Dataset Information

Lung cancer serum biomarker discovery using label-free liquid chromatography-tandem mass spectrometry.

ABSTRACT:

Introduction

Lung cancer remains the leading cause of cancer-related death with poor survival due to the late stage at which lung cancer is typically diagnosed. 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.

Methods

We performed a global lung cancer serum biomarker discovery study using liquid chromatography-tandem mass spectrometry in a set of pooled non-small cell lung cancer case sera and matched controls. Immunoaffinity subtraction was used to deplete the top most abundant serum proteins; the remaining serum proteins were subjected to trypsin digestion and analyzed in triplicate by liquid chromatography-tandem mass spectrometry. The tandem mass spectrum data were searched against the human proteome database, and the resultant spectral counting data were used to estimate the relative abundance of proteins across the case/control serum pools. The spectral counting-derived abundances of some candidate biomarker proteins were confirmed with multiple reaction monitoring mass spectrometry assays.

Results

A list of 49 differentially abundant candidate proteins was compiled by applying a negative binomial regression model to the spectral counting data (p < 0.01). Functional analysis with Ingenuity Pathway Analysis tools showed significant enrichment of inflammatory response proteins, key molecules in cell-cell signaling and interaction network, and differential physiological responses for the two common non-small cell lung cancer subtypes.

Conclusions

We identified a set of candidate serum biomarkers with statistically significant differential abundance across the lung cancer case/control pools, which, when validated, could improve lung cancer early detection.

SUBMITTER: Zeng X

PROVIDER: S-EPMC3104087 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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Publications

Lung cancer serum biomarker discovery using label-free liquid chromatography-tandem mass spectrometry.

Zeng Xuemei X Hood Brian L BL Zhao Ting T Conrads Thomas P TP Sun Mai M Gopalakrishnan Vanathi V Grover Himanshu H Day Roger S RS Weissfeld Joel L JL Wilson David O DO Siegfried Jill M JM Bigbee William L WL

Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer 20110401 4

<h4>Introduction</h4>Lung cancer remains the leading cause of cancer-related death with poor survival due to the late stage at which lung cancer is typically diagnosed. 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.<h4>Methods</h4>We performed a global lung cancer serum biomarker discovery study using liquid chromatography-tandem ma ...[more]

PMID: 21304412

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Project description: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-N-glycosidase 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.

Dataset Information

Lung cancer serum biomarker discovery using label-free liquid chromatography-tandem mass spectrometry.

Introduction

Methods

Results

Conclusions

Publications

Lung cancer serum biomarker discovery using label-free liquid chromatography-tandem mass spectrometry.

Similar Datasets

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