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1From the Department of Molecular Ophthalmology, Lions Eye Institute and the 3Centre for Ophthalmology and Visual Science, The University of Western Australia, Nedlands, Australia; the 2Division of Genetics and Bioinformatics, Walter and Eliza Hall Institute for Medical Research, The Royal Melbourne Hospital, Parkville, Victoria, Australia; the 4Department of Statistics and Program in Biostatistics, University of California, Berkeley, Berkeley, California; the 5University of Western Australia Centre for Child Health Research, TVW Telethon Institute for Child Health Research, Subiaco, Australia; and the 6Western Australian Institute for Medical Research, Sir Charles Gairdner Hospital, Nedlands, Australia.
| Abstract |
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METHODS. Argon laser irradiation was delivered to the left eye of normal C57BL/6J mice (n = 30), with the right eye serving as the control in each animal. Three days after laser treatment, mice were culled, eyes enucleated, and the retinas dissected and pooled into respective groups. The total RNA of replicate samples was extracted, and expression profiles were obtained by microarray analysis. Data comparisons between control and treated samples were performed and statistically analyzed.
RESULTS. Data revealed that the expression of 265 known genes and expressed sequence tags (ESTs) changed after laser treatment. Of those, 25 were found to be upregulated. These genes represented a number of biological processes, including photoreceptor metabolism, synaptic function, structural proteins, and adhesion molecules. Thus angiotensin II type 2 receptor (Agtr2), a potential candidate in the inhibition of VEGF-induced angiogenesis, was upregulated, whereas potential modulators of endothelial cell function, permeability factors, and VEGF inducers, such as FGF-14, FGF-16, IL-1ß, calcitonin receptor-like receptor (CRLR), and plasminogen activator inhibitor-2 (PAI2), were downregulated.
CONCLUSIONS. In this study, genes were identified that both explain and contribute to the beneficial effects of laser photocoagulation in the treatment of angiogenic retinal diseases. The molecular insights into the therapeutic effects of laser photocoagulation may provide a basis for future therapeutic strategies.
It has been proposed that the therapeutic effects of laser photocoagulation are due to the destruction of photoreceptors, the highest oxygen consumers in the retina. Subsequently, these photoreceptors are replaced by glial cells, allowing increased oxygen diffusion from the choroid to the inner retina and thereby relieving inner retinal hypoxia.5 6 This improved oxygenation triggers a two-pronged cascade of events: (1) Constriction of the retinal arteries results in decreased hydrostatic pressure in capillaries and the constriction of capillaries and venules,7 and (2) the cellular production of VEGF is inhibited.8 9 Together, these effects are believed to result in the ultimate inhibition of neovascularization and a decrease in edema. However, altered gene expression and thus the altered regulation of cellular proteins in response to laser photocoagulation are likely to play an important role in achieving the desired therapeutic effects.
With the development of microarray technology, it is possible to monitor thousands of genes simultaneously, enabling the high throughput analysis of treatment methods, such as laser photocoagulation, on retinal gene expression. Such global investigations into altered gene expression can facilitate the identification of key regulatory factors and/or events that contribute to the therapeutic effects of laser photocoagulation in the inhibition of both neovascularization and the progression of retinal diseases. An examination of altered gene expression patterns in normal tissue also provides a baseline from which comparisons to the effects of laser photocoagulation in retinal disease models can then ensue.
In this study, the effects of laser photocoagulation on gene expression in the retina, RPE, and choroid were examined by using microarray technology. To validate the methodology, the expression profiles of selected genes were confirmed by quantitative PCR techniques. The molecular insights into the therapeutic effects of laser photocoagulation will not only increase our understanding of the mechanisms that underlie this treatment but will also identify genes for future gene therapy strategies.
| Methods |
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Perfusion of Laser-Treated Eyes with Fluorescence-Labeled Dextran
Two laser-treated mice were perfused with fluorescence-labeled dextran, as described previously.10 Briefly, the animals were anesthetized as just described. PBS (4 mL) was perfused through the left ventricle into the aorta to wash away the circulating blood, followed by 2 mL fluorescence-labeled dextran (50 mg/mL, molecular weight, 2.0 x 106; Sigma, St. Louis, MO) for perfusion. The eyes were enucleated, fixed in 2% paraformaldehyde for 30 minutes, and flatmounted for fluorescence microscopy, as described previously.11
Histology of Laser-Treated Eyes
Eyes (control, n = 2; laser-treated, n = 2) were harvested for histology 3 days after laser photocoagulation. The enucleated eyes were fixed in 4% paraformaldehyde for 2 hours and embedded in paraffin. Sections (
5 µm in thickness) were cut and stained with hematoxylin and eosin (H&E). The sections were then viewed under a light microscope to confirm the anticipated structural changes at the site of the laser burns.
Sample Preparation and Assessing RNA Quality
Enucleated control- and laser-treated eyes were harvested 3 days after laser treatment and maintained in RNA stabilization solution (RNAlater; Ambion, Austin, TX) for a minimum of 2 hours. To maximize the solutions penetration into the inner parts of the eye and to minimize RNA degradation, the eyes were slit before storage. The tissue was then dissected from the anterior segment and the lens. The resultant eyecups (comprising the retina and adjoining RPE layer and choroid) were pooled (n = 5 eyes per pool) to both maximize the amount of RNA obtained and to minimize bias due to biological variation. Total RNA was isolated with extraction reagent (TRIzol; Invitrogen, Life Technologies, San Diego, CA) and further purified using a kit (RNeasy; Qiagen, Valencia, CA). The RNA concentration was determined spectrophotometrically.
Microarray Hybridization and Analysis
Biotinylated cRNA samples were prepared as described by the manufacturer (Affymetrix, Santa Clara, CA) and hybridized onto arrays (Test 3 Arrays; Affymetrix), which provided information on the quality of the cRNA product, background levels, and enabled maintenance of quality control of the hybridization technique and the scanning equipment. "Spiked" controls were added to the hybridization cocktail, to enable quality control of the hybridization process. Samples of sufficient quality were then hybridized onto the gene chip standard arrays (MG-U74Av2 GeneChip; Affymetrix). The sequence source for the MG-U74Av2 array was largely the C57BL/6J mouse strain, making it an appropriate array for this study. Replicate hybridizations of three independent pooled samples were performed by using separate chips for both control and laser-treated samples.
Statistical Analysis
The raw-image data were analyzed using the accompanying software (GeneChip Expression Analysis Software; Affymetrix) to produce perfect match (PM) and mismatch (MM) values to which we applied our own analysis. Normalization of each array was performed using a method that is intended to make the PM and MM quantiles of all arrays agree, referred to as quantile normalization.12 Normalized PM data were log transformed (base 2) and corrected for the effects of nonspecific binding by a novel background correction (for more details of this analysis procedure, see Ref. 13 ).
The three replicate arrays of treatment and control were combined at the probe level, and the difference between the combined treatment and control arrays was calculated. For treatment arrays T1, T2, and T3 and control arrays C1, C2, and C3 the difference (d) between treatment and control for probe i of a given gene was formed:
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) and SE over all probes i = 1... n for a given gene were calculated by
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A t statistic was formed for the difference between treatment and control for each gene: t =
/SE. Genes were ranked according to the size of their mean difference and t statistic. Ranking is performed on both statistics in an attempt to produce a list of genes with large mean differences and reasonable SEs. Requiring that the t statistic be large removes genes with large SEs from the list, and requiring that the mean difference also be large removes genes for which the t statistic is large, only because of very small SEs. Those genes for which both statistics are large relative to most genes are most likely to be differentially expressed.
Quantitative Real-Time PCR
Real time PCR (performed on three independent pooled samples) was used to confirm the gene expression data obtained in the microarray experiment. The RNA from eyecups of pooled groups of control and laser-treated eyes was reverse transcribed and used as a template in a real-time PCR reaction, using specific oligonucleotide primers and a fluorescent gel dye (SYBR green I; Applied Biosystems, Foster City, CA). The reaction was performed on a commercial system (RotorGene 2000; Corbett Research, Sydney, Australia). A standard curve was established for each PCR reaction. This was derived from the serial dilutions (10-310-7 pmol/µL) of a single-stranded, synthetic cDNA standard designed to represent the fragments of the genes listed later, and was used to calculate mRNA concentrations in the RNA samples. A "melt-curve" analysis of the PCR products was performed after the amplification, to demonstrate that only a single product was amplified.
Oligonucleotide primers were designed to span intronic sequences to exclude the possibility of amplifying genomic DNA during the limited extension time of the PCR protocol (15 seconds). Primer sequences: glyceraldehyde-3 phosphate dehydrogenase (GAPDH; GenBank accession number: NM_008084), 5' primer (nucleotides 960-980), 3' primer (nucleotides 1048-1028); ß-actin (M12481, 888-909, 973-955); hypoxanthine phosphoribosyl transferase (HPRT; NM_013556, 172-192, 266-247); IGF-I (NM_010512, 524-544, 644-624); opsin (M55171, 7720-7740, 7825-7807); TGF
(U65016, 2561-1584, 2660-2642); VEGF (NM_011697, 1040-1060, 1147-1125); angiotensin II type 2 receptor (Agtr2; NM_007429, 188-205, 280-261); µ-crystallin (AF039391, 501-520, 619-601); inosine monophosphate dehydrogenase type 1 (IMPDH1; U00978, 358-377, 490-472); rod transducin
(M25513, 297-315, 420-401); AMOG (X16645, 531-549, 665-647); dynamin (L31397, 2962-2981, 3105-3089); Supt5hp (U88539, 2841-2859, 2979-2962); C/EBP (M61007, 658-677, 762-745); cellular retinoic acid binding protein II (CRABPII; M35523, 671-688, 802-785); mouse atonal homologue 3 (math3; AF036257, 2490-2510, 2588-2570).
| Results |
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, and t statistics. Figure 2 shows a plot of t versus SE for all genes (represented by small black dots) and for the genes with the highest t and
represented by the open circles. Values of t at or near zero represent genes that are not differentially expressed. Because t is
divided by SE, genes with large SEs tend to have small t statistics. Genes for which a single animal has skewed the expression level measured by one of the three replicate chips have a larger SE and therefore a smaller t statistic. This ensures that the gene appears much lower in the list of ranked t statistics and greatly reduces the possibility that it will be included in the final list of candidates for differential expression. Conversely, the largest t statistics occur for genes with the smallest SEs. Only those genes with large t and
are considered to be differentially expressed. As such, those points with large t and small SE, which are not highlighted, correspond to genes with low
s. The 265 genes shown highlighted in this figure were considered to be the most likely candidates for differential expression. It can be seen that the highlighted genes were distinct from the dense cloud of unchanged genes clustered about t = 0.
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, Hex (prh), AMOG, Supt5hp, µ-crystallin, ß-actin, dynamin, type 1 inosine monophosphate dehydrogenase, and several miscellaneous proteins of unknown function in the eye, such as inactive X-specific transcript, germline Ig variable region heavy chain, and a variable group of two-cell-stage gene families (Table 2) . Figure 4 shows the distribution of these genes and again, the EST classification was the largest group of upregulated genes (52% of total number of upregulated genes).
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The oligonucleotide primers and standards designed for the quantitative analysis were derived from the same sequence source as that for the probes. The real-time PCR, performed on two independent samples, confirmed the pattern of expression observed in the microarray data (Table 3) for 15 of the 16 genes analyzed. The multiple of change (ranging between no change to 70-fold differences shown by the real-time PCR), however, did not correspond to the change observed with the microarray (ranging between no change and 3.19-fold differences). The real-time PCR data from replicate samples was consistent. The exception to the above was the gene math3. The expression pattern of math3 identified in the microarray was not confirmed by real-time PCR. The microarray data showed that math3 was reduced in expression by 2.45-fold, whereas the real-time PCR data demonstrated a significant increase in math3 expression of almost 20-fold. For each gene analyzed by real-time PCR, the melt-curve confirmed that only a single product was amplified. The melting temperatures (Tm) of the products derived by amplification of the cDNAs were identical with the Tm of the products derived from the standards, additionally confirming the identity of the observed products.
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| Discussion |
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In our study, three replicate microarray comparisons demonstrated consistent changes in the gene expression profiles. The direction of the regulation was also confirmed by quantitative PCR techniques in 15 of the 16 genes analyzed, although the absolute multiple of change differed between the two techniques. This is not surprising, because the normalization of spot intensity, the initial step in the microarray data analysis, often represses very large differences in the expression levels, whereas the quantitation by real-time PCR is linear over many orders of magnitude. Overall, the 94% confirmation of the gene array data demonstrated the reliability of our methods in which retinal tissue was pooled and the microarray experiment was performed in triplicate.
The histopathologic consequences of laser photocoagulation have been studied, and the immediate effects noted were edema, inflammation, and necrosis, resulting from the tissue damage,14 15 16 17 which appeared to settle considerably by 3 to 4 days after treatment. In our study, the genes involved in apoptosis and inflammation contributed less than 5% of the total number of genes modified by laser photocoagulation, indicating that these processes had settled by 3 days after laser treatment. The genes involved in tissue remodeling, extracellular matrix, and structural proteins were found to be modified by laser treatment. Altered expression of this class of genes was expected, considering the degree of damage resulting from the laser burns and the initiation of wound-healing and repair (Fig. 1) . The laser treatment was also shown to impact on genes involved in regulating cell function: genes involved in transcription, translation, and the cell cycle, as well as regulatory molecules (enzymes and transporters), showed decreased expression. Yet, some rescue of the neural retina and compensation of the loss of peripheral photoreceptor function was implied by the upregulation of inosine monophosphate dehydrogenase type 1 (IMPDH1); µ-crystallin and Hex (prh), genes important for the metabolic activity of the photoreceptors18 19 20 ;
-transducin for photoreceptor signal transduction; and genes involved in axonal growth, morphology, and synaptic function (such as dynamin).
The expression of genes involved in angiogenesis, inflammation, and apoptosis, and those encoding extracellular matrix proteins and growth factors have previously been shown to be upregulated in the retina of diabetic animals.21 Our data suggested that the beneficial effects of laser photocoagulation in the treatment of diabetic retinopathy may not only be the inhibition of angiogenesis but also the altered regulation of the genes involved in the inflammation and tissue damage associated with the disease. However, it is possible that the diseased state may respond differently to laser treatment and thus, future studies are directed at examining the effects of laser photocoagulation in models of angiogenic retinal diseases, such as diabetic retinopathy to determine the genetic response of the diseased tissue to laser treatment.
At present the most used method of laser treatment in the clinic is the ablative treatment, which results in the destruction of the peripheral retina. The proliferating RPE cells, infiltrating macrophages, damaged photoreceptor cells, and affected choroid cells, resulting from the laser photocoagulation, may all have contributed to the gene expression profiles observed in this study. Although the changing cell populations and tissue composition are part of the process of laser photocoagulation, the particular cell type(s) contributing to the different gene expression patterns after treatment remain unknown. Localization studies identifying these cells are planned for future experiments. However, the stimulated cells (namely the proliferating RPE and infiltrating macrophages) may release factors that may act to inhibit angiogenesis. An example of a well-studied antiangiogenic factor expressed by proliferating RPE cells and macrophages is pigment epithelium-derived factor (PEDF).22
Genes of particular interest to us were those that showed increased expression after laser photocoagulation and those particularly involved in the inhibition of angiogenesis. In this study, the most intriguing was angiotensin II type 2 receptor (Agtr2), which was significantly increased after laser photocoagulation. Angiotensin II is a vasoactive hormone that induces both endothelial cell proliferation23 and VEGF.24 These actions are mediated by the angiotensin II type I receptor.24 25 High levels of angiotensin II and VEGF have been reported in the vitreous fluid of patients with active proliferative diabetic retinopathy.26 In contrast, the angiotensin II type 2 receptor (Agtr2) has demonstrated antiproliferative effects,27 28 particularly in endothelial cells.29 Recent preliminary evidence has demonstrated a possible role for Agtr2 in the inhibition of VEGF-induced angiogenesis in the treatment of proliferative diabetic retinopathy. The significant increase in Agtr2 expression after laser photocoagulation may explain the success of laser therapy in the treatment of proliferative diabetic retinopathy.
A number of genes showed decreased expression after laser photocoagulation that may also contribute to the antiangiogenic effects of laser therapy. These include calcitonin receptor-like receptor (CRLR) precursor, interleukin (IL)-1ß, the fibroblast growth factors (FGF 14 and FGF 16), and plasminogen activator inhibitor II (PAI2). CRLR is expressed in endothelial cells and is a receptor for adrenomedullin, a potent vasodilator and permeability factor,30 whereas IL-1ß has been shown to induce VEGF expression in human endothelial cell lines.31 32 IL-1ß also mediates ischemic injury in the retina as a consequence of increased ocular pressure33 and has been shown to be upregulated in the retina in early diabetes.21 PAI2 is a fibrinolytic factor that is associated with endothelial proliferation and migration,34 whereas the FGF family has been implicated in a number of biological activities including angiogenesis and mitogenesis.35 36 The functions of FGF 14 and FGF 16, the newest members of the FGF family, are not fully understood. However, these factors have been shown to induce proliferation in a variety of cell types.37 38 39 FGF 14 is widely expressed in the major arteries, brain, and spinal cord of the developing mouse embryo.37 It is plausible, therefore, to assume that FGF 14 and FGF 16 in the retina may act to stimulate endothelial proliferation and neural growth. The suppression of these factors after laser treatment suggests a possible multiple benefit to the retina: a reduction in VEGF production leading to a reduction in angiogenesis, a decline in edema formation as vascular permeability is reduced, and a decrease in ischemic injury as a result of decreased nitric oxide production.
Other genes found to be downregulated by laser photocoagulation that may be beneficial in the treatment of ocular disorders were those genes encoding extracellular matrix proteins:
ß-crystallin and stromelysin 1. These genes are induced by different types of stress, such as oxidative stress (in glaucoma) and diabetic retinopathy.21 40 41 Stromelysin 1 has been associated with retinal pigment epithelial contraction and retinal detachment.42
This study is a preliminary investigation in which laser photocoagulation modulated the expression of genes that may contribute to the therapeutic effects of this treatment in angiogenic retinal diseases. However, whether the expression pattern changes are reflective of the gene expression levels within the viable cells of the affected retina, RPE, and/or choroidal tissue or is the result of changes in tissue composition has yet to be determined. Further analysis is needed to identify the cell type(s) affected by laser treatment, to localize the gene expression and to determine whether these gene expression changes translate to functional changes. Future studies are also planned to examine the long-term effects of laser treatment and to compare these effects with those observed in models of angiogenic retinal diseases.
This study demonstrated that microarray analysis is a powerful tool for identifying cellular responses to different treatment strategies. Although, at present, global approaches are complemented with traditional gene expression studies, such as in situ hybridization, immunohistochemistry, and in vitro and in vivo functional studies, with the advances in sequencing of the human and mouse genomes, genome-wide expression monitoring with instant identification of individual genes43 and cluster analysis44 will improve our understanding of the underlying biological processes and may accelerate the identification of disease-causing and therapeutic genes.
| Footnotes |
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Supported by the National Health and Medical Research Council, Australia; the Juvenile Diabetes Research Foundation, United States; and WestPac Australia.
Submitted for publication June 24, 2002; revised September 19 and October 27, 2002; accepted October 31, 2002.
Disclosure: A.S. Wilson, (P); B.G. Hobbs, (P); W.-Y. Shen, None; T.P. Speed, (P); U. Schmidt, None; C.G. Begley, (P); P.E. Rakoczy, (P)
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: P. Elizabeth Rakoczy, Centre for Ophthalmology and Visual Science, The University of Western Australia, Lions Eye Institute, 2 Verdun Street, Nedlands, WA 6009, Australia; rakoczy{at}cyllene.uwa.edu.au.
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