Physical Characterization of the 'Immunosignaturing Effect'

The effort to make medicine preventative should include the development of systems to detect disease before the appearance of major symptoms. The value of early detection is widely accepted and has been the spur to develop new biomarkers of disease that enable earlier diagnosis and treatment. Over 100,000 biomarkers have been reported in the literature to date 1 yet there are only 43 approved by the FDA 2 including 19 genomic markers 3. This low return on investment for biomarker discovery suggests that new approaches are needed. Here we characterize a method that has been proposed as an alternative strategy for biomarker discovery. Discovery of biomarkers for early diagnosis of disease poses exceptional demands. For example, in the case of cancer, in order to detect the small number of cells in an early tumor one has to overcome the blood dilution problem. For example, if 106 initiating cancer cells release 1000 molecules each of a biomarker into five liters of blood at steady state, the concentration of this biomarker would only be 3 × 10−14 m. Clearly, it would be an advantage if the response to the biomarker could be amplified. Antibodies are ideal in this sense. An activated B cell produces 5000–20,000 antibodies per minute 4, 5 and the cell itself replicates every ∼70 h 6 with a lifespan of up to 4 ½ months 7, 8 leading to ∼1011 amplification of a specific signal in 1 week. Unpurified antibodies are stable in blood, unlike other biomarkers, opening up the possibility of testing historical samples 9. There are three key issues relative to using antibodies as biomarkers of early disease. Do they respond to diseases other than infections? Do they respond early in the course of disease? Can these antibodies be identified with a simple and inexpensive detection system? There are reports in diabetes 10, arthritis 11, and cancer 12 that the humoral response is activated specifically and early in these chronic diseases. A number of autoantibodies have been identified that appear months or years before the disease is first diagnosed 13–15. In the case of Type I diabetes, antibodies against GAD, IA2 and insulin are found in various combinations well before the onset of clinical disease 16. In patients with paraneoplastic syndrome, specific neurological symptoms appear years before a cancer is detected 17–19. The immune response to the nascent tumor reacts with neurons to elicit neurological symptoms 20 that correlate with future tumor appearance. These examples for cancer, diabetes and arthritis also address the second issue: is there an immune response among different individuals that appears early in patients with the same disease? The fact that the same autoantigens, or symptoms in the case of paraneoplastic syndrome, commonly occur indicates that antibodies might also be consistent across patients. The third issue, and the one we address here, is how to detect the informative antibodies in an efficient and simple way. Most antibody biomarkers were the product of arduous research. Protein microarrays have facilitated this process 21 by immobilizing most of the proteins from a pathogen or human onto a glass slide, but these arrays are expensive, exclude non-transcribed antigens, and are pathogen or auto-antibody specific. The ProtoArrayTM v5 of Invitrogen currently has ∼9000 unique human proteins; these can detect autoantigens associated with a specific disease. However, only autoantigens can be discovered and the cost impedes epidemiology-sized studies. A more complicated approach has been to biochemically fractionated cellular proteins, spot and then react these fractions with patient sera 22. Although this method does use authentic material, it is limited by having no control over the relative amounts of proteins spotted, and it requires cells from the case subjects' own tissue. Screening for antibody reactivity to random peptides has been generally successful when using phage or mRNA display of random 8–12 amino acid sequences. Pasqualini and Ruosiahti 23 panned a phage library against sera from cancer and healthy subjects to find phage that were preferentially bound by the cancer associated antibodies. This method is unbiased as to the nature of the antigen, and the antibody can eventually be captured (if arduously). Given that random sequence peptides can yield mimotopes of almost any type of antigen 24, any disease-associated antigen could theoretically be detected. However promising this method appeared, to date this approach has not produced disease biomarkers for a number of reasons. A serious limitation is that the recurrent panning of the phage is subject to many influences besides just binding of the antibody, it does not lend itself to large numbers of samples, and there is no simple way to measure intermediate or low binding. In order to discover and display relevant antibodies contained in the 1010 antibody complexity in humans, we explored a technology (PCT/US2010/039269, “Compound Arrays for Sample Profiling”) for antibody biomarker discovery that combines simple, rapid and inexpensive assays from microarrays with the enhanced breadth of the ligand repertoire found in phage-based systems. We created microarrays with only 10,000 random sequence peptides but chose a relatively long length (17 amino acids + 3 residue linker) to allow each peptide to encompass much more complexity than typical epitope peptides. The random sequences allow an unbiased display of antibody binding; the length provides many possible epitope positions per peptide and (potentially) allows for some structural complexity. The array format allows the assay to be run without the biological complications of phage display and high-speed piezo printing onto commercially produced substrate allows thousands of microarrays to be consistently produced each month. We recently demonstrated the potential utility of these arrays by immunosignaturing vaccines, infections, and Alzheimer's disease 25,26. In order to utilize this technology as a clinical diagnostic, we must first characterize the physical and chemical properties of antibody binding to these peptide microarrays.