title: A comprehensive peptidome profiling technology for the identification of early detection biomarkers for lung adenocarcinoma.
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.
authors.affiliation: Laboratory for Biomarker Development, Center for Genomic Medicine, RIKEN, Yokohama, Japan. k-ueda@riken.jp
authors.forename: Koji
authors.initials: K
authors.lastname: Ueda
authors.forename: Naomi
authors.initials: N
authors.lastname: Saichi
authors.forename: Sachiko
authors.initials: S
authors.lastname: Takami
authors.forename: Daechun
authors.initials: D
authors.lastname: Kang
authors.forename: Atsuhiko
authors.initials: A
authors.lastname: Toyama
authors.forename: Yataro
authors.initials: Y
authors.lastname: Daigo
authors.forename: Nobuhisa
authors.initials: N
authors.lastname: Ishikawa
authors.forename: Nobuoki
authors.initials: N
authors.lastname: Kohno
authors.forename: Kenji
authors.initials: K
authors.lastname: Tamura
authors.forename: Taro
authors.initials: T
authors.lastname: Shuin
authors.forename: Masato
authors.initials: M
authors.lastname: Nakayama
authors.forename: Taka-Aki
authors.initials: TA
authors.lastname: Sato
authors.forename: Yusuke
authors.initials: Y
authors.lastname: Nakamura
authors.forename: Hidewaki
authors.initials: H
authors.lastname: Nakagawa
mesh_terms: D000230:Adenocarcinoma / Q000378:metabolism*; D014408:Biomarkers, Tumor / Q000378:metabolism*; D016022:Case-Control Studies; D002853:Chromatography, Liquid; D006801:Humans; D008175:Lung Neoplasms / Q000378:metabolism*; D009363:Neoplasm Proteins / Q000378:metabolism*; D012372:ROC Curve; D053719:Tandem Mass Spectrometry
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins