Applications of High Throughput Gene Expression Profiling in Early Drug Discovery

Early stages of drug discovery often depend on relatively simple reporter assays or phenotypic readouts, providing little or no information on the drug’s mechanism of action (MOA). Gene expression profiling technologies like RNA sequencing (RNA-seq) enable a more comprehensive characterization of compounds by measuring the activity of molecular pathways. This information can complement phenotypic readouts and can be used to prioritize candidate compounds for further testing. RNA expression profiling also serves as a generic test that can be applied to any drug development pipeline without the need for target-dependent customization.

In this webinar, a workflow will be presented for the processing of 384 cell lysates with RNA-seq to generate expression data analyzed at the pathway level. The data show that shallow sequencing of crude cell lysates reproducibly detects over 5000 genes with at least ten reads. Subsampling of deep sequencing datasets demonstrated that differential pathway analysis is largely unaffected when reducing the number of genes to this level. Consequently, reliable pathway insights can be obtained at high throughput and relatively low cost while not being limited to a predefined set of genes or pathways.

In cell perturbation screenings (small molecules, RNAi, antisense or CRISPR), the application can provide in-depth information on the mode of action underlying the induced cellular phenotypes as well as molecular similarity scores to identify those perturbations acting similar to a reference condition or via shared molecular mechanisms. This methodology can also be applied to repurpose off-target siRNA hits from library screens to reveal novel candidate therapeutic targets for drug development.

Finally, it will be demonstrated how coupling the data generated from the workflow with a tailored visualization platform can facilitate data interpretation enabling:

• Easy exploration of the enriched gene sets for individual contrasts in addition to informative descriptions and gene details
• Rapid evaluation of activity of various gene sets associated to canonical toxicity pathways
• Effortless assessment of molecular similarity among compounds based on the enriched gene sets
• Rapid investigation of leading-edge overlaps of the top gene sets per contrast

Speaker

Pieter Mestdagh PhD, Senior Scientist, Biogazelle

Pieter Mestdagh is a Senior Scientist at Biogazelle, as well as Associate Professor at the Faculty of Medicine and Health Sciences, Ghent University, Belgium. He holds Master’s degrees in Industrial Engineering and Biochemistry (2004), and Bioscience Engineering and Cell and Gene Biotechnology (2006), as well as a PhD in Biomedical Sciences (2011). He is the author of more than 100 scientific articles in international journals, as well as six European Patents.

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