news
hPDQ: pretty darn quick generation of verification assays? The discovery of new potential biomarkers is at the forefront of most proteomics researchers’ minds, but a group of well-known proteomics scientists say that the time is right to start evaluating some of the thousands of candidates that already have been reported. However, one problem is that few specific assays for biomarker verification exist. So, Leigh Anderson, who is at the Plasma Proteome Institute, and colleagues at various institutions in the U.S., Canada, and Switzerland have proposed the Human Proteome Detection and Quantitation project (hPDQ) to shift the development of verification assays into high gear. In a recent paper, the researchers outline how such a project could be undertaken (Mol. Cell. Proteomics 2009, DOI 10.1074/mcp.R800015-MCP200). “We have not been generating real clinical biomarkers out of proteomics to date, and now it’s time to do it,” says Anderson. He adds that the application of biomarker assays for the diagnosis of illnesses is the most costeffective way to improve the health care system because these assays can be automated. Also, early diagnoses can obviate the need for expensive treatments. However, “if there aren’t any new biomarkers out there, we need to prove that and then go on to something else,” he explains. “Personally, I believe there will be lots of useful biomarkers, but we need now to find them and not just hypothesize their existence.” The idea for hPDQ grew out of a large collaboration funded by the U.S. National Cancer Institute’s Clinical Proteomic Technologies Assessment for Cancer (CPTAC) program. One of the CPTAC projects was focused on further developing and evaluating specific assays for candidate biomarkers, including the assay known as stable-isotope standards with capture by antipeptide antibodies (SISCAPA). Anderson worked with several investigators, including Steve Carr, who is at the Broad Institute and who was the principal
10.1021/pr9001564
2009 American Chemical Society
investigator of the project. This experience “led us to think about what would be necessary to implement this technology to measure a significantly large number of candidate biomarkers and get the job donesactually go in and determine which ones are effective as biomarkers,” he states. Enter hPDQ. “The obvious follow-on if SISCAPA works as well as our studies suggest it does is to figure out a way to enable the broader clinical research community to apply this method,” says Anderson. The stated goal of hPDQ is to detect proteins with a sensitivity of 1 ng/mL and absolute specificity for large clinical sample sets (∼500-5000 samples). Of course, the gold-standard verification assay is the ELISA. However, the researchers say that SISCAPA (and the similar technique called iMALDI) is much more specific, easier to multiplex, and less costly to produce than ELISAs after an initial investment in a triple-quadrupole mass spectrometer. With SISCAPA, a protein is digested into peptides. A peptide-specific antibody pulls the peptide of interest out from the background of hundreds of thousands of other peptides that could be in the original sample. The peptide is ionized, and its m/z is selected in the first mass filter. Then the peptide is fragmented, and the m/z of one of those fragments is selected and monitored. Thus, the mass spectrometer is reminiscent of the second antibody in an ELISA, but with SISCAPA, a researcher obtains information at two m/z values; this provides two dimensions of specificity, according to Anderson. In addition, a synthetic, stableisotope-labeled version of the peptide can be spiked into the mass spectrometer for quantitation. To bring MS-based immunoassays to the masses, four resources are required, say the researchers. These resources include a database of proteotypic peptides (those peptides that are unique to one protein), two or more synthetic stable-isotope-labeled peptides for each protein, antipeptide antibodies against the proteotypic peptides, and robust mass spectrometers for quantitation.
Anderson notes that most of these tools ultimately should be produced commercially. “I think the major involvement of the research community will be as users of these reagents,” he says. “The purpose of this is not so much to involve all the proteomics labs in assay development as it is to generate a series of reagents that enable all the labs to easily measure all these proteins very accurately in whatever samples they want.” Therefore, hPDQ is not meant to compete for finances and labor with such efforts as HUPO’s Human Proteome Project (HPP), which aims to catalog at least one protein product from every human gene. Anderson points out that hPDQ could help HPP by translating that project’s discoveries to the clinic. In fact, the SISCAPA assay could even be the clinical test for a biomarker. He says that the economics may not yet favor such an implementation, but SISCAPA could perform better than an ELISA in cases in which interferences are observed. The researchers propose starting with a pilot project that aims to develop MS-based immunoassays for ∼10% of the proteins in human plasma. Eventually, the project would be expanded to cover protein products from all human genes. No funding has been announced yet for hPDQ, but Anderson says that the group has had discussions with CPTAC representatives. The main goal right now is to get feedback from the research community, Anderson explains. He hopes to find out whether proteomics scientists agree that biomarker verification is a limiting factor for bringing markers to the clinic. Also, he would like to know whether researchers think this is the best method for the verification of biomarkers. Finally, he is interested in how important biomarkers are to the community. “A lot of discussion needs to occur to decide where we put the resources to get to the clinical answer,” he says. —Katie Cottingham
Journal of Proteome Research • Vol. 8, No. 4, 2009 1621
