(Investigative Ophthalmology and Visual Science. 2008;49:1886-1897.)
© 2008 by The Association for Research in Vision and Ophthalmology, Inc.
DOI: 10.1167/iovs.07-0414
Gene Expression Profiles of Human Trabecular Meshwork Cells Induced by Triamcinolone and Dexamethasone
Bao Jian Fan,1,2,3
Dan Yi Wang,1,2,3
Clement Chee Yung Tham,1
Dennis Shun Chiu Lam,1 and
Chi Pui Pang1
1From the Department of Ophthalmology and Visual Sciences, the Chinese University of Hong Kong, Hong Kong, China.
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Abstract
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PURPOSE. Triamcinolone acetonide (TA) and dexamethasone (DEX) are corticosteroids commonly used for ocular inflammation, but both can cause ocular hypertension. In this study, the differential gene expression profile of human trabecular meshwork (TM) cells in response to treatment by TA in comparison with DEX was investigated.
METHODS. Total RNA was extracted from cultured human TM cells treated with TA or DEX and used for microarray gene expression analysis. The microarray experiments were repeated three times. Differentially expressed genes were identified by an empiric Bayes approach and confirmed by real-time quantitative PCR.
RESULTS. TA (0.1 mg/mL) treatment resulted in 15 genes upregulated and 12 genes downregulated, whereas 1 mg/mL TA resulted in 36 genes upregulated and 21 genes downregulated. These genes were mainly associated with acute-phase response, cell adhesion, cell cycle and growth, growth factor, ion binding, metabolism, proteolysis and transcription factor. Two genes, MYOC and GAS1, were upregulated, and three genes, SENP1, ZNF343, and SOX30, were downregulated by both TA and DEX treatment. Eight differentially expressed genes were located in known primary open-angle glaucoma (POAG) loci, including MYOC, SOAT1, CYP27A1, SPOCK, SEMA6A, EGR1, GAS1, and ATP10A.
CONCLUSIONS. Differential gene expression profiles of human TM cells treated by TA and DEX, and a dosage effect by TA, were revealed by microarray technology. TA and DEX treatment shared several differentially expressed genes, suggesting a common mechanism to cause ocular hypertension. Some differentially expressed genes located in the known POAG loci are potential candidates for glaucoma genes.
Corticosteroids such as triamcinolone acetonide (TA) and dexamethasone (DEX) are potent and effective modalities available for the treatment of ocular inflammation.1 2 TA is a sustained-release crystalline form of cortisone, which may provide intraocularly available cortisone for a longer period than soluble cortisone.3 4 TA crystals can be injected directly to the vitreous, and soluble TA can still be detected in the aqueous humor for 9 months or longer after intravitreous injection of 25 mg of TA.5 However, TA treatment very often induces elevation in intraocular pressure (IOP), which is a risk factor for the development of glaucoma.6 7 DEX is a widely used topical ocular anti-inflammatory drug,2 but it can also cause an increase in IOP and subsequently, glaucoma.8 Corticosteroids like TA and DEX are believed to decrease outflow of aqueous humor by inhibiting degradation of extracellular matrix (ECM) material in the trabecular meshwork (TM), leading to aggregation of an excessive amount of the material within the outflow channels and a subsequent increase in outflow resistance.9 10 Ultimately, the elevated IOP increases the risk of optic nerve fiber damage indistinguishable from those associated with primary open-angle glaucoma (POAG).2 Investigation into the molecular mechanism of this form of secondary ocular hypertension or glaucoma would provide new insights into the etiology of POAG.
Cultured human TM cells share many properties with human TM cells in situ11 and are commonly used to study the biological effects of corticosteroids. Study of the prolonged biological effects of DEX on human TM cells in culture has helped to identify the first glaucoma gene, MYOC.12 13 In recent years, microarray technology has been successfully used to identify changes in gene expression profiles of human TM cells in culture in response to DEX treatment.14 15 16 17 There are both consistencies and differences in the gene expression profiles obtained in these studies. We have previously used a microarray with 2400 genes to study the effects of DEX on gene expression in human TM cells.16 In the present study, we investigated for the first time the differential gene expression profile of human TM cells in response to TA in comparison with DEX. Microarrays containing 41,421 cDNA probes were used to study TA and DEX effects in parallel.
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Methods
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Cell Culture and Treatment
A human TM cell line was established from trabecular specimens obtained postmortem from a 52-year-old male Caucasian patient with no personal or family history of glaucoma.11 The tissue was obtained and managed in conformity with the Declaration of Helsinki. The cells were grown in Dulbeccos modified Eagles medium (DMEM), supplemented with 10% fetal bovine serum, 100 U/mL penicillin, and 100 µg/mL streptomycin sulfate and maintained in a humidified 5% CO2 environment at 37°C. All culture reagents were obtained from Invitrogen Corp. (Carlsbad, CA). The eighth-passage cells at 80% confluence were used for corticosteroid treatment. The TA (Kenacort-A; Bristol-Myers-Squibb, New York, NY) dosage concentrations, 0.1 mg/mL and 1 mg/mL, were derived from reported experiments and clinical practice.4 18 Intravitreous injection of 1 mg/mL TA has been widely applied in clinical practice in the treatment of various posterior segment diseases.4 TA 0.1 mg/mL was used because the TA is less concentrated in aqueous humor after intravitreous injection. The vehicle, 0.0025% and 0.025% benzyl alcohol (BA; Sigma-Aldrich Chemie GmbH, Munich, Germany), was used as the control. The cells were maintained for 12 hours before harvesting. The time for TA treatment was determined by a parallel study on two selected index genes, MYOC and GAS1, which had been reported to be consistently upregulated in TM cells by DEX treatment.14 15 16 17 Briefly, the human TM cells after exposure to TA (0.1 mg/mL, 1 mg/mL) or BA (0.0025%, 0.025%) were collected at 0, 10, 20, 30, 50, and 80 minutes and 2, 12, 24 and 48 hours for RNA extraction. The ratios of gene expression levels at each time point against those at 0 minutes were normalized with GAPDH. All experiments were performed in triplicate by RT-qPCR. An unpaired t-test was applied to compare the changes in gene expression between TA and BA treatment.
For DEX treatment, 100 nM DEX (Weimer Pharma GmbH, Rastatt, Germany) was used as in previous studies.16 19 The vehicle, 1.1 µM BA (Sigma-Aldrich Chemie GmbH) was used as the control. The cells were maintained for 7 days before harvesting. The time for DEX treatment was based on clinical practice.14 During DEX treatment, the medium was changed every other day. Three replicates consisting of individual sets of treated and control cells were prepared for each treatment (n = 3).
RNA Extraction
The human TM cells after TA or DEX treatment were harvested and homogenized using a shredder column (QIA column; Qiagen, Hilden, Germany). Total RNA was extracted (RNeasy mini kit; Qiagen) and RNA yield determined with a spectrophotometer (model ND-1000; NanoDrop Technologies, Wilmington, DE). The RNA quality was assessed by the ratio of ribosomal bands 28S and 18S (Gel Doc 2000 System; Bio-Rad Laboratories, Hercules, CA). The yield of total RNA extracted from TA- or DEX-treated human TM cells were comparable with that from control cells treated with benzyl alcohol, ranging from 67 to 233 µg RNA/plate (0.1 mg/mL TA: 104 ± 17 µg RNA/plate, n = 3; 0.0025% BA vehicle: 117 ± 47 µg RNA/plate, n = 3; 1 mg/mL TA: 134 ± 12 µg RNA/plate, n = 3; 0.025% BA vehicle: 167 ± 40 µg RNA/plate, n = 3; 100 nM DEX: 147 ± 52 µg RNA/plate, n = 3; 1.1 µM BA vehicle: 198 ± 55 µg RNA/plate, n = 3). The quality of RNA was also consistent among the samples, with rRNA ratio (28S/18S) ranging between 1.8 and 2.0. Thus, all RNA preparations in this study were deemed satisfactory for hybridization to the microarrays.
