4 research outputs found
Immunoscreening of the extracellular proteome of colorectal cancer cells
<p>Abstract</p> <p>Background</p> <p>The release of proteins from tumors can trigger an immune response in cancer patients involving T lymphocytes and B lymphocytes, which results in the generation of antibodies to tumor-derived proteins. Many studies aim to use humoral immune responses, namely autoantibody profiles, directly, as clinical biomarkers. Alternatively, the antibody immune response as an amplification system for tumor associated alterations may be used to indicate putative protein biomarkers with high sensitivity. Aiming at the latter approach we here have implemented an autoantibody profiling strategy which particularly focuses on proteins released by tumor cells in vitro: the so-called secretome.</p> <p>Methods</p> <p>For immunoscreening, the extracellular proteome of five colorectal cancer cell lines was resolved on 2D gels, immobilized on PVDF membranes and used for serological screening with individual sera from 21 colorectal cancer patients and 24 healthy controls. All of the signals from each blot were assigned to a master map, and autoantigen candidates were defined based of the pattern of immunoreactivities. The corresponding proteins were isolated from preparative gels, identified by MALDI-MS and/or by nano-HPLC/ESI-MS/MS and exemplarily confirmed by duplex Western blotting combining the human serum samples with antibodies directed against the protein(s) of interest.</p> <p>Results</p> <p>From 281 secretome proteins stained with autoantibodies in total we first defined the "background patterns" of frequently immunoreactive extracellular proteins in healthy and diseased people. An assignment of these proteins, among them many nominally intracellular proteins, to the subset of exosomal proteins within the secretomes revealed a large overlap. On this basis we defined and consequently confirmed novel biomarker candidates such as the extreme C-terminus of the extracellular matrix protein agrin within the set of cancer-enriched immunorectivities.</p> <p>Conclusions</p> <p>Our findings suggest, first, that autoantibody responses may be due, in large part, to cross-presentation of antigens to the immune system via exosomes, membrane vesicles released by tumor cells and constituting a significant fraction of the secretome. In addition, this immunosecretomics approach has revealed novel biomarker candidates, some of them secretome-specific, and thus serves as a promising complementary tool to the frequently reported immunoproteomic studies for biomarker discovery.</p
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A validated web-application (GFDC) for automatic classification of glaucomatous visual field defects using Hodapp-Parrish-Anderson criteria
Acknowledgements: The authors extend their thanks to Professor David Crabb (Department of Optometry and Visual Sciences, City, University of London) for his assistance with distilling Hodapp-Parrish-Anderson criteria into a workable algorithm for computer vision-based analysis.AbstractSubjectivity and ambiguity of visual field classification limits the accuracy and reliability of glaucoma diagnosis, prognostication, and management decisions. Standardised rules for classifying glaucomatous visual field defects exist, but these are labour-intensive and therefore impractical for day-to-day clinical work. Here a web-application, Glaucoma Field Defect Classifier (GFDC), for automatic application of Hodapp-Parrish-Anderson, is presented and validated in a cross-sectional study. GFDC exhibits perfect accuracy in classifying mild, moderate, and severe glaucomatous field defects. GFDC may thereby improve the accuracy and fairness of clinical decision-making in glaucoma. The application and its source code are freely hosted online for clinicians and researchers to use with glaucoma patients.</jats:p