Literature DB >> 31175671

Toward a Consensus on Applying Quantitative Liquid Chromatography-Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper.

Bhagwat Prasad1, Brahim Achour2, Per Artursson3, Cornelis E C A Hop4, Yurong Lai5, Philip C Smith6, Jill Barber2, Jacek R Wisniewski7, Daniel Spellman8, Yasuo Uchida9, Michael A Zientek10, Jashvant D Unadkat1, Amin Rostami-Hodjegan2,11.   

Abstract

Quantitative translation of information on drug absorption, disposition, receptor engagement, and drug-drug interactions from bench to bedside requires models informed by physiological parameters that link in vitro studies to in vivo outcomes. To predict in vivo outcomes, biochemical data from experimental systems are routinely scaled using protein quantity in these systems and relevant tissues. Although several laboratories have generated useful quantitative proteomic data using state-of-the-art mass spectrometry, no harmonized guidelines exit for sample analysis and data integration to in vivo translation practices. To address this gap, a workshop was held on September 27 and 28, 2018, in Cambridge, MA, with 100 experts attending from academia, the pharmaceutical industry, and regulators. Various aspects of quantitative proteomics and its applications in translational pharmacology were debated. A summary of discussions and best practices identified by this expert panel are presented in this "White Paper" alongside unresolved issues that were outlined for future debates.
© 2019 The Authors Clinical Pharmacology & Therapeutics © 2019 American Society for Clinical Pharmacology and Therapeutics.

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Year:  2019        PMID: 31175671      PMCID: PMC6692196          DOI: 10.1002/cpt.1537

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


  97 in total

1.  Large-scale proteomic analysis of the human spliceosome.

Authors:  Juri Rappsilber; Ursula Ryder; Angus I Lamond; Matthias Mann
Journal:  Genome Res       Date:  2002-08       Impact factor: 9.043

2.  Absolute quantification of proteins by LCMSE: a virtue of parallel MS acquisition.

Authors:  Jeffrey C Silva; Marc V Gorenstein; Guo-Zhong Li; Johannes P C Vissers; Scott J Geromanos
Journal:  Mol Cell Proteomics       Date:  2005-10-11       Impact factor: 5.911

3.  Exponentially modified protein abundance index (emPAI) for estimation of absolute protein amount in proteomics by the number of sequenced peptides per protein.

Authors:  Yasushi Ishihama; Yoshiya Oda; Tsuyoshi Tabata; Toshitaka Sato; Takeshi Nagasu; Juri Rappsilber; Matthias Mann
Journal:  Mol Cell Proteomics       Date:  2005-06-14       Impact factor: 5.911

4.  A practical recipe for stable isotope labeling by amino acids in cell culture (SILAC).

Authors:  Shao-En Ong; Matthias Mann
Journal:  Nat Protoc       Date:  2006       Impact factor: 13.491

5.  Quantitative analysis of complex protein mixtures using isotope-coded affinity tags.

Authors:  S P Gygi; B Rist; S A Gerber; F Turecek; M H Gelb; R Aebersold
Journal:  Nat Biotechnol       Date:  1999-10       Impact factor: 54.908

6.  Modulation and compensation of the mRNA expression of energy related transporters in the brain of glucose transporter 1-deficient mice.

Authors:  Sumio Ohtsuki; Tazuru Kikkawa; Satoko Hori; Tetsuya Terasaki
Journal:  Biol Pharm Bull       Date:  2006-08       Impact factor: 2.233

7.  Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents.

Authors:  Philip L Ross; Yulin N Huang; Jason N Marchese; Brian Williamson; Kenneth Parker; Stephen Hattan; Nikita Khainovski; Sasi Pillai; Subhakar Dey; Scott Daniels; Subhasish Purkayastha; Peter Juhasz; Stephen Martin; Michael Bartlet-Jones; Feng He; Allan Jacobson; Darryl J Pappin
Journal:  Mol Cell Proteomics       Date:  2004-09-22       Impact factor: 5.911

8.  Quantitative atlas of membrane transporter proteins: development and application of a highly sensitive simultaneous LC/MS/MS method combined with novel in-silico peptide selection criteria.

Authors:  Junichi Kamiie; Sumio Ohtsuki; Ryo Iwase; Ken Ohmine; Yuki Katsukura; Kazunari Yanai; Yumi Sekine; Yasuo Uchida; Shingo Ito; Tetsuya Terasaki
Journal:  Pharm Res       Date:  2008-06       Impact factor: 4.200

9.  Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.

