Gene expression profile changes in brain regions following traumatic brain injury at the gene level cannot sufficiently elucidate gene expression time, expression amount, protein post-translational processing or modif...Gene expression profile changes in brain regions following traumatic brain injury at the gene level cannot sufficiently elucidate gene expression time, expression amount, protein post-translational processing or modification. Therefore, it is necessary to quantitatively analyze the gene expression profile using proteomic techniques. In the present study, we established a rat model of closed brain injury using Marmarou＇s weight-drop device, and investigated hippocampal differential protein expression using two-dimensional gel electrophoresis and surface-enhanced laser desorption ionization-time of flight-mass spectrometry. A total of 364 protein peaks were detected on weak cation exchange-2 protein chips, including 37 differential protein peaks. 345 protein peaks were detected on immobilized metal affinity capture arrays-Cu, including 12 differential protein peaks Further examination of these differential proteins revealed that glucose-regulated protein and proteasome subunit alpha type 3 expression were significantly upregulated post-injury. These results indicate that brain injury can alter protein expression in the hippocampus, and that glucose-regulated protein and proteasome subunit alpha type 3 are closely associated with the occurrence and development of traumatic brain injury.展开更多
Background and Objective: Early diagnosis of nasopharyngeal carcinoma (NPC) is difficult due to the insufficient specificity of the conventional examination method. This study was to investigate potential and consiste...Background and Objective: Early diagnosis of nasopharyngeal carcinoma (NPC) is difficult due to the insufficient specificity of the conventional examination method. This study was to investigate potential and consistent biomarkers for NPC, particularly for early detection of NPC. Methods: A proteomic pattern was identified in a training set (134 NPC patients and 73 control individuals) using the surface-enhanced laser desorption and ionization-mass spectrometry (SELDI-MS), and used to screen the test set (44 NPC patients and 25 control individuals) to determine the screening accuracy. To confirm the accuracy, it was used to test another group of 52 NPC patients and 32 healthy individuals at 6 months later. Results: Eight proteomic biomarkers with top-scored peak mass/charge ratios (m/z) of 8605 Da, 5320 Da, 5355 Da, 5380 Da, 5336 Da, 2791 Da, 7154 Da, and 9366 Da were selected as the potential biomarkers of NPC with a sensitivity of 90.9% (40/44) and a specificity of 92.0% (23/25). The performance was better than the current diagnostic method by using the Epstein-Barr virus (EBV) capsid antigen IgA antibodies (VCA/IgA). Similar sensitivity (88.5%) and specificity (90.6%) were achieved in another group of 84 samples. Conclusion: SELDI-MS profiling might be a potential tool to identify patients with NPC, particularly at early clinical stages.展开更多
Androgens play a central role in prostate cancer pathogenesis, and hence most of the patients respond to androgen deprivation therapies. However, patients tend to relapse with aggressive prostate cancer, which has bee...Androgens play a central role in prostate cancer pathogenesis, and hence most of the patients respond to androgen deprivation therapies. However, patients tend to relapse with aggressive prostate cancer, which has been termed as hormone refractory. To identify the proteins that mediate progression to the hormone-refractory state, we used protein-chip technology for mass profiling of patients＇ sera. This study included 16 patients with metastatic hormone-refractory prostate cancer who