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 |
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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. |
doi_str_mv | 10.3390/genes13050882 |
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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/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 by the authors. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3972-cb6d44b6de1ebbc4bdd1b5752ae09c00a9131b1f5f9d6a6be96195279bcbf15c3</citedby><cites>FETCH-LOGICAL-c3972-cb6d44b6de1ebbc4bdd1b5752ae09c00a9131b1f5f9d6a6be96195279bcbf15c3</cites><orcidid>0000-0002-4855-4251 ; 0000-0001-7003-030X ; 0000-0002-1246-4166</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140469/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140469/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27903,27904,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35627267$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><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><title>A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells</title><title>Genes</title><addtitle>Genes (Basel)</addtitle><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.</description><subject>Analysis</subject><subject>Care and treatment</subject><subject>Cell adhesion</subject><subject>Cell culture</subject><subject>Corticosteroids</subject><subject>Cytochrome P450</subject><subject>Dexamethasone</subject><subject>Diagnosis</subject><subject>Dosage and administration</subject><subject>Drug metabolism</subject><subject>Ethanol</subject><subject>Experiments</subject><subject>Eye</subject><subject>Gene expression</subject><subject>Gene Expression Profiling</subject><subject>Genetic aspects</subject><subject>Genomes</subject><subject>Glaucoma</subject><subject>Glucocorticoids</subject><subject>Glucocorticoids - metabolism</subject><subject>Glucocorticoids - pharmacology</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Intraocular Pressure</subject><subject>MAP kinase</subject><subject>Pressure transducers</subject><subject>Ribonucleic acid</subject><subject>RNA</subject><subject>RNA sequencing</subject><subject>Signal transduction</subject><subject>Steroids</subject><subject>Therapeutic targets</subject><subject>Trabecular Meshwork - metabolism</subject><subject>Transcriptome - genetics</subject><subject>Transcriptomes</subject><subject>Wnt protein</subject><issn>2073-4425</issn><issn>2073-4425</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNptkltvFCEUxydGY5vaR18NiS--TAVmgPJistno1qRe0rTpI-FyZkudgRFmavoF_Nyybm27ppAAOfzOH86lql4TfNQ0Er9fQ4BMGszw8TF9Vu1TLJq6bSl7_ui8Vx3mfI3LaDHFmL2s9hrGqaBc7Fe_F2gZh1EnPfkbQCsIcYD60jtA50mHbJMfp2JCi6D72-wzih1a9bONNqbJ2-gdOoM8xuAgIR0c-hpD_WD5nvyg0y06mQcdNpIG7NzrhL5AvvoV0w-0hL7Pr6oXne4zHN7tB9XFp4_ny5P69Nvq83JxWttGClpbw13blgUIGGNb4xwxTDCqAUuLsZakIYZ0rJOOa25AciIZFdJY0xFmm4Pqw1Z3nM0AzkKYku7VuP2litqr3Zvgr9Q63ihJWtxyWQTe3Qmk-HOGPKnBZ1tC0AHinFVJKqGCC0EL-vY_9DrOqaTxL4UJLwURD9Ra96B86GJ5125E1UJQimUJDxfq6AmqTAdDKUKAzhf7jkO9dbAp5pygu4-RYLXpHbXTO4V_8zgx9_S_Tmn-AJurwX8</recordid><startdate>20220515</startdate><enddate>20220515</enddate><creator>Kathirvel, Kandasamy</creator><creator>Haribalaganesh, Ravinarayanan</creator><creator>Krishnadas, Ramasamy</creator><creator>Muthukkaruppan, Veerappan</creator><creator>Willoughby, Colin E</creator><creator>Bharanidharan, Devarajan</creator><creator>Senthilkumari, Srinivasan</creator><general>MDPI AG</general><general>MDPI</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M7P</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><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></search><sort><creationdate>20220515</creationdate><title>A Comparative Genome-Wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells</title><author>Kathirvel, Kandasamy ; 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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