Immune Tolerance: from Gene Expression to Drug Discovery
Immune Tolerance: from Gene Expression to Drug Discovery Therapeutic Immunology Group (Prof. H. Waldmann) Therapeutic Antibody Centre (Prof. G. Hale) Immune Tolerance and
Therapy Therapy to reverse breakdown of self tolerance in autoimmune diseases Tolerance induction rather than nonspecific immunosuppression to avoid rejection of transplanted organs Reversal of acquired tolerance to tumour antigens and latent viral infections
Why Start from Gene Expression? What are the approaches to find new therapeutics: Random screening of chemical libraries in a surrogate assay (eg. suppression of antigen specific proliferation in vitro). Look for monoclonal antibodies that modulate a function (eg. same assay). Targeted chemical design/antibodies against specific protein structures. But:
How to identify the most relevant/specific target proteins on possibly rare cells? Ideally we want targets expressed ONLY on target cells to avoid potential toxicity against other tissues. An answer: Look for genes that are specifically expressed in the functional cell type of interest in our example, Th1 but NOT T regulatory (Treg) cells.
Methods for Analysing Gene Expression Analysis of known genes (RT-PCR/Antibodies/Protein Gels): There are >1000 interesting immunological genes and probably many more important but unidentified genes. How to choose? Differential Display and Gene Cloning: Clones genes over-expressed in one cell compared to one other, but these may be shared with other cells and you dont know what you are working with until
you have it cloned and sequenced. How to choose? Gene Chips/Arrays Can identify patterns of expression from many (10,000+) genes and multiple samples. Genes must already have been cloned (<1/3 of genome?), it is quick, but not very sensitive (or reliable?), and currently expensive. SAGE (Serial Analysis of Gene Expression)
Can identify almost the entire pattern of gene expression (the transcriptome) with no a priori knowledge of the gene sequences. Multiple samples are directly comparable as a database. Sensitivity depends on the number of tags sequenced: this can be labour intensive. CD4+ T cell clones/lines against DBY-Ek male antigen Clone
SAGE details AE = Nla-III TE = BsmF1 Automated DNA Sequencing Machine
Analysis of SAGE data Use SAGEv3.01 software (Velculescu et al) to extract numbers of tags from raw sequence files. Use Access to link tags to known genes, Unigene clusters, and ESTs (from NCBI reliable tag list). Use Excel to manipulate data tables and calculate statistics (custom written function for Beysian stats). Use custom written cluster analysis and
presentation program (running on Acorn RISC-PC). DC cluster T cell clone cluster Spleen CD4 cell cluster Clustered Expression Chart
of approx. 300 known genes (CD antigens, cytokines and receptors) A close up of a Treg cluster of known genes
Real Time PCR Machine HPRT TM4 HPRT
TM4 Th1 Treg Th1 Treg
Quantitative RT-PCR from rejecting, syngeneic and tolerant skin grafts Ratio of tolerant to rejecting skin graft expression 14.8** 624** 32.6** 2.8* 0.14 0.5
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