Development and characterization of a patient‑derived orthotopic xenograft of therapy‑resistant breast cancer

Ramesh Butti1, Prachi Kapse1, Garima Bhadauriya1

  • 1Laboratory of Tumor Biology, Angiogenesis and Nanomedicine Research, National Centre for Cell Science, Pune, Maharashtra 411007, India.

Oncology Reports
|March 31, 2023
PubMed

Insights

Patient-derived orthotopic xenografts (PDOXs) were developed from hormone-resistant breast cancer. These models accurately reflect patient tumors, proving useful for preclinical drug screening and biomarker discovery.

Area of Science:

  • Oncology
  • Translational Research
  • Cancer Models

Background:

  • Hormone receptor-positive, HER2-negative metastatic breast cancer often becomes refractory to treatment.
  • Existing cell line models inadequately represent this aggressive cancer subtype.
  • There is a critical need for better preclinical models for this specific breast cancer type.

Purpose of the Study:

  • To develop and characterize patient-derived orthotopic xenografts (PDOXs) from treatment-resistant breast cancer.
  • To assess the fidelity of PDOX models compared to the original patient tumors.
  • To evaluate the utility of PDOXs for preclinical research.

Main Methods:

  • Tumor tissue from a patient with metastatic, hormone-resistant breast cancer was used.
  • Tumor fragments were implanted into mice and serially passaged to create multiple generations of PDOXs.
  • Histological, immunofluorescence, and western blot analyses were performed for characterization.

Main Results:

  • Established PDOX models retained the original patient tumor's morphology, histology, and molecular features.
  • Characterization confirmed the subtype-specific molecular characteristics were maintained across passages.
  • PDOX models demonstrated high fidelity to the patient's original tumor.

Conclusions:

  • Successfully established and characterized PDOXs from hormone-resistant breast cancer.
  • PDOX models are reliable and valuable for preclinical drug screening and biomarker discovery in this cancer type.
  • These models offer a more accurate representation of patient tumors than traditional cell lines.

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