Application of surface-enhanced laser desorption/ionization time-of-flight-based serum proteomic array technique for the early diagnosis of prostate cancer

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）

Serum Amyloid A Protein: A Potential Biomarker Correlated With Clinical Stage of Lung Cancer

Objective To identify serum diagnosis or progression biomarkers in patients with lung cancer using protein chip profiling analysis. Method Profiling analysis was performed on 450 sera collected from 213 patients with lung cancer, 19 with pneumonia, 16 with pulmonary tuberculosis, 65 with laryngeal carcinoma, 55 with laryngopharyngeal carcinoma patients, and 82 normal individuals. A new strategy was developed to identify the biomarkers on chip by trypsin pre-digestion. Results Profiling analysis demonstrated that an 11.6kDa protein was significandy elevated in lung cancer patients, compared with the control groups （P〈0.001）. The level and percentage of 11.6kDa protein progressively increased with the clinical stages Ⅰ-Ⅳ and were also higher in patients with squamous cell carcinoma than in other subtypes. This biomarker could be decreased after operation or chemotherapy. On the other hand, 11.6kDa protein was also increased in 50% benign diseases of lung and 13% of other cancer controls. After trypsin pre-digestion, a set of new peptide biomarkers was noticed to appear only in the samples containing a 11.6kDa peak. Further identification showed that 2177Da was a fragment of serum amyloid A （SAA, MW 11.6kDa）. Two of the new peaks, 1550Da and 1611Da, were defined from the same protein by database searching. This result was further confirmed by partial purification of 11.6kDa protein and MS analysis. Conclusion SAA is a useful biomarker to monitor the progression of lung cancer and can directly identify some biomarkers on chip.

Protein Profile of Human Lung Squamous Carcinoma Cell Line NCI-H226

Objective To construct a database of human lung squamous carcinoma cell line NCI-H226 and to facilitate discovery of novel subtypes markers of lung cancer. Method Proteomic technique was used to analyze human lung squamous carcinoma cell line NCI-H226. The proteins of the NCI-H226 cells were separated by two-dimensional gel electrophoresis and identified by mass spectrometry. Results The results showed that a good reproducibility of the 2-D gel pattern was attained. The position deviation of matched spots among three 2-D gels was 1.95±0.53 mm in the isoelectric focusing direction, and 1.73±0.45 mm in the sodium dodecyl sulfate-polyacrylamide gel electrophoresis direction. One hundred and twenty-seven proteins, including enzymes, signal transduction proteins, structure proteins, transport proteins, etc. were characterized, of which, 29 identified proteins in NCI-H226 cells were reported for the first time to be involved in lung cancer carcinogenesis. Conclusion The information obtained from this study could provide some valuable clues for further study on the carcinogenetic mechanism of different types of lung cancer, and may help us to discover some potential subtype-specific biomarkers of lung cancer.