A patient-derived organoid model identifies TP53-dependent gemcitabine sensitivity in spinal chordoma

Panpan Hu1, Shengxin Zeng2, Juncai Lei2

  • 1Department of Orthopaedics and Beijing Key Laboratory of Spinal Disease Research, Peking University Third Hospital, 49 North Garden Rd, Haidian District, 100191, Beijing, China. pphu@bjmu.edu.cn.

Discover Oncology
|April 30, 2026
PubMed
Abstract

Insights

Patient-derived organoids (PDOs) offer a new way to study chordoma, a rare bone cancer. Gemcitabine shows promise by targeting a TP53-dependent vulnerability, paving the way for personalized treatments.

Area of Science:

  • Oncology
  • Translational Research
  • Cancer Modeling

Background:

  • Chordoma is a rare bone malignancy with limited treatment options.
  • Conventional chemotherapy is largely ineffective, necessitating novel preclinical models.
  • Patient-derived organoids (PDOs) offer a promising 3D culture system for preserving tumor characteristics.

Purpose of the Study:

  • To establish and characterize spinal chordoma PDOs for functional precision oncology.
  • To identify therapeutic vulnerabilities and drug responses in chordoma using PDO models.
  • To investigate the role of TP53 in mediating drug response in chordoma.

Main Methods:

  • Generation and characterization of three-dimensional chordoma PDOs from patient specimens.
  • Histological, immunohistochemical, and molecular analyses of PDOs.
  • Functional drug screening with clinically relevant agents, including gemcitabine, and TP53 knockdown experiments.

Main Results:

  • Established PDOs accurately recapitulated primary tumor features across multiple passages.
  • Gemcitabine demonstrated significant growth inhibition in chordoma PDOs.
  • TP53 knockdown abrogated gemcitabine's efficacy, highlighting a TP53-dependent vulnerability.

Conclusions:

  • A robust spinal chordoma PDO platform for precision oncology has been established.
  • Gemcitabine targets a TP53-dependent DNA-damage pathway in chordoma.
  • This PDO model facilitates biomarker-informed drug discovery for rare cancers.

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