Diverse Hematological Malignancies Including Hodgkin-Like Lymphomas Develop in Chimeric MHC Class II Transgenic Mice

A chimeric HLA-DR4-H2-E (DR4) homozygous transgenic mouse line spontaneously develops diverse hematological malignancies with high frequency (70%). The majority of malignancies were distributed equally between T and B cell neoplasms and included lymphoblastic T cell lymphoma (LTCL), lymphoblastic B cell lymphoma (LBCL), diffuse large B cell lymphoma (DLBCL), the histiocyte/T cell rich variant of DLBCL (DLBCL-HA/T cell rich DLBCL), splenic marginal zone lymphoma (SMZL), follicular B cell lymphoma (FBL) and plasmacytoma (PCT). Most of these neoplasms were highly similar to human diseases. Also, some non-lymphoid malignancies such as acute myeloid leukemia (AML) and histiocytic sarcoma were found. Interestingly, composite lymphomas, including Hodgkin-like lymphomas, were also detected that had CD30+ Hodgkin/Reed-Sternberg (H/RS)-like cells, representing a tumor type not previously described in mice. Analysis of microdissected H/RS-like cells revealed their origin as germinal center B cells bearing somatic hypermutations and, in some instances, crippled mutations, as described for human Hodgkin lymphoma (HL). Transgene integration in an oncogene was excluded as an exclusive driving force of tumorigenesis and age-related lymphoma development suggests a multi-step process. Thus, this DR4 line is a useful model to investigate common molecular mechanisms that may contribute to important neoplastic diseases in man

Expitope 2.0: a tool to assess immunotherapeutic antigens for their potential cross-reactivity against naturally expressed proteins in human tissues

Abstract Background Adoptive immunotherapy offers great potential for treating many types of cancer but its clinical application is hampered by cross-reactive T cell responses in healthy human tissues, representing serious safety risks for patients. We previously developed a computational tool called Expitope for assessing cross-reactivity (CR) of antigens based on tissue-specific gene expression. However, transcript abundance only indirectly indicates protein expression. The recent availability of proteome-wide human protein abundance information now facilitates a more direct approach for CR prediction. Here we present a new version 2.0 of Expitope, which computes all naturally possible epitopes of a peptide sequence and the corresponding CR indices using both protein and transcript abundance levels weighted by a proposed hierarchy of importance of various human tissues. Results We tested the tool in two case studies: The first study quantitatively assessed the potential CR of the epitopes used for cancer immunotherapy. The second study evaluated HLA-A*02:01-restricted epitopes obtained from the Immune Epitope Database for different disease groups and demonstrated for the first time that there is a high variation in the background CR depending on the disease state of the host: compared to a healthy individual the CR index is on average two-fold higher for the autoimmune state, and five-fold higher for the cancer state. Conclusions The ability to predict potential side effects in normal tissues helps in the development and selection of safer antigens, enabling more successful immunotherapy of cancer and other diseases

Additional file 2 of Expitope 2.0: a tool to assess immunotherapeutic antigens for their potential cross-reactivity against naturally expressed proteins in human tissues

TableS2_Healthy. Comma-separated table containing Table S2. (CSV 67 kb