Microarray Experiments and Data Analysis
All the microarray experiments were performed in our laboratory. Coated human cDNA microarrays20 21 (UltraGAPS; Stanford Functional Genomics Facility, Stanford, CA; http://www.microarray.org/sfgf/jsp/home.jsp) containing 41,421 cDNA probes representing 22,904 unique Unigene gene clusters (Unigene Build Number 173; http://www.ncbi.nlm.nih.gov/UniGene; provided in the public domain by the National Center for Biotechnology Information, Bethesda, MD) were used. The cDNA probes were derived from IMAGE (Integrated Molecular Analysis of Genomes and their Expression) Consortium clones from the Research Genetics Sequence Verified clone set (http://www.invitrogen.com/content/sfs/manuals/sequenceverifiedclones_man.pdf) and CGAP (Cancer Genome Anatomy Project, National Cancer Institute, Bethesda, MD) clone set (http://cgap.nci.nih.gov/Genes/PurchaseReagents; National Institutes of Health, Bethesda, MD). At the time of our experiments this array represented the largest number of genes compared with other type of arrays (e.g., U133A; Affymetrix, Santa Clara, CA). It was not capable of differentiating between splice variants. However, it was more sensitive than other oligonucleotide-based microarrays, because it possessed longer probes and more genes. The same lot of microarrays (print batch: SHEW) was used for all microarray experiments. An equal amount of total RNA obtained from TM cells treated with TA or DEX and their controls was reverse transcribed into cDNA and labeled with Cy3 and Cy5 respectively (CyScribe Post-Labeling kit; GE Healthcare, Amersham, UK). The first step involved the incorporation of amino allyl-dUTP during cDNA synthesis using an optimized nucleotide mix, and the second step involved chemically labeling the amino allyl-modified cDNA (CyDye NHS-ester; GE Healthcare). The labeled cDNA was hybridized to the microarray at 42°C for 16 hours, and scanned (ScanArray 4000 scanner; Packard Biochip Technologies, Billerica, MA).
Image acquisition and raw signal intensity extraction were performed (ScanArray ver. 2.1 and QuantArray ver. 3.0, respectively; Packard Biochip Technologies). The fluorescent images were visually inspected to flag and exclude the abnormal spots with irregular shape or dirt. To be consistent across arrays and under different experimental conditions, 62 (0.15%) abnormal spots found in any arrays were excluded from all subsequent analyses. Data analysis was performed using the Bioconductor (http://www.bioconductor.org)22 statistics package Limma (ver. 2.7.9; http://bioinf.wehi.edu.qu/limma)23 implemented on R ver. 2.3.1 for windows (http://www.r-project.org). The print-tip loess normalization method was used for within-array normalization. The quantile normalization method was used for between-array normalization.24 Differentially expressed genes were identified by an empiric Bayes approach.25 The B-statistic is the log-odds that a gene is differentially expressed that has been adjusted for multiple testing. We based our gene selection on a B-statistic >2, meaning that these were >100 times more likely to be differentially expressed than to remain unaffected. To be comparable with published data, the probability was computed based on the distribution of the moderated t-statistics. The probability was adjusted for multiple testing using the FDR method.26
Genes with statistically significant difference were classified into gene families using the Ingenuity Pathways Knowledge Base database (Ingenuity Systems Inc., Mountain View, CA). Genes absent from the Ingenuity database were classified according to their reported functions or using the databases of Gene Ontology (http://www.geneontology.org/) or SwissProt (http://srs.ebi.ac.uk/srsbin/cgi-bin/wgetz).
