An integrated quantification method to increase the precision, robustness, and resolution of protein measurement in human plasma samples

Clinical Proteomics

Douglas Spicer¹  Xiao-jun Li¹  JoAnne Mulligan¹  Matthew McLean³  Paul Kearney¹  Mi-Youn Brusniak²  Stephen W Hunsucker¹  Kenneth C Fang¹  Lik Wee Lee¹  Clive Hayward¹  Pui-Yee Fong¹ 

[1]Integrated Diagnostics, Seattle, USAIntegrated Diagnostics, Seattle, USAIntegrated Diagnostics, Seattle, USA

[2]Integrated Diagnostics, Seattle, USAFred Hutchinson Cancer Research Center, Seattle, USAIntegrated Diagnostics, Seattle, USAIntegrated Diagnostics, Seattle, USAFred Hutchinson Cancer Research Center, Seattle, USAFred Hutchinson Cancer Research Center, Seattle, USAIntegrated Diagnostics, Seattle, USAFred Hutchinson Cancer Research Center, Seattle, USA

[3]Integrated Diagnostics, Seattle, USADuPont Industrial Biosciences, Alto, USAIntegrated Diagnostics, Seattle, USAIntegrated Diagnostics, Seattle, USADuPont Industrial Biosciences, Alto, USADuPont Industrial Biosciences, Alto, USAIntegrated Diagnostics, Seattle, USADuPont Industrial Biosciences, Alto, USA

关键词: Multiple reaction monitoring;    Plasma or serum analysis;    Quantitative proteomics;    Clinical proteomics;    Mass spectrometry;    Immunoaffinity depletion;    Bioinformatics;   

DOI  :  10.1186/1559-0275-12-3

来源: Humana Press Inc

【 摘 要 】

Abstract

Background

Current quantification methods for mass spectrometry (MS)-based proteomics either do not provide sufficient control of variability or are difficult to implement for routine clinical testing.

Results

We present here an integrated quantification (InteQuan) method that better controls pre-analytical and analytical variability than the popular quantification method using stable isotope-labeled standard peptides (SISQuan). We quantified 16 lung cancer biomarker candidates in human plasma samples in three assessment studies, using immunoaffinity depletion coupled with multiple reaction monitoring (MRM) MS. InteQuan outperformed SISQuan in precision in all three studies and tolerated a two-fold difference in sample loading. The three studies lasted over six months and encountered major changes in experimental settings. Nevertheless, plasma proteins in low ng/ml to low μg/ml concentrations were measured with a median technical coefficient of variation (CV) of 11.9% using InteQuan. The corresponding median CV using SISQuan was 15.3% after linear fitting. Furthermore, InteQuan surpassed SISQuan in measuring biological difference among clinical samples and in distinguishing benign versus cancer plasma samples.

Conclusions

We demonstrated that InteQuan is a simple yet robust quantification method for MS-based quantitative proteomics, especially for applications in biomarker research and in routine clinical testing.

【 授权许可】

Unknown