Transcriptome-Guided Drug Repositioning.

Arsen Arakelyan,Maria Nikoghosyan,Lilit Nersisyan,Hans Binder,Siras Hakobyan,Lydia Hopp,Arman Simonyan,Henry Loeffler-Wirth

doi:10.3390/pharmaceutics11120677

Abstract

Drug repositioning can save considerable time and resources and significantly speed up the drug development process. The increasing availability of drug action and disease-associated transcriptome data makes it an attractive source for repositioning studies. Here, we have developed a transcriptome-guided approach for drug/biologics repositioning based on multi-layer self-organizing maps (ml-SOM). It allows for analyzing multiple transcriptome datasets by segmenting them into layers of drug action- and disease-associated transcriptome data. A comparison of expression changes in clusters of functionally related genes across the layers identifies “drug target” spots in disease layers and evaluates the repositioning possibility of a drug. The repositioning potential for two approved biologics drugs (infliximab and brodalumab) confirmed the drugs’ action for approved diseases (ulcerative colitis and Crohn’s disease for infliximab and psoriasis for brodalumab). We showed the potential efficacy of infliximab for the treatment of sarcoidosis, but not chronic obstructive pulmonary disease (COPD). Brodalumab failed to affect dysregulated functional gene clusters in Crohn’s disease (CD) and systemic juvenile idiopathic arthritis (SJIA), clearly indicating that it may not be effective in the treatment of these diseases. In conclusion, ml-SOM offers a novel approach for transcriptome-guided drug repositioning that could be particularly useful for biologics drugs.

Highlights

Drug repositioning is the identification of alternative target diseases for already approved drugs, which can save tremendous resources and significantly speed up the drug development process [1,2]
We propose a transcriptome based approach for drug repositioning, which is based on a multi-layer self-organizing maps algorithm for clustering transcription profiles of genes in healthy and disease conditions and upon drug action. ml-SOM is an extension of a previously developed SOM based transcriptome analysis pipeline [16,17] that has been used for comprehensive analysis of transcription landscapes in cancers and other chronic diseases and proven to be valuable for the general understanding of disease pathomechanisms, identification of molecular subtypes, biomarker selection, and functional information mining [18,19,20,21]
Evaluation of Infliximab as a Potential Therapeutics for Ulcerative Colitis, Crohn’s Disease, chronic obstructive pulmonary disease (COPD), and Sarcoidosis To evaluate the effect of infliximab (T1) on ulcerative colitis (UC) (D1), Crohn’s disease (CD) (D2), COPD (R1), and sarcoidosis (R2) we performed ml-SOM training of four transcriptomic datasets, including one drug response and three diseases-related datasets

Summary

Introduction

Drug repositioning (repurposing) is the identification of alternative target diseases for already approved drugs, which can save tremendous resources and significantly speed up the drug development process [1,2]. The first strategy employs structural bioinformatics approaches (molecular modeling, dynamics simulations, and docking) to identify compound–target pairs [3]. Though it has demonstrated its efficacy in several studies, the main limitation of this approach is the knowledge of the chemical structure of the drug and the 3D structure of its target. This, in turn, severely impedes the repositioning potential of structural bioinformatics approaches. For the category of drugs known as biologics, such as vaccines, blood components, allergenics, somatic cells, gene therapy, tissues, and recombinant therapeutic proteins and antibodies, their structural models are not available, making structural bioinformatics-based repositioning studies not suitable [4,5]

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Conclusion