Real-Time Quantitative PCR
Gene-specific RT-qPCR was used to confirm the differentially expressed genes identified from the microarray experiments. First-strand cDNA for RT-qPCR was synthesized from 500 ng of RNA using random primer p[dN]6 (Roche Diagnostics, Mannheim, Germany) and a reverse transcriptase kit with RNase inhibitor (Superscript III Reverse Transcriptase kit and RNase OUT inhibitor; Invitrogen). The amount of cDNA corresponding to 25 ng of RNA was amplified with intron-spanning primers (Table 1) . RT-qPCR was performed using SYBR green PCR master mix (Bio-Rad Laboratories), according to the manufacturers instructions, on a sequence detection system (prism 7000; Applied Biosystems, Inc. [ABI], Foster City, CA). The thermocycler parameters were 95°C for 2 minutes, 40 cycles of 95°C for 15 seconds, and 60°C for 1 minute. All PCR reactions were performed in triplicate.
Relative quantification of gene expression was performed using the standard curve method (User Bulletin 2; Prism 7000 Sequence Detection System; ABI) and normalized to the housekeeping gene GAPDH expression level. Mean Ct (threshold cycle: the cycle at which the increase in signal associated with exponential growth of PCR product was first detected) of the TA or DEX treated sample was compared to that of the untreated control sample by using the Ct of GAPDH as an internal control.
Ct was calculated as the difference in Ct values derived from the target gene (in each sample assayed) and the GAPDH gene, while 
Ct represented the difference between the paired samples. The changes (x-fold) of expression level for upregulated genes were expressed as 2–
Ct, whereas those for downregulated genes were expressed as –2
Ct. All data were expressed as the mean ± SD.
Replication from a Different TM Cell Line Treated with DEX
Gene expressions induced by DEX were further studied in a second TM cell line from a different source.27 It was obtained from a 56-year-old male Caucasian patient with no personal or family history of glaucoma. After treatment by 100 nM DEX for 7 days, 19 genes were investigated by RT-qPCR (Table 1) , including an additional four genes previously reported to be highly upregulated by DEX, ANGPTL7,17 PEDF,14 15 APOD,15 17 and TAGLN.16 17 The conditions for cell culture, DEX treatment, RNA extraction and RT-qPCR were the same as those for the first TM cell line.
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Results
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Determination of the Time for TA Treatment
Compared with the vehicles, both 0.1- and 1-mg/mL TA treatments induced expression of MYOC at 2 hours (P < 0.05) and reached the highest expression at 12 hours (P < 0.01; Fig. 1A ). Similarly, both TA concentrations induced expression of GAS1 at 80 minutes and 2 hours (P < 0.05) and reached the peak expression at 12 hours (P < 0.01). Elevated expression of GAS1 remained significant at 24 hours (P < 0.05; Fig. 1B ). Our results showed that both MYOC and GAS1 were most upregulated at 12 hours in both TA concentrations. Although the time for their highest gene expression may not be the same for other genes, this time point should be appropriate and relevant, since they were reported to be consistently upregulated in TM cells by DEX treatment.14 15 16 17 We therefore used 12 hours for TA treatment in the present study.

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FIGURE 1. Changes in gene expression of MYOC (A) and GAS1 (B) after TA treatment. The ratios of gene expression levels at each time point against those at 0 minutes were normalized with GAPDH. All experiments were performed in triplicate by RT-qPCR. Unpaired t-test was used to compare the gene expression changes between TA and BA treatment. *P < 0.05; **(horizontal) P < 0.01; **(vertical) significant gene expression observed in both TA concentrations (P < 0.05).
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Differentially Expressed Genes in 0.1 and 1 mg/mL TA
The human TM cells treated with 0.1 mg/mL TA resulted in a significant expression level change in 27 genes (B-statistic > 2; Table 2 ). Among them, 15 genes were upregulated with changes multiples ranging from 2.33- to 9.86-fold, whereas 12 genes were downregulated, with changes ranging from –2.27- to –33.33-fold. The MYOC gene was the most upregulated gene, increased by 9.86-fold. The housekeeping gene and the other four glaucoma-related genes were not differentially expressed (B-statistic < –2). TA (1 mg/mL) caused a significant expression level change in 57 genes (B-statistic > 2; Table 3 ). Among them, 36 genes were upregulated ranging from 2.49- to 12.60-fold, whereas 21 genes were downregulated from –2.50- to –11.11-fold. MYOC was upregulated by the largest change 12.60-fold. The housekeeping gene and other four glaucoma-related genes were not differentially expressed (B-statistic < –2).
Intriguingly, when compared to 0.1 mg/mL TA, 1 mg/mL TA resulted in an additional 24 genes upregulated and 13 genes downregulated. On the contrary, only three upregulated genes (HIPK2, SERPINA3, and EDNRA) and four downregulated genes (MARVELD2, TCF7L2, COL13A1, and IRF2) were induced by 0.1 mg/mL TA, but not by 1 mg/mL TA. This suggests a strong dosage effect of TA on gene expression of human TM cells (Fig. 2 , Tables 2 3 ).

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FIGURE 2. Venn diagrams showing the differentially expressed genes between 0.1 mg/mL TA, 1 mg/mL TA, and DEX treatments.
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Differentially Expressed Genes in DEX
DEX resulted in a significant change in expression levels of 29 genes (B-statistic > 2; Table 4 ): 14 genes upregulated at 2.36- to 10.62-fold and 15 genes downregulated at –2.54- to –14.93-fold. MYOC was the most upregulated gene at 10.62-fold. The housekeeping gene and the other four glaucoma-related genes were not differentially expressed (B-statistic < –2).
Differentially Expressed Genes Induced by Both TA and DEX
Five genes were differentially expressed at both concentrations (0.1 and 1 mg/mL) of TA and DEX (Fig. 2) : two upregulated genes (MYOC and GAS1) and three downregulated genes (SENP1, ZNF343, and SOX30). Another three genes (SERPINA3, HIPK2, and TCF7L2) were differentially expressed at 0.1 mg/mL TA and DEX. Two other genes (MT1X and IGFBP3) were differentially expressed in 1 mg/mL TA and DEX (Fig. 2) . Notably, the up- or downregulations for these genes were consistent in TA or DEX (Tables 2 3 4) . Twenty genes were differentially expressed in both 0.1 and 1 mg/mL TA: 12 upregulated genes (MYOC, MT2A, GAS1, MT1G, CSNK1G2, MT1F, SF1, MT1L, IRF7, AGXT, DNA2L, and MED6) and 8 downregulated genes (SENP1, ZNF343, SOX30, HNT, FOS, SPRY1, TREH, and CD44; Tables 2 3 ).
RT-qPCR Confirmation of Differentially Expressed Genes
To confirm the microarray results, we chose a subset of 10 genes for validation by RT-qPCR. These genes were either highly upregulated (MYOC, GAS1, SERPINA3, HIPK2, SCD, MT1X, and IGFBP2) or highly downregulated (HNT, SENP1, and IGFBP3) in the microarray analysis. In addition, four glaucoma-related genes (OPTN, WDR36, CYP1B1, and APOE) were also included for RT-qPCR.28 Consistent results were obtained (Table 5 , Fig. 3 ). Microarray experiments demonstrated that the housekeeping gene GAPDH had no significant change in expression between treated TM cells and control cells under various conditions (changes were –1.05-, 1.09-, and –1.05-fold in 0.1 mg/mL TA–, 1 mg/mL TA–, and DEX-treated TM cells, respectively; B-statistic < –3.6).

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FIGURE 3. RT-qPCR confirmation of expression changes for selected genes between treated and untreated human TM cells. The data were normalized with GAPDH, and the changes were calculated. *P < 0.05; **P < 0.01 (t-test, n = 3).
