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

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

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Veröffentlicht in:Genes 2022-05, Vol.13 (5), p.882
Hauptverfasser: Kathirvel, Kandasamy, Haribalaganesh, Ravinarayanan, Krishnadas, Ramasamy, Muthukkaruppan, Veerappan, Willoughby, Colin E, Bharanidharan, Devarajan, Senthilkumari, Srinivasan
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container_issue 5
container_start_page 882
container_title Genes
container_volume 13
creator Kathirvel, Kandasamy
Haribalaganesh, Ravinarayanan
Krishnadas, Ramasamy
Muthukkaruppan, Veerappan
Willoughby, Colin E
Bharanidharan, Devarajan
Senthilkumari, Srinivasan
description To investigate genes and pathways involved in differential glucocorticoid (GC) responsiveness in human trabecular meshwork (HTM) cells using RNA sequencing. 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. 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. 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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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. 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. 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.</description><identifier>ISSN: 2073-4425</identifier><identifier>EISSN: 2073-4425</identifier><identifier>DOI: 10.3390/genes13050882</identifier><identifier>PMID: 35627267</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Analysis ; Care and treatment ; Cell adhesion ; Cell culture ; Corticosteroids ; Cytochrome P450 ; Dexamethasone ; Diagnosis ; Dosage and administration ; Drug metabolism ; Ethanol ; Experiments ; Eye ; Gene expression ; Gene Expression Profiling ; Genetic aspects ; Genomes ; Glaucoma ; Glucocorticoids ; Glucocorticoids - metabolism ; Glucocorticoids - pharmacology ; Humans ; Hypertension ; Intraocular Pressure ; MAP kinase ; Pressure transducers ; Ribonucleic acid ; RNA ; RNA sequencing ; Signal transduction ; Steroids ; Therapeutic targets ; Trabecular Meshwork - metabolism ; Transcriptome - genetics ; Transcriptomes ; Wnt protein</subject><ispartof>Genes, 2022-05, Vol.13 (5), p.882</ispartof><rights>COPYRIGHT 2022 MDPI AG</rights><rights>2022 by the authors. 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/). 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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. 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. This is the first study reporting distinct gene signatures and their associated pathways for GC-R and GC-NR HTM cells. 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Haribalaganesh, Ravinarayanan ; Krishnadas, Ramasamy ; Muthukkaruppan, Veerappan ; Willoughby, Colin E ; Bharanidharan, Devarajan ; Senthilkumari, Srinivasan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3972-cb6d44b6de1ebbc4bdd1b5752ae09c00a9131b1f5f9d6a6be96195279bcbf15c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Analysis</topic><topic>Care and treatment</topic><topic>Cell adhesion</topic><topic>Cell culture</topic><topic>Corticosteroids</topic><topic>Cytochrome P450</topic><topic>Dexamethasone</topic><topic>Diagnosis</topic><topic>Dosage and administration</topic><topic>Drug metabolism</topic><topic>Ethanol</topic><topic>Experiments</topic><topic>Eye</topic><topic>Gene expression</topic><topic>Gene Expression Profiling</topic><topic>Genetic aspects</topic><topic>Genomes</topic><topic>Glaucoma</topic><topic>Glucocorticoids</topic><topic>Glucocorticoids - metabolism</topic><topic>Glucocorticoids - pharmacology</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Intraocular Pressure</topic><topic>MAP kinase</topic><topic>Pressure transducers</topic><topic>Ribonucleic acid</topic><topic>RNA</topic><topic>RNA sequencing</topic><topic>Signal transduction</topic><topic>Steroids</topic><topic>Therapeutic targets</topic><topic>Trabecular Meshwork - metabolism</topic><topic>Transcriptome - genetics</topic><topic>Transcriptomes</topic><topic>Wnt protein</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kathirvel, Kandasamy</creatorcontrib><creatorcontrib>Haribalaganesh, Ravinarayanan</creatorcontrib><creatorcontrib>Krishnadas, Ramasamy</creatorcontrib><creatorcontrib>Muthukkaruppan, Veerappan</creatorcontrib><creatorcontrib>Willoughby, Colin E</creatorcontrib><creatorcontrib>Bharanidharan, Devarajan</creatorcontrib><creatorcontrib>Senthilkumari, Srinivasan</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Genes</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kathirvel, Kandasamy</au><au>Haribalaganesh, Ravinarayanan</au><au>Krishnadas, Ramasamy</au><au>Muthukkaruppan, Veerappan</au><au>Willoughby, Colin E</au><au>Bharanidharan, Devarajan</au><au>Senthilkumari, Srinivasan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells</atitle><jtitle>Genes</jtitle><addtitle>Genes (Basel)</addtitle><date>2022-05-15</date><risdate>2022</risdate><volume>13</volume><issue>5</issue><spage>882</spage><pages>882-</pages><issn>2073-4425</issn><eissn>2073-4425</eissn><abstract>To investigate genes and pathways involved in differential glucocorticoid (GC) responsiveness in human trabecular meshwork (HTM) cells using RNA sequencing. 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. 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. 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.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>35627267</pmid><doi>10.3390/genes13050882</doi><orcidid>https://orcid.org/0000-0002-4855-4251</orcidid><orcidid>https://orcid.org/0000-0001-7003-030X</orcidid><orcidid>https://orcid.org/0000-0002-1246-4166</orcidid><oa>free_for_read</oa></addata></record>
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subjects Analysis
Care and treatment
Cell adhesion
Cell culture
Corticosteroids
Cytochrome P450
Dexamethasone
Diagnosis
Dosage and administration
Drug metabolism
Ethanol
Experiments
Eye
Gene expression
Gene Expression Profiling
Genetic aspects
Genomes
Glaucoma
Glucocorticoids
Glucocorticoids - metabolism
Glucocorticoids - pharmacology
Humans
Hypertension
Intraocular Pressure
MAP kinase
Pressure transducers
Ribonucleic acid
RNA
RNA sequencing
Signal transduction
Steroids
Therapeutic targets
Trabecular Meshwork - metabolism
Transcriptome - genetics
Transcriptomes
Wnt protein
title A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells
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