Identification of endothelial cell genes by combined database mining and microarray analysis
1 Donald W. Reynolds Cardiovascular Clinical Research Center, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California 94305 2 Agilent Technologies, Inc., Palo Alto, California 94304 Vascular endothelial cells maintain the interface between the systemic circu...
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creator | Ho, Michael Yang, Eugene Matcuk, George Deng, David Sampas, Nick Tsalenko, Anya Tabibiazar, Raymond Zhang, Ying Chen, Mary Talbi, Said Ho, Yen Dong Wang, James Tsao, Philip S Ben-Dor, Amir Yakhini, Zohar Bruhn, Laurakay Quertermous, Thomas |
description | 1 Donald W. Reynolds Cardiovascular Clinical Research Center, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California 94305
2 Agilent Technologies, Inc., Palo Alto, California 94304
Vascular endothelial cells maintain the interface between the systemic circulation and soft tissues and mediate critical processes such as inflammation in a vascular bed-selective fashion. To expand our understanding of the genetic pathways that underlie these specific functions, we have focused on the identification of novel genes that are differentially expressed in all endothelial cells, as well as restricted groups of this cell type. Virtual subtraction was conducted employing gene expression data deposited in public databases and 384 genes identified. 1
These genes were spotted on custom microarrays, along with 288 genes identified through subtraction cloning from TGF-ß-stimulated endothelial cells. Arrays were evaluated with RNA samples representing endothelial cells cultured from four vascular sources and five non-endothelial cell types. These studies identified 64 pan-endothelial markers that were differentially expressed with at least a threefold difference (range 3- to 55-fold). In addition, differences in gene expression profiles among endothelial cells from different vascular beds were identified. Validation of these findings was performed by RNA blot expression studies, and a number of the novel genes were shown to be expressed under angiogenic conditions in the developing mouse embryo. The combined tools of database mining and transcriptional profiling thus provide expanded knowledge of endothelial cell gene expression and endothelial cell biology.
transcriptional profiling; vascular; expression database; cell specificity; angiogenesis |
doi_str_mv | 10.1152/physiolgenomics.00186.2002 |
format | Article |
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2 Agilent Technologies, Inc., Palo Alto, California 94304
Vascular endothelial cells maintain the interface between the systemic circulation and soft tissues and mediate critical processes such as inflammation in a vascular bed-selective fashion. To expand our understanding of the genetic pathways that underlie these specific functions, we have focused on the identification of novel genes that are differentially expressed in all endothelial cells, as well as restricted groups of this cell type. Virtual subtraction was conducted employing gene expression data deposited in public databases and 384 genes identified. 1
These genes were spotted on custom microarrays, along with 288 genes identified through subtraction cloning from TGF-ß-stimulated endothelial cells. Arrays were evaluated with RNA samples representing endothelial cells cultured from four vascular sources and five non-endothelial cell types. These studies identified 64 pan-endothelial markers that were differentially expressed with at least a threefold difference (range 3- to 55-fold). In addition, differences in gene expression profiles among endothelial cells from different vascular beds were identified. Validation of these findings was performed by RNA blot expression studies, and a number of the novel genes were shown to be expressed under angiogenic conditions in the developing mouse embryo. The combined tools of database mining and transcriptional profiling thus provide expanded knowledge of endothelial cell gene expression and endothelial cell biology.
transcriptional profiling; vascular; expression database; cell specificity; angiogenesis</description><identifier>ISSN: 1094-8341</identifier><identifier>EISSN: 1531-2267</identifier><identifier>DOI: 10.1152/physiolgenomics.00186.2002</identifier><identifier>PMID: 12644598</identifier><language>eng</language><publisher>United States: Am Physiological Soc</publisher><subject>Adult ; Animals ; Cells, Cultured ; Child, Preschool ; Computational Biology - methods ; Databases, Genetic ; Endothelium, Vascular - chemistry ; Endothelium, Vascular - cytology ; Endothelium, Vascular - metabolism ; Female ; Gene Expression Profiling - methods ; Gene Expression Regulation - genetics ; Genes - genetics ; Genes - physiology ; Genome, Human ; Humans ; In Situ Hybridization - methods ; Infant ; Infant, Newborn ; Male ; Mice ; Middle Aged ; Oligonucleotide Array Sequence Analysis - methods ; Organ Specificity - genetics ; Sequence Homology, Nucleic Acid ; Tumor Cells, Cultured</subject><ispartof>Physiological genomics, 2003-05, Vol.13 (3), p.249-262</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c512t-36909fd8d354bb2f0c4e9c9f94c58f194a76f7087d782f9c2704f3906fadd8e63</citedby><cites>FETCH-LOGICAL-c512t-36909fd8d354bb2f0c4e9c9f94c58f194a76f7087d782f9c2704f3906fadd8e63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,3026,27905,27906</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/12644598$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ho, Michael</creatorcontrib><creatorcontrib>Yang, Eugene</creatorcontrib><creatorcontrib>Matcuk, George</creatorcontrib><creatorcontrib>Deng, David</creatorcontrib><creatorcontrib>Sampas, Nick</creatorcontrib><creatorcontrib>Tsalenko, Anya</creatorcontrib><creatorcontrib>Tabibiazar, Raymond</creatorcontrib><creatorcontrib>Zhang, Ying</creatorcontrib><creatorcontrib>Chen, Mary</creatorcontrib><creatorcontrib>Talbi, Said</creatorcontrib><creatorcontrib>Ho, Yen Dong</creatorcontrib><creatorcontrib>Wang, James</creatorcontrib><creatorcontrib>Tsao, Philip S</creatorcontrib><creatorcontrib>Ben-Dor, Amir</creatorcontrib><creatorcontrib>Yakhini, Zohar</creatorcontrib><creatorcontrib>Bruhn, Laurakay</creatorcontrib><creatorcontrib>Quertermous, Thomas</creatorcontrib><title>Identification of endothelial cell genes by combined database mining and microarray analysis</title><title>Physiological genomics</title><addtitle>Physiol Genomics</addtitle><description>1 Donald W. Reynolds Cardiovascular Clinical Research Center, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California 94305
2 Agilent Technologies, Inc., Palo Alto, California 94304
Vascular endothelial cells maintain the interface between the systemic circulation and soft tissues and mediate critical processes such as inflammation in a vascular bed-selective fashion. To expand our understanding of the genetic pathways that underlie these specific functions, we have focused on the identification of novel genes that are differentially expressed in all endothelial cells, as well as restricted groups of this cell type. Virtual subtraction was conducted employing gene expression data deposited in public databases and 384 genes identified. 1
These genes were spotted on custom microarrays, along with 288 genes identified through subtraction cloning from TGF-ß-stimulated endothelial cells. Arrays were evaluated with RNA samples representing endothelial cells cultured from four vascular sources and five non-endothelial cell types. These studies identified 64 pan-endothelial markers that were differentially expressed with at least a threefold difference (range 3- to 55-fold). In addition, differences in gene expression profiles among endothelial cells from different vascular beds were identified. Validation of these findings was performed by RNA blot expression studies, and a number of the novel genes were shown to be expressed under angiogenic conditions in the developing mouse embryo. The combined tools of database mining and transcriptional profiling thus provide expanded knowledge of endothelial cell gene expression and endothelial cell biology.