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Consistent results were obtained from replicating DEX induction effects on gene expressions in a different TM cell line. All eight differentially expressed genes due to DEX treatment in the first TM cell line were also upregulated (MYOC, GAS1, SERPINA3, HIPK2, MT1X, and IGFBP2) or downregulated (SENP1 and IGFBP3). The other 10 genes with expression that was not affected by DEX treatment in the first cell line (SCD, HNT, OPTN, WDR36, CYP1B1, APOE, ANGPTL7, PEDF, APOD, and TAGLN) were also not differentially expressed in the second cell line (Table 5) .
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Discussion
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In the present study, the differential gene expression profile of human TM cells in response to TA was investigated for the first time. We found expressions of several genes affected both by TA and DEX treatment. The microarray results were confirmed by RT-qPCR. The microarray raw data have been submitted to NCBI Gene Expression Omnibus (GEO, series accession number: GSE6298).
The genes affected by TA could be grouped into nine categories according to their functions: acute-phase response, cell adhesion, cell cycle and growth, growth factor, ion binding, metabolism, proteolysis, transcription factors, and others. Such diversity is consistent with the existence of numerous regulatory mechanisms in the human TM in response to biochemical disturbances.29 Some of these genes are potentially associated with ocular hypertension and subsequently glaucoma. They added to the pool of putative genes for glaucoma. Many genes attributed to glaucoma are still to be identified, since mutations in all known glaucoma genes can only account for no more than 10% of patients with glaucoma.28
GAS1, HIPK2, DCBLD2, and SFRP2 are involved in cell cycle and growth. GAS1 encodes an integral membrane protein and suppresses cell proliferation by blocking entry to the S-phase.30 GAS1 may interact with integrins and modify the attachment of cells to the ECM.31 Therefore its upregulation may inhibit cell proliferation, raise cell adhesion, and hence increase the outflow resistance of aqueous humor. Intriguingly, GAS1 was downregulated in human TM cells by treatment with transforming growth factor (TGF)-β132 and with overexpression of MYOC.33 TGF-β1 is a cytokine that alters ECM metabolism, and excess ECM has been shown to increase aqueous outflow resistance in the TM of glaucomatous eyes.34 However, the gene expression of TGFB1 was not altered by treatment with TA or DEX in the present study. On the other hand, MYOC was the most upregulated gene by TA or DEX treatment, whereas GAS1 was also upregulated in our study. This is consistent with previous reports.15 16 Although MYOC and GAS1 are most likely simultaneously involved in regulation of IOP, the underlying mechanism is unclear. HIPK2 encodes a conserved serine/threonine nuclear kinase that interacts with homeodomain transcription factors and inhibits cell growth.35 HIPK2 is an upstream protein kinase for PAX6 modulating PAX6-mediated transcriptional regulation which involves in organogenesis of the eye and central nervous system.36 However, its role in increasing IOP remains to be elucidated.
A group of genes encoding metallothioneins (MTs) were upregulated by TA: MT1E, MT1F, MT1G, MT1H, MT1K, MT1L, MT1X, and MT2A. But only MT1X was upregulated by DEX. MTs are a large family of proteins playing multiple roles including binding of toxic metals, free radical scavenging, and oxidative stress.37 In the TM, MTs are upregulated by DEX treatment13 and elevated IOP.38
We also found that TA affects upregulation of OSBP, SOAT1, AGXT, and downregulation of STC2, which regulate steroid hormone metabolism. Abnormal steroid metabolism in the human TM is associated with elevated IOP and glaucomatous optic neuropathy.15 Other genes encoding enzymes that regulate steroid metabolism, such as AKR1C1 and AKR1C3, have been reported to be induced by DEX in human TM.15 However, in the present study, OSBP, SOAT1, AGXT, and STC2 were affected by TA, but not by DEX.
