Secretome, the totality of secreted proteins, is viewed as a promising pool of candidate cancer biomarkers. Simple and reliable methods for identifying secreted proteins are highly desired. We used an optimized semi-shotgun liquid chromatography followed by tandem mass spectrometry (LC-MS/MS) method to analyze the secretome of breast cancer cell line MDA-MB-231. A total of 464 proteins were identified. About 63% of the proteins were classified as secreted proteins, including many promising breast cancer biomarkers, which were thought to be correlated with tumorigenesis, tumor development and metastasis. These results suggest that the optimized method may be a powerful strategy for cell line secretome profiling, and can be used to find potential cancer biomarkers with great clinical significance.
TANG XiaorongYAO LingCHEN KeyingHU XiaofangXU Lisa X.FAN Chunhai
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 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.
