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BACKGROUND:The correlation between blood stasis syndrome and non-blood stasis syndrome of lumbar intervertebral disc protrusion remains unclear. OBJECTIVE:To construct serum protein pattern model for diagnosing blood stasis syndrome of lumbar intervertebral disc protrusion. METHODS:A total of 180 cases were included in this study and divided into treatment group (120 patients with lumbar intervertebral disc protrusion) and control group (60 healthy cases from physical examination). Furthermore treatment group was equal y assigned into blood stasis syndrome subgroup and non-blood stasis syndrome subgroup, with 60 cases in each subgroup. The involved cases were wel matched in nations, genders and ages. Serum samples of peripheral blood from the 180 cases were col ected. Surface-enhanced laser desorption/inionation time of flight mass spectrometry and ProteinChip technology were employed to detect and plot protein mass spectrum. The protein peak values were identified using Biomarker Wizard software. Then serum diagnosis model of blood stasis syndrome of lumbar intervertebral disc protrusion was established. The obtained models were verified through double blind method. The differential proteins were searched by ExPASy data. RESULTS AND CONCLUSION:We detected that peak values of eleven proteins had statistical significance (P<0.05) from the involved 180 cases. Among them, two proteins were highly expressed while the other nine proteins were lowly expressed. Serum protein pattern model for diagnosing blood stasis syndrome of lumbar intervertebral disc protrusion was established through Biomarker Patterns software, and the sensibility was 86.667%, the specificity was 94.167%, the positive predictive value was 88.136%. There are a variety of abnormal y expressed proteins in the serum of the patients with blood stasis syndrome of lumbar intervertebral disc protrusion. The serum protein pattern model involved eleven different proteins can be used to diagnose blood stasis syndrome of lumbar intervertebral disc protrusion.
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Objective To establish protein fingerprinting identification model of Pseudomonas aeruginosa (P. aeruginosa) and to lay a foundation for rapid identification of P. aeruginosa by proteinchip golden array. Methods Sixty-four P. aeruginosa and one hundred and ninety-nine control bacteria identified in our laboratory were collected and divided into training and testing group. Surface enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) and proteinchip golden array were used to detect the protein profiling of the bacteria. Data were automatically collected by Ciphergen Proteinchip Software and protein markers of P. aeruginosa were screened by BioMarker Wizard Software. Classification tree model was developed and validated by BioMarker Patterns Software. The model was blindly tested with twenty-nine P. aeruginosa and sixty-four control bacteria. Results Eighty protein peaks were detected between 3000 and 20 000, among which fifty-eight ones showed significantly difference between P. aeruginosa and the control bacteria (P＜0.01). By BioMarker Patterns Software, one protein peak ( M/Z at 14 045.2) was chosen to develop a classification tree model. The results exhibited with sensitivity of 96. 55% and specificity of 100%. Conclusion Proteinchip golden array has the potential for rapid identification of P. aeruginosa.
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Objective:To screen the tumor markers of laryngeal carcinoma and to investigate their expression in preoperative and postoperative serum.Method:The distinct protein in serum was detected in 32 cases of laryngeal carcinoma and 38 healthy people by IMAC-Cu proteinchip array and surface-enhanced laser desorption/ionization time-of-flight mass spectrometry(SELDI-TOF-MS).The distinct proteins in serum were detected in 32 cases of laryngeal carcinoma preoperation and within 10 days 15 cases of laryngeal carcinoma postoperation with the same methods.The discriminatory profiling between preoperative and postoperative patients was analyzed by Biomarker Wizard software and Biomarker Pattern software.Result:The results showed that fifteen differentially expressed proteins in serum were screened by analysis of protemic spectra of preoprative patients and normal subjects.Seventeen kinds of protein differentially expressed in serum were screened by analysis of protemic spectra of preoperative and postoperative patients.Six kinds of protein(2 958.52,3 796.89,5 148.86,6 115.57, 052.18,and7 770.76)were obtained for making up patterns that was able to class the preoperative-team and postoperativeteam.Corresponding correct ratio were 84.38%(27/32)and 73.33%(11/15).Conclusion:The preliminary results suggest that classification system will provide a highly accurate and innovative approach for the arly dioagnosis of laryngeal carcinoma and judgement of prognosis.SELDI-TOF-MS technology is a useful tool for a high throughput screening of large-sized serum samples tO discover potential biomarkers for laryngeal carcinoma.