TM treated with corticosteroids leads to a reduction in extracellular proteolytic activity of stromelysin and tissue plasminogen activator.39 Our results showed a large decrease in the expression of some genes that encode proteases, especially SENP1, suggesting induced regulation of proteolysis in human TM cells by TA. SENP1 is a sentrin-specific protease.40 In this study, a decrease in SENP1 expression is accompanied by an increase in expression in protease inhibitors such as SERPINA3, which is a plasma protease inhibitor and a member of the serine protease inhibitor class.41 Variations in SERPINA3 have been implicated in Alzheimers disease and Parkinsons disease for their antichymotrypsin effects.42 43
In addition, more than 10 genes encoding transcription factors were differentially expressed under TA treatment (Tables 2 3) . SF1, ZNF263, EGR1, and ZNF343 are zinc finger proteins that bind nucleic acids and regulate gene transcriptions.44 EGR1 was downregulated. Known as early growth response 1 and as nerve growth factor-induced clone A (NGF1A), it directly controls TGFB1 gene expression.45 Therefore, reduced expression of EGR1 by TA may lead to disruption in TGF-B1 activity in ECM metabolism and subsequent impairment of aqueous outflow which causes elevation in IOP.
Five genes were commonly differentially expressed by both TA and DEX: MYOC, GAS1, SENP1, ZNF343 and SOX30. Among them, MYOC was upregulated as expected. GAS1, encoding the growth arrest specific 1 protein, which suppresses cell proliferation in lung carcinoma cell lines, was also upregulated. GAS1 disrupts the attachment of cells to the ECM.31 The expression of SENP1, ZNF343, and SOX30 was reduced. SENP1 is involved in the degradation of ECM.40 ZNF343 and SOX30 are members of transcription factor genes. Like EGR1, ZNF343 is a zinc finger protein involved in ECM metabolism. Since excess ECM has been shown to increase aqueous outflow resistance in the TM of glaucomatous eyes,34 alteration in expressions of these genes and subsequent changes in the activities of their encoded proteins in the ECM may cause disruption of aqueous outflow through the TM.
Eight differentially expressed genes in human TM cells treated with TA or DEX were located in known POAG loci (Table 6) . Among them, SPOCK and EGR1 were downregulated and the rest upregulated. GAS1 was located in one locus (GLC1J) for juvenile-onset POAG.46 SPOCK, SEMA6A, and EGR1 were in another locus (GLC1M) for juvenile-onset POAG.47 Since high IOP is a characteristic feature of juvenile-onset POAG, these genes are potential candidates for this severe type of hypertensive glaucoma. The fact that four other known glaucoma related genes (OPTN, WDR36, CYP1B1, and APOE) were not differentially expressed in human TM cells treated with TA or DEX indicates that they may not be the cause of elevated IOP in high-tension glaucoma (Tables 2 3 4) .
Among the differentially expressed genes in this study, nine genes (MYOC, GAS1, SAA2, SERPINA3, HIPK2, IGFBP2, SAA1, MT1X, and CSPG2) have been reported in other microarray studies (Table 7) .14 15 16 17 SAA1 and SAA2 are serum amyloid genes that are arranged in a head-to-head transcriptional orientation.48 SAA1 and SAA2 are members of an acute-phase response family of proteins whose systemic concentrations dramatically change during the initial inflammatory process.49 The increased expression of IGFBP2 can modulate the biological actions of insulin-like growth factors (IGFs) by either enhancing50 or inhibiting51 ligand-receptor interactions, and provide storage for IGFs in the ECM. These genes are involved in the degradation of ECM, inflammation, and acute-phase response and ultimately may affect ECM formation in TM. Increased expressions of these genes may thus enhance the degradation of ECM that regulates the outflow resistance of aqueous humor.2 However, expressions of several genes which had been reported to be highly upregulated by DEX, such as, ANGPTL7,17 PEDF,14 15 APOD,15 17 and TAGLN,16 17 were found not to be affected by DEX in this study (B-statistic < –3). Notably, consistent results of unaffected expression of these genes were obtained from a different cell line in the present study (Table 5) . Experimental variations, such as the differences in the sources of the human TM, number of cell passages, exposure time to DEX, array type, and methodologies for data analysis may be reasons for such discrepancies.17 In this study, we used an empiric Bayes approach to identify differentially expressed genes. All significant genes had a B-statistic of at least 2 which approximately corresponded to P < 0.02, derived by t-test (Tables 2 3 4) .
