Two hundred and eighteen serum samples from 175 lung cancer patients and 43 healthy individuals were analyzed by using Surface Enhaced Laser Desorption/Ionization Time of Flight Mass Spectrome- try (SELDI-TOF-MS). The data analyzed by both Biomarker Wizard? and Biomarker Patterns? software showed that a protein peak with the molecular weight of 11.6 kDa significantly increased in lung cancer. Meanwhile,the level of this biomarker was progressively increased with the clinical stages of lung cancer. The candidate biomarker was then obtained from tricine one-dimensional sodium dodecyl sul- fate-polyacrylamide gel electrophoresis by matching the molecular weight with peaks on WCX2 chips and was identified as Serum Amyloid A protein (SAA) by MALDI/MS-MS and database searching. It was further validated in the same serum samples by immunoprecipitation with commercial SAA antibody. To confirm the SAA differential expression in lung cancer patients, the same set of serum samples was measured by ELISA assay. The result showed that at the cutoff point 0.446(OD value)on the Receiver Operating Characteristic (ROC) curve, SAA could better discriminate lung cancer from healthy indi- viduals with sensitivity of 84.1% and specificity of 80%. These findings demonstrated that SAA could be characterized as a biomarker related to pathological stages of lung cancer.
DAI SongWei1,2, WANG XiaoMin1,2, LIU LiYun1,2, LIU JiFu3, WU ShanShan3, HUANG LingYun1,2, XIAO XueYuan1,2 & HE DaCheng1,2 1 Key Laboratory of Cell Proliferation and Regulation of Ministry of Education, Beijing Normal University, Beijing 100875, China
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.
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 significantly 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.
There are multiple reports of autoimmune response in patients with lung cancer. To investigate whether a novel autoantibody is present in patients with lung cancer and evaluate its clinical diagnostic and prognostic value, sera from 10 patients with lung cancer and 10 normal individuals were analyzed using immunofluorescence and Western blotting. It was found that one serum sample from the patients with squamous carcinoma gave a fine speckled pattern staining in nucleus and had a high titer antinuclear autoantibody which could recognize 31 kD of nuclear protein isolated from both cancer cells and normal cells. The same patient’s serum was further used to immunoprecipitate the target antigen. The protein bands were excised from the SDS-PAGE gels and were analyzed with a Qstar Pulser I Quadrupole time-flight mass spec-trometer, and the 31 kD target antigen was identified as U1-A snRNP. To test the prevalence of anti-U1-A snRNP antibody, sera from 93 patients including 36 squmaous carcinomas (SCC), 26 adenocarcinomas (Ad), and 31 small cell carcinomas (SCLC) were screened by Western blotting. The results demonstrated that anti-U1-A snRNP antibody was present in 50% of SCC sera, 26.9% of Ad sera and 54.8% of SCLC sera. In this paper, we report for the first time that anti-U1-A snRNP antibody could be detected in the patients with lung cancer.
ZHANG Lijuan1, LIU Jifu2, ZHANG Hao1, WU Shanshan2, HUANG Lingyun1, HE Dacheng1 & XIAO Xueyuan1 1. Key Laboratory of Cell Proliferation and Regulation of Ministry of Education, Beijing Normal University, Beijing 100875, China
