Proteomics-based identification of tumor relevant proteins in lung adenocarcinoma

Background: Lung cancer has the highest mortality rate among malignant tumors. Proteomics is a powerful tool to identify protein biomarkers. The identification of protein biomarkers associated with lung adenocarcinoma would have significance for making prognoses and designing targeted therapies.

Methods: In our study, we applied a two-dimensional difference gel electrophoresis approach coupled to a matrix-assisted laser desorption/ionization time-of-flight mass spectrometric analysis for the identification of proteins differentially expressed between lung adenocarcinoma and the paired normal bronchial epithelial tissues derived from seven patients (four of them developed distant metastasis after operation). In addition, we chose two candidate proteins and examine their expression levels in lung adenocarcinoma and adjacent normal tissues using immunohistochemistry methods, and their expression levels in serum of patients and healthy donors by ELISA.

Result: In this study, 173 proteins were found to be differentially expressed (ratio>1.5 or<-1.5, P≤0.05), and 22 of them were identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Thirteen proteins were at lower levels in the lung adenocarcinoma group, while nine proteins were at higher abundance. Immunohistochemistry analysis confirmed the expression levels of the two candidate proteins. The differential expression of the candidate secreted protein in serum from lung adenocarcinoma samples and healthy controls was showed by ELISA.

Conclusion: Our results demonstrated a differential protein expression pattern for lung adenocarcinoma compared with the paired normal bronchial epithelial tissues. Further functional validation of candidate proteins is ongoing and might provide new insights in lung adenocarcinoma.