Abstract

   Therapeutics against pathologic new blood vessel growth, particularly
   those targeting vascular endothelial growth factor (VEGF) are of
   enormous clinical interest. In the eye, where anti-VEGF agents are in
   widespread clinical use for treating retinal and corneal blindness,
   only partial or transient efficacy and resistance to anti-VEGF agents
   are among the major drawbacks. Conversely, corticosteroids have long
   been used in ophthalmology for their potency in suppressing
   inflammation and angiogenesis, but their broad biological activity can
   give rise to side effects such as glaucoma and cataract. To aid in the
   search for more targeted and effective anti-angiogenic therapies in the
   eye, we present here a dataset comparing gene expression changes in
   dexamethasone versus anti-Vegfa treatment of inflammation leading to
   angiogenesis in the rat cornea. Global gene expression analysis with
   GeneChip Rat 230 2.0 microarrays was conducted and the metadata
   submitted to Expression Omnibus repository. Here, we present a
   high-quality validated dataset enabling genome-wide comparison of genes
   differentially targeted by dexamethasone and anti-Vegf treatments, to
   identify potential alternative therapeutic targets for evaluation.

   Subject terms: Rat, Microarray analysis, Angiogenesis, Inflammation,
   Animal disease models

Background & Summary

   Pathological angiogenesis is a hallmark of many blinding diseases such
   as age-related macular degeneration, diabetic retinopathy, and corneal
   graft failure. In the eye, angiogenesis (or neovascularisation) is
   favoured by stimuli such as inflammation^[38]1, immunologic rejection,
   limbal stem cell deficiency, and hypoxia^[39]2. The choice of treatment
   for neovascularisation in the eye can be influenced by the stage of the
   neovascularisation process. While newly formed sprouts are usually
   leaky and susceptible to anti-VEGF treatment^[40]3, mature vessels
   require fewer angiogenic mediators^[41]4 necessitating other
   angioregressive therapies^[42]5. In the cornea in particular,
   therapeutics are used off-label to manage corneal angiogenesis, given
   the current lack of approved treatments specific for the cornea.
   Corticosteroids and/or nonsteroidal anti-inflammatory drugs (NSAIDs)
   are used to target neovascularisation^[43]6,[44]7, however, steroids
   may promote infection^[45]8,[46]9, glaucoma^[47]10, cataract^[48]11,
   and herpes simplex recurrence^[49]12,[50]13 while NSAIDs are reported
   to cause corneal ulceration and melting^[51]14.

   To date, targeting the VEGF family of pro-angiogenic factors is the
   most promising therapeutic approach as an alternative to steroid or
   NSAID use. Bevacizumab, a full-length recombinant humanized monoclonal
   antibody against VEGFA has been reported to treat corneal
   neovascularisation with some success^[52]15,[53]16. Ranibizumab, a
   monoclonal antibody fragment also targeting VEGFA has similarly been
   shown to treat corneal neovascularisation^[54]17 and corneal graft
   rejection^[55]18. Compared to bevacizumab and ranibizumab, pegaptanib
   (a 28-base ribonucleic aptamer) is of limited efficacy, since it is
   specific to the VEGF-165 isoform^[56]19. The VEGF trap (aflibercept), a
   decoy receptor for all VEGFA isoforms, is the latest therapeutic
   approach being tested for use in the cornea^[57]20. In spite of the
   benefits of these anti-VEGF targeted therapies, some side effects of
   VEGF targeting have been documented, for example impaired corneal
   epithelialization and wound healing, a pathology attributed to the
   possible adverse effects of VEGF deficiency on nerve growth and
   regeneration^[58]21,[59]22. In addition, anti-VEGF therapies are
   reported to be only partially effective^[60]23,[61]24. Likewise, an
   antisense oligonucleotide against the insulin receptor substrate-1,
   aganirsen, was recently reported to reduce corneal neovascularisation
   only partially (by 26%) in patients with keratitis in a phase III
   study^[62]19. In a previous study we reported that topical
   administration of anti-Vegf led to a 14% reduction in neovessels
   compared to a 90% reduction with dexamethasone treatment in a rat
   corneal model of angiogenesis^[63]25.