were initially treated with androgen deprivation therapy. Serum samples were collected from each patient at five time points： point A, pre-treatment; point B, at the nadir of the prostate- specific antigen （PSA） level; point C, PSA failure; point D, the early hormone-refractory phase; and point E, the late hormone-refractory phase. Using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry, we performed protein mass profiling of the patients＇ sera and identified a 6 640-Da peak that increased with disease progression. Target proteins were partially purified, and by amino acid sequencing the peak was identified as a fragment of apolipoprotein C-I （ApoC-I）. Serum ApoC-I protein levels increased with disease progression. On immunohistochemical analysis, the ApoC-i protein was found localized to the cytoplasm of the hormone-refractory cancer cells. In this study, we showed an increase in serum ApoC-I protein levels in prostate cancer patients during their progression to the hormone-refractory state, which suggests that ApoC-I protein is related to progression of prostate cancer. However, as the exact role of ApoC-I in prostate cancer pathogenesis is unclear, further research is required.展开更多
Background Endometriosis is a common gynecological disease. This study aimed to screen proteins that were expressed differently in patients with endometriosis versus normal controls using proteomic techniques, surface...Background Endometriosis is a common gynecological disease. This study aimed to screen proteins that were expressed differently in patients with endometriosis versus normal controls using proteomic techniques, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry （SELDI-TOF-MS）.Methods Protein chip SELDI-TOF-MS combines the advantages of microarray and mass spectrometry, and can screen latent markers in sera of patients with endometriosis. Serum samples from patients and normal volunteers were analyzed by SELDI-TOF-MS. Results After comparing the serum protein spectra of 36 patients with 24 normal controls, 24 differently expressed potential biomarkers （P 〈0.01） were identified. Using Biomarker Pattern software, we established a tree model of the 60 serum protein spectra. When using the three bJomarkers to classify the samples, the sensitivity for diagnosing endometriosis was 91.7%, specificity was 95.8%, and coincidence rate was 93.3%. Then we used serum samples from 12 patients and 8 normal controls to validate the tree model and report the sensitivity for diagnosing endometriosis was 91.7%, specificity was 75%, and coincidence rate was 85%. Conclusions SELDI-TOF-MS may be a useful tool in high-risk population screening for endometriosis. The identification and application of the biomarkers need to further study.展开更多
Objectives： To detect the serum proteomic patterns by using SELDI-TOF-MS （surface enhanced laser desorption/ ionization-time of flight-mass spectrometry） technology and CM10 ProteinChip in colorectal cancer （CRC）...Objectives： To detect the serum proteomic patterns by using SELDI-TOF-MS （surface enhanced laser desorption/ ionization-time of flight-mass spectrometry） technology and CM10 ProteinChip in colorectal cancer （CRC） patients, and to evaluate the significance of the proteomic patterns in the tumour staging of colorectal cancer. Methods： SELDI-TOF-MS and CM10 ProteinChip were used to detect the serum proteomic patterns of 76 patients with colorectal cancer, among them, 10 Stage Ⅰ, 19 Stage Ⅱ, 16 Stage Ⅲ and 31 Stage Ⅳ samples. Different stage models were developed and validated by support vector machines, disctiminant analysis and time-sequence analysis. Results： The Model Ⅰ formed by 6 protein peaks （m/z： 2759.58, 2964.66, 2048.01, 4795.90, 4139.77 and 37761.60） could be used to distinguish local CRC patients （Stage Ⅰ and Stage Ⅱ） from regional CRC patients （Stage Ⅲ） with an accuracy of 86.67% （39/45）. The Model Ⅱ formed by 3 protein peaks （m/z： 6885.30, 2058.32 and 8567,75） could be used to distinguish locoregional CRC patients （Stage Ⅰ, Stage Ⅱ and Stage Ⅲ） from systematic CRC patients （Stage IV） With an accuracy of 75.00% （57/76）. The Model Ⅲ could distinguish Stage Ⅰ from Stage Ⅱ with an accuracy of 86.21% （25/29）. The Model Ⅳ could distinguish Stage Ⅰ from Stage Ⅲ with accuracy of 84.62% （22/26）. The Model Ⅴ could distinguish Stage Ⅱ from Stage Ⅲ with accuracy of 85.71% （30/35）. The Model Ⅵ could distinguish Stage Ⅱ from Stage Ⅳ with accuracy of 80.00% （40/50）. The Model Ⅶ could distinguish Stage Ⅲ from Stage Ⅳ with accuracy of 78.72% （37/47）. Different stage groups could be distinguished by the two-dimensional scattered spots figure obviously. Conclusion： This method showed great success in preoperatively determining the colorectal cancer stage of patients.展开更多
背景与目的肺癌是当今世界上最常见的恶性肿瘤之一,迄今缺乏临床诊断可用的分子标志物。本实验应用SELDI技术寻找肺癌新的血清标志物。方法对227例血清样品(包括146例肺癌、13例肺炎、28例结核性胸膜炎和40例正常人血清样品)进行蛋白质...背景与目的肺癌是当今世界上最常见的恶性肿瘤之一,迄今缺乏临床诊断可用的分子标志物。本实验应用SELDI技术寻找肺癌新的血清标志物。方法对227例血清样品(包括146例肺癌、13例肺炎、28例结核性胸膜炎和40例正常人血清样品)进行蛋白质谱检测。对候选蛋白进行质谱鉴定,并结合免疫共沉淀和ELISA技术筛选出肺癌新的候选标志物。结果通过Biomarker WizardTM软件分析显示13.78kDa、13.90kDa和14.07kDa的蛋白峰在肺癌病人血清样品中明显低于对照组。通过1-D胶分离,质谱鉴定和免疫沉淀分析显示这3个差异蛋白峰为野生型甲状腺运载蛋白(nativeTTR)和它的两个变体(cysTTR and glutTTR)。ELISA和SELDI技术分析上述血清样品均发现TTRs在肺癌血清中的表达下调。结论采用SELDI技术首次筛选并鉴定出TTRs,表明其可能作为肺癌诊断的候选血清标志物。展开更多
目的采用表面增强激光解析离子化飞行时间质谱(surface-enhanced laser desorption/ionization time of flight mass spectrometry,SELDI-TOF-MS)技术研究慢性肾衰竭(chronic renal failure,CRF)中医湿证患者的尿液蛋白标志物。方法采集...目的采用表面增强激光解析离子化飞行时间质谱(surface-enhanced laser desorption/ionization time of flight mass spectrometry,SELDI-TOF-MS)技术研究慢性肾衰竭(chronic renal failure,CRF)中医湿证患者的尿液蛋白标志物。方法采集CRF湿证患者90例和非湿证患者60例的尿液,采用H4蛋白芯片技术进行尿液蛋白质组学研究,用蛋白芯片阅读器PBSⅡ对芯片进行扫描、分析。结果 (1)湿证组与非湿证组尿液样本的蛋白质图谱在质荷比1000-20000范围内检测到25个差异蛋白峰(P<0.01)。(2)经生物信息学分析建立CRF中医湿证尿液蛋白预测模型,得到M/Z8654.96、M/Z2081.65、M/Z18667.3和M/Z2242.14共4个差异蛋白峰组成的生物标记物可以将湿证组和非湿证组样本较好地分类,其正确率84.7%,灵敏度为92.2%,特异性为73.3%。(3)湿证组与非湿证组尿液中差异蛋白峰经SwissProt数据库鉴定,可能为7种蛋白质。结论初步筛选出CRF中医湿证的尿液蛋白标志物,建立了CRF中医湿证尿液蛋白预测模型,通过数据库对尿液蛋白标志物进行了鉴定,为CRF中医湿证的临床辨证提供了一定的实验依据。展开更多
背景与目的:采用现代治疗方法治疗非霍奇金淋巴瘤(non-Hodgkin’s lymphoma,NHL)完全缓解率可达70%～80%,但仍有40%～50%患者最终会复发,而微小残留病灶是复发的根源。本研究应用SELDI蛋白芯片技术,分析初诊NHL患者与正常人群血清蛋白...背景与目的:采用现代治疗方法治疗非霍奇金淋巴瘤(non-Hodgkin’s lymphoma,NHL)完全缓解率可达70%～80%,但仍有40%～50%患者最终会复发,而微小残留病灶是复发的根源。本研究应用SELDI蛋白芯片技术,分析初诊NHL患者与正常人群血清蛋白质谱的差异和化疗前后血清蛋白质谱的变化,寻找NHL血清小分子标记物。方法:采用表面增强激光解吸电离飞行时间质谱分析技术(surface-enhanced laser desorption/ionization time of flight mass spectrometry,SELDI-TOF-MS)分析3组血清标本:44例NHL初诊组、51例正常对照组和44例完全缓解组(NHL患者自身配对)。应用Ciphergen ProteinChip 3.1软件进行原始数据的校正和分析。结果:与正常对照组比较,有1个差异蛋白峰(M11710)在NHL初诊组高表达而在CR组降低至接近正常(P<0.05);另外有9个差异蛋白峰(M3322、M4355、M6445、M6646、M8581、M8708、M8918、M13959、M15149)在NHL初诊组血清中低表达,而在CR组升高至接近正常(P<0.05)。通过建立决策树模型,发现初诊NHL患者血清存在有5个候选标志蛋白,高表达为M11710,低表达为M8581、M15149、M6646和M8918。结论:应用SELDI-TOF-MS分析可在化疗前后筛选出NHL患者血清中的标志蛋白,有可能在微小残留病监测、早期复发预测、疗效判断等方面提供有用的信息。展开更多
基金the National Natural Science Foundation of China,No. 30471934
文摘Gene expression profile changes in brain regions following traumatic brain injury at the gene level cannot sufficiently elucidate gene expression time, expression amount, protein post-translational processing or modification. Therefore, it is necessary to quantitatively analyze the gene expression profile using proteomic techniques. In the present study, we established a rat model of closed brain injury using Marmarou＇s weight-drop device, and investigated hippocampal differential protein expression using two-dimensional gel electrophoresis and surface-enhanced laser desorption ionization-time of flight-mass spectrometry. A total of 364 protein peaks were detected on weak cation exchange-2 protein chips, including 37 differential protein peaks. 