Cargando…
Statistical characterization of therapeutic protein modifications
Peptide mapping with liquid chromatography–tandem mass spectrometry (LC-MS/MS) is an important analytical method for characterization of post-translational and chemical modifications in therapeutic proteins. Despite its importance, there is currently no consensus on the statistical analysis of the r...
Autores principales: | , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5554216/ https://www.ncbi.nlm.nih.gov/pubmed/28801661 http://dx.doi.org/10.1038/s41598-017-08333-y |
_version_ | 1783256751025422336 |
---|---|
author | Tsai, Tsung-Heng Hao, Zhiqi Hong, Qiuting Moore, Benjamin Stella, Cinzia Zhang, Jeffrey H. Chen, Yan Kim, Michael Koulis, Theo Ryslik, Gregory A. Verschueren, Erik Jacobson, Fred Haskins, William E. Vitek, Olga |
author_facet | Tsai, Tsung-Heng Hao, Zhiqi Hong, Qiuting Moore, Benjamin Stella, Cinzia Zhang, Jeffrey H. Chen, Yan Kim, Michael Koulis, Theo Ryslik, Gregory A. Verschueren, Erik Jacobson, Fred Haskins, William E. Vitek, Olga |
author_sort | Tsai, Tsung-Heng |
collection | PubMed |
description | Peptide mapping with liquid chromatography–tandem mass spectrometry (LC-MS/MS) is an important analytical method for characterization of post-translational and chemical modifications in therapeutic proteins. Despite its importance, there is currently no consensus on the statistical analysis of the resulting data. In this manuscript, we distinguish three statistical goals for therapeutic protein characterization: (1) estimation of site occupancy of modifications in one condition, (2) detection of differential site occupancy between conditions, and (3) estimation of combined site occupancy across multiple modification sites. We propose an approach, which addresses these goals in terms of summarizing the quantitative information from the mass spectra, statistical modeling, and model-based analysis of LC-MS/MS data. We illustrate the approach using an LC-MS/MS experiment from an antibody-drug conjugate and its monoclonal antibody intermediate. The performance was compared to a ‘naïve’ data analysis approach, by using computer simulation, evaluation of differential site occupancy in positive and negative controls, and comparisons of estimated site occupancy with orthogonal experimental measurements of N-linked glycoforms and total oxidation. The results demonstrated the importance of replicated studies of protein characterization, and of appropriate statistical modeling, for reproducible, accurate and efficient site occupancy estimation and differential analysis. |
format | Online Article Text |
id | pubmed-5554216 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-55542162017-08-15 Statistical characterization of therapeutic protein modifications Tsai, Tsung-Heng Hao, Zhiqi Hong, Qiuting Moore, Benjamin Stella, Cinzia Zhang, Jeffrey H. Chen, Yan Kim, Michael Koulis, Theo Ryslik, Gregory A. Verschueren, Erik Jacobson, Fred Haskins, William E. Vitek, Olga Sci Rep Article Peptide mapping with liquid chromatography–tandem mass spectrometry (LC-MS/MS) is an important analytical method for characterization of post-translational and chemical modifications in therapeutic proteins. Despite its importance, there is currently no consensus on the statistical analysis of the resulting data. In this manuscript, we distinguish three statistical goals for therapeutic protein characterization: (1) estimation of site occupancy of modifications in one condition, (2) detection of differential site occupancy between conditions, and (3) estimation of combined site occupancy across multiple modification sites. We propose an approach, which addresses these goals in terms of summarizing the quantitative information from the mass spectra, statistical modeling, and model-based analysis of LC-MS/MS data. We illustrate the approach using an LC-MS/MS experiment from an antibody-drug conjugate and its monoclonal antibody intermediate. The performance was compared to a ‘naïve’ data analysis approach, by using computer simulation, evaluation of differential site occupancy in positive and negative controls, and comparisons of estimated site occupancy with orthogonal experimental measurements of N-linked glycoforms and total oxidation. The results demonstrated the importance of replicated studies of protein characterization, and of appropriate statistical modeling, for reproducible, accurate and efficient site occupancy estimation and differential analysis. Nature Publishing Group UK 2017-08-11 /pmc/articles/PMC5554216/ /pubmed/28801661 http://dx.doi.org/10.1038/s41598-017-08333-y Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Tsai, Tsung-Heng Hao, Zhiqi Hong, Qiuting Moore, Benjamin Stella, Cinzia Zhang, Jeffrey H. Chen, Yan Kim, Michael Koulis, Theo Ryslik, Gregory A. Verschueren, Erik Jacobson, Fred Haskins, William E. Vitek, Olga Statistical characterization of therapeutic protein modifications |
title | Statistical characterization of therapeutic protein modifications |
title_full | Statistical characterization of therapeutic protein modifications |
title_fullStr | Statistical characterization of therapeutic protein modifications |
title_full_unstemmed | Statistical characterization of therapeutic protein modifications |
title_short | Statistical characterization of therapeutic protein modifications |
title_sort | statistical characterization of therapeutic protein modifications |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5554216/ https://www.ncbi.nlm.nih.gov/pubmed/28801661 http://dx.doi.org/10.1038/s41598-017-08333-y |
work_keys_str_mv | AT tsaitsungheng statisticalcharacterizationoftherapeuticproteinmodifications AT haozhiqi statisticalcharacterizationoftherapeuticproteinmodifications AT hongqiuting statisticalcharacterizationoftherapeuticproteinmodifications AT moorebenjamin statisticalcharacterizationoftherapeuticproteinmodifications AT stellacinzia statisticalcharacterizationoftherapeuticproteinmodifications AT zhangjeffreyh statisticalcharacterizationoftherapeuticproteinmodifications AT chenyan statisticalcharacterizationoftherapeuticproteinmodifications AT kimmichael statisticalcharacterizationoftherapeuticproteinmodifications AT koulistheo statisticalcharacterizationoftherapeuticproteinmodifications AT ryslikgregorya statisticalcharacterizationoftherapeuticproteinmodifications AT verschuerenerik statisticalcharacterizationoftherapeuticproteinmodifications AT jacobsonfred statisticalcharacterizationoftherapeuticproteinmodifications AT haskinswilliame statisticalcharacterizationoftherapeuticproteinmodifications AT vitekolga statisticalcharacterizationoftherapeuticproteinmodifications |