Researchers from Columbia University have demonstrated that a transcriptome reversal drug discovery technique, originally developed for cancer, can be applied to neurodevelopmental disorders.
Drug discovery and neurodevelopmental disorders
Whole genome sequencing has increased our understanding of the mechanisms underlying neurodevelopmental disorders. This has led to the development of targeted treatments, such as enzyme replacement therapies in deficiency disorders, and antisense oligonucleotide therapies for spinal muscular atrophy. However, the development of precision therapeutics has lagged behind the progress made in gene discovery. One of the major challenges facing precision medicine for neurodevelopmental disorders is the vast heterogeneity underlying these conditions.
The researchers behind this study argue that neurodevelopmental disorder-associated genes that directly influence the transcriptome, such as chromatin modifiers and transcription factors, represent a group of genes that are amenable to drug discovery efforts and that are well characterised in cancer datasets. Although the concept of transcriptome reversal has been explored to some extent by researchers in relation to dementia, this approach is largely unexplored across neurodevelopmental disorders.
Transcriptome reversal
The transcriptome reversal approach to drug discovery works off the premise that if gene expression changes underlie the pathophysiology of a particular disease, then correcting this transcriptomic signature toward a normal state may have therapeutic potential. This approach has three main steps: (1) identification of the disease gene expression signature through the use of connectivity maps (CMaps), (2) in silico or experimental screening to prioritise compounds most likely to reverse the disease signature, and (3) targeted experimental validation of candidate compounds.
CMaps
Research groups have made significant efforts to create a publicly accessible CMap, which includes data from microarray signatures for small molecules applied to human cell lines.
More recently, researchers developed a new version of the CMap that leverages a novel gene expression profiling technique called L1000. The assay measures the expression level of 978 landmark genes that were selected to capture genome-wide variation in gene expression. The gene measurements are then used to infer expression of over 10,000 other genes in the transcriptome. Despite this assay being roughly only 80% accurate, it is much more affordable than RNA sequencing, so researchers have been able to use this technique to profile roughly 20,000 small molecules in variable cell lines. These resources have facilitated drug discovery in cancer and non-neurological diseases, including diabetes.
In addition to this, based on the success of CMap analysis in other diseases, the investigations in this study outlined the main steps and considerations required to facilitate the implementation of this approach for neurodevelopmental disorders.
The first step involves the generation of mouse and organoid models of the disease, as it is rarely possible to acquire brain tissue from patients with neurodevelopmental disorders. Secondly, researchers must derive disease gene expression signatures via scRNA-seq for each implicated transcriptome regulator. Next researchers must develop a publicly accessible compendium of compound signatures, as existing CMaps containing compound signatures are primarily derived from cancer cell lines. Finally, experts must undertake compound prioritization and validation, by administering candidate compounds to cells containing the mutated gene to verify that they restore the transcriptome towards normal.
Data sharing
To facilitate transcription reversal as an approach for drug discovery for neurodevelopmental disorders, a community-based effort, and substantial data sharing is required to produce a CMap for neurodevelopmental cell lines. The researchers in this study argue that existing, publicly accessible, CMaps for cancer cell lines demonstrate how this method of data sharing can open the floodgates for novel therapies. This study proposes how data sharing can facilitate the use of transcriptome reversal drug discovery for neurodevelopmental disorders and outlined the steps required for implementation of this technique.
Moreover, the investigators suggest that implementation of transcriptome reversal has the potential to identify effective treatments for many genetic disorders, given the importance of genes with transcriptomic effects.
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