345 protein peaks were detected on immobilized metal affinity capture arrays-Cu, including 12 differential protein peaks Further examination of these differential proteins revealed that glucose-regulated protein and proteasome subunit alpha type 3 expression were significantly upregulated post-injury. These results indicate that brain injury can alter protein expression in the hippocampus, and that glucose-regulated protein and proteasome subunit alpha type 3 are closely associated with the occurrence and development of traumatic brain injury.
基金National Science & Technology Pillar Program in the Eleventh Five-year Plan of China (No. 2006BAI02A11)Planned Sci-Tech Project of Guangdong Province (No. 2005B50301006)
文摘Background and Objective: Early diagnosis of nasopharyngeal carcinoma (NPC) is difficult due to the insufficient specificity of the conventional examination method. This study was to investigate potential and consistent biomarkers for NPC, particularly for early detection of NPC. Methods: A proteomic pattern was identified in a training set (134 NPC patients and 73 control individuals) using the surface-enhanced laser desorption and ionization-mass spectrometry (SELDI-MS), and used to screen the test set (44 NPC patients and 25 control individuals) to determine the screening accuracy. To confirm the accuracy, it was used to test another group of 52 NPC patients and 32 healthy individuals at 6 months later. Results: Eight proteomic biomarkers with top-scored peak mass/charge ratios (m/z) of 8605 Da, 5320 Da, 5355 Da, 5380 Da, 5336 Da, 2791 Da, 7154 Da, and 9366 Da were selected as the potential biomarkers of NPC with a sensitivity of 90.9% (40/44) and a specificity of 92.0% (23/25). The performance was better than the current diagnostic method by using the Epstein-Barr virus (EBV) capsid antigen IgA antibodies (VCA/IgA). Similar sensitivity (88.5%) and specificity (90.6%) were achieved in another group of 84 samples. Conclusion: SELDI-MS profiling might be a potential tool to identify patients with NPC, particularly at early clinical stages.
文摘Androgens play a central role in prostate cancer pathogenesis, and hence most of the patients respond to androgen deprivation therapies. However, patients tend to relapse with aggressive prostate cancer, which has been termed as hormone refractory. To identify the proteins that mediate progression to the hormone-refractory state, we used protein-chip technology for mass profiling of patients＇ sera. This study included 16 patients with metastatic hormone-refractory prostate cancer who were initially treated with androgen deprivation therapy. Serum samples were collected from each patient at five time points： point A, pre-treatment; point B, at the nadir of the prostate- specific antigen （PSA） level; point C, PSA failure; point D, the early hormone-refractory phase; and point E, the late hormone-refractory phase. Using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry, we performed protein mass profiling of the patients＇ sera and identified a 6 640-Da peak that increased with disease progression. Target proteins were partially purified, and by amino acid sequencing the peak was identified as a fragment of apolipoprotein C-I （ApoC-I）. Serum ApoC-I protein levels increased with disease progression. On immunohistochemical analysis, the ApoC-i protein was found localized to the cytoplasm of the hormone-refractory cancer cells. In this study, we showed an increase in serum ApoC-I protein levels in prostate cancer patients during their progression to the hormone-refractory state, which suggests that ApoC-I protein is related to progression of prostate cancer. However, as the exact role of ApoC-I in prostate cancer pathogenesis is unclear, further research is required.
