Omics · study · 2026
Gene Regulatory Network-Driven Drug Repurposing Identifies Anti-Atherosclerotic Properties of Auranofin [dataset 1]
Listed in NCBI GEO
The identification of new therapies for coronary artery disease (CAD) has been challenging due to its inherent molecular complexity, which involves thousands of genes acting within and across tissues and cells.
Description
Gene-regulatory networks (GRNs) address this complexity by providing a mechanistic framework for common disease etiologies. Using system genetics, we previously identified the human arterial wall specific GRN42 as a critical regulator of foam cell formation.
In this study, we applied a GRN-driven drug repurposing method by combining transcriptional signatures resulting from the silencing of key drivers of GRN42 to drug-related gene expression profiles from the NIH LINCS Program. This analysis identified candidate compounds predicted to modulate foam cell formation. In vitro screenings of top-selected compounds confirmed the computational predictions and demonstrated the efficacy of auranofin — an FDA-approved gold salt compound for rheumatoid arthritis — in reducing foam cell formation.
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In vivo, auranofin reduced atherosclerosis progression and inflammation in mice and decreased inflammation and wall thickness in the rabbit atherosclerotic aorta, as measured by 18F-FDG PET/MRI. These findings suggest that a GRN-based drug repurposing approach, combined with in vitro and in vivo validation using translational molecular imaging, can uncover new uses for existing drugs, such as auranofin, for the treatment of CAD.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE293nnn/GSE293697 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE293697 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1246065 ncbi.nlm.nih.gov/bioproject/PRJNA1246065 ↗
project · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing · Mus musculus
- From keywords
- Life Sciences
- Inferred from text
- Disease 75% · Imaging 75% · Magnetic resonance imaging 65%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE293697 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[disease].local:disease:disease | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:expression-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[modality].local:modality:imaging | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:mri | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[organism].NCBITaxon:10090 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |