膜、腹腔液诊断模型,为探索子宫内膜异位症发病机制提供新思路。
第一部分子宫内膜异位症患者血清蛋白质指纹图谱模型的临床意义
用SELDI—TOF—MS技术和H4蛋白芯片检测36例子宫内膜异位症和30例正常女性的血清蛋白质指纹图谱,随机抽取其中2／3的血清标本(24例子宫内膜异位症和20例正常女性血清标本)作为训练组,并建立诊断模型。然后,将余下的1／3的血清标本(12例子宫内膜异位症患者样本和10名健康人血清标本)作为实验组,进行交叉验证该模型。筛选出5个有明显表达差异的蛋白,其质荷比(m／z)分别为8142、5640、5847、8940和3269。我们建立的诊断模型对子宫内膜异位症检测的灵敏度为91.7%(11／12),特异性为90.0%(9／10),总准确率为90.9%(20／22)。
第二部分子宫内膜异位症血清蛋白质质谱标准化分析平台的验证
本研究在第一部分的36例子宫内膜异位症患者血清标本中随机抽选16例作为研究对象,3个月后用H4蛋白质芯片对上述16例子宫内膜异位症样本和16例健康志愿者总共32份血清标本再次进行检测,本研究严格按照第一部分的血清蛋白质质谱标准化实验方法。将前后两次结果进行对比,分析,比较两次不同时间实验选择的作为诊断模型的蛋白质峰的值,结果发现统计差异显著的峰在两次不同时间检测中都仍然差异显著,能够重复出来,而且各个不同的峰在两次不同时间的检测中在子宫内膜异位症患者和健康人血清中表达高低也能够重复,验证了子宫内膜异位症血清诊断模型的有效性。
第三部分子宫内膜异位症患者在位子宫内膜指纹图谱模型的临床意义
用SELDI—TOF—MS技术和H4蛋白芯片检测13例子宫内膜异位症和13例良性妇科疾病并排除子宫内膜异位症的患者的在位子宫内膜组织蛋白质指纹图谱,我们优化选择了5个蛋白质荷比峰作子宫内膜异位症在位内膜的诊断模型：6898 m/z、5891 m/z、5385 m/z、6448 m/z和5425 m／z。其中6898m／z、5891m／z和6448 m／z的3个峰在子宫内膜异位症患者在位内膜中表达高于对照组在位内膜；而5385m/z和5425m/z的2个蛋白质峰在子宫内膜异位症患者在位内膜中表达则低于对照组在位内膜。
第四部分子宫内膜异位症患者腹水指纹图谱模型的临床意义用SELDI—TOF—MS技术和H4蛋白芯片检测14例子宫内膜异位症和16例对照组的腹水蛋白质指纹图谱,我们优化选择了4个蛋白质荷比峰作子宫内膜异位症腹水的诊断模型：4428m/z、6891m/z 13766m/z和6427m／z。其中4428m／z、6427m／z的2个峰在子宫内膜异位症患者腹水中高表达；13766m／z和6891m／z的2个蛋白质峰在子宫内膜异位症患者腹水中则低表达。
结论：
5个蛋白质峰8142m/z、5640m/z、5847m/z、8940m/z和3269m／z组合所构建的血清诊断模型鉴别子宫内膜异位症和健康志愿者的总准确率为90.9%(20／22)。其中5640m/z、5847m/z、和3269 m／z的3个峰在子宫内膜异位症患者血清中高表达；8142m/z和8940m/z的2个蛋白质峰在子宫内膜异位症患者血清中则低表达。
本研究建立的的标准方法建立的模型在样本的不同时间上有效性和重复性均得到了验证。
5个蛋白质峰6898 m/z、5891 m/z、5385 m/z、6448 m/z和5425 m／z组合构建了子宫内膜异位症的在位子宫内膜的诊断模型。其中6898m/z、5891m／z和6448 m／z在子宫内膜异位症中高表达,5385m／z和5425m／z在子宫内膜异位症中低表达。
4个蛋白质峰4428m/z、6891m/z 13766m/z和6427m／z组合构建了子宫内膜异位症的腹水的诊断模型。其中4428m/z、6891m/z在子宫内膜异位症腹水中高表达,13766m／z和6427m／z在子宫内膜异位症腹水中低表达。
Endometriosis is classically described as the presence of functioning endometrial tissue (glandular epithelium and stroma) outside the uterine cavity, more frequently in the ovaries, peritoneum and so on. Endometriosis is completely benign histologic endometrial tissue, but its behavior look like cancer such as:proliferation, invasion, proliferation and metastasis, causing the corresponding clinical symptoms. The common symptoms include:dysmenorrhea, painful intercourse, infertility, intestinal or urinary tract symptoms (defecation difficulties, diarrhea, constipation, and even periodic blood in the stool, frequent urination, hematuria, etc.). Endometriosis seriously affects the lives of many women of reproductive age.
The pathogenesis of endometriosis is still unclear, at present there is no effective early screening and specific diagnostic methods. How to improve the diagnosis of endometriosis especially early diagnosis is the key to improve its efficacy and prognosis. Thus, in asymptomatic population screening using non-invasive means of endometriosis to achieve early discovery, early diagnosis and early treatment is important endometriosis prevention and treatment strategies.
Protein but not nuclear acid is the material executant and embodiment of life. So, the studies on proteomics are preferred to approach to the pathogenesis of breast cancer and screen sensitive and specific biomarkers. The ProteinChip based on surface enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS) could bind the proteins in the samples unselectively. It combines ProteinChip array with time-of-flight mass spectrometry and offers the advantages of speed, simplicity, sensitivity and suitability for a comparative study. It can directly obtain high-throughput protein profilings from clinical samples with high sensitivity and this is the main advantage of this technology.
To look for such "fingerprints" of protein, it will require not only high-throughput genomic or proteomic profiling, but also sophisticated bioinformatics tools for complex data analysis and pattern recognition. In proteomics, the technology of bioinformatics carved out a new way to effectively seek biologic markers.
Our study project aimed at finding potential biomarkers in the serum, eutopic endometrium and ascites of endometriosis and establishing the different patterns for diagnosis of endometriosis respectively.
Part 1:The Application of Serum Protein Fingerprints in the endometriosis.
SELDI—TOF—MS protein chip was used to detect the serum proteomic patterns of 36 patients with endometriosis and 30 normal women, Two thirds of the total samples of every compared pair as training set were used to set up discriminating patterns, and one third of total samples of every compared pair as test set were used to cross-validate. Five potential biomarkers were found(8142、5640、5847、8940和3269m /z), and the diagnostic system separated the endometriosis from the healthy samples with a sensitivity of 91.7%,a specificity of 90.0% and a positive predictive value of 90.9%.
Part 2:Confirm the reproducibility of the protein Mass spectrometry high-throughput analysis platforms utilizing the serum samples of endometriosis.
In this study,16 cases of the serum samples from the endometriosis patients in the first part were selected randomly. Three months later, the 16 cases of endometrial samples and 16 cases of health volunteers samples were tested again using the H4 protein chip in strict accordance with the first part of this study. The results at different times were compared and the value of the protein peaks can be repeated three months later. And the expression of the level of serum can also be repeated to verify the diagnosis model of endometriosis serum.
Part 3:Identification biomarkers of eutopic endometrium in endometriosis using artificial neural networks and protein fingerprinting.
SELDI-TOF-MS protein chip array technology was used to detect biomarkers of eutopic endometrium in 13 endometriosis patients and 13 controls(patients with benign gynecological disease excluding endometriosis). Five potential biomarkers (6898 m/z、5891 m/z、5385 m/z、6448 m/z and 5425 m/ z) were found. Peaks of 6898m/z,5891m/z and 6448 m/z in endometriosis patients expressed higher in eutopic eutopic endometrium; peaks of 5385m/z and 5425m/z in endometriosis patients expressed lower in eutopic endometrium than the control group.
Part 4:Identification biomarkers of ascites in endometriosis using artificial neural networks and protein fingerprinting.
SELDI-TOF-MS protein chip array technology was used to detect biomarkers of ascites in 14 endometriosis patients and 16 controls(patients with benign gynecological disease excluding endometriosis). Four potential biomarkers (4428m/z、6891m/z 13766m/z and 6427m/z) were found. Peaks of 4428m/z and 6427m/ z in endometriosis patients expressed higher in ascites; peaks of 6891m/z and 13766m /z in endometriosis patients expressed lower in ascites than the control group.
Conclusion
1. The combination of 5 protein peaks 8142m/z,5640m/z,5847m/z,8940m/z and 3269m/z built the serum diagnostic model of endometriosis with the accuracy rate of 90.9% (20/22).5640m/z,5847m/z, and 3269 m/z of the three peaks in the serum of patients with endometriosis were highly expressed; 8142m/z and 8940m/ z of the two protein peaks in patients with endometriosis serum were low expression.
2. The endometriosis detect serum pattern established by this platform have a good reproducibility in different period.
3. The combination of 5 protein peaks 6898 m/z、5891 m/z、5385 m/z、6448 m /z and 5425 m/z built the diagnostic model of eutopic endometrium in endometriosis.6898m/z,5891m/z and 6448 m/z of the three peaks in the eutopic endometrium of patients with endometriosis were highly expressed; 5385m/ z and 5425m/z of the two protein peaks in patients with endometriosis were low expression.
4. The combination of 4 protein peaks 4428m/z、6891m/z 13766m/z and 6427m /z built the diagnostic model of ascites in endometriosis.4428m/z and 6427m/ z of the three peaks in the ascites of patients with endometriosis were highly expressed; 6891m/z and 13766m/z of the two protein peaks in the ascites of patients with endometriosis were low expression. The method showed great potential for the detection and screening better biomarkers for endometriosis.
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