Abstract
The mass spectrometry-based peptidomics approaches have proven its usefulness in several areas such as the discovery of physiologically active peptides or biomarker candidates derived from various biological fluids including blood and cerebrospinal fluid. However, to identify biomarkers that are reproducible and clinically applicable, development of a novel technology, which enables rapid, sensitive, and quantitative analysis using hundreds of clinical specimens, has been eagerly awaited. Here we report an integrative peptidomic approach for identification of lung cancer-specific serum peptide biomarkers. It is based on the one-step effective enrichment of peptidome fractions (molecular weight of 1,000–5,000) with size exclusion chromatography in combination with the precise label-free quantification analysis of nano-LC/MS/MS data set using Expressionist proteome server platform. We applied this method to 92 serum samples well-managed with our SOP (standard operating procedure) (30 healthy controls and 62 lung adenocarcinoma patients), and quantitatively assessed the detected 3,537 peptide signals. Among them, 118 peptides showed significantly altered serum levels between the control and lung cancer groups (p<0.01 and fold change >5.0). Subsequently we identified peptide sequences by MS/MS analysis and further assessed the reproducibility of Expressionist-based quantification results and their diagnostic powers by MRM-based relative-quantification analysis for 96 independently prepared serum samples and found that APOA4 273–283, FIBA 5–16, and LBN 306–313 should be clinically useful biomarkers for both early detection and tumor staging of lung cancer. Our peptidome profiling technology can provide simple, high-throughput, and reliable quantification of a large number of clinical samples, which is applicable for diverse peptidome-targeting biomarker discoveries using any types of biological specimens.
Highlights
Lung cancer is the leading cause of cancer death worldwide [1]
After quantitative comparison of 3,537 serum peptides among 92 cases in the lung cancer biomarker discovery, we further evaluated the accuracy of quantification results by another more reliable quantification method multiple reaction monitoring (MRM) technology using independently prepared 96 serum samples
The methodology to purify preanalytical samples without loss of targeted components is crucial. From this point of view, the previous peptidome profiling technologies, such as SELDI-TOFMS coupled with ProteinChip arrays or MALDI-TOF-MS
Summary
Lung cancer is the leading cause of cancer death worldwide [1]. Smoking is still the leading risk factor for lung cancer, but recently the proportion of never smoker-related lung cancer is significantly increasing, its cause or other risk factor(s) is unknown [2]. Serum biomarkers for lung cancer have been investigated to achieve early detection of the disease and improve clinical management of patients [5] Their present clinical usefulness remains limited [6,7]. CEA (carcinoembryonic antigen) and CYFRA (cytokeratin 19 fragment) are elevated in sera in a subset of lung cancer patients, and are clinically applied to monitor the disease status and evaluate the response to treatments. They are not recommended to use in clinical diagnosis and screening [8] because they are elevated in certain non-cancerous conditions such as smoking and lung inflammation as well as in patients with other types of cancers. Development of novel serum/plasma biomarkers applicable for lung cancer diagnosis is urgently required
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