title: Immunosignature system for diagnosis of cancer.
abstract: Although the search for disease biomarkers continues, the clinical return has thus far been disappointing. The complexity of the body's response to disease makes it difficult to represent this response with only a few biomarkers, particularly when many are present at low levels. An alternative to the typical reductionist biomarker paradigm is an assay we call an "immunosignature." This approach leverages the response of antibodies to disease-related changes, as well as the inherent signal amplification associated with antigen-stimulated B-cell proliferation. To perform an immunosignature assay, the antibodies in diluted blood are incubated with a microarray of thousands of random sequence peptides. The pattern of binding to these peptides is the immunosignature. Because the peptide sequences are completely random, the assay is effectively disease-agnostic, potentially providing a comprehensive diagnostic on multiple diseases simultaneously. To explore the ability of an immunosignature to detect and identify multiple diseases simultaneously, 20 samples from each of five cancer cohorts collected from multiple sites and 20 noncancer samples (120 total) were used as a training set to develop a reference immunosignature. A blinded evaluation of 120 blinded samples covering the same diseases gave 95% classification accuracy. To investigate the breadth of the approach and test sensitivity to biological diversity further, immunosignatures of >1,500 historical samples comprising 14 different diseases were examined by training with 75% of the samples and testing the remaining 25%. The average accuracy was >98%. These results demonstrate the potential power of the immunosignature approach in the accurate, simultaneous classification of disease.
authors.affiliation: Center for Innovations in Medicine, The Biodesign Institute, Arizona State University, Tempe, AZ 85287-5901 phillip.stafford@asu.edu.
authors.forename: Phillip
authors.initials: P
authors.lastname: Stafford
authors.affiliation: Center for Innovations in Medicine, The Biodesign Institute, Arizona State University, Tempe, AZ 85287-5901.
authors.forename: Zbigniew
authors.initials: Z
authors.lastname: Cichacz
authors.affiliation: Center for Innovations in Medicine, The Biodesign Institute, Arizona State University, Tempe, AZ 85287-5901.
authors.forename: Neal W
authors.initials: NW
authors.lastname: Woodbury
authors.affiliation: Center for Innovations in Medicine, The Biodesign Institute, Arizona State University, Tempe, AZ 85287-5901.
authors.forename: Stephen Albert
authors.initials: SA
authors.lastname: Johnston
mesh_terms: D000912:Antibodies, Neoplasm / Q000097:blood* / Q000276:immunology; D000951:Antigens, Neoplasm / Q000737:chemistry* / Q000276:immunology; D014408:Biomarkers, Tumor / Q000097:blood* / Q000276:immunology; D005260:Female; D006801:Humans; D007159:Immunologic Tests / Q000295:instrumentation / Q000379:methods; D008297:Male; D009369:Neoplasms / Q000097:blood* / Q000175:diagnosis* / Q000276:immunology; D040081:Protein Array Analysis / Q000379:methods
chemical_list: D000912:Antibodies, Neoplasm; D000951:Antigens, Neoplasm; D014408:Biomarkers, Tumor
keywords: antibody biomarker; cancer diagnostic; immunodiagnostic; peptide microarray