Transcriptome-Guided Drug Repositioning.

Area of Science:

• Computational Biology
• Pharmacology
• Genomics

Background:

• Drug repositioning accelerates development by repurposing existing drugs.
• Transcriptome data offers a rich resource for identifying new therapeutic applications.
• Current methods require efficient analysis of complex, multi-source transcriptome data.

Purpose of the Study:

• To develop a transcriptome-guided drug repositioning approach using multi-layer self-organizing maps (ml-SOM).
• To identify potential new indications for biologics based on gene expression patterns.
• To validate the efficacy of ml-SOM in predicting drug efficacy for specific diseases.

Main Methods:

• Development of a multi-layer self-organizing map (ml-SOM) model.
• Analysis of segmented transcriptome datasets for drug action and disease association.
• Comparison of gene expression changes to identify drug targets and evaluate repositioning potential.
• Validation using approved biologics: infliximab and brodalumab.

Main Results:

• ml-SOM successfully confirmed existing therapeutic uses for infliximab (ulcerative colitis, Crohn's disease) and brodalumab (psoriasis).
• Identified potential efficacy of infliximab for sarcoidosis treatment.
• Demonstrated lack of efficacy for infliximab in COPD and brodalumab in Crohn's disease and systemic juvenile idiopathic arthritis.
• ml-SOM accurately predicted drug efficacy and non-efficacy in tested conditions.

Conclusions:

• ml-SOM provides a novel and effective transcriptome-guided method for drug repositioning, particularly for biologics.
• This approach can significantly reduce time and resources in drug development.
• The method aids in identifying "drug target" spots within disease transcriptome layers.