ArticleClinical proteomics2015
An integrated quantification method to increase the precision, robustness, and resolution of protein measurement in human plasma samples.
Article in Clinical proteomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Use of a Novel Whole Blood Separation and Transport Device for Targeted and Untargeted Proteomics.Biomedicines · 2024Article
- Design and Characterization of a Novel Blood Collection and Transportation Device for Proteomic Applications.Diagnostics (Basel, Switzerland) · 2020Article
- Extending the information content of the MALDI analysis of biological fluids via multi-million shot analysis.PloS one · 2019Article
- Analytical validation of protein biomarkers for risk of spontaneous preterm birth.Clinical mass spectrometry (Del Mar, Calif.) · 2017Article
- An integrated risk predictor for pulmonary nodules.PloS one · 2017Article
- Plasma degradome affected by variable storage of human blood.Clinical proteomics · 2016Article
- Observational
- Validation of a multiprotein plasma classifier to identify benign lung nodules.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2015Article
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11 authors.
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Abstract
backgroundCurrent 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.
resultsWe 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.
conclusionsWe 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.
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