Aim： To identify the serum biomarkers of prostate cancer （PCa） by protein chip and bioinformatics. Methods： Serum samples from 83 PCa patients and 95 healthy men were taken from a mass screening in Changchun, Chin...Aim： To identify the serum biomarkers of prostate cancer （PCa） by protein chip and bioinformatics. Methods： Serum samples from 83 PCa patients and 95 healthy men were taken from a mass screening in Changchun, China. Protein profiling was carried out using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry （SELDI-TOF MS）. The data of spectra were analyzed using two bioinformatics tools. Results： Eighteen serum differential proteins were identified in the PCa group compared with the control group （P 〈 0.01）. There were four proteins at the higher serum level and 14 proteins at the lower serum level in the PCa group. A decision tree classification algorithm that used an eight-protein mass pattern was developed to correctly classify the samples. A sensitivity of 92.0 % and a specificity of 96.7 % for the study group were obtained by comparing the PCa and control groups. Conclusion： We identified new serum biomarkers of PCa. SELDI-TOF MS coupled with a decision tree classification algorithm will provide a highly accurate and innovative approach for the early diagnosis of PCa. （Asian J Androl 2006 Jan; 8： 45-51）展开更多
AIM： To study the variabilities of serum proteomic spectra in patients with gastric cancer before and after operation in order to detect the specific protein markers that can be used for quick diagnosis of gastric ca...AIM： To study the variabilities of serum proteomic spectra in patients with gastric cancer before and after operation in order to detect the specific protein markers that can be used for quick diagnosis of gastric cancer. METHODS： Proteomic spectra of 46 serum samples from patients with gastric cancer before and after operation and 40 from normal individuals were generated by IMAC-Cu protein chip and surface-enhanced laser desorption/ionization time of flight mass spectrometry. RESULTS： Fourteen differentially expressed proteins in serum were screened by analysis of proteomic spectra of preoperative patients and normal individuals. We obtained 4 proteins （heat shock protein 27, glucoseregulated protein, prohibitin, protein disulfide isomerase A3） making up marker pattern which was able to class the patient-team and normal-team. These marker patterns yielded 95.7% sensitivity and 92.5% specificity, respectively. The proteins over-expressed in serum of preoperative patients were obviously down-regulated. CONCLUSION： Specific protein markers of gastric cancer can be used for the quick diagnosis of gastric cancer and judgment of prognosis. SELDI-TOF-MS is a useful tool for the detection and identification of new protein markers in serum.展开更多
Laryngeal carcinoma is the most common malignancy among head and neck tu-mors. The purpose of this study is to find biomarkers for laryngeal carcinoma in patient blood serum using the Surface Enhanced Laser Desorption...Laryngeal carcinoma is the most common malignancy among head and neck tu-mors. The purpose of this study is to find biomarkers for laryngeal carcinoma in patient blood serum using the Surface Enhanced Laser Desorption/Ionization (SELDI) technique. Serum samples from 33 laryngeal carcinoma (12 cases of glottis, 18 of supraglottis and 3 of subglottis) patients and 31 age- and sex-matched healthy people were analyzed by SELDI-TOF on a Pro-teinChip reader, PBSII-C. Protein profiles were generated using WCX2 protein chips. Protein peak clustering and classification analyses were performed utilizing the Biomarker Wizard and Biomarker Pattern software packages, respectively. The results showed that sixteen peaks had significant difference between laryngeal cancer patients and healthy group, eight of which were up-regulated in the patient samples, and the others were down-regulated. Two protein peaks 8153 Da and 2035 Da were automatically chosen for the system training and development of a classification tree. The analysis yielded a correct percentage of 96.9% for patients and 96.7% for control. The results suggest that serum is a useful resource for the detection of specific bio-markers for laryngeal carcinoma. Proteinchip Array System was a useful tool for a high throughput screening of large-sized serum samples to discover potential biomarkers for carci-noma.展开更多
Proteomics is the study of proteins and their interactions in a cell. With the completion of the Human Genome Project, the emphasis is shifting to the protein compliment of the human organism. Because proteome reflect...Proteomics is the study of proteins and their interactions in a cell. With the completion of the Human Genome Project, the emphasis is shifting to the protein compliment of the human organism. Because proteome reflects more accurately on the dynamic state of a cell, tissue, or organism, much is expected from proteomics to yield better disease markers for diagnosis and therapy monitoring. The advent of proteomics technologies for global detection and quantitation of proteins creates new opportunities and challenges for those seeking to gain greater understanding of diseases. High-throughput proteomics technologies combining with advanced bioinformatics are extensively used to identify molecular signatures of diseases based on protein pathways and signaling cascades. Mass spectrometry plays a vital role in proteomics and has become an indispensable tool for molecular and cellular biology. While the potential is great, many challenges and issues remain to be solved, such as mining low abundant proteins and integration of proteomics with genomics and metabolomics data. Nevertheless, proteomics is the foundation for constructing and extracting useful knowledge to biomedical research. In this review, a snapshot of contemporary issues in proteomics technologies is discussed.展开更多
