SEARCH, a machine learning methodology developed by our lab, has been previously used to discover ELTD1 as driver of angiogenesis. We confirmed that its expression is increased in the vasculature and associated with good prognosis in multiple cancer types. Here we show that 35% of primary human breast tumours is positive for ELTD1 expression. Using immunocompetent, syngeneic mouse breast cancer models we found that tumours expressing recombinant murine Eltd1 grow faster and have enhanced ability to metastasize and promote systemic immune effects. Eltd1-expressing tumours have larger and better perfused vessels and tumour-endothelial cell interaction leading to the release of pro-angiogenic and immune modulating factors. The results in this study suggest that ELTD1 expression may enhance delivery of therapeutic antibodies to reverse the immunosuppression and increase response to chemotherapy and radiotherapy.

ADGRL4/ELTD1 expression in breast cancer cells induces vascular normalization and immune suppression

Buffa, Francesca M.
Methodology
;
2021-01-01

Abstract

SEARCH, a machine learning methodology developed by our lab, has been previously used to discover ELTD1 as driver of angiogenesis. We confirmed that its expression is increased in the vasculature and associated with good prognosis in multiple cancer types. Here we show that 35% of primary human breast tumours is positive for ELTD1 expression. Using immunocompetent, syngeneic mouse breast cancer models we found that tumours expressing