Nucleic Acid TherapeuticsMolecular BiologyPeer-reviewed journal article
MicroRNA-143 plays a protective role in ischemia-induced retinal neovascularization
Jiang-Hui WangiD, Yu-Fan Chuang, Jinying Chen, Vikrant Singh, Fan‐Li LiniD, Richard WilsoniD, Leilei Tu, Chenkai MaiD, Raymond C.B. WongiD, Peng‐Yuan WangiD, Jingxiang ZhongiD, Alex William HewittiD, Peter van WijngaardeniD, Gregory James DustingiD, Guei‐Sheung LiuiD
Abstract
Retinal neovascularization is a severe complication of proliferative diabetic retinopathy. MicroRNAs (miRNAs) are master regulators of gene expression that play important roles in retinal neovascularization. Here, we investigated the retinal miRNA expression profile in a rat model of oxygen-induced retinopathy (OIR) through miRNA-Seq. We found that miR-143-3p, miR-126-3p, miR-150-5p and miR-145-5p were significantly down-regulated in the retina of OIR rats, and directly involved in the development of retinal neovascularization. Of these identified miRNAs, miR-143 is enriched in retina and was first reported being associated with pathological retinal angiogenesis. Our RNA-Seq data further suggested that miR-143 alleviates retinal neovascularization by mediating the inflammation/stress pathways via Fos. Moreover, the computational analysis indicated that Transforming Growth Factor-beta Activated Kinase 1 (TAK1) is involved in several key pathways associated with the dysregulated miRNAs. The pharmacological inhibition of TAK1 suppressed angiogenesis in vitro and retinal neovascularization in vivo. Our data highlight the utility of next-generation sequencing in the development of therapeutics for ocular neovascularization and further suggest that therapeutic targeting the dysregulated miRNAs or TAK1 may be a feasible adjunct therapeutic approach in patients with retinal neovascularization.
- organism: rat
- assay: bulk RNA-seq
- assay: long-read sequencing
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: drug response / drug discovery
- approach: statistical model
- approach: experimental assay
- Citations
- 7
- FWCI
- 1.12
- Field percentile
- top 28%
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