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Monitoring the Wall Mechanics During Stent Deployment in a Vessel
Published on: May 8, 2012
Network analysis of human in-stent restenosis
Euan A Ashley1, Rossella Ferrara, Jennifer Y King
1Division of Cardiovascular Medicine, Falk CVRC, Stanford University, Stanford, Calif 94305, USA. euan@stanford.edu
Insights
Researchers analyzed human coronary atheroma to find new targets for treating in-stent restenosis (ISR). Gene network analysis identified potential therapies, with sirolimus showing broader action against ISR than paclitaxel.
Area of Science:
- Cardiovascular Biology
- Molecular Medicine
- Genomics
Background:
- Drug-eluting stents show success but challenges remain for in-stent restenosis (ISR).
- Human coronary atheroma in de novo and restenotic disease requires further investigation for novel therapeutic targets.
Purpose of the Study:
- To identify novel therapeutic targets for in-stent restenosis (ISR) by analyzing human coronary atheroma.
- To compare gene expression profiles in de novo atherosclerosis and ISR.
- To evaluate potential therapeutic agents based on gene network analysis.
Main Methods:
- Recruited 89 patients undergoing coronary atherectomy for de novo atherosclerosis or ISR.
- Performed histological analysis and gene expression profiling using oligonucleotide microarrays.
- Utilized network analysis combining literature mining with gene expression signatures.
Main Results:
- ISR samples showed greater cellularity and less inflammation/lipid content compared to de novo lesions.
- Gene ontology revealed cell proliferation in ISR and inflammation in de novo disease.
- Network analysis identified procollagen type 1 alpha2 and ADAM17 as potential ISR targets.
- Sirolimus demonstrated broader suppressive action against ISR than paclitaxel in network analysis.
Conclusions:
- Histological and gene network analysis of human ISR provides potential targets for directed therapy.
- The findings support the clinical efficacy of existing agents like sirolimus and paclitaxel.
- This approach can identify and validate therapeutic targets for restenotic disease.
Background:
Recent successes in the treatment of in-stent restenosis (ISR) by drug-eluting stents belie the challenges still faced in certain lesions and patient groups. We analyzed human coronary atheroma in de novo and restenotic disease to identify targets of therapy that might avoid these limitations.
Methods And Results:
We recruited 89 patients who underwent coronary atherectomy for de novo atherosclerosis (n=55) or in-stent restenosis (ISR) of a bare metal stent (n=34). Samples were fixed for histology, and gene expression was assessed with a dual-dye 22,000 oligonucleotide microarray. Histological analysis revealed significantly greater cellularity and significantly fewer inflammatory infiltrates and lipid pools in the ISR group. Gene ontology analysis demonstrated the prominence of cell proliferation programs in ISR and inflammation/immune programs in de novo restenosis. Network analysis, which combines semantic mining of the published literature with the expression signature of ISR, revealed gene expression modules suggested as candidates for selective inhibition of restenotic disease. Two modules are presented in more detail, the procollagen type 1 alpha2 gene and the ADAM17/tumor necrosis factor-alpha converting enzyme gene. We tested our contention that this method is capable of identifying successful targets of therapy by comparing mean significance scores for networks generated from subsets of the published literature containing the terms "sirolimus" or "paclitaxel." In addition, we generated 2 large networks with sirolimus and paclitaxel at their centers. Both analyses revealed higher mean values for sirolimus, suggesting that this agent has a broader suppressive action against ISR than paclitaxel.
Conclusions:
Comprehensive histological and gene network analysis of human ISR reveals potential targets for directed abrogation of restenotic disease and recapitulates the results of clinical trials of existing agents.