transcriptional profiling; vascular; expression database; cell specificity; angiogenesis</description><subject>Adult</subject><subject>Animals</subject><subject>Cells, Cultured</subject><subject>Child, Preschool</subject><subject>Computational Biology - methods</subject><subject>Databases, Genetic</subject><subject>Endothelium, Vascular - chemistry</subject><subject>Endothelium, Vascular - cytology</subject><subject>Endothelium, Vascular - metabolism</subject><subject>Female</subject><subject>Gene Expression Profiling - methods</subject><subject>Gene Expression Regulation - genetics</subject><subject>Genes - genetics</subject><subject>Genes - physiology</subject><subject>Genome, Human</subject><subject>Humans</subject><subject>In Situ Hybridization - methods</subject><subject>Infant</subject><subject>Infant, Newborn</subject><subject>Male</subject><subject>Mice</subject><subject>Middle Aged</subject><subject>Oligonucleotide Array Sequence Analysis - methods</subject><subject>Organ Specificity - genetics</subject><subject>Sequence Homology, Nucleic Acid</subject><subject>Tumor Cells, Cultured</subject><issn>1094-8341</issn><issn>1531-2267</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkV1rFDEUhoMotlb_ggQvvJs13x_eiBRbCwVv2rtCyORjN5KZrJNZdP692e4WoVJ6dc6B93nPSV4APmC0wpiTT9vNUlPJ6zCWIbm6QggrsSIIkRfgFHOKO0KEfNl6pFmnKMMn4E2tP5uOScVfgxNMBGNcq1Nwd-XDOKeYnJ1TGWGJMIy-zJuQk83QhZxhWxQq7BfoytCnMXjo7Wx7WwMc0pjGNbSjb62bip0mu7TR5nZifQteRZtreHesZ-D24tvN-ffu-sfl1fnX685xTOaOCo109MpTzvqeRORY0E5HzRxXEWtmpYgSKemlIlE7IhGLVCMRrfcqCHoGPh58t1P5tQt1NkOq-9PtGMquGkmJIkLgZ4VYSc0R3zt-Pgjbm2qdQjTbKQ12WgxGZh-CeRSCuQ_B7ENo8Pvjll0_BP8PPf56E9CDYJPWm99pCg9uZb38Z4ypoYYw3agvT1MXu5xvwp_5Mf5Am62P9C8DxbTM</recordid><startdate>20030513</startdate><enddate>20030513</enddate><creator>Ho, Michael</creator><creator>Yang, Eugene</creator><creator>Matcuk, George</creator><creator>Deng, David</creator><creator>Sampas, Nick</creator><creator>Tsalenko, Anya</creator><creator>Tabibiazar, Raymond</creator><creator>Zhang, Ying</creator><creator>Chen, Mary</creator><creator>Talbi, Said</creator><creator>Ho, Yen Dong</creator><creator>Wang, James</creator><creator>Tsao, Philip S</creator><creator>Ben-Dor, Amir</creator><creator>Yakhini, Zohar</creator><creator>Bruhn, Laurakay</creator><creator>Quertermous, Thomas</creator><general>Am Physiological Soc</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>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20030513</creationdate><title>Identification of endothelial cell genes by combined database mining and microarray analysis</title><author>Ho, Michael ; Yang, Eugene ; Matcuk, George ; Deng, David ; Sampas, Nick ; Tsalenko, Anya ; Tabibiazar, Raymond ; Zhang, Ying ; Chen, Mary ; Talbi, Said ; Ho, Yen Dong ; Wang, James ; Tsao, Philip S ; Ben-Dor, Amir ; Yakhini, Zohar ; Bruhn, Laurakay ; Quertermous, Thomas</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c512t-36909fd8d354bb2f0c4e9c9f94c58f194a76f7087d782f9c2704f3906fadd8e63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Adult</topic><topic>Animals</topic><topic>Cells, Cultured</topic><topic>Child, Preschool</topic><topic>Computational Biology - methods</topic><topic>Databases, Genetic</topic><topic>Endothelium, Vascular - chemistry</topic><topic>Endothelium, Vascular - cytology</topic><topic>Endothelium, Vascular - metabolism</topic><topic>Female</topic><topic>Gene Expression Profiling - methods</topic><topic>Gene Expression Regulation - genetics</topic><topic>Genes - genetics</topic><topic>Genes - physiology</topic><topic>Genome, Human</topic><topic>Humans</topic><topic>In Situ Hybridization - methods</topic><topic>Infant</topic><topic>Infant, Newborn</topic><topic>Male</topic><topic>Mice</topic><topic>Middle Aged</topic><topic>Oligonucleotide Array Sequence Analysis - methods</topic><topic>Organ Specificity - genetics</topic><topic>Sequence Homology, Nucleic Acid</topic><topic>Tumor Cells, Cultured</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ho, Michael</creatorcontrib><creatorcontrib>Yang, Eugene</creatorcontrib><creatorcontrib>Matcuk, George</creatorcontrib><creatorcontrib>Deng, David</creatorcontrib><creatorcontrib>Sampas, Nick</creatorcontrib><creatorcontrib>Tsalenko, Anya</creatorcontrib><creatorcontrib>Tabibiazar, Raymond</creatorcontrib><creatorcontrib>Zhang, Ying</creatorcontrib><creatorcontrib>Chen, Mary</creatorcontrib><creatorcontrib>Talbi, Said</creatorcontrib><creatorcontrib>Ho, Yen Dong</creatorcontrib><creatorcontrib>Wang, James</creatorcontrib><creatorcontrib>Tsao, Philip S</creatorcontrib><creatorcontrib>Ben-Dor, Amir</creatorcontrib><creatorcontrib>Yakhini, Zohar</creatorcontrib><creatorcontrib>Bruhn, Laurakay</creatorcontrib><creatorcontrib>Quertermous, Thomas</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>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Physiological genomics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ho, Michael</au><au>Yang, Eugene</au><au>Matcuk, George</au><au>Deng, David</au><au>Sampas, Nick</au><au>Tsalenko, Anya</au><au>Tabibiazar, Raymond</au><au>Zhang, Ying</au><au>Chen, Mary</au><au>Talbi, Said</au><au>Ho, Yen Dong</au><au>Wang, James</au><au>Tsao, Philip S</au><au>Ben-Dor, Amir</au><au>Yakhini, Zohar</au><au>Bruhn, Laurakay</au><au>Quertermous, Thomas</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of endothelial cell genes by combined database mining and microarray analysis</atitle><jtitle>Physiological genomics</jtitle><addtitle>Physiol Genomics</addtitle><date>2003-05-13</date><risdate>2003</risdate><volume>13</volume><issue>3</issue><spage>249</spage><epage>262</epage><pages>249-262</pages><issn>1094-8341</issn><eissn>1531-2267</eissn><abstract>1 Donald W. Reynolds Cardiovascular Clinical Research Center, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California 94305
2 Agilent Technologies, Inc., Palo Alto, California 94304
Vascular endothelial cells maintain the interface between the systemic circulation and soft tissues and mediate critical processes such as inflammation in a vascular bed-selective fashion. To expand our understanding of the genetic pathways that underlie these specific functions, we have focused on the identification of novel genes that are differentially expressed in all endothelial cells, as well as restricted groups of this cell type. Virtual subtraction was conducted employing gene expression data deposited in public databases and 384 genes identified. 1
These genes were spotted on custom microarrays, along with 288 genes identified through subtraction cloning from TGF-ß-stimulated endothelial cells. Arrays were evaluated with RNA samples representing endothelial cells cultured from four vascular sources and five non-endothelial cell types. These studies identified 64 pan-endothelial markers that were differentially expressed with at least a threefold difference (range 3- to 55-fold). In addition, differences in gene expression profiles among endothelial cells from different vascular beds were identified. Validation of these findings was performed by RNA blot expression studies, and a number of the novel genes were shown to be expressed under angiogenic conditions in the developing mouse embryo. The combined tools of database mining and transcriptional profiling thus provide expanded knowledge of endothelial cell gene expression and endothelial cell biology.
transcriptional profiling; vascular; expression database; cell specificity; angiogenesis</abstract><cop>United States</cop><pub>Am Physiological Soc</pub><pmid>12644598</pmid><doi>10.1152/physiolgenomics.00186.2002</doi><tpages>14</tpages></addata></record> |
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subjects | Adult Animals Cells, Cultured Child, Preschool Computational Biology - methods Databases, Genetic Endothelium, Vascular - chemistry Endothelium, Vascular - cytology Endothelium, Vascular - metabolism Female Gene Expression Profiling - methods Gene Expression Regulation - genetics Genes - genetics Genes - physiology Genome, Human Humans In Situ Hybridization - methods Infant Infant, Newborn Male Mice Middle Aged Oligonucleotide Array Sequence Analysis - methods Organ Specificity - genetics Sequence Homology, Nucleic Acid Tumor Cells, Cultured |
title | Identification of endothelial cell genes by combined database mining and microarray analysis |
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