A glycomic method was used to screen the aberrantly ?1-6 fucosylated glycoproteins related to HCC metastasis and analyze the alteration of CK8 both in its expression level and its glycan parts associated with metastatic ability. Based on the approach, 2-DE coupled with lectin affinity blot, lectin affinity precipitation followed by MALDI-TOF-MS/MS, the lens culinaris agglutinin (LCA) affinity glycoprotein profiles from MHCC97-L and MHCC97-H cells, two higher metastatic HCC cell lines, were obtained, in which a differentially displayed protein spot was indicated when compared with Hep3B, in the region within 55～60 ku in molecular mass and 4～6 in isoelectric point. The identification result was CK8 by MALDI-TOF-MS/MS. To confirm the relation between increased core-fucosylation of CK8 and HCC metastasis, LCA affinity precipitation was used to extract the ?1-6 fucosylated glycoproteins, followed by Western blot. And it was found that CK8 was highly fucosylated in both MHCC97-L and MHCC97-H cells compared to Hep3B. Immunofluorescence analysis and Western blot were used to detect its intracellular localization and its protein expression levels, indicating that CK8 distributed in cytoplasm and increased protein expressions in MHCC97-L and MHCC97-H cell lines. And further lectin binding studies found that CK8 has a high affinity for Con A in both MHCC97-H and Hep3B cells, indicating that CK8 was a glycoprotein with high-mannose type N-glycans. But the amount of the lectin RCA-1 binding to CK8 was greater in MHCC97-H than Hep3B, suggesting that CK8 contained the increased terminal galactose residues ?-1, 4-linked to GlcNAc in MHCC97-H. All the results suggested that the increase of CK8 in its protein expression level, core-fucosylation and terminal gal ?1,4 GlcNAc disaccharides might be related to HCC metastatic ability.

Objective To explore the changes of proteomic spectra from plasma of patients with lung cancer or benign lung diseases and health controls in order to establish a primary diagnosis model of lung cancer. Methods The proteomic spectra from plasma of 108 patients with lung cancer, 40 patients with benign lung diseases and 22 healthy individuals were analysed by surface-enhanced laser desorption/ionization time of flight mass spectrometry ( SELDI-TOF-MS). The best decision tree model was established by cluster analysis and principal component analysis. Then the model was blindly validated by the protein of 21 patients with lung benign diseases and 47 patients with stage I lung cancer. Results Twenty-three significantly differentially expressed protein peaks were successfully detected (P <0.001). Blinded validation suggested that the accuracy for diagnosing lung cancer was 72. 06%, the sensitivity and specificity were 72. 34% and 71.43%, respectively, and the positive predictive value and negative predictive value were 85. 0% and 78. 95%, respectively. Conclusion SELDI-TOF-MS protein chip technology provides a new tool for the early diagnosis of lung cancer.