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A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells

Aim: To investigate genes and pathways involved in differential glucocorticoid (GC) responsiveness in human trabecular meshwork (HTM) cells using RNA sequencing. Methods: Using paired human donor eyes, human organ-cultured anterior segment (HOCAS) was established in one eye to characterize GC respon...

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Autores principales: Kathirvel, Kandasamy, Haribalaganesh, Ravinarayanan, Krishnadas, Ramasamy, Muthukkaruppan, Veerappan, Willoughby, Colin E., Bharanidharan, Devarajan, Senthilkumari, Srinivasan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140469/
https://www.ncbi.nlm.nih.gov/pubmed/35627267
http://dx.doi.org/10.3390/genes13050882
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author Kathirvel, Kandasamy
Haribalaganesh, Ravinarayanan
Krishnadas, Ramasamy
Muthukkaruppan, Veerappan
Willoughby, Colin E.
Bharanidharan, Devarajan
Senthilkumari, Srinivasan
author_facet Kathirvel, Kandasamy
Haribalaganesh, Ravinarayanan
Krishnadas, Ramasamy
Muthukkaruppan, Veerappan
Willoughby, Colin E.
Bharanidharan, Devarajan
Senthilkumari, Srinivasan
author_sort Kathirvel, Kandasamy
collection PubMed
description Aim: To investigate genes and pathways involved in differential glucocorticoid (GC) responsiveness in human trabecular meshwork (HTM) cells using RNA sequencing. Methods: Using paired human donor eyes, human organ-cultured anterior segment (HOCAS) was established in one eye to characterize GC responsiveness based on intra ocular pressure (IOP) change and, in the other eye, primary HTM cell culture was established. For RNA sequencing, total RNA extracted from GC-responder (GC-R) and non-responder (GC-NR) cells after dexamethasone (DEX) or ethanol (ETH) treatment for 7d was used. Differentially expressed genes (DEGs) were compared among five groups and validated. Results: In total, 616 and 216 genes were identified as significantly dysregulated in Group #1 and #2 (#1: ETH vs. DEX-treated GC-R; #2: ETH vs. DEX-treated GC-NR), respectively. Around 80 genes were commonly dysregulated in Group #3 (overlapping DEGs between #1 and #2), whereas 536 and 136 genes were uniquely expressed in GC-R (#4) and GC-NR HTM (#5) cells, respectively. Pathway analysis revealed that WNT signaling, drug metabolism cytochrome p450, cell adhesion, TGF-β signaling, and MAPK signaling were associated with GC responsiveness. Conclusion: This is the first study reporting distinct gene signatures and their associated pathways for GC-R and GC-NR HTM cells. WNT and MAPK signaling are potential therapeutic targets for the management of GC-induced glaucoma.
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spelling pubmed-91404692022-05-28 A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells Kathirvel, Kandasamy Haribalaganesh, Ravinarayanan Krishnadas, Ramasamy Muthukkaruppan, Veerappan Willoughby, Colin E. Bharanidharan, Devarajan Senthilkumari, Srinivasan Genes (Basel) Article Aim: To investigate genes and pathways involved in differential glucocorticoid (GC) responsiveness in human trabecular meshwork (HTM) cells using RNA sequencing. Methods: Using paired human donor eyes, human organ-cultured anterior segment (HOCAS) was established in one eye to characterize GC responsiveness based on intra ocular pressure (IOP) change and, in the other eye, primary HTM cell culture was established. For RNA sequencing, total RNA extracted from GC-responder (GC-R) and non-responder (GC-NR) cells after dexamethasone (DEX) or ethanol (ETH) treatment for 7d was used. Differentially expressed genes (DEGs) were compared among five groups and validated. Results: In total, 616 and 216 genes were identified as significantly dysregulated in Group #1 and #2 (#1: ETH vs. DEX-treated GC-R; #2: ETH vs. DEX-treated GC-NR), respectively. Around 80 genes were commonly dysregulated in Group #3 (overlapping DEGs between #1 and #2), whereas 536 and 136 genes were uniquely expressed in GC-R (#4) and GC-NR HTM (#5) cells, respectively. Pathway analysis revealed that WNT signaling, drug metabolism cytochrome p450, cell adhesion, TGF-β signaling, and MAPK signaling were associated with GC responsiveness. Conclusion: This is the first study reporting distinct gene signatures and their associated pathways for GC-R and GC-NR HTM cells. WNT and MAPK signaling are potential therapeutic targets for the management of GC-induced glaucoma. MDPI 2022-05-15 /pmc/articles/PMC9140469/ /pubmed/35627267 http://dx.doi.org/10.3390/genes13050882 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kathirvel, Kandasamy
Haribalaganesh, Ravinarayanan
Krishnadas, Ramasamy
Muthukkaruppan, Veerappan
Willoughby, Colin E.
Bharanidharan, Devarajan
Senthilkumari, Srinivasan
A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells
title A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells
title_full A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells
title_fullStr A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells
title_full_unstemmed A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells
title_short A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells
title_sort comparative genome-wide transcriptome analysis of glucocorticoid responder and non-responder primary human trabecular meshwork cells
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140469/
https://www.ncbi.nlm.nih.gov/pubmed/35627267
http://dx.doi.org/10.3390/genes13050882
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