Statistical characterization of therapeutic protein modifications

Abstract 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...

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Autores principales:	Tsung-Heng Tsai, Zhiqi Hao, Qiuting Hong, Benjamin Moore, Cinzia Stella, Jeffrey H. Zhang, Yan Chen, Michael Kim, Theo Koulis, Gregory A. Ryslik, Erik Verschueren, Fred Jacobson, William E. Haskins, Olga Vitek
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/08510379a20f40e192b97fe2f553e394
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spelling	oai:doaj.org-article:08510379a20f40e192b97fe2f553e3942021-12-02T12:32:03ZStatistical characterization of therapeutic protein modifications10.1038/s41598-017-08333-y2045-2322https://doaj.org/article/08510379a20f40e192b97fe2f553e3942017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-08333-yhttps://doaj.org/toc/2045-2322Abstract 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.Tsung-Heng TsaiZhiqi HaoQiuting HongBenjamin MooreCinzia StellaJeffrey H. ZhangYan ChenMichael KimTheo KoulisGregory A. RyslikErik VerschuerenFred JacobsonWilliam E. HaskinsOlga VitekNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-13 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tsung-Heng Tsai Zhiqi Hao Qiuting Hong Benjamin Moore Cinzia Stella Jeffrey H. Zhang Yan Chen Michael Kim Theo Koulis Gregory A. Ryslik Erik Verschueren Fred Jacobson William E. Haskins Olga Vitek Statistical characterization of therapeutic protein modifications
description	Abstract 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	article
author	Tsung-Heng Tsai Zhiqi Hao Qiuting Hong Benjamin Moore Cinzia Stella Jeffrey H. Zhang Yan Chen Michael Kim Theo Koulis Gregory A. Ryslik Erik Verschueren Fred Jacobson William E. Haskins Olga Vitek
author_facet	Tsung-Heng Tsai Zhiqi Hao Qiuting Hong Benjamin Moore Cinzia Stella Jeffrey H. Zhang Yan Chen Michael Kim Theo Koulis Gregory A. Ryslik Erik Verschueren Fred Jacobson William E. Haskins Olga Vitek
author_sort	Tsung-Heng Tsai
title	Statistical characterization of therapeutic protein modifications
title_short	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_sort	statistical characterization of therapeutic protein modifications
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/08510379a20f40e192b97fe2f553e394
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Statistical characterization of therapeutic protein modifications

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