文摘Aim： To identify the serum biomarkers of prostate cancer （PCa） by protein chip and bioinformatics. Methods： Serum samples from 83 PCa patients and 95 healthy men were taken from a mass screening in Changchun, China. Protein profiling was carried out using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry （SELDI-TOF MS）. The data of spectra were analyzed using two bioinformatics tools. Results： Eighteen serum differential proteins were identified in the PCa group compared with the control group （P 〈 0.01）. There were four proteins at the higher serum level and 14 proteins at the lower serum level in the PCa group. A decision tree classification algorithm that used an eight-protein mass pattern was developed to correctly classify the samples. A sensitivity of 92.0 % and a specificity of 96.7 % for the study group were obtained by comparing the PCa and control groups. Conclusion： We identified new serum biomarkers of PCa. SELDI-TOF MS coupled with a decision tree classification algorithm will provide a highly accurate and innovative approach for the early diagnosis of PCa. （Asian J Androl 2006 Jan; 8： 45-51）
文摘AIM： To study the variabilities of serum proteomic spectra in patients with gastric cancer before and after operation in order to detect the specific protein markers that can be used for quick diagnosis of gastric cancer. METHODS： Proteomic spectra of 46 serum samples from patients with gastric cancer before and after operation and 40 from normal individuals were generated by IMAC-Cu protein chip and surface-enhanced laser desorption/ionization time of flight mass spectrometry. RESULTS： Fourteen differentially expressed proteins in serum were screened by analysis of proteomic spectra of preoperative patients and normal individuals. We obtained 4 proteins （heat shock protein 27, glucoseregulated protein, prohibitin, protein disulfide isomerase A3） making up marker pattern which was able to class the patient-team and normal-team. These marker patterns yielded 95.7% sensitivity and 92.5% specificity, respectively. The proteins over-expressed in serum of preoperative patients were obviously down-regulated. CONCLUSION： Specific protein markers of gastric cancer can be used for the quick diagnosis of gastric cancer and judgment of prognosis. SELDI-TOF-MS is a useful tool for the detection and identification of new protein markers in serum.
文摘Laryngeal carcinoma is the most common malignancy among head and neck tu-mors. The purpose of this study is to find biomarkers for laryngeal carcinoma in patient blood serum using the Surface Enhanced Laser Desorption/Ionization (SELDI) technique. Serum samples from 33 laryngeal carcinoma (12 cases of glottis, 18 of supraglottis and 3 of subglottis) patients and 31 age- and sex-matched healthy people were analyzed by SELDI-TOF on a Pro-teinChip reader, PBSII-C. Protein profiles were generated using WCX2 protein chips. Protein peak clustering and classification analyses were performed utilizing the Biomarker Wizard and Biomarker Pattern software packages, respectively. The results showed that sixteen peaks had significant difference between laryngeal cancer patients and healthy group, eight of which were up-regulated in the patient samples, and the others were down-regulated. Two protein peaks 8153 Da and 2035 Da were automatically chosen for the system training and development of a classification tree. The analysis yielded a correct percentage of 96.9% for patients and 96.7% for control. The results suggest that serum is a useful resource for the detection of specific bio-markers for laryngeal carcinoma. Proteinchip Array System was a useful tool for a high throughput screening of large-sized serum samples to discover potential biomarkers for carci-noma.
文摘Proteomics is the study of proteins and their interactions in a cell. With the completion of the Human Genome Project, the emphasis is shifting to the protein compliment of the human organism. Because proteome reflects more accurately on the dynamic state of a cell, tissue, or organism, much is expected from proteomics to yield better disease markers for diagnosis and therapy monitoring. The advent of proteomics technologies for global detection and quantitation of proteins creates new opportunities and challenges for those seeking to gain greater understanding of diseases. High-throughput proteomics technologies combining with advanced bioinformatics are extensively used to identify molecular signatures of diseases based on protein pathways and signaling cascades. Mass spectrometry plays a vital role in proteomics and has become an indispensable tool for molecular and cellular biology. While the potential is great, many challenges and issues remain to be solved, such as mining low abundant proteins and integration of proteomics with genomics and metabolomics data. Nevertheless, proteomics is the foundation for constructing and extracting useful knowledge to biomedical research. In this review, a snapshot of contemporary issues in proteomics technologies is discussed.
