Skip to main content
eScholarship
Open Access Publications from the University of California

Generation of Transplantable Retinal Photoreceptors from a Current Good Manufacturing Practice-Manufactured Human Induced Pluripotent Stem Cell Line.

  • Author(s): Zhu, Jie
  • Reynolds, Joseph
  • Garcia, Thelma
  • Cifuentes, Helen
  • Chew, Shereen
  • Zeng, Xianmin
  • Lamba, Deepak Ashok
  • et al.
Abstract

Retinal degeneration often results in the loss of light-sensing photoreceptors, which leads to permanent vision loss. Generating transplantable retinal photoreceptors using human somatic cell-derived induced pluripotent stem cells (iPSCs) holds promise to treat a variety of retinal degenerative diseases by replacing the damaged or dysfunctional native photoreceptors with healthy and functional ones. Establishment of effective methods to produce retinal cells including photoreceptors in chemically defined conditions using current Good Manufacturing Practice (cGMP)-manufactured human iPSC lines is critical for advancing cell replacement therapy to the clinic. In this study, we used a human iPSC line (NCL-1) derived under cGMP-compliant conditions from CD34+ cord blood cells. The cells were differentiated into retinal cells using a small molecule-based retinal induction protocol. We show that retinal cells including photoreceptors, retinal pigmented epithelial cells and optic cup-like retinal organoids can be generated from the NCL-1 iPSC line. Additionally, we show that following subretinal transplantation into immunodeficient host mouse eyes, retinal cells successfully integrated into the photoreceptor layer and developed into mature photoreceptors. This study provides strong evidence that transplantable photoreceptors can be generated from a cGMP-manufactured human iPSC line for clinical applications. Stem Cells Translational Medicine 2018;7:210-219.

Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.

Main Content
Current View