MOTIVATION: Cross-reactivity (CR) or invocation of autoimmune side effects in various tissues has important safety implications in adoptive immunotherapy directed against selected antigens. The ability to predict CR (on-target and off-target toxicities) may help in the early selection of safer therapeutically relevant target antigens. RESULTS: We developed a methodology for the calculation of quantitative CR for any defined peptide epitope. Using this approach, we performed assessment of 4 groups of 283 currently known human MHC-class-I epitopes including differentiation antigens, overexpressed proteins, cancer-testis antigens and mutations displayed by tumor cells. In addition, 89 epitopes originating from viral sources were investigated. The natural occurrence of these epitopes in human tissues was assessed based on proteomics abundance data, while the probability of their presentation by MHC-class-I molecules was modelled by the method of Keşmir et al. which combines proteasomal cleavage, TAP affinity and MHC-binding predictions. The results of these analyses for many previously defined peptides are presented as CR indices and tissue profiles. The methodology thus allows for quantitative comparisons of epitopes and is suggested to be suited for the assessment of epitopes of candidate antigens in an early stage of development of adoptive immunotherapy. AVAILABILITY AND IMPLEMENTATION: Our method is implemented as a Java program, with curated datasets stored in a MySQL database. It predicts all naturally possible self-antigens for a given sequence of a therapeutic antigen (or epitope) and after filtering for predicted immunogenicity outputs results as an index and profile of CR to the self-antigens in 22 human tissues. The program is implemented as part of the iCrossR webserver, which is publicly available at http://webclu.bio.wzw.tum.de/icrossr/ CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.

MOTIVATION: Adoptive T cell therapies based on introduction of new T cell receptors (TCRs) into patient recipient T cells is a promising new treatment for various kinds of cancers. A major challenge, however, is the choice of target antigens. If an engineered TCR can cross-react with self-antigens in healthy tissue, the side-effects can be devastating. We present the first web server for assessing epitope sharing when designing new potential lead targets. We enable the users to find all known proteins containing their peptide of interest. The web server returns not only exact matches, but also approximate ones, allowing a number of mismatches of the users choice. For the identified candidate proteins the expression values in various healthy tissues, representing all vital human organs, are extracted from RNA Sequencing (RNA-Seq) data as well as from some cancer tissues as control. All results are returned to the user sorted by a score, which is calculated using well-established methods and tools for immunological predictions. It depends on the probability that the epitope is created by proteasomal cleavage and its affinities to the transporter associated with antigen processing and the major histocompatibility complex class I alleles. With this framework, we hope to provide a helpful tool to exclude potential cross-reactivity in the early stage of TCR selection for use in design of adoptive T cell immunotherapy. AVAILABILITY AND IMPLEMENTATION: The Expitope web server can be accessed via http://webclu.bio.wzw.tum.de/expitope.