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TABLE 7. Commonly Differentially Expressed Genes in Human TM Cells Induced by DEX between This Study and Published Studies
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In one study, MYOC change was 191.3-fold with qPCR and 16.7-fold with microarray.17 However, Lo et al.15 reported a similar change in MYOC between RT-PCR and microarray. The MYOC change was 315-fold with RT-PCR and 148-fold with micorarray. An even lower MYOC change in RT-PCR has been reported: the respective MYOC mRNA expression ratios for the four sample pairs were 4.1, 2.4, 1.5, and 1.7 with RT-PCR, and 3.2, 42.7, 47.3, and 2.4 with microarray.14 In this study, the MYOC change induced by DEX was 12.81-fold with RT-qPCR and 10.62-fold with microarray. We compared detailed changes between RT-qPCR and microarray and found that the RT-qPCR identified greater changes than microarray for most genes (Table 5) . The difference in array type and methodologies for image analysis may be the major reasons for such discrepancies between studies. Intriguingly, we found similar changes in MYOC between 12 hours of TA treatment and 7 days of DEX treatment (Table 5) . This suggests that TA could induce a MYOC increase in a shorter time than DEX. However, the underlying mechanism remains to be elucidated.
We found some differences in the effects of DEX on human TM gene expression from our previous study,16 although the same TM cell line was used. The culture conditions that we used previously16 followed those for establishment of this cell line.11 The time for DEX treatment was 10 days, and the cells were grown until 100% confluence before DEX treatment.16 In the present study, the time for DEX treatment was 7 days, and the cells were grown to 80% confluence before DEX treatment. We wanted to improve the culture conditions analogous to clinical practice and to apply the commonly used conditions for cell culture. Also, microarrays of 2400 genes were used,16 but, in the present study, we used microarrays of 41,421 probes. Consequently, more differentially expressed genes were identified. Despite such differences, three genes (MYOC, GAS1, and IGFBP2) were commonly identified by two studies.
In summary, the simultaneous investigation of gene expression profiles of human TM cells treated with TA and DEX provides a technical approach to the identification of candidate genes for glaucoma. Most of the genes identified from the present study are novel candidates that have not been directly implicated in IOP regulation. Some genes particularly merit attention, including the genes commonly differentially expressed under TA and DEX treatment (e.g., GAS1, SENP1, ZNF343, and SOX30) and the genes located in known POAG loci (e.g., SPOCK, SEMA6A, and EGR1). Future sequence analysis, association study, and functional analysis of these genes should be helpful in identifying glaucoma genes.
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Acknowledgements
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The authors thank Thai Nguyen for providing established human TM cell lines and Yuk Fai Leung for valuable comments.
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Footnotes
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2 Present affiliation: Department of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts. 
3 Contributed equally to the work and therefore should be considered equivalent authors. 
Supported by a block grant from the University Grants Committee, Hong Kong, and direct Grant 2040997 from the Medical Panel, the Chinese University of Hong Kong.
Submitted for publication April 5, 2007; revised August 15 and December 22, 2007; accepted March 24, 2008.
Disclosure: B.J. Fan, None; D.Y. Wang, None; C.C.Y. Tham, None; D.S.C. Lam, None; C.P. Pang, None
The publication costs of this article were defrayed in part by page charge payment. This article must therefore be marked "advertisement" in accordance with 18 U.S.C.
1734 solely to indicate this fact.
Corresponding author: Chi Pui Pang, Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Eye Hospital, 147K Argyle Street, Kowloon, Hong Kong; cppang{at}cuhk.edu.hk.
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