Patient-derived renal cell carcinoma organoids for personalized cancer therapy

Zhichao Li1,2,3, Haibo Xu1,2,3, Lei Yu2

  • 1Department of Urology, Shenzhen Institute of Translational Medicine, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, International Cancer Center, Shenzhen University School of Medicine, Shenzhen, China.

Abstract

Insights

Researchers developed kidney cancer organoids from patient tumors. These models accurately reflect diverse kidney cancers and aid in drug screening and personalized treatment strategies.

Area of Science:

  • Oncology
  • Translational Medicine
  • Biotechnology

Background:

  • Kidney cancer is a common solid tumor with diverse subtypes.
  • Current research is limited by a lack of models that capture disease heterogeneity.
  • Effective models are crucial for advancing kidney cancer research and treatment.

Purpose of the Study:

  • To establish a 3D culture system for generating kidney cancer organoids from clinical samples.
  • To characterize these organoids for their fidelity to the original tumors.
  • To evaluate the utility of organoids in personalized cancer therapy.

Main Methods:

  • Developed a 3D culture system for renal cell carcinoma (RCC) organoids.
  • Characterized organoids using histology, immunofluorescence, and multi-omics (WES, RNA-seq, scRNA-seq).
  • Assessed organoid response to drugs and CAR T-cell therapy for personalized treatment evaluation.

Main Results:

  • Generated 33 kidney cancer organoid lines across major subtypes (ccRCC, pRCC, chRCC).
  • Organoids retained histological, mutational, and transcriptional features of primary tumors.
  • Single-cell RNA-seq confirmed inter- and intra-tumoral heterogeneity.
  • Organoids enabled in vitro drug screening and CAR T-cell efficacy assessment.

Conclusions:

  • Patient-derived RCC organoids are effective pre-clinical models.
  • These organoids represent a significant advancement for kidney cancer research.
  • Organoids offer a valuable platform for personalized medicine approaches.

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