Retinoblastoma: unveiling molecular pathogenesis and pioneering organoid-driven therapeutic innovations

Hua Li1, Chenrui Jin2

  • 1Department of Ophthalmology, The Affiliated Yongchuan Hospital of Chongqing Medical University, Yongchuan District, Chongqing, 402160, People's Republic of China. 2022220507@stu.cqmu.edu.cn.

PubMed

Insights

Retinal organoids offer advanced 3D models for studying retinoblastoma (RB) pathogenesis and testing therapies. Future organoid development aims to improve personalized treatments and patient outcomes for this pediatric eye cancer.

Area of Science:

  • Ophthalmology
  • Developmental Biology
  • Cancer Research

Background:

  • Retinoblastoma (RB) is a common pediatric intraocular malignancy driven by RB1 inactivation, posing treatment challenges like toxicity, relapse, and resistance.
  • Existing models fail to fully replicate human RB genetics and tumor heterogeneity, necessitating improved in vitro platforms.

Purpose of the Study:

  • To review retinoblastoma pathogenesis, including genetic and epigenetic factors.
  • To highlight the application of retinal organoids and CRISPR-engineered models in studying RB.
  • To discuss the limitations and future directions of organoid technology for RB research.

Main Methods:

  • Review of existing literature on retinoblastoma pathogenesis and modeling.
  • Focus on retinal organoids derived from human pluripotent or patient-specific stem cells.
  • Discussion of CRISPR-engineered organoids for identifying tumor origins and validating therapies.

Main Results:

  • Retinal organoids provide a 3D model for the tumor microenvironment, enabling drug screening and mechanistic studies.
  • CRISPR-engineered organoids have identified cone precursors as potential tumor origins and validated therapies like CDK4/6 inhibitors and sunitinib.
  • Key RB pathogenesis factors include RB1 loss, MYCN amplification, METTL3-mediated m6A epigenetic dysregulation, and aberrant PI3K/AKT/mTOR and Hedgehog pathways.

Conclusions:

  • Organoid technology offers significant potential for advancing personalized therapies for retinoblastoma.
  • Limitations such as cost, variability, and incomplete mimicry of physiological systems need to be addressed.
  • Future research should focus on integrating multiomics, improving vascularization through 3D bioprinting, and developing immunocompetent models to bridge the gap between preclinical findings and clinical application.