1.
Department of Human Oncology, University of Wisconsin, Madison, WI, USA
2.
SMPH, Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA
3.
Department of Obstetrics and Gynecology, SMPH, Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA
4.
Department of Pediatrics, Department of Human Oncology, University of Wisconsin, Madison, WI, USA
Description
Antibodies can play an important role in innate and adaptive immune responses against cancer, and in preventing infectious disease. Using a Nimble Therapeutics high-density peptide array, we assessed potential protein-targets for antibodies found in sera of immune mice, that were previously cured of their melanoma through a combined immunotherapy regimen with long-term memory. Using flow cytometry, immune sera showed strong antibody-binding against melanoma tumor cell lines. Sera from 6 of these cured mice were analyzed with this high-density, whole-proteome peptide-array to determine specific antibody-binding sites and their linear peptide sequence. We identified thousands of peptides that were targeted by 2 or more of these 6 mice and exhibited strong antibody binding only by immune, not naive sera. Confirmatory studies were done to validate these results using 2 separate ELISA-based systems. This technology may be helpful in studying the “immunome”. of protein-based epitopes that are recognized by immune sera from mice, or possibly patients, cured of cancer via immunotherapy.
Notes
This work was supported by Midwest Athletes Against Childhood Cancer; Stand Up 2 Cancer and CRUK; the St. Baldrick's Foundation; the Crawdaddy Foundation; the University of Wisconsin Carbone Cancer Center; the Data Science Initiative grant from the University of Wisconsin Office of the Chancellor and the Vice Chancellor for Research and Graduate Education, The Cancer Research Institute, Alex's Lemonade Stand Foundation, and the Children's Neuroblastoma Cancer Foundation. This research was also supported in part by public health service grants U54-CA232568, R35-CA197078, U01-CA233102, and Project 3 of P01CA250972 from the National Cancer Institute; Clinical and Translational Science Award (CTSA) program (ncats.nih.gov/ctsa), through the National Institutes of Health National Center for Advancing Translational Sciences (NCATS), grants UL1TR002373 and KL2TR002374; 2U19AI104317-06U19-2 from the National Institute of Allergy and Infectious Diseases; and UL1TR002373 from the National Institutes of Health and the Department of Health and Human Services. Shared resource flow cytometry reagents and equipment are funded by University of Wisconsin Carbone Cancer Center Support Grant P30 CA014520.
This work has also been supported by the University of Wisconsin Carbone Cancer Center and the Data Science Initiative grant from the University of Wisconsin Office of the Chancellor and the Vice Chancellor for Research and Graduate Education. This research was also supported in part by public health service grants Clinical and Translational Science Award (CTSA) program (ncats.nih.gov/ctsa), through the National Institutes of Health National Center for Advancing Translational Sciences (NCATS), grants UL1TR002373 and KL2TR002374; and 2U19AI104317-06U19-2 from the National Institute of Allergy and Infectious Diseases. Shared resource funded by University of Wisconsin Carbone Cancer Center Support Grant P30 CA014520. This work was also supported by the St. Baldrick's Foundation; the Crawdaddy Foundation; The Cancer Research Institute, Alex's Lemonade Stand Foundation and the Children's Neuroblastoma Cancer Foundation. This research was also supported in part by public health service grants U54-CA232568, R35-CA197078, U01-CA233102, Project 3 and Biostatistics and Bioinformatics Core of P01CA250972 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
