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Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping

BACKGROUND: We have previously used the rat 4 day Complete Freund's Adjuvant (CFA) model to screen compounds with potential to reduce osteoarthritic pain. The aim of this study was to identify genes altered in this model of osteoarthritic pain and use this information to infer analgesic potenti...

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Autores principales: Chang, Meiping, Smith, Sarah, Thorpe, Andrew, Barratt, Michael J, Karim, Farzana
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2949723/
https://www.ncbi.nlm.nih.gov/pubmed/20846436
http://dx.doi.org/10.1186/1744-8069-6-56
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author Chang, Meiping
Smith, Sarah
Thorpe, Andrew
Barratt, Michael J
Karim, Farzana
author_facet Chang, Meiping
Smith, Sarah
Thorpe, Andrew
Barratt, Michael J
Karim, Farzana
author_sort Chang, Meiping
collection PubMed
description BACKGROUND: We have previously used the rat 4 day Complete Freund's Adjuvant (CFA) model to screen compounds with potential to reduce osteoarthritic pain. The aim of this study was to identify genes altered in this model of osteoarthritic pain and use this information to infer analgesic potential of compounds based on their own gene expression profiles using the Connectivity Map approach. RESULTS: Using microarrays, we identified differentially expressed genes in L4 and L5 dorsal root ganglia (DRG) from rats that had received intraplantar CFA for 4 days compared to matched, untreated control animals. Analysis of these data indicated that the two groups were distinguishable by differences in genes important in immune responses, nerve growth and regeneration. This list of differentially expressed genes defined a "CFA signature". We used the Connectivity Map approach to identify pharmacologic agents in the Broad Institute Build02 database that had gene expression signatures that were inversely related ('negatively connected') with our CFA signature. To test the predictive nature of the Connectivity Map methodology, we tested phenoxybenzamine (an alpha adrenergic receptor antagonist) - one of the most negatively connected compounds identified in this database - for analgesic activity in the CFA model. Our results indicate that at 10 mg/kg, phenoxybenzamine demonstrated analgesia comparable to that of Naproxen in this model. CONCLUSION: Evaluation of phenoxybenzamine-induced analgesia in the current study lends support to the utility of the Connectivity Map approach for identifying compounds with analgesic properties in the CFA model.
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spelling pubmed-29497232010-10-06 Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping Chang, Meiping Smith, Sarah Thorpe, Andrew Barratt, Michael J Karim, Farzana Mol Pain Research BACKGROUND: We have previously used the rat 4 day Complete Freund's Adjuvant (CFA) model to screen compounds with potential to reduce osteoarthritic pain. The aim of this study was to identify genes altered in this model of osteoarthritic pain and use this information to infer analgesic potential of compounds based on their own gene expression profiles using the Connectivity Map approach. RESULTS: Using microarrays, we identified differentially expressed genes in L4 and L5 dorsal root ganglia (DRG) from rats that had received intraplantar CFA for 4 days compared to matched, untreated control animals. Analysis of these data indicated that the two groups were distinguishable by differences in genes important in immune responses, nerve growth and regeneration. This list of differentially expressed genes defined a "CFA signature". We used the Connectivity Map approach to identify pharmacologic agents in the Broad Institute Build02 database that had gene expression signatures that were inversely related ('negatively connected') with our CFA signature. To test the predictive nature of the Connectivity Map methodology, we tested phenoxybenzamine (an alpha adrenergic receptor antagonist) - one of the most negatively connected compounds identified in this database - for analgesic activity in the CFA model. Our results indicate that at 10 mg/kg, phenoxybenzamine demonstrated analgesia comparable to that of Naproxen in this model. CONCLUSION: Evaluation of phenoxybenzamine-induced analgesia in the current study lends support to the utility of the Connectivity Map approach for identifying compounds with analgesic properties in the CFA model. BioMed Central 2010-09-16 /pmc/articles/PMC2949723/ /pubmed/20846436 http://dx.doi.org/10.1186/1744-8069-6-56 Text en Copyright ©2010 Chang et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Chang, Meiping
Smith, Sarah
Thorpe, Andrew
Barratt, Michael J
Karim, Farzana
Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping
title Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping
title_full Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping
title_fullStr Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping
title_full_unstemmed Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping
title_short Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping
title_sort evaluation of phenoxybenzamine in the cfa model of pain following gene expression studies and connectivity mapping
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2949723/
https://www.ncbi.nlm.nih.gov/pubmed/20846436
http://dx.doi.org/10.1186/1744-8069-6-56
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