Journal Article

Identification and ranking of recurrent neo-epitopes in cancer

Blanc, Eric, Willimsky, Gerald, Blankenstein, Thomas, Beule, Dieter, Dhamodaran, Arunraj, Holtgrewe, Manuel, Messerschmidt, Clemens

2019

Overview

Background Immune escape is one of the hallmarks of cancer and several new treatment approaches attempt to modulate and restore the immune system’s capability to target cancer cells. At the heart of the immune recognition process lies antigen presentation from somatic mutations. These neo-epitopes are emerging as attractive targets for cancer immunotherapy and new strategies for rapid identification of relevant candidates have become a priority. Methods We carefully screen TCGA data sets for recurrent somatic amino acid exchanges and apply MHC class I binding predictions. Results We propose a method for in silico selection and prioritization of candidates which have a high potential for neo-antigen generation and are likely to appear in multiple patients. While the percentage of patients carrying a specific neo-epitope and HLA-type combination is relatively small, the sheer number of new patients leads to surprisingly high reoccurence numbers. We identify 769 epitopes which are expected to occur in 77629 patients per year. Conclusion While our candidate list will definitely contain false positives, the results provide an objective order for wet-lab testing of reusable neo-epitopes. Thus recurrent neo-epitopes may be suitable to supplement existing personalized T cell treatment approaches with precision treatment options.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Algorithms / Alleles / Amino acids / Animals / Antigen presentation / Antigenic determinants / Antigens / Artificial intelligence / Bioinformatic and algorithmical studies / Bioinformatics / Biomedical and Life Sciences / Biomedicine / Cancer / Cancer cells / Cancer immunotherapy / Cancer treatment / Candidates / Computational Biology - methods / Databases, Factual / Epitopes / Epitopes - genetics / Epitopes - immunology / Gene Expression / Genes, MHC Class I - genetics / Genomes / Histocompatibility antigen HLA / Human Genetics / Humans / Immune system / Immunotherapy / Lymphocytes / Lymphocytes T / Machine learning / Major histocompatibility complex / Mice / Microarrays / Mutation / Neo-antigen / Neo-epitope / Neoplasms - genetics / Neoplasms - immunology / Patients / Peptides / Precision treatment / Proteins / Rankings / Recurrence (Disease) / Research Article / Studies / T cells