Humanized avian embryo models replicate an immune tumor environment for rapid immunotherapy studies

Marjorie Lacourrège1, Loraine Jarrosson2, Clélia Costechareyre2

  • 1Oncofactory ERBC, Bioparc 60 Avenue Rockefeller, Lyon, 69008, France. mlacourrege@erbc-group.com.

Insights

A novel humanized avian embryo model offers a rapid platform for evaluating cancer immunotherapies. This system successfully recapitulates the tumor immune microenvironment, aiding in patient stratification and biomarker discovery.

Area of Science:

  • Oncology
  • Immunology
  • Developmental Biology

Background:

  • Cancer immunotherapy aims to harness the patient's immune system to combat tumors.
  • Current preclinical models often lack the speed and reliability needed for effective immunotherapy evaluation.
  • There is a critical need for advanced models that accurately reflect the human tumor immune microenvironment.

Purpose of the Study:

  • To develop and validate a humanized avian embryo model for preclinical cancer immunotherapy research.
  • To establish methods for rapid screening of immune-based therapeutic strategies.
  • To enable patient response stratification and biomarker discovery.

Main Methods:

  • Creation of miniature, humanized tumor replicas in avian embryo tissues using patient or cell line-derived xenografts.
  • Two implantation approaches: co-micro-implantation of human peripheral blood mononuclear cells (PBMCs) and cancer cells, or sequential implantation and injection.
  • Integration of whole-embryo light sheet microscopy and immune cell molecular marker analysis.

Main Results:

  • The humanized avian embryo model successfully recapitulates a relevant tumor immune microenvironment.
  • Demonstrated the capability to rapidly screen immune-based therapeutic strategies, including anti-PD-1 therapy.
  • Showcased potential for patient response stratification and identification of predictive biomarkers.

Conclusions:

  • The humanized avian embryo technology provides a promising platform for accelerating cancer immunotherapy development.
  • This model facilitates efficient preclinical evaluation and personalized treatment strategies.
  • It supports the discovery of biomarkers for predicting patient responses to immunotherapy.