Identifying the transcriptomic basis underlying individualised drug response: moving towards personalised medicine in motor neurone disease (MND) usin

Individual genetic characteristics determine how we respond to drugs, thus the need to identify the molecular mechanisms involved in treatment response. This will allow to assign the most effective drug to different groups of patients depending on their genetics. While this approach is used in asthma and cancer, no match between genetic profile and therapy has been identified for patients affected by neurodegenerative disorders.
Motor neurone disease (MND) is the most common adult onset motor disorder, characterized by progressive loss of motoneurons and death. In vitro studies pioneered by the supervisor and others have shown that astrocytes from MND patients cause wild-type motoneuron death (Re et al 2014; Meyer et al 2014).
At present, Riluzole is the only drug licensed for the treatment of MND. The mechanism(s) of action is/are unclear and it is thought that Riluzole might be active through various pathways.
Moreover, a drug screening performed in our laboratories has identified 3 potent activators of Nrf2, a transcription factor driving the expression of multiple cytoprotective genes via its interaction with the antioxidant response element (ARE) (Mead et al 2013). We have now screened increasing doses of these 3 ARE activators, as well Riluzole in a co-culture system with patient astrocytes and motoneurons. Patient astrocytes typically lead to a decrease in motoneuron survival by 50%. We found that treatment of astrocytes with these 4 compounds dampens their toxicity towards motoneurons, thus leading to an increase in motoneuron survival, depending on the donor genetic subtype.
The main aims of this study are 1) to identify modes of riluzole and ARE activators action on gene expression in astrocytes and 2) correlate the mechanism of action of specific drugs with donor genotype.
Research strategy: We will derive astrocytes from human induced neural progenitors (iNPCs) and differentiate them to astrocytes as previously described (Meyer et al 2014). We will use astrocytes from patients carrying mutations associated with MND, namely SOD1, C9orf72 and TDP43, sporadic ALS patients and controls. We will screen 3 different concentrations of Riluzole as well as 3 concentrations of each of the 3 ARE activators.
We will identify the most effective concentration of each treatment and perform RNA-sequencing before and after drug treatment.
The student will develop significant bioinformatics skills by working with the large bioinformatics group within the Institute. We will determine 1. The modes of action of each drug by comparing differentially expressed transcripts between treated and untreated samples, both patients and controls.
2. The different mechanism of action of each drug on groups of patients carrying different mutations by comparing the transcripts involved in drug response between those groups.
Identifying groups of transcripts involved in specific drug response in patients with defined genetic mutations will also help us better categorise sporadic patients, accounting for 95% of all ALS cases.
To validate our screening, we will also perform RNA-Sequencing of 10 additional sporadic samples, predict which ARE activator they should be more responsive to by looking at their transcriptomic profile and test the results in our co-culture assay.