   In summary, there is need for new targeted therapies that mimic the
   potent effects of corticosteroids, but without the side effects
   attributed to their broad activity. A better understanding of specific
   factors suppressed by steroids but not by VEGF-A blockade is of
   potential importance for the development of more effective therapies.
   Here, we provide a detailed comparative dataset describing whole-genome
   differences in the activity of the corticosteroid dexamethasone, versus
   anti-VEGF treatment in a rat model of inflammatory corneal
   angiogenesis. GeneChip Rat 230 2.0 microarrays were used to monitor the
   global gene expression changes, and all microarray files including
   associated controls are described here, along with detailed information
   on the conditions of their generation and instructions for their
   re-use.

   The dataset described here (Data Citation 1) can be a valuable resource
   for investigating genes and pathways to identify novel factors to
   target in order to improve the management of inflammation-associated
   neovascularisation in the cornea. The dataset described here has been
   thoroughly analysed in our related manuscript^[64]26, where it was
   shown that dexamethasone treatment led to a suppression of inflammatory
   chemokines and other genes within known signaling pathways like
   PI3K-Akt and focal adhesion, while notably anti-Vegf treatment did not
   have this suppressive activity. Furthermore, dexamethasone treatment
   led to an unexpected activation of the classical complement
   pathway^[65]26.

Methods

   The methods described here are an expansion of those described in our
   related work^[66]26.

Suture model of inflammatory corneal angiogenesis

   The model of suture induced cornea neovascularisation was used as
   previously described^[67]1,[68]25,[69]27. In summary, two nylon sutures
   were placed temporally to induce an inflammatory response that leads to
   new sprouting from limbal vessels after 2–3 days^[70]27. As a follow up
   of our previous findings^[71]25, here eye drops were administered
   topically immediately after suture placement i.e., during the
   pre-sprouting phase, but with high inflammation present in the cornea.
   At 48 h, in vivo confocal microscopy (IVCM) and slit lamp data was
   collected and corneal tissue was harvested for RNA processing. Global
   gene expression changes were assayed using microarrays. An illustration
   of the experimental design is shown in [72]Fig. 1.

Figure 1. Schematic illustration of the experimental procedure that was
followed.

   Figure 1
   [73]Open in a new tab

   (1) sutures were placed intrastromally into the temporal cornea, and
   immediately followed by topical application of eye drops (IgG,
   anti-Vegf or dexamethasone). Eye drops were applied until the 48 h time
   point. At t=48 h, IVCM and slit lamp data was collected and used for
   phenotypic characterisation. (2) cornea tissue was harvested and used
   for RNA extraction, and RNA quality verified. (3) high quality RNA was
   used for target preparation for microarray hybridisation on to GeneChip
   Rat 230 2.0 microarray chips. The microarray chips were scanned and
   image files acquired. (4) CEL files were normalised using expression
   console software. The generated CHP together with the CEL files were
   submitted to Gene Expression Omnibus repository.

Treatment regime

   Three groups of six rats each were treated with one of three topical
   treatments: IgG (Cat. No. 108-C, R&D Systems) at 20 μgml^−1, anti-Vegf
   (Cat. No AF 564, a neutralizing rat-specific goat polyclonal pan-VEGFA
   antibody, R&D Systems, Minneaplois MN, USA) at 20 μgml^−1 or
   dexamethasone (Opnol, Clean Chemical, Sweden AB, Borlänge, Sweden) at
   1 mgml^−1. The treatments were administered topically, 4 times daily,
   starting immediately following suture placement, and continuing up to
   48 h ([74]Fig. 1). Additionally, a group of four non-sutured and
   non-treated corneas was harvested to serve as the control.

