Search

Objectives: Screening method of endometrial cancer (EC) has not been established yet. Our study was to explore serum biomarkers of EC patients using surface-enhanced laser desorption and ionization-time-of-flight mass spectrometry (SELDI-TOF MS)., Methods: Serum samples from 65 EC patients and 40 controls were analyzed by SELDI-TOF MS (training set). Single- and multi-variant analyses were performed to compare protein profiles in serum of EC patients and healthy controls. Subsequently, blind test set including 40 EC patients and 40 controls were analyzed for validation., Results: A panel of four biomarker candidates were selected in training set analysis. These markers could also distinguish stage I patients from controls. Among them, two biomarkers were purified and identified as apolipoprotein A1 and a modified form of apolipoprotein C1. Screening for blind test set using dual-biomarker analysis yielded a sensitivity of 82% and a specificity of 86%., Conclusions: Involvement of apolipoproteins with EC is first suggested in this study. In addition to possibility of screening method for EC, findings of these new biomarkers might be related with carcinogenesis or predisposition to EC.

To screen for glycoproteins showing aberrant sialylation patterns in sera of cancer patients and apply such information for biomarker identification, we performed SELDI-TOF MS analysis coupled with lectin-coupled ProteinChip arrays (Jacalin or SNA) using sera obtained from lung cancer patients and control individuals. Our approach consisted of three processes (i) removal of 14 abundant proteins in serum, (ii) enrichment of glycoproteins with lectin-coupled ProteinChip arrays, and (iii) SELDI-TOF MS analysis with acidic glycoprotein-compatible matrix. We identified 41 protein peaks showing significant differences (p<0.05) in the peak levels between the cancer and control groups using the Jacalin- and SNA-ProteinChips. Among them, we identified loss of Neu5Ac (alpha2,6) Gal/GalNAc structure in apolipoprotein C-III (apoC-III) in cancer patients through subsequent MALDI-QIT-TOF MS/MS. Furthermore, subsequent validation experiments using an additional set of 60 lung adenocarcinoma patients and 30 normal controls demonstrated that there is a higher frequency of serum apoC-III with loss of alpha2,6-linkage Neu5Ac residues in lung cancer patients compared to controls. Our results have demonstrated that lectin-coupled ProteinChip technology allows the high-throughput and specific recognition of cancer-associated aberrant glycosylations, and implied a possibility of its applicability to studies on other diseases.

To identify biomarkers for predicting sensitivity to phosphatidylinositol 3-kinase (PI3K) inhibitors, we have developed a proteomics-based approach. Using surface-enhanced laser desorption-ionization time-of-flight mass spectrometry (SELDI-TOF MS), we measured the expression of 393 proteins in 39 human cancer cell lines (JFCR-39), and combined it with our previously established chemosensitivity database to select for proteins whose expressions show significant correlations to drug sensitivities. This integrated approach allowed us to identify peaks from two proteins, 11.6 and 11.8 kDa, that showed significant correlations with the sensitivity to a PI3K inhibitor, LY294002. We found that the 11.8 kDa protein was a phosphorylated form of the 11.6 kDa protein. While the 11.8 kDa protein showed a positive correlation with the sensitivity to LY294002, the 11.6 kDa protein showed a negative correlation with that of the LY294002. The 11.6 kDa protein was purified chromatographically, and was identified by SELDI-TOF MS as the ribosomal P2 protein, which possesses two prospective phosphorylation sites. These results suggested that the phosphorylation status of the ribosomal P2 was responsible for determining the sensitivity to LY294002, and that the ribosomal P2 could be a potential biomarker for predicting chemosensitivity.

Useful biomarkers are needed for early detection of cancers. To demonstrate the potential diagnostic usefulness of a new proteomic technology, we performed Expression Difference Mapping analysis on 39 cancer cell lines from 9 different tissues using ProteinChip technology. A protein biomarker candidate of 12kDa was found in colon cancer cells. We then optimized the purification conditions for this biomarker by utilizing Retentate Chromatography mass spectrometry (RC-MS). The optimized purification conditions developed "on-chip" were directly transferred to conventional chromatography to purify the biomarker, which was identified as prothymosin-alpha by ProteinChip time-of-flight mass spectrometry (TOF MS) and ProteinChip-Tandem MS systems. The relative expression level of prothymosin-alpha between colon cancer cells and normal colon mucosal cells was evaluated on the same ProteinChip platform. Prothymosin-alpha expression in colon cancer cells was clearly higher than in normal colon cells. These results indicate that prothymosin-alpha could be a potential biomarker for colon cancer, and that the ProteinChip platform could perform the whole process of biomarker discovery from screening to evaluation of the identified marker.