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A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma
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 rep...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3075260/ https://www.ncbi.nlm.nih.gov/pubmed/21533267 http://dx.doi.org/10.1371/journal.pone.0018567 |
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author | Ueda, Koji Saichi, Naomi Takami, Sachiko Kang, Daechun Toyama, Atsuhiko Daigo, Yataro Ishikawa, Nobuhisa Kohno, Nobuoki Tamura, Kenji Shuin, Taro Nakayama, Masato Sato, Taka-Aki Nakamura, Yusuke Nakagawa, Hidewaki |
author_facet | Ueda, Koji Saichi, Naomi Takami, Sachiko Kang, Daechun Toyama, Atsuhiko Daigo, Yataro Ishikawa, Nobuhisa Kohno, Nobuoki Tamura, Kenji Shuin, Taro Nakayama, Masato Sato, Taka-Aki Nakamura, Yusuke Nakagawa, Hidewaki |
author_sort | Ueda, Koji |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-3075260 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-30752602011-04-29 A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma Ueda, Koji Saichi, Naomi Takami, Sachiko Kang, Daechun Toyama, Atsuhiko Daigo, Yataro Ishikawa, Nobuhisa Kohno, Nobuoki Tamura, Kenji Shuin, Taro Nakayama, Masato Sato, Taka-Aki Nakamura, Yusuke Nakagawa, Hidewaki PLoS One Research Article 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. Public Library of Science 2011-04-12 /pmc/articles/PMC3075260/ /pubmed/21533267 http://dx.doi.org/10.1371/journal.pone.0018567 Text en Ueda et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Ueda, Koji Saichi, Naomi Takami, Sachiko Kang, Daechun Toyama, Atsuhiko Daigo, Yataro Ishikawa, Nobuhisa Kohno, Nobuoki Tamura, Kenji Shuin, Taro Nakayama, Masato Sato, Taka-Aki Nakamura, Yusuke Nakagawa, Hidewaki A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma |
title | A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma |
title_full | A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma |
title_fullStr | A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma |
title_full_unstemmed | A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma |
title_short | A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma |
title_sort | comprehensive peptidome profiling technology for the identification of early detection biomarkers for lung adenocarcinoma |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3075260/ https://www.ncbi.nlm.nih.gov/pubmed/21533267 http://dx.doi.org/10.1371/journal.pone.0018567 |
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