Physiol Genomics 13: 249–262, 2003. First published March 18, 2003; 10.1152/physiolgenomics.00186.2002. Identification of endothelial cell genes by combined database mining and microarray analysis Michael Ho,1 Eugene Yang,1 George Matcuk,1 David Deng,2 Nick Sampas,2 Anya Tsalenko,2 Raymond Tabibiazar,1 Ying Zhang,1 Mary Chen,1 Said Talbi,1 Yen Dong Ho,1 James Wang,1 Philip S. Tsao,1 Amir Ben-Dor,2 Zohar Yakhini,2 Laurakay Bruhn,2 and Thomas Quertermous1 1Donald W. Reynolds Cardiovascular Clinical Research Center, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California 94305; and 2Agilent Technologies, Inc., Palo Alto, California 94304 Submitted 30 December 2002; accepted in final form 14 March 2003 Ho, Michael, Eugene Yang, George Matcuk, David transcriptional profiling; vascular; expression database; cell Deng, Nick Sampas, Anya Tsalenko, Raymond Tabibi- specificity; angiogenesis azar, Ying Zhang, Mary Chen, Said Talbi, Yen Dong Ho, James Wang, Philip S. Tsao, Amir Ben-Dor, Zohar Ya- khini, Laurakay Bruhn, and Thomas Quertermous. Iden- IN ADDITION TO SERVING A BROAD range of physiological tification of endothelial cell genes by combined database functions, the endothelial cell is widely appreciated to mining and microarray analysis. Physiol Genomics 13: have a central role in the development of vascular 249–262, 2003. First published March 18, 2003; 10.1152/ disease. There has been a longstanding interest in physiolgenomics.00186.2002.—Vascular endothelial cells endothelial cell-specific gene expression, to identify maintain the interface between the systemic circulation and specific pathways for therapeutic targeting in this cell soft tissues and mediate critical processes such as inflamma- type. Primarily, genes specifically expressed in endo- tion in a vascular bed-selective fashion. To expand our un- thelial cells have been identified through molecular derstanding of the genetic pathways that underlie these cloning of molecules that mediate vascular wall-spe- specific functions, we have focused on the identification of cific processes. Endothelial genes identified in this novel genes that are differentially expressed in all endothe- lial cells, as well as restricted groups of this cell type. Virtual fashion include platelet endothelial cell adhesion mol- subtraction was conducted employing gene expression data ecule, vascular endothelial cell adhesion molecule, and deposited in public databases and 384 genes identified.1 endothelin-1, among others. In addition, a small num- These genes were spotted on custom microarrays, along with ber of directed efforts have sought to expand the rep- 288 genes identified through subtraction cloning from TGF- ertoire of endothelial cell genes through directed clon- ␤-stimulated endothelial cells. Arrays were evaluated with ing efforts, employing differential display and other RNA samples representing endothelial cells cultured from molecular methods (18, 37). At least one effort has four vascular sources and five non-endothelial cell types. employed the publicly available gene expression data- These studies identified 64 pan-endothelial markers that bases to identify endothelial genes (19). Unfortunately, were differentially expressed with at least a threefold differ- such databases are biased, depending on the cell types ence (range 3- to 55-fold). In addition, differences in gene chosen for study and the depth to which the libraries expression profiles among endothelial cells from different were sequenced. vascular beds were identified. Validation of these findings The development of high-throughput transcriptional was performed by RNA blot expression studies, and a num- profiling employing microarray technology has dra- ber of the novel genes were shown to be expressed under matically expanded the ability to characterize patterns angiogenic conditions in the developing mouse embryo. The of gene expression in isolated cells and normal and combined tools of database mining and transcriptional pro- diseased tissues. Originally applied to basic questions filing thus provide expanded knowledge of endothelial cell regarding metabolic pathways in model organisms gene expression and endothelial cell biology. such as yeast, there is now widespread use of the technology to answer a broad range of biological ques- Article published online before print. See web site for date of tions. Arrays have been employed to develop molecular publication (http://physiolgenomics.physiology.org). classifications of lymphoid tumors and melanoma, to Address for reprint requests and other correspondence: T. Quer- link metastasis of breast cancer to gene expression, termous, Division of Cardiovascular Medicine, Stanford Univ. School of Medicine, 300 Pasteur Drive, Falk CVRC, Stanford, CA 94305 and to provide new clues to the molecular basis of (E-mail: [email protected]). glioblastoma and melanoma (6, 24, 30, 32, 34, 39). 