I’ve got algorithm: predicting tumor and autoimmune peptide targets for CD8+ T cells

• Published in: The Journal of clinical investigation Vol. 126; no. 12; pp. 4399 - 4401
• Main Authors: Dersh, Devin, Yewdell, Jonathan W.
• Format: Journal Article
• Language: English
• Published: United States American Society for Clinical Investigation 01.12.2016
• Subjects: Algorithms; Autoimmune Diseases - immunology; Autoimmune Diseases - pathology; B-Lymphocytes - immunology; B-Lymphocytes - pathology; CD8-Positive T-Lymphocytes - immunology; CD8-Positive T-Lymphocytes - pathology; Cell Line; HLA-A Antigens - immunology; HLA-B Antigens - immunology; Humans; Neoplasm Proteins - immunology; Neoplasms - immunology; Neoplasms - pathology; Peptides - immunology
• ISSN: 0021-9738; 1558-8238; 1558-8238
• DOI: 10.1172/JCI91302

CD8+ T cells play a central role in eradicating intracellular pathogens, but also are important for noninfectious diseases, including cancer and autoimmunity. The ability to clinically manipulate CD8+ T cells to target cancer and autoimmune disease is limited by our ignorance of relevant self-peptide target antigens. In this issue of the JCI, Pearson et al. describe 25,270 MHC class I-associated peptides presented by a wide range of HLA A and B allomorphs expressed by 18 different B cell lines. Via extensive bioinformatic analysis, the authors make surprising conclusions regarding the selective nature of peptide generation at the level of individual gene products and create a predictive algorithm for disease-relevant self-peptides that will be of immediate use for clinical and basic immunological research.