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Objective To analyze the association between C12 tumor markers and colorectal cancer,in order to screen for colorectal cancer related tumor markers so as to provide theoretical base for the establishment of colorectal cancer diagnostic biochips. Methods The sera of 173 colorectal cancer patients were detected for 12 common tumor markers including carcinoembryonic antigen (CEA), alpha-fetoprotein (AFP), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 242 (CA242), cancer antigen 15-3 (CA15-3), cancer antigen 125 (CA125), prostate specific antigen (PSA), free-PSA, neuron-specific enolase (NSE),human chorionic gonagotropin-beta (β-HCG), human growth hormone (HGH), and ferritin using the C12tumor markers proteinchip, and colorectal cancer related parameters were analyzed by Kappa test and cost-effectiveness analysis to find the most optimal tumor marker program. Results CEA (36.4 %), CA242(19.7 %), CA19-9 (18.5 %), CA125(9.8 %) were major tumor markers increased among the 173 colorectal cancer patients. Kappa test revealed 7 tumor marker programs having strong consistency with the detection results of C12 tumor markers proteinchip, and CEA singly detected was proved to be the best program by cost-effectiveness analysis. Conclusion C12 tumor markers proteinchip system have limited value in the diagnosis of colorectal cancer, but the design of chip is too complicated and costly for widespread screening among the high risk populations. Searching for new colorectal cancer biomarkers and designing small diagnostic chip could significantly enhance the clinical value of tumor markers in terms of diagnostic rate and practical utility.
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Background and purpose:Surface enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) is useful in helping to identify the molecular changes closely related to renal cell carcinoma. We explored the different expression of sera protein between human renal cell carcinoma patients and normal to screen renal cancer-specific biomarkers. Methods:The protein mass spectrometry of 28 cases with renal cell carcinoma and 28 normal persons were detected by WCX2 protein chip combining with SELDI-TOF-MS technique for screening the different proteins. Serum samples from 28 patients with clear renal cell carcinoma and 28 normal persons were used to detect biomarkers for clear renal cell carcinoma by SELDI-TOF-MS technique with WCX2 Proteinchip. Results:170 effective protein wave crests between 1.5?103-30?103(1.5-30 kD) were detected. Seven proteins were specifically detected in sera of patients with clear renal cell carcinoma, but not in normal donor. The proteins with MW 4.098,5.917,6.643 ?103 were down-regulated ,and four proteins with MW 5.572,6.344,6.529,8.518 ?103 were up-regulated. Conclusion:Detection of specific protein in human renal cell carcinoma sera is significant both for determination of clinical specific biomarkers and study of cancer development mechanism.
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Protein separation method is the core factor of the proteomics strategy. There are three methods for the protein separation, include two dimensional gel electrophoresis, liquid-phase electrophoresis and Mass Spectrometry, and protein-chip. In this article, the principles, processos, and development on the three separation protein methods.were reviewed.
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Objective To search for new tumor markers from urine of bladder transitional cell carcinomas. Methods Urine samples from 61 bladder cancer patients who were histologically diagnosed and 53 healthy volunteers and 42 cases with other urogenital diseases were analyzed using surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS) IMAC-Cu-3 ProteinChip technology,which can specifically bind the metal-combining-proteins.Proteomic spectra were generated by mass spectrometry.A blinded test set was used to determine the sensitivity and specificity of the differentially expressed markers. Results Four differentialy expressed potential markers were identified.Their corresponding molecular weights were 3445,3703,3896 and 5932, respectively.The 3445 protein was identified as ?-defensin,with its sensitivity for diagnosing bladder cancer being 80% and specificity being 75%.The sensitivity of 3703 protein was 32%,while its specificity was 94%.97% of the patients who were positive for 3703 protein were with high grade and invasive bladder cancer.The sensitivity for 3896 and 5932 proteins were 78% and 55%;the specificity for them were 40% and 35%,respectively. Conclusions SELDI-TOF-MS ProteinChip technology is a quick,easy and practical,high throughput analytic method.It can screen out several relatively specific,potential markers from urine of bladder cancer patients,so it has better clinical feasibility.