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Oct 1, 2011 (Vol. 31, No. 17)

Proteomics: Pathways and Biomarkers

As Technical Barriers Fall, the Role of Proteins in Clinical Medicine Is Being Transformed

  • Sensitivity

    Until recently, what remained a challenge for MRM was sensitivity, particularly in the measurement of low-abundance biomarkers in plasma or serum. With MRM supplying the specificity and quantitation, antibody affinity for enrichment re-entered the picture. Targeted analytes, either proteins or unique “proteotypic” peptides derived from them by tryptic digestion, can be captured by specific antibodies from larger amounts of sample than the mass spectrometer can otherwise ingest. These enriched analytes are simultaneously “cleaned up” allowing shorter LC cycle times and higher throughput.

    This approach, called SISCAPA (for stable isotope standards and capture by antipeptide antibodies), when applied at the peptide level, provides a general platform for rapid biomarker assay development and has been proposed as a means to provide quantitation of the entire human baseline proteome (the hPDQ project).

    SISCAPA may shortly play a role in the clinical laboratory as well, as shown in Hoofnagle’s work on the thyroglobulin assay, where tryptic digestion removes most of the sources of interference that plague this clinical immunoassay (and many others).

    By isolating low abundance target peptides to a state of near purity, and thus no longer requiring extensive LC separation prior to MS, very high throughput can be achieved (12–60 samples per hour) at sensitivities reaching below 1 ng/mL in the case of a protein in plasma.

    Further gains in sensitivity occur with each improvement in mass spectrometer design (e.g., the recent introduction of ion funnel technology), suggesting that within two to four years MS-based assays will equal the best current immunoassays while using only 10 μL of plasma for up to 50 analytes.

  • Translation

    These developments presage major positive changes in the role of proteins in clinical medicine. Today, a newly discovered protein biomarker candidate languishes in the pages of a journal until someone finds funding to create a relatively crude immunoassay. Then, if two or three clinical studies show promise, one of the IVD companies that control hospital analyzer platforms may embark on an effort to develop an FDA-approvable immunoassay through a process that can take two to four years and cost $3–5 million per protein. The entire process, in the rare success cases, takes a decade or more.

    However a much more rational alternative path is emerging based on the ability of automated affinity-MS platforms to simultaneously fill roles in Type 2 biomarker research, clinical evaluation of candidates, and finally, in the clinical lab itself. Common instrument platforms justify greater investments in performance and automation and, ultimately, lower cost per result.

    Current evidence supports the notion that the same assay reagents (antibodies and internal standards) may also suffice from research to clinic, albeit with increasing levels of quality and regulatory documentation.

    Thus, the technical barriers limiting translation of candidate biomarkers can be radically reduced, and several disconnected steps of the current process removed. With these improvements, and assuming the availability of stored samples appropriate to the specific clinical questions at hand, it will be feasible to test thousands of candidate biomarkers, and to translate the successes into clinical use in something on the order of five years.

    Of even greater long-term significance is the change this could bring about in the economics of healthcare. MS-based analysis provides a very low incremental cost per protein analyte once a sample is in process, as opposed to testing of each protein in separate aliquots in current clinical-quality immunoassay instruments. This paradigm change makes the development of multiplex tests more practical and less expensive, opening the way to successful tests for more complex and heterogeneous diseases including cancer.

    The positive economic impact of early disease detection at reasonable cost is enormous, and justifies substantial efforts to re-engineer our currently unproductive biomarker pipeline.


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