ArticlePloS one2011
A comprehensive peptidome profiling technology for the identification of early detection biomarkers for lung adenocarcinoma.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Article
- Differential toxicity and localization of arginine-richiScience · 2023Article
- Apolipoprotein A-IV Has Bi-Functional Actions in Alcoholic Hepatitis by Regulating Hepatocyte Injury and Immune Cell Infiltration.International journal of molecular sciences · 2022Article
- Article
- The Patterning and Proportion of Charged Residues in the Arginine-Rich Mixed-Charge Domain Determine the Membrane-Less Organelle Targeted by the Protein.International journal of molecular sciences · 2022Article
- Phase separation and toxicity of C9orf72 poly(PR) depends on alternate distribution of arginine.The Journal of cell biology · 2021Article
- Article
- Review
- Novel Biomarker Proteins in Chronic Lymphocytic Leukemia: Impact on Diagnosis, Prognosis and Treatment.PloS one · 2016Article
- Secretomes are a potential source of molecular targets for cancer therapies and indicate that APOE is a candidate biomarker for lung adenocarcinoma metastasis.Molecular biology reports · 2014Article
- Review
- Article
- Serum biomarkers identification by mass spectrometry in high-mortality tumors.International journal of proteomics · 2013Article
- Sample preparation techniques for the untargeted LC-MS-based discovery of peptides in complex biological matrices.Journal of biomedicine & biotechnology · 2011Review
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Authors and funding
14 authors.
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No grant is acknowledged in the PubMed record.
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.
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