基金This study was supported by the grants from Beijing Municipal Science ＆ Technology Commission （No.H030930040230） and the National Natural Science Foundation of China （No.30772319）.
文摘Background Endometriosis is a common gynecological disease. This study aimed to screen proteins that were expressed differently in patients with endometriosis versus normal controls using proteomic techniques, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry （SELDI-TOF-MS）.Methods Protein chip SELDI-TOF-MS combines the advantages of microarray and mass spectrometry, and can screen latent markers in sera of patients with endometriosis. Serum samples from patients and normal volunteers were analyzed by SELDI-TOF-MS. Results After comparing the serum protein spectra of 36 patients with 24 normal controls, 24 differently expressed potential biomarkers （P 〈0.01） were identified. Using Biomarker Pattern software, we established a tree model of the 60 serum protein spectra. When using the three bJomarkers to classify the samples, the sensitivity for diagnosing endometriosis was 91.7%, specificity was 95.8%, and coincidence rate was 93.3%. Then we used serum samples from 12 patients and 8 normal controls to validate the tree model and report the sensitivity for diagnosing endometriosis was 91.7%, specificity was 75%, and coincidence rate was 85%. Conclusions SELDI-TOF-MS may be a useful tool in high-risk population screening for endometriosis. The identification and application of the biomarkers need to further study.
基金Project (No. 30471987) supported by the National Natural ScienceFoundation of China
文摘Objectives： To detect the serum proteomic patterns by using SELDI-TOF-MS （surface enhanced laser desorption/ ionization-time of flight-mass spectrometry） technology and CM10 ProteinChip in colorectal cancer （CRC） patients, and to evaluate the significance of the proteomic patterns in the tumour staging of colorectal cancer. Methods： SELDI-TOF-MS and CM10 ProteinChip were used to detect the serum proteomic patterns of 76 patients with colorectal cancer, among them, 10 Stage Ⅰ, 19 Stage Ⅱ, 16 Stage Ⅲ and 31 Stage Ⅳ samples. Different stage models were developed and validated by support vector machines, disctiminant analysis and time-sequence analysis. Results： The Model Ⅰ formed by 6 protein peaks （m/z： 2759.58, 2964.66, 2048.01, 4795.90, 4139.77 and 37761.60） could be used to distinguish local CRC patients （Stage Ⅰ and Stage Ⅱ） from regional CRC patients （Stage Ⅲ） with an accuracy of 86.67% （39/45）. The Model Ⅱ formed by 3 protein peaks （m/z： 6885.30, 2058.32 and 8567,75） could be used to distinguish locoregional CRC patients （Stage Ⅰ, Stage Ⅱ and Stage Ⅲ） from systematic CRC patients （Stage IV） With an accuracy of 75.00% （57/76）. The Model Ⅲ could distinguish Stage Ⅰ from Stage Ⅱ with an accuracy of 86.21% （25/29）. The Model Ⅳ could distinguish Stage Ⅰ from Stage Ⅲ with accuracy of 84.62% （22/26）. The Model Ⅴ could distinguish Stage Ⅱ from Stage Ⅲ with accuracy of 85.71% （30/35）. The Model Ⅵ could distinguish Stage Ⅱ from Stage Ⅳ with accuracy of 80.00% （40/50）. The Model Ⅶ could distinguish Stage Ⅲ from Stage Ⅳ with accuracy of 78.72% （37/47）. Different stage groups could be distinguished by the two-dimensional scattered spots figure obviously. Conclusion： This method showed great success in preoperatively determining the colorectal cancer stage of patients.
文摘背景与目的肺癌是当今世界上最常见的恶性肿瘤之一,迄今缺乏临床诊断可用的分子标志物。本实验应用SELDI技术寻找肺癌新的血清标志物。方法对227例血清样品(包括146例肺癌、13例肺炎、28例结核性胸膜炎和40例正常人血清样品)进行蛋白质谱检测。对候选蛋白进行质谱鉴定,并结合免疫共沉淀和ELISA技术筛选出肺癌新的候选标志物。结果通过Biomarker WizardTM软件分析显示13.78kDa、13.90kDa和14.07kDa的蛋白峰在肺癌病人血清样品中明显低于对照组。通过1-D胶分离,质谱鉴定和免疫沉淀分析显示这3个差异蛋白峰为野生型甲状腺运载蛋白(nativeTTR)和它的两个变体(cysTTR and glutTTR)。ELISA和SELDI技术分析上述血清样品均发现TTRs在肺癌血清中的表达下调。结论采用SELDI技术首次筛选并鉴定出TTRs,表明其可能作为肺癌诊断的候选血清标志物。
文摘目的采用表面增强激光解析离子化飞行时间质谱(surface-enhanced laser desorption/ionization time of flight mass spectrometry,SELDI-TOF-MS)技术研究慢性肾衰竭(chronic renal failure,CRF)中医湿证患者的尿液蛋白标志物。方法采集CRF湿证患者90例和非湿证患者60例的尿液,采用H4蛋白芯片技术进行尿液蛋白质组学研究,用蛋白芯片阅读器PBSⅡ对芯片进行扫描、分析。结果 (1)湿证组与非湿证组尿液样本的蛋白质图谱在质荷比1000-20000范围内检测到25个差异蛋白峰(P<0.01)。(2)经生物信息学分析建立CRF中医湿证尿液蛋白预测模型,得到M/Z8654.96、M/Z2081.65、M/Z18667.3和M/Z2242.14共4个差异蛋白峰组成的生物标记物可以将湿证组和非湿证组样本较好地分类,其正确率84.7%,灵敏度为92.2%,特异性为73.3%。(3)湿证组与非湿证组尿液中差异蛋白峰经SwissProt数据库鉴定,可能为7种蛋白质。结论初步筛选出CRF中医湿证的尿液蛋白标志物,建立了CRF中医湿证尿液蛋白预测模型,通过数据库对尿液蛋白标志物进行了鉴定,为CRF中医湿证的临床辨证提供了一定的实验依据。
文摘背景与目的:采用现代治疗方法治疗非霍奇金淋巴瘤(non-Hodgkin’s lymphoma,NHL)完全缓解率可达70%～80%,但仍有40%～50%患者最终会复发,而微小残留病灶是复发的根源。本研究应用SELDI蛋白芯片技术,分析初诊NHL患者与正常人群血清蛋白质谱的差异和化疗前后血清蛋白质谱的变化,寻找NHL血清小分子标记物。方法:采用表面增强激光解吸电离飞行时间质谱分析技术(surface-enhanced laser desorption/ionization time of flight mass spectrometry,SELDI-TOF-MS)分析3组血清标本:44例NHL初诊组、51例正常对照组和44例完全缓解组(NHL患者自身配对)。应用Ciphergen ProteinChip 3.1软件进行原始数据的校正和分析。结果:与正常对照组比较,有1个差异蛋白峰(M11710)在NHL初诊组高表达而在CR组降低至接近正常(P<0.05);另外有9个差异蛋白峰(M3322、M4355、M6445、M6646、M8581、M8708、M8918、M13959、M15149)在NHL初诊组血清中低表达,而在CR组升高至接近正常(P<0.05)。通过建立决策树模型,发现初诊NHL患者血清存在有5个候选标志蛋白,高表达为M11710,低表达为M8581、M15149、M6646和M8918。结论:应用SELDI-TOF-MS分析可在化疗前后筛选出NHL患者血清中的标志蛋白,有可能在微小残留病监测、早期复发预测、疗效判断等方面提供有用的信息。
