Response definition criteria for ELISPOT assays revisited |
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Authors: | Z Moodie L Price C Gouttefangeas A Mander S Janetzki M Löwer M J P Welters C Ottensmeier S H van der Burg Cedrik M Britten |
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Institution: | 1. Statistical Center for HIV/AIDS Research and Prevention (SCHARP), Fred Hutchinson Cancer Research Center, Seattle, WA, USA 2. Division of Biostatistics, Department of Environmental Medicine, New York University School of Medicine, New York, NY, USA 3. Department of Immunology, University of Tuebingen, Tübingen, Germany 4. Experimental Cancer Medicine Centre and Cancer Sciences Division, Southampton University Hospitals, Southampton, UK 5. ZellNet Consulting, Inc., Fort Lee, NJ, USA 6. Department of Bioinformatics, TrOn GmbH, Center for Translational Oncology and Immunology, Mainz, Germany 7. Department of Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, The Netherlands 8. Department of Clinical Oncology, Leiden University Medical Center, Leiden, The Netherlands 10. BioNTech AG, Mainz, Germany 9. Medical Department, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
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Abstract: | No consensus has been reached on how to determine if an immune response has been detected based on raw data from an ELISPOT
assay. The goal of this paper is to enable investigators to understand and readily implement currently available methods for
response determination. We describe empirical and statistical approaches, identifying the strengths and limitations of each
approach to allow readers to rationally select and apply a scientifically sound method appropriate to their specific laboratory
setting. Five representative approaches were applied to data sets from the CIMT Immunoguiding Program and the response detection
and false positive rates were compared. Simulation studies were also performed to compare empirical and statistical approaches.
Based on these, we recommend the use of a non-parametric statistical test. Further, we recommend that six medium control wells
or four wells each for both medium control and experimental conditions be performed to increase the sensitivity in detecting
a response, that replicates with large variation in spot counts be filtered out, and that positive responses arising from
experimental spot counts below the estimated limit of detection be interpreted with caution. Moreover, a web-based user interface
was developed to allow easy access to the recommended statistical methods. This interface allows the user to upload data from
an ELISPOT assay and obtain an output file of the binary responses. |
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