JoVE - Journal of Visualized Experiments
JoVE Visualize
Contact Us

Clinical and pathological predictors of engraftment for patient-derived xenografts in lung adenocarcinoma

  • 0Division of Thoracic Surgery, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada; Division of Thoracic Surgery, Graduate School of Medicine, Kobe University, Hyogo, Japan.
Lung +

|

July 5, 2024

|

July 5, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Establishing patient-derived xenografts (PDXs) for lung adenocarcinoma is more successful with solid tumors. Tumors with ground-glass opacity (GGO) show low engraftment rates, impacting preclinical research efficiency.

Area Of Science

  • Oncology
  • Preclinical Research
  • Translational Medicine

Background

  • Patient-derived xenografts (PDXs) are valuable preclinical models for cancer research.
  • PDXs retain patient tumor characteristics, aiding drug efficacy studies.
  • Successful PDX establishment is crucial for advancing cancer therapeutics.

Purpose Of The Study

  • To identify factors influencing the successful engraftment of lung adenocarcinoma patient-derived xenografts (PDXs).
  • To analyze the impact of tumor characteristics, including radiological features and gene mutations, on PDX engraftment.
  • To optimize the selection of primary tumors for establishing reliable PDX models.

Main Methods

  • Lung adenocarcinoma PDXs were established from surgically resected primary tumors.
  • Tumors were categorized based on preoperative CT scans into solid nodules and those with ground-glass opacity (GGO).
  • Gene mutation status was determined using next-generation sequencing and MassARRAY panels.

Main Results

  • A total of 254 lung adenocarcinomas were used, with a 16.9% stable engraftment rate after three passages.
  • Stable engraftment rates significantly differed between solid tumors (22.1%) and tumors with GGO (1.6%).
  • Advanced stage, poor differentiation, solid subtype, and KRAS/TP53 mutations were associated with successful PDX engraftment.

Conclusions

  • Tumor characteristics, particularly the absence of GGO features, are critical for successful PDX establishment in lung adenocarcinoma.
  • Avoiding GGO tumors can improve the efficiency and cost-effectiveness of creating PDX models.
  • These findings will guide the selection of optimal tissues for generating predictive preclinical models.

Keywords: