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  • 标题:Genome-wide expression datasets of anti-VEGF and dexamethasone treatment of angiogenesis in the rat cornea
  • 本地全文:下载
  • 作者:Anthony Mukwaya ; Pierfrancesco Mirabelli ; Anton Lennikov
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2017
  • 卷号:4
  • DOI:10.1038/sdata.2017.111
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要: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.
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