Prediction of outcome of non-small cell lung cancer patients treated with chemotherapy and bortezomib by time-course MALDI-TOF-MS serum peptide profiling

摘要

BackgroundOnly a minority of patients with advanced non-small cell lung cancer (NSCLC) benefit from chemotherapy. Serum peptide profiling of NSCLC patients was performed to investigate patterns associated with treatment outcome.Using magnetic bead-assisted serum peptide capture coupled to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), serum peptide mass profiles of 27 NSCLC patients treated with cisplatin-gemcitabine chemotherapy and bortezomib were obtained. Support vector machine-based algorithms to predict clinical outcome were established based on differential pre-treatment peptide profiles and dynamic changes in peptide abundance during treatment.