Microarray Gene Expression Analysis to Evaluate Cell Type Specific Expression of Targets Relevant for Immunotherapy of Hematological Malignancies.

Cellular immunotherapy has proven to be effective in the treatment of hematological cancers by donor lymphocyte infusion after allogeneic hematopoietic stem cell transplantation and more recently by targeted therapy with chimeric antigen or T-cell receptor-engineered T cells. However, dependent on the tissue distribution of the antigens that are targeted, anti-tumor responses can be accompanied by undesired side effects. Therefore, detailed tissue distribution analysis is essential to estimate potential efficacy and toxicity of candidate targets for immunotherapy of hematological malignancies. We performed microarray gene expression analysis of hematological malignancies of different origins, healthy hematopoietic cells and various non-hematopoietic cell types from organs that are often targeted in detrimental immune responses after allogeneic stem cell transplantation leading to graft-versus-host disease. Non-hematopoietic cells were also cultured in the presence of IFN-γ to analyze gene expression under inflammatory circumstances. Gene expression was investigated by Illumina HT12.0 microarrays and quality control analysis was performed to confirm the cell-type origin and exclude contamination of non-hematopoietic cell samples with peripheral blood cells. Microarray data were validated by quantitative RT-PCR showing strong correlations between both platforms. Detailed gene expression profiles were generated for various minor histocompatibility antigens and B-cell surface antigens to illustrate the value of the microarray dataset to estimate efficacy and toxicity of candidate targets for immunotherapy. In conclusion, our microarray database provides a relevant platform to analyze and select candidate antigens with hematopoietic (lineage)-restricted expression as potential targets for immunotherapy of hematological cancers.

A computational model of afferent neural activity from the cochlea to the dorsal acoustic stria.

The first comprehensive computational model of the precortical mammalian auditory system to include afferent neural processing up to the level of the dorsal acoustic stria (DAS) is described. The model consists of two scissile stages simulating (1) the cochlea and auditory nerve (AN) and (2) the dorsal cochlear nucleus (DCN). The model derives its input from a 128-channel cochlear filterbank. Cochlear transduction, rectification, logarithmic compression, and two-tone suppression functions are performed at the first stage of the simulation. The 512 artificial neurons employed model the cell at the level of transmembrane potential and have interconnections that follow closely those reported in recent anatomical and physiological studies of the cat AN and DCN. The responses of the model to pure-tone stimuli (at various sound-pressure levels) and noise stimuli (at various levels and bandwidths) are reported in detail and compare well with published results. The model is being used to investigate the representation of initial English stop consonants (differing in voice-onset time) in the DAS; this work is briefly described.

A computerized database of 'normal' auditory brainstem responses.

A computerized database of auditory brainstem responses (ABRs) from 'normal-hearing' volunteers is described. The database contains 'raw' responses recorded from 81 individuals; subjects varied in age from 20 to 56 years. The database is currently being used in a study to aid in the interpretation of ABRs for diagnostic purposes. Copies of the database are available over the world-wide web (http:¿¿www.engg.le.ac.uk¿abrdata).