Drug Discovery 2021 After the Storm: Re-connect, Re-invent, Re-imagine
Poster
22

The Identification of Novel Drug Target Candidates in T cells

Authors

L Suckling1
1 GSK, UK

Abstract

Objective

Advances in functional genomics and chemogenomics methods are enabling the identification of novel drug target candidates. Such screens provide platforms for the rapid identification of multiple therapeutic target candidates which, when targeted, result in a desired phenotypic response. When combined with multiparametric readouts, these screens can provide a wealth of data for the drug discovery field. We set out to establish gene-editing and chemogenomic screening workflows in primary CD4+ T cells in order to identify novel targets for immune-mediated inflammatory diseases.


Methods

To enable target identification in CD4+ T cells, we established several different screening workflows. This included automated arrayed CRISPR-Cas9 editing screens, pooled CRISPR screening using the SLICE protocol, and Chemogenomics workflows. Each of the screens utilises multiplexed flow cytometry based endpoint assays. In these assays, we stain T cells simultaneously for viability, cell surface markers and intracellular markers.


Results

We have successfully established pooled and automated arrayed CRISPR-Cas9 workflows and chemogenomics library screening in CD4+ T cells for the identification of novel drug discovery targets for immune-mediated inflammatory disease. Through the measurement of multiple markers simultaneously, we can phenotype populations of T cells and determine whether a compound/gene edit skews the T cell population to a particular phenotype, desired for combating disease. Automation of arrayed screening workflows will enable higher-throughput, less resource-intensive applications of this approach.


Conclusion

The target identification workflows we have established in CD4+ T cells will enable the identification of novel gene targets which, when modulated, cause T cell subsets to elicit desirable immunomodulatory effects. These data will provide information for multiple immune-mediated inflammatory diseases and enable us to select novel drug discovery targets for further development.