Authors:  Shao-En Ong; Blagoy Blagoev; Irina Kratchmarova; Dan Bach Kristensen; Hanno Steen; Akhilesh Pandey; Matthias Mann
Journal:  Mol Cell Proteomics       Date:  2002-05       Impact factor: 5.911

10.  Equivalence of protein inventories obtained from formalin-fixed paraffin-embedded and frozen tissue in multidimensional liquid chromatography-tandem mass spectrometry shotgun proteomic analysis.

Authors:  Robert W Sprung; Jonathan W C Brock; Jarred P Tanksley; Ming Li; Mary Kay Washington; Robbert J C Slebos; Daniel C Liebler
Journal:  Mol Cell Proteomics       Date:  2009-05-24       Impact factor: 5.911

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  26 in total

1.  Parameterization of Microsomal and Cytosolic Scaling Factors: Methodological and Biological Considerations for Scalar Derivation and Validation.

Authors:  Michael J Doerksen; Robert S Jones; Michael W H Coughtrie; Abby C Collier
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2020-12-19       Impact factor: 2.441

2.  Comparative Proteomics Analysis of Human Liver Microsomes and S9 Fractions.

Authors:  Xinwen Wang; Bing He; Jian Shi; Qian Li; Hao-Jie Zhu
Journal:  Drug Metab Dispos       Date:  2019-11-07       Impact factor: 3.922

3.  Prediction of Drug Clearance from Enzyme and Transporter Kinetics.

Authors:  Priyanka R Kulkarni; Amir S Youssef; Aneesh A Argikar
Journal:  Methods Mol Biol       Date:  2021

4.  Quantification of Neonatal Fc Receptor and Beta-2 Microglobulin in Human Liver Tissues by Ultraperformance Liquid Chromatography-Multiple Reaction Monitoring-based Targeted Quantitative Proteomics for Applications in Biotherapeutic Physiologically-based Pharmacokinetic Models.

Authors:  Xiazi Qiu; Michael Zhuo Wang
Journal:  Drug Metab Dispos       Date:  2020-07-28       Impact factor: 3.922

5.  Extracellular Vesicles as Drug Delivery System for Treatment of Neurodegenerative Disorders: Optimization of the Cell Source.

Authors:  Matthew J Haney; Yuling Zhao; John K Fallon; Wang Yue; Samuel M Li; Emily E Lentz; Dorothy Erie; Philip C Smith; Elena V Batrakova
Journal:  Adv Nanobiomed Res       Date:  2021-06-29

6.  Human Hepatic Transporter Signature Peptides for Quantitative Targeted Absolute Proteomics: Selection, Digestion Efficiency, and Peptide Stability.

Authors:  Ayano Mori; Takeshi Masuda; Shingo Ito; Sumio Ohtsuki
Journal:  Pharm Res       Date:  2022-09-21       Impact factor: 4.580

7.  Furmonertinib (Alflutinib, AST2818) is a potential positive control drug comparable to rifampin for evaluation of CYP3A4 induction in sandwich-cultured primary human hepatocytes.

Authors:  Ya-Li Wu; Ya-Ru Xue; Zi-Tao Guo; Zhen-Dong Chen; Xin-Yu Ge; Da-Fang Zhong; Xing-Xing Diao
Journal:  Acta Pharmacol Sin       Date:  2021-05-25       Impact factor: 6.150

8.  Differential Detergent Fractionation of Membrane Protein From Small Samples of Hepatocytes and Liver Tissue for Quantitative Proteomic Analysis of Drug Metabolizing Enzymes and Transporters.

Authors:  Rani J Qasem; John K Fallon; Manisha Nautiyal; Merrie Mosedale; Philip C Smith
Journal:  J Pharm Sci       Date:  2020-10-22       Impact factor: 3.534

9.  Interindividual Variability and Differential Tissue Abundance of Mitochondrial Amidoxime Reducing Component Enzymes in Humans.

Authors:  Deepak Ahire; Abdul Basit; Lisa J Christopher; Ramaswamy Iyer; J Steven Leeder; Bhagwat Prasad
Journal:  Drug Metab Dispos       Date:  2021-12-23       Impact factor: 3.922

10.  Hepatic Transporter Alterations by Nuclear Receptor Agonist T0901317 in Sandwich-Cultured Human Hepatocytes: Proteomic Analysis and PBPK Modeling to Evaluate Drug-Drug Interaction Risk.

Authors:  Katsuaki Ito; Noora Sjöstedt; Melina M Malinen; Cen Guo; Kim L R Brouwer
Journal:  J Pharmacol Exp Ther       Date:  2020-03-03       Impact factor: 4.030

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