Computational Drug-repositioning Approach Identifying Sirolimus as a Potential Therapeutic Option for Inflammatory Dilated Cardiomyopathy

Drug Res (Stuttg). 2019 Oct;69(10):565-571. doi: 10.1055/a-0950-9608. Epub 2019 Jun 25.

Abstract

Objective: The aim of this study was to determine promising treatment options for human inflammatory dilated cardiomyopathy using a computational drug-repositioning approach (repurposing established drug compounds for new therapeutic indications).

Background: If the myocardial tissue is detected to be infiltrated with inflammatory cells, primarily of lymphocytes, and if the virus is confirmed using genetic examination (PCR) or immunostaining, the infection is suspected. However, there is no specific treatment (i. e., an antiviral drug) even if the virus is identified; therefore, we used Connectivity Map to identify compounds showing inverse drug-disease signatures, indicating activity against inflammatory dilated cardiomyopathy.

Results: Potential drug-repositioning candidates for the treatment of inflammatory dilated cardiomyopathy were explored through a systematic comparison of the gene expression profiles induced by drugs using Gene Expression Omnibus and Connectivity Map databases.

Conclusion: Using a computational drug-repositioning approach based on the integration of publicly available gene expression signatures of drugs and diseases, sirolimus was suggested as a novel therapeutic option for inflammatory dilated cardiomyopathy.

MeSH terms

  • Cardiomyopathy, Dilated / drug therapy*
  • Cardiomyopathy, Dilated / pathology
  • Computational Biology / methods*
  • Datasets as Topic
  • Drug Repositioning / methods*
  • Gene Expression Profiling
  • Humans
  • Myocardium / pathology
  • Sirolimus / therapeutic use*
  • Tissue Array Analysis

Substances

  • Sirolimus