Immunosignaturing microarrays distinguish antibody profiles of related pancreatic diseases

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Abstract

Immunosignaturing is a technology that allows the humoral immune response to be observed through the binding of antibodies to random sequence peptides. Profiles of the antibody repertoire produced during infection or during long-term chronic disease have proven to be informative for disease classification. An important unanswered question relative to this technology is whether different diseases that target the same organ and result in similar early phenotypes have similar or distinguishable immunosignatures. This question is of clinical relevance when considering patients who present with similar symptoms early during their disease. The pancreas is one such organ; diseases that affects this organ can cause the patient both broad and acute distress, with little to distinguish the disease source. If the cause were made clear without biopsy, and could be accomplished during routine monitoring, earlier intervention could improve health. Pancreatic cancer, chronic or acute pancreatitis, diabetes mellitus, hepatitis B or C infection, and other diseases can deeply affect the function of the pancreas, complicating diagnosis. We tested the immunosignaturing platform for its ability to resolve four different diseases that target the same organ; pancreatic cancer, pre-pancreatic cancer (panIN), type II diabetes and acute pancreatitis. These diseases were separated with >90% specificity from controls and from each other. We also describe a mathematical method that allows identification of 3 distinct components of an immunosignature: disease specific, 'housekeeping' and patient specific variation. The first component is useful in diagnosing disease, the second for baseline for the technology and third for monitoring changes in a healthy individual over time. © 2012 Kukreja M, et al.

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APA

Kukreja, M., Johnston, S. A., & Stafford, P. (2013). Immunosignaturing microarrays distinguish antibody profiles of related pancreatic diseases. Journal of Proteomics and Bioinformatics, 6(7). https://doi.org/10.4172/jpb.S6-001

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