A targeted proteomics–based pipeline for verification of biomarkers in plasma

• Published in: Nature biotechnology Vol. 29; no. 7; pp. 625 - 634
• Main Authors: Whiteaker, Jeffrey R, Lin, Chenwei, Kennedy, Jacob, Hou, Liming, Trute, Mary, Sokal, Izabela, Yan, Ping, Schoenherr, Regine M, Zhao, Lei, Voytovich, Uliana J, Kelly-Spratt, Karen S, Krasnoselsky, Alexei, Gafken, Philip R, Hogan, Jason M, Jones, Lisa A, Wang, Pei, Amon, Lynn, Chodosh, Lewis A, Nelson, Peter S, McIntosh, Martin W, Kemp, Christopher J, Paulovich, Amanda G
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.07.2011; Nature Publishing Group
• Subjects: 631/61/475; 692/308/1892; 692/699/67/1347; Agriculture; Animals; Bioassays; Bioinformatics; Biological and medical sciences; Biological markers; Biomarkers; Biomarkers, Tumor - blood; Biomedical Engineering/Biotechnology; Biomedicine; Biotechnology; Blood Chemical Analysis - methods; Breast cancer; Fundamental and applied biological sciences. Psychology; Health. Pharmaceutical industry; Industrial applications and implications. Economical aspects; Life Sciences; Mass spectrometry; Mass Spectrometry - methods; Mice; Miscellaneous; Neoplasm Proteins - blood; Neoplasms, Experimental - blood; Peptide Mapping - methods; Physiological aspects; Plasma; Proteins; Proteome - analysis; Proteomics; Proteomics - methods; United States; Human; Animal model; Targeting; Rodentia; Biological marker; Identification; Protein; Research and development; Pipeline; Blood plasma; Vertebrata; Mammalia; Mouse; Proteomics; Mass spectrometry; Cancer
• ISSN: 1087-0156; 1546-1696; 1546-1696
• DOI: 10.1038/nbt.1900

Prioritizing candidate biomarkers for verification remains a formidable obstacle to the translation of protein diagnostics to clinical applications. Whiteaker et al . assemble a multistage, targeted proteomics pipeline to relieve this bottleneck and use a mouse cancer model to demonstrate its analytical performance. High-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical studies. We tested whether the analytical performance of a biomarker identification pipeline based on targeted mass spectrometry would be sufficient for data-dependent prioritization of candidate biomarkers, de novo development of assays and multiplexed biomarker verification. We used a data-dependent triage process to prioritize a subset of putative plasma biomarkers from >1,000 candidates previously identified using a mouse model of breast cancer. Eighty-eight novel quantitative assays based on selected reaction monitoring mass spectrometry were developed, multiplexed and evaluated in 80 plasma samples. Thirty-six proteins were verified as being elevated in the plasma of tumor-bearing animals. The analytical performance of this pipeline suggests that it should support the use of an analogous approach with human samples.