Abstract 4564: Lung cancer serum biomarker discovery using label free LC-MS/MS

Abstract

Abstract Lung cancer remains the leading cause of cancer-related death with a 5-year survival rate of less than 15%. Poor survival is largely due to the late stage at which lung cancer is typically diagnosed and the absence of proven imaging and molecular screening modalities for effective early detection. Given the clinical burden from lung cancer, and the relatively favorable survival associated with early stage lung cancer, biomarkers for early detection of lung cancer are of important potential clinical benefit. To identify candidate serum biomarkers for lung cancer, we performed a global proteomic discovery study using LC-MS/MS applied to a set of pooled non-small cell lung cancer (NSCLC) case sera (8 adenocarcinoma and 7 squamous cell carcinoma pools) and matched controls pools. Agilent Human 14 Multiple Affinity Removal spin cartridges were used to deplete the top 14 most abundant serum proteins; the remaining serum proteins were then subjected to trypsin digestion and analyzed in triplicate by nano-LC-ESI-MS/MS. The resulting MS/MS data were searched against the UNIPROT derived human proteome database. A total of 7268 proteins were identified more than 3 times from the combined LC-MS/MS analyses. Both the observed peptide spectral counts and extracted ion chromatograms (EICs) were then used to estimate the relative abundance of proteins across the case/control serum pools. A list of 198 differentially abundant candidate proteins was compiled by applying the Wilcoxon rank sum test to the peptide spectral count data (P<0.02). A MATLABTM based in-house tool was developed to extract ion chromatograms for 5397 peptides attributed to 3221 proteins. A total of 181 peptides from 149 proteins were significantly differentially abundant across the case/control pools (P<0.005 Student's t test). These candidate biomarker proteins include positive acute phase response proteins, key molecules in cell-cell signaling and interaction network, DNA replication/recombination/repair network, and a number of previously identified lung cancer-associated serum proteins such as alpha-1-glycoprotein, ceruloplasmin, leucine-rich-α-glycoproteins, and kinnogen-1. The peptide spectral count and EIC derived abundances of some of these candidate proteins have been confirmed with multiple reaction monitoring (MRM) assays which will serve as targeted quantitative assays to evaluate the classification performance of selected candidate biomarkers in planned sequential independent case/control validation studies. [Supported by Hirtzel Foundation Postdoctoral Fellowship to XZ, P50 CA90440 NCI SPORE in Lung Cancer to JMS, and NCI Early Detection Research Network Biomarker Discovery Laboratory, U01 CA084968 to WLB]. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4564.