Sample collection and RNA extraction

   After 48 h of topical treatment, animals were euthanized and a
   standardized region of tissue between the sutures and limbus which
   indicated a strong inflammatory response by in vivo confocal
   microscopy^[75]26 was carefully dissected out. The tissue was harvested
   from all groups (i.e., IgG, anti-Vegf, dexamethasone and
   non-sutured/non-treated control), six animals per treatment group and
   then immediately immersed in RNA later (Qiagen) and temporarily stored
   at 4 °C. Total RNA was then extracted from all the six samples using
   Qiagen mini RNA preparation kit (Qiagen). RNA concentration was then
   determined using a NanoDrop spectrophotometer (Thermo Scientific), and
   RNA quality was determined using the Agilent bioanalyzer 2100 (Agilent
   Technologies). RNA integrity number (RIN)≥7 was set as the cut-off for
   sample inclusion for downstream processing for microarray analysis. Of
   the six RNA samples extracted per treatment group, four RNA samples per
   treatment group (with highest RIN) were selected for downstream
   processing.

Microarray target preparation

   GeneChip Rat 230 2.0 microarrays were used for global gene expression
   analysis. Four microarray chips were used per experimental group,
   including non-sutured and non-treated control corneas. Each microarray
   chip represented a single corneal sample (16 microarrays in total)
   i.e., no pooling of cornea tissue was performed. As per the protocol
   (Manual Target Preparation for GeneChip 3′ Expression
   Arrays-Affymetrix), a total of 100 ng of high quality RNA per sample
   was mixed with poly-A spike-in Controls, and the mixture was used for
   first-strand synthesis to yield single-stranded cDNA with the T7
   promoter sequence at the 5′ end. Next, using a DNA polymerase and RNase
   H, the single-stranded cDNA was converted to double-stranded cDNA to
   serve as a template for in vitro transcription using T7 RNA polymerase.
   This resulted in the synthesis of labelled complementary RNA (cRNA).
   The labelled cRNA was then purified, and then both the yield and size
   distribution was verified using a NanoDrop spectrophotometer. The
   labelled cRNA was then fragmented and used for the preparation of the
   array hybridisation master mix. Samples were hybridised to the
   microarray chips at 60 rpm for 16 h, at 45 °C in GeneChip Hybridization
   Oven 645 (Affymetrix.inc). The microarray chips were washed and stained
   in a GeneChip Fluidics Station 450 (Affymetrix.inc.) and then scanned
   in a GeneChip Scanner 3000 7 G (Affymetrix.inc.).

Data Records

   Following data acquisition, the CEL files were normalised, and CHP
   files were generated using Expression Console Software (Affymetrix.
   Inc). The CEL and CHP files were submitted to Gene Expression Omnibus
   repository (Data Citation 1). The samples used in the study are
   summarised in [76]Table 1.

Table 1. Dataset and sample description across treatment groups.

   GSM-ID ID Organism Age (Weeks) Description/ Treatment Sample type and
   source Technology
   [77]GSM2327895 F1 rattus norvegicus albino 12 anti-Vegf_F1 RNA-Cornea
   Microarray
   [78]GSM2327896 F2 rattus norvegicus albino 13 anti-Vegf_F2 RNA-Cornea
   Microarray
   [79]GSM2327897 F6 rattus norvegicus albino 12 anti-Vegf_F6 RNA-Cornea
   Microarray
   [80]GSM2327898 F7 rattus norvegicus albino 13 anti-Vegf_F7 RNA-Cornea
   Microarray
   [81]GSM2327899 F17 rattus norvegicus albino 12 IgG_F17 RNA-Cornea
   Microarray
   [82]GSM2327900 F19 rattus norvegicus albino 13 IgG_F19 RNA-Cornea
   Microarray
   [83]GSM2327901 F22 rattus norvegicus albino 13 IgG_F22 RNA-Cornea
   Microarray
   [84]GSM2327902 F23 rattus norvegicus albino 12 IgG_F23 RNA-Cornea
   Microarray
   [85]GSM2327903 F25 rattus norvegicus albino 13 dexamethasone_F25
   RNA-Cornea Microarray
   [86]GSM2327904 F26 rattus norvegicus albino 13 dexamethasone_F26
   RNA-Cornea Microarray
   [87]GSM2327905 F27 rattus norvegicus albino 12 dexamethasone_F27
   RNA-Cornea Microarray
   [88]GSM2327906 F30 rattus norvegicus albino 12 dexamethasone_F30
   RNA-Cornea Microarray
   [89]GSM2327907 Cont 1 rattus norvegicus albino 13 Control 1 RNA-Cornea
   Microarray
   [90]GSM2327908 Cont 2 rattus norvegicus albino 13 Control 2 RNA-Cornea
   Microarray
   [91]GSM2327909 Cont 3 rattus norvegicus albino 12 Control 3 RNA-Cornea
   Microarray
   [92]GSM2327910 Cont 4 rattus norvegicus albino 12 Control 4 RNA-Cornea
   Microarray
   [93]Open in a new tab

