Author
Listed:
- Vanda Póvoa
(Champalimaud Foundation)
- Cátia Rebelo de Almeida
(Champalimaud Foundation)
- Mariana Maia-Gil
(Champalimaud Foundation)
- Daniel Sobral
(Universidade NOVA de Lisboa)
- Micaela Domingues
(Champalimaud Foundation)
- Mayra Martinez-Lopez
(Champalimaud Foundation)
- Miguel de Almeida Fuzeta
(Champalimaud Foundation)
- Carlos Silva
(Champalimaud Foundation)
- Ana Rita Grosso
(Universidade NOVA de Lisboa)
- Rita Fior
(Champalimaud Foundation)
Abstract
Cancer immunoediting is a dynamic process of crosstalk between tumor cells and the immune system. Herein, we explore the fast zebrafish xenograft model to investigate the innate immune contribution to this process. Using multiple breast and colorectal cancer cell lines and zAvatars, we find that some are cleared (regressors) while others engraft (progressors) in zebrafish xenografts. We focus on two human colorectal cancer cells derived from the same patient that show contrasting engraftment/clearance profiles. Using polyclonal xenografts to mimic intra-tumor heterogeneity, we demonstrate that SW620_progressors can block clearance of SW480_regressors. SW480_regressors recruit macrophages and neutrophils more efficiently than SW620_progressors; SW620_progressors however, modulate macrophages towards a pro-tumoral phenotype. Genetic and chemical suppression of myeloid cells indicates that macrophages and neutrophils play a crucial role in clearance. Single-cell-transcriptome analysis shows a fast subclonal selection, with clearance of regressor subclones associated with IFN/Notch signaling and escaper-expanded subclones with enrichment of IL10 pathway. Overall, our work opens the possibility of using zebrafish xenografts as living biomarkers of the tumor microenvironment.
Suggested Citation
Vanda Póvoa & Cátia Rebelo de Almeida & Mariana Maia-Gil & Daniel Sobral & Micaela Domingues & Mayra Martinez-Lopez & Miguel de Almeida Fuzeta & Carlos Silva & Ana Rita Grosso & Rita Fior, 2021.
"Innate immune evasion revealed in a colorectal zebrafish xenograft model,"
Nature Communications, Nature, vol. 12(1), pages 1-15, December.
Handle:
RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21421-y
DOI: 10.1038/s41467-021-21421-y
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