Clinical relevance and therapeutic predictive ability of hypoxia biomarkers in head and neck cancer tumour models

  • 0Auckland Cancer Society Research Centre, University of Auckland, New Zealand.

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Summary

This summary is machine-generated.

Tumour hypoxia in head and neck squamous cell carcinoma (HNSCC) impacts outcomes. New preclinical models show promise for testing hypoxia-targeting therapies, but additional biomarkers are needed to predict drug sensitivity.

Area Of Science

  • Oncology
  • Cancer Biology
  • Preclinical Research

Background

  • Tumour hypoxia is linked to poor patient outcomes, especially in head and neck squamous cell carcinoma (HNSCC).
  • Effective hypoxia-targeting therapies require accurate preclinical models and selection biomarkers.
  • Current models may not fully recapitulate clinical HNSCC hypoxia.

Purpose Of The Study

  • To establish and characterize patient-derived xenograft (PDX) and cell line-derived xenograft (CDX) models of HNSCC.
  • To evaluate the fidelity of these models in representing clinical HNSCC gene expression, hypoxia, and proliferation.
  • To assess the sensitivity of these models to hypoxia-activated prodrugs (HAPs).

Main Methods

  • Established 20 HNSCC PDX and CDX models.
  • Characterized models for gene expression, hypoxia (gene signatures, pimonidazole IHC), and proliferation.
  • Evaluated HAP sensitivity using tumour growth inhibition and ex vivo clonogenic assays.

Main Results

  • PDX models demonstrated higher gene expression fidelity to clinical HNSCC than cell lines.
  • PDX models were significantly more hypoxic than CDX models, mirroring clinical HNSCC hypoxia.
  • Neither hypoxia nor proliferation status alone predicted HAP sensitivity across models.

Conclusions

  • Developed clinically relevant HNSCC preclinical models for evaluating hypoxia-targeting therapies.
  • PDX models offer superior fidelity for hypoxia research compared to CDX models.
  • Additional biomarkers beyond hypoxia are necessary for predicting HAP drug sensitivity in HNSCC.