Technical Validation

   Following suture placement, randomisation was performed in assigning
   the rats to different treatment groups. For the purpose of statistical
   inference, a total of four rats was used per treatment to correspond to
   four microarray chips per treatment group. ANOVA was used to compare
   effects of the given treatments across treatment groups, with Tukey
   multiple comparison test used to isolate pairwise differences.

   Efficacy of the anti-Vegf treatment was verified by Western blot
   analysis prior to the beginning of the study to confirm the expected
   effect on the gene target^[94]26. Suture placement was performed by the
   same experienced surgeon for all treatment groups, to reduce the
   chances of technical variation. In addition, a similar phenotypic
   appearance within each group was confirmed by slit lamp biomicroscopy
   and in vivo confocal microscopy^[95]26.

RNA quality check

   The quality of the RNA was checked prior to downstream analysis, using
   the Agilent Bioanalyser 2100 (Agilent Technologies), using the 2100
   expert_Eukaryote Total RNA Nano settings. The analysis showed clear,
   defined 28 and 18 s rRNA peaks, an indication of high quality RNA.
   Moreover, low noise between the peaks, and minimal low molecular weight
   noise was detected. In [96]Fig. 2a an elctrophoregram is presented
   illustrating the peaks for the 18 and 28 s rRNA, and in [97]Fig. 2b the
   sample RIN values are given.

Figure 2. RNA and microarray data quality check.

   [98]Figure 2
   [99]Open in a new tab

   Following Bioanalyser RNA quality check, (a) is an electrophoregram
   showing RNA sample quality. The distinct peaks in (a) represent the 18
   and 28 s rRNA. (b) are the obtained RIN values across treatments. (c)
   is a display of the Relative Log Expression Signal-RMA, while (d) are
   Boxplot of four of Affymetrix Spike-In controls, lys-M, phe-M, thr-M
   and dap-M illustrating the range of signal (log2) over the experiment
   as well as quality control of the arrays technical run. (e) is the
   PCA-Probe Cell Intensity Data.

Quality control of microarray data

   The raw CEL files were converted into expression measures,
   background-corrected, and data-normalized using the RMA method^[100]28,
   with the help of Expression Console Software (Affymetrix. Inc). In
   [101]Fig. 2c the relative log expression Signal-RMA is given. In
   [102]Fig. 2d are boxplots representing four of the Affymetrix Spike-In
   controls, lys-M, phe-M, thr-M and dap-M illustrating the range of
   signal (log2) over the experiment. In [103]Fig. 2e is the PCA-Probe
   Cell Intensity Data. The PCA1 (67.0%) represents anti-Vegf and IgG
   treated groups in blue and red colours, respectively. PCA2 (11.7%)
   represents dexamethasone treated group in the orange colour, while PCA3
   (4.2%) displays the control samples in green colour. Note the partial
   overlap of anti-Vegf and IgG groups and clear separation from the
   dexamethasone treated corneas.

   The CHP files were used for gene expression analysis using
   Transcriptome Analysis Console (TAC) Software (Affymetrix, Inc.). Using
   the obtained linearized signal intensity values from the TAC analysis,
   a correlation analysis between samples within the same treatment groups
   was performed. The resulting scatter plots with their corresponding
   correlation coefficient (R^2) are presented in [104]Fig. 3a–d. There
   was strong correlation within samples of the same treatment group. The
   linearized values can then be log transformed and used for functional
   annotation analysis. As an example, STRING^[105]29 pathway enrichment
   analysis was performed using the differentially expressed genes in the
   dexamethasone treated group. Selected pathways from this analysis are
   presented in [106]Fig. 3e, and the genes involved in one of the
   pathways (PI3K-Akt signalling pathway) are represented as an example in
   [107]Fig. 3f.

