Protein biomarker discovery and validation: the long and uncertain path to clinical utility
Abstract
Better biomarkers are urgently needed to improve diagnosis, guide molecularly targeted therapy and monitor activity and therapeutic response across a wide spectrum of disease. Proteomics methods based on mass spectrometry hold special promise for the discovery of novel biomarkers that might form the foundation for new clinical blood tests, but to date their contribution to the diagnostic armamentarium has been disappointing. This is due in part to the lack of a coherent pipeline connecting marker discovery with well-established methods for validation. Advances in methods and technology now enable construction of a comprehensive biomarker pipeline from six essential process components: candidate discovery, qualification, verification, research assay optimization, biomarker validation and commercialization. Better understanding of the overall process of biomarker discovery and validation and of the challenges and strategies inherent in each phase should improve experimental study design, in turn increasing the efficiency of biomarker development and facilitating the delivery and deployment of novel clinical tests.
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MS detection of low-abundance proteins from blood remains an unsolved challenge due to the extraordinary dynamic range of the blood proteome.
“However, the MS detection of low-abundance proteins remains an unsolved challenge due to high dynamic range of the human proteome8–10.”
From Nanoproteomics enables proteoform-resolved analysis of low-abundance proteins in human serum (2020) · cites this paper as [9]
Front-end protein enrichment strategies are required to specifically capture and enrich low-abundance proteins from complex biological milieu prior to MS analysis.
“Front-end protein enrichment strategies are therefore required to specifically capture and enrich low-abundance proteins from the complex biological milieu prior to MS analysis9,11.”
From Nanoproteomics enables proteoform-resolved analysis of low-abundance proteins in human serum (2020) · cites this paper as [9]
The human blood proteome has a huge dynamic range (~10^12) dominated by highly abundant proteins such as human serum albumin (HSA), making detection of low-abundance proteins extremely difficult.
“In particular, the human blood proteome, a circulating representation of all pathophysiological processes, is immensely complex and the huge dynamic range of the blood proteome (1012) dominated by the presence of numerous highly abundant proteins, such as human serum albumin (HSA), makes the detection of low-abundance proteins extremely difficult9,10.”
From Nanoproteomics enables proteoform-resolved analysis of low-abundance proteins in human serum (2020) · cites this paper as [9]
Additional sources of uncertainty may arise from processes such as protein quantification in bottom-up proteomics because measurements are made at the peptide level and isoforms can be difficult to identify.
“additional sources of uncertainty may arise from processes such as protein quantification in bottom-up proteomics (Rifai et al., 2006; Plubell et al., 2022) as measurements are made at the peptide level and isoforms can be difficult to identify (Forshed et al., 2011; Webb-Robertson et al., 2014).”
From Missing data in multi-omics integration: Recent advances through artificial intelligence (2023) · cites this paper as Rifai et al., 2006
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Early Detection of Ovarian Cancer
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Self-citationLarge-scale serum protein biomarker discovery in Duchenne muscular dystrophy
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Self-citationSelected reaction monitoring applied to proteomics
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Self-citationReproducible Quantification of Cancer-Associated Proteins in Body Fluids Using Targeted Proteomics
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Self-citationAdvancing the sensitivity of selected reaction monitoring‐based targeted quantitative proteomics
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Surface plasmon resonance applications in clinical analysis
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Self-citationBreaking the concentration limit of optical single-molecule detection
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Risk Prediction With Procalcitonin and Clinical Rules in Community-Acquired Pneumonia
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- Authors
- Rifai, N., Gillette, M. A., & Carr, S. A.
- Affiliations
- Boston Children's Hospital (US)
- Broad Institute (US)
- Corresponding author
- Carr, Steven A
- Venue
- Nature Biotechnology
- Published
- 2006-08
- Volume
- 24
- Issue
- 8
- Pages
- 971-983
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- OpenAlex
- W2094229819
- Cited by
- 1,867
- References
- 118
- Citations by year
- 2026: 56 · 2025: 70 · 2024: 75 · 2023: 66 · 2022: 69 · 2021: 85 · 2020: 74 · 2019: 88 · 2018: 91 · 2017: 96 · 2016: 99 · 2015: 130 · 2014: 131 · 2013: 116 · 2012: 138
- FWCI
- 7.25
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced Biosensing Techniques and Applications
- Life Sciences › Immunology and Microbiology › Immunology › Biomarkers in Disease Mechanisms
- Keywords
- protein biomarkers, biomarker discovery, biomarker validation, mass spectrometry-based proteomics, diagnostic biomarkers, biomarker qualification, research design
- MeSH terms
- Animals, Blood Chemical Analysis, Blood Proteins, Humans, Peptide Mapping, Sensitivity and Specificity, Mass Spectrometry, Biomarkers, Protein Array Analysis
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