1 The microarray data derived through these experiments have Additional imaginative uses of microarrays include the been deposited in the GEO expression database at the NCBI and has study of downstream targets of developmental tran- been given the accession number GPL217, with others pending. Primary data and supplementary material associated with this scription factors and the genetic basis of circadian manuscript are being deposited at the following website: http:// rhythms (25, 31, 36). Transcriptional profiling with quertermous.stanford.edu. microarrays provides a novel approach to characteriz- 1094-8341/03 $5.00 Copyright © 2003 the American Physiological Society 249 250 IDENTIFICATION OF ENDOTHELIAL CELL GENES ing cell-specific gene expression and could be employed ments: 20 ng/ml hEGF, 25 ␮g/ml insulin, 25 ng/ml proges- to identify endothelial cell-specific genes. Indeed, mi- terone, 50 ng/ml transferrin, Clonetics GA-1000 at 1:100, and croarray methodology has already been employed to 5% FBS. NHK were cultured in keratinocyte basal medium-2 identify genes in endothelial cells that are responsive (CCMD 151, Clonetics) and the following growth supple- to cytokines and physical forces or activated in the ments: 0.03 mg/ml bovine pituitary extract, 0.1 ng/ml hEGF, 5 ␮g/ml insulin, 0.5 ␮g/ml hydrocortisone, 0.05 mg/ml trans- context of in vitro morphogenesis models (1, 3, 8, 9, 12, ferrin, Clonetics GA-1000 at 1:100, and 5% FBS. HMEC were 13, 21, 26–28, 40–43). cultured in mammary epithelial cell basal medium (modified As a method to identify minimally characterized MCDB 170, Clonetics) and the following growth supple- genes that are selectively expressed by endothelial ments: 52 ng/ml bovine pituitary extract (BPE), 10 ng/ml cells, we have coupled cloning-based gene expression hEGF, 0.5 ng/ml hydrocortisone, 5 ng/ml insulin, GA-1000 at databases that are available to the public with the 1:100, and 5% FBS. HepG2 were cultured in minimum es- high-throughput capability of microarrays. Using sential medium (Eagle’s) with 2 mM L-glutamine and Earle’s bioinformatics tools and queries designed to screen for BSS adjusted to contain 1.5 g/l sodium bicarbonate, 0.1 mM those genes with the highest level of differential ex- non-essential amino acids, 1.0 mM sodium pyruvate, and pression, we have identified 384 genes. These genes, 10% FBS. ␤ RNA isolation. RNA was isolated from cells employing a along with 288 TGF- -responsive genes, were placed combination of Trizol (Life Technologies, Rockville, MD) and on a custom-spotted cDNA microarray and probed with RNeasy columns (Qiagen, Valencia, CA) techniques. Briefly, RNA samples derived from endothelial and non-endo- media was removed, and 2 ml Trizol was used per 3 ϫ 106 thelial cells. It was possible to identify over 64 clones cells. Cells were sheared through a 21-gauge needle, this that were differentially expressed in endothelial cells, solution was extracted with chloroform, and the supernatant with a number of these being novel expressed sequence was mixed with 500 ␮l of 70% ethanol for every milliliter tags (ESTs) or putative expressed sequences deduced Trizol used. This mixture was then loaded and eluted from an from the human genome. Interestingly, the cultured RNeasy column for further purification. RNA quality and cells from different vascular beds were found to exhibit concentration were evaluated by gel visualization and spec- specific patterns of gene expression, likely reflecting trophotometric analysis. Database screening methodology. Top “endothelial-en- differences in their gene expression in vivo. Thus these riched” candidate genes were compiled from the UniGene, studies define a panel of unique endothelial genes and Serial Analysis of Gene Expression (SAGE), and BodyMap identify putative new vascular bed restricted markers. libraries as follows. MATERIALS AND METHODS Using the “library differential display” feature of UniGene ؍http://www.ncbi.nlm.nih.gov/UniGene/ddd.cgi?ORG) Cell culture. Human umbilical vein endothelial cells Hs), we generated a list of the top 100 genes representing (HUVEC), human aortic endothelial cells (HAEC), human those differentially expressed between endothelial cell lines coronary artery endothelial cells (HCAEC), human lung mi- (pool A) and all nonvascular cell lines (pool B). A metric was crovascular endothelial cells (HMVEC), human aortic developed termed the score; score ϭ pool A/(pool B ϩ smooth muscle cells (HASMC), human mammary epithelial 0.00001), with the “0.00001” factor added to prevent division cells (HMEC), normal human astrocytes (NHA), and normal by zero and to compensate for