Figure 3. A correlation analysis within treatment group.

   [108]Figure 3
   [109]Open in a new tab

   (a–d) are signal intensity values correlated between control, IgG,
   anti-Vegf and dexamethasone treated samples respectively. (e) is an
   example of pathway enrichment analysis and (f) is a display of the
   genes involved in a selected pathway (PI3K-Akt signalling pathway).

Gene fold change by qPCR

   To validate microarray^[110]30 gene fold change ([111]Fig. 4a), here we
   used a separate set of rats (3 per treatment group) for qPCR analysis.
   Rats were sutured and treated identically as for microarray samples. At
   the 48 h time point, animals were sacrificed and cornea tissue was
   harvested and used for RNA extraction, without pooling. Following RNA
   extraction, cDNA was synthesised using superscript cDNA synthesis kit
   (Invitrogen), and used for qPCR analysis using TaqMan primers. Genes
   Fgf7 and Serpinb2 were assayed as exemplary genes, with results shown
   in [112]Fig. 4b.

Figure 4. Gene fold change, and localisation of target protein expression in
cornea sections.

   [113]Figure 4
   [114]Open in a new tab

   (a) is the gene fold change by microarray. (b) is the gene fold change
   by qPCR. n=4 and 3 corneas for (a,b), respectively. ANOVA followed by
   Tukey’s multiple comparisons test was used to isolate pairwise
   differences, with alpha <0.05. In both (a,b), asterisks represent
   adjusted P<0.05 and the error bars represent standard deviation. ns,
   not significant. The data in (a,b) was analysed using GraphPad Prism 5
   (GraphPad Software, Inc. CA 92037 USA). (c) is the localisation of the
   corresponding protein expression in cornea cross sections stained by
   immunohistochemistry. White scale bars represent 20 μm.

Localisation of translated genes

   Cornea samples from the respective treatment groups were harvested and
   fixed in paraformaldehyde for 24 h, and then stabilised in paraffin
   blocks. Then 5 μm cross-sections of the tissue were made. Prior to
   staining, the sections were deparaffinised and rehydrated. The sections
   were probed with primary antibody for Fgf7 and Serpinb2, and detected
   with fluorescently (Alexa 488) labelled secondary antibody [115]Fig.
   4c. Images were acquired using a laser scanning confocal fluorescent
   microscope (Zeiss LSM700).

Usage Notes

   The raw CEL files can be normalised using Expression console, and gene
   fold change can be obtained using Transcriptome Analysis Console. Both
   software packages can be freely accessed from Affymetrix (Affymetrix
   Inc).

   Transcriptome Analysis Console (Affymetrix Inc) can be used for pathway
   enrichment analysis, where both pathway P-value and significance can be
   obtained. The genes involved in a given pathway can also be mapped
   within a pathway of interest.

   Also using other publicly available software for bioinformatics
   analysis such as STRING^[116]29, Venny^[117]31, DAVID^[118]32,
   PANTHER^[119]33, etc., and those commercially available like Ingenuity
   pathway analysis (IPA-Qiagen) ([120]http://www.ingenuity.com/), the
   differentially expressed genes can be used to deduce pathway and
   biological processes of interest, and to further isolate the genes
   involved in them.

   In combination with our recently published Data Descriptor^[121]34,
   genes important for endogenous restoration of corneal avascularity
   during either an angiogenic sprouting or regression phase can be
   compared to their behaviour observed with either dexamethasone or
   anti-Vegf treatment in the current dataset, to gain an understating of
   how these treatments modulate these factors.

Additional Information

   How to cite this article: Mukwaya, A. et al. Genome-wide expression
   datasets of anti-VEGF and dexamethasone treatment of angiogenesis in
   the rat cornea. Sci. Data 4:170111 doi: 10.1038/sdata.2017.111 (2017).

   Publisher’s note: Springer Nature remains neutral with regard to
   jurisdictional claims in published maps and institutional affiliations.

Supplementary Material

   [122]sdata2017111-isa1.zip^ (3KB, zip)

Acknowledgments