Lung Cancer Serum Biomarker Discovery Using Glycoprotein Capture and Liquid Chromatography Mass Spectrometry Xuemei Zeng,† Brian L. Hood,† Mai Sun,† Thomas P. Conrads,†,‡,§ Roger S. Day,| Joel L. Weissfeld,⊥,# Jill M. Siegfried,‡,§ and William L. Bigbee*,†,‡,⊥,¶ Mass Spectrometry Platform, Cancer Biomarkers Facility, Lung and Thoracic Malignancies Program, Cancer Epidemiology Program, University of Pittsburgh Cancer Institute, Department of Epidemiology, Graduate School of Public Health, Departments of Biomedical Informatics, Pathology, and Pharmacology & Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania Received July 6, 2010
Targeted glycoproteomics represents an attractive approach for conducting peripheral blood based cancer biomarker discovery due to the well-known altered pattern of protein glycosylation in cancer and the reduced complexity of the resultant glycoproteome. Here we report its application to a set of pooled nonsmall cell lung cancer (NSCLC) case sera (9 adenocarcinoma and 6 squamous cell carcinoma pools from 54 patients) and matched controls pools, including 8 clinical control pools with computed tomography detected nodules but being nonmalignant as determined by biopsy from 54 patients, and 8 matched healthy control pools from 106 cancer-free subjects. The goal of the study is to discover biomarkers that may enable improved early detection and diagnosis of lung cancer. Immunoaffinity subtraction was used to first deplete the topmost abundant serum proteins; the remaining serum proteins were then subjected to hydrazide chemistry based glycoprotein capture and enrichment. Hydrazide resin in situ trypsin digestion was used to release nonglycosylated peptides. Formerly N-linked glycosylated peptides were released by peptide-Nglycosidase F (PNGase F) treatment and were subsequently analyzed by liquid chromatography (LC)-tandem mass spectrometry (MS/MS). A MATLAB based in-house tool was developed to facilitate retention time alignment across different LC-MS/MS runs, determination of precursor ion m/z values and elution profiles, and the integration of mass chromatograms based on determined parameters for identified peptides. A total of 38 glycopeptides from 22 different proteins were significantly differentially abundant across the case/control pools (P < 0.01, Student’s t test) and their abundances led to a near complete separation of case and control pools based on hierarchical clustering. The differential abundances of three of these candidate proteins were verified by commercially available ELISAs applied in the pools. Strong positive correlations between glycopeptide mass chromatograms and ELISA-measured protein abundance was observed for all of the selected glycoproteins. Keywords: lung cancer • serum biomarkers • glycoproteomics • LC-MS/MS • mass chromatogram
1. Introduction Lung cancer is the leading cause of cancer deaths in the US partly due to its high fatality rate, with an overall 5-year survival rate of 15.6% (Surveillance Epidemiology and End Results; SEER). Poor survival from lung cancer is strongly related to the late stage at clinical presentation. The majority of lung cancer patients are diagnosed after their primary lung * To whom correspondence should be addressed. William L Bigbee, Ph.D. Tel: 412-641-7555. Fax: 412-641-2458. E-mail:
[email protected]. † Mass Spectrometry Platform, Cancer Biomarkers Facility. ‡ Lung and Thoracic Malignancies Program. § Pharmacology & Chemical Biology. | Departments of Biomedical Informatics. ⊥ Cancer Epidemiology Program, University of Pittsburgh Cancer Institute. # Department of Epidemiology, Graduate School of Public Health. ¶ Departments of Pathology.
6440 Journal of Proteome Research 2010, 9, 6440–6449 Published on Web 10/08/2010
tumors have metastasized and have only a 3.5% five-year survival rate. In contrast, early stage lung cancer has relatively favorable survival. A recent review reported that Stage 1A patients, with tumor size
