Innate immune evasion revealed in a colorectal zebrafish xenograft model

Vanda Póvoa1, Cátia Rebelo de Almeida1, Mariana Maia-Gil1

  • 1Champalimaud Centre for the Unknown, Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal.

Nature Communications
|February 20, 2021
PubMed

Insights

Zebrafish xenografts reveal how cancer cells interact with the immune system. Certain cancer cells are cleared, while others grow, highlighting the potential of zebrafish models for understanding tumor microenvironments.

Area of Science:

  • Immunology
  • Oncology
  • Developmental Biology

Background:

  • Cancer immunoediting involves complex interactions between tumor cells and the immune system.
  • Understanding the innate immune system's role in this process is crucial for developing new cancer therapies.

Purpose of the Study:

  • To investigate the innate immune contribution to cancer immunoediting using a zebrafish xenograft model.
  • To explore the potential of zebrafish xenografts as biomarkers for the tumor microenvironment.

Main Methods:

  • Utilized zebrafish xenografts with various human breast and colorectal cancer cell lines (zAvatars).
  • Employed polyclonal xenografts to model intra-tumor heterogeneity.
  • Performed genetic and chemical suppression of myeloid cells.
  • Conducted single-cell transcriptome analysis.

Main Results:

  • Identified distinct cancer cell behaviors: clearance (regressors) versus engraftment (progressors) in zebrafish.
  • Demonstrated that progressor cells can inhibit the clearance of regressor cells.
  • Showed that macrophages and neutrophils are critical for cancer cell clearance.
  • Observed subclonal selection linked to specific signaling pathways (IFN/Notch for clearance, IL10 for escape).

Conclusions:

  • Zebrafish xenografts effectively model cancer immunoediting dynamics and innate immune responses.
  • Macrophages and neutrophils play a vital role in eliminating tumor cells.
  • Zebrafish xenografts show promise as living biomarkers for evaluating the tumor microenvironment and predicting treatment responses.

Related Concept Videos