uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Variability in Mass Spectrometry-based Quantification of Clinically Relevant Drug Transporters and Drug Metabolizing Enzymes
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmacy. AstraZeneca R&D, Innovat Med & Early Dev Biotech Unit, Cardiovasc & Metab Dis, S-43150 Molndal, Sweden..ORCID iD: 0000-0002-2810-7518
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmacy.
AstraZeneca R&D, Innovat Med & Early Dev Biotech Unit, Cardiovasc & Metab Dis, S-43150 Molndal, Sweden..
Max Planck Inst Biochem, Dept Prote & Signal Transduct, Biochem Prote Grp, D-82152 Martinsried, Germany..
Show others and affiliations
2017 (English)In: Molecular Pharmaceutics, ISSN 1543-8384, E-ISSN 1543-8392, Vol. 14, no 9, p. 3142-3151Article in journal (Refereed) Published
Abstract [en]

Many different methods are used for mass-spectrometry-based protein quantification in pharmacokinetics and systems pharmacology. It has not been established to what extent the results from these various methods are comparable. Here, we compared six different mass spectrometry-based proteomics methods by measuring the expression of clinically relevant drug transporters and metabolizing enzymes in human liver. Mean protein concentrations were in general quantified to similar levels by methods using whole tissue lysates. Methods using subcellular membrane fractionation gave incomplete enrichment of the proteins. When the enriched proteins were adjusted to levels in whole tissue lysates, they were on average 4 fold lower than those quantified directly in whole tissue lysates. The differences in protein levels were propagated into differences in predictions of hepatic clearance. In conclusion, caution is needed when comparing and applying quantitative proteomics data obtained with different methods, especially since membrane fractionation is common practice for protein quantification used in drug clearance predictions.

Place, publisher, year, edition, pages
AMER CHEMICAL SOC , 2017. Vol. 14, no 9, p. 3142-3151
Keywords [en]
drug transporters, drug metabolizing enzymes, membrane proteins, protein quantification, targeted proteomics, label-free proteomics
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-335414DOI: 10.1021/acs.molpharmaceut.7b00364ISI: 000410005100027PubMedID: 28767254OAI: oai:DiVA.org:uu-335414DiVA, id: diva2:1163146
Funder
Swedish Research Council, 2822, 5715Available from: 2017-12-06 Created: 2017-12-06 Last updated: 2019-07-26Bibliographically approved
In thesis
1. Proteomics-informed analysis of drug disposition in the human liver and small intestine
Open this publication in new window or tab >>Proteomics-informed analysis of drug disposition in the human liver and small intestine
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Orally administered drugs are absorbed in the intestine and generally metabolized in the liver. Therefore, understanding factors determining drug distribution and elimination in these tissues is important. This thesis aimed at using mass spectrometry (MS)-based proteomics and functional studies to better understand in vitro model systems used for drug clearance predictions. Further, it aimed at understanding the changes in drug disposition caused by obesity and gastric bypass surgery (GBP).

The study was initiated by investigating factors influencing MS-based protein quantification by comparing results from different proteomics methods, and by studying protein distribution during subcellular fractionation. The largest variability in protein quantification was ascribed to insufficient enrichment from subcellular fractionation, most likely due to collection of the majority of the proteins in the initial fraction of the fractionation protocols.

Proteomics and metabolic activity analyses were then used to investigate differences in intrinsic clearance from two commonly used in vitro systems, human liver microsomes and hepatocytes. For some compounds, the faster microsomal metabolism could be explained by a higher available unbound drug concentration and CYP content in the microsomes as compared to in the hepatocytes.

Next, inter-individual protein expression variability in human liver and jejunum was explored. This showed that proteins covered a wide inter-individual variability spectrum, in which proteins with low variabilities were associated with essential cellular functions, while many proteins with high variabilities were disease-related.

Further, the effects of obesity, GBP, and weight loss on the proteomes of human liver and jejunum were analyzed. After GBP and subsequent weight loss, patients showed lower levels of jejunal proteins involved in inflammatory response and drug metabolism.

Finally, proteomics data from patients with and without obesity was combined with parameters from in vitro transport kinetics, and a mechanistic model to predict drug disposition was developed. The model successfully predicted rosuvastatin plasma concentrations in the patients.

In conclusion, this thesis has provided insights into factors influencing protein quantification and function in vitro. Furthermore, this thesis demonstrates how proteomics contributes to improved understanding of inter-individual and physiological differences, and how it can be used for in vitro-in vivo scaling of drug clearance.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2019. p. 79
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 273
Keywords
proteomics, protein concentration, drug disposition, drug transport, drug metabolism, human small intestine, human liver, human hepatocytes, human liver microsomes, inter-individual variability, drug clearance, obesity, prediction model
National Category
Pharmaceutical Sciences
Research subject
Pharmaceutical Science
Identifiers
urn:nbn:se:uu:diva-389741 (URN)978-91-513-0694-0 (ISBN)
Public defence
2019-09-13, B42, Biomedical center, Husargatan 3, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2019-08-22 Created: 2019-07-26 Last updated: 2019-08-22

Open Access in DiVA

fulltext(3371 kB)104 downloads
File information
File name FULLTEXT01.pdfFile size 3371 kBChecksum SHA-512
9a27024d2584faf89b439fd25b9078d54cbfc3d454c22815d7a8a7dba333b2e6e900e0fa464986af08c4a28bb3a4c5795741e1edb36b38251104a20b16ece18e
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMed

Authority records BETA

Wegler, ChristineNorén, AgnetaArtursson, Per

Search in DiVA

By author/editor
Wegler, ChristineNorén, AgnetaArtursson, Per
By organisation
Department of PharmacyUpper Abdominal Surgery
In the same journal
Molecular Pharmaceutics
Pharmaceutical Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 104 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 122 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf