The Protein Mass Spectrometry High-throughput Analysis Platforms Established And Applied In Endometriosis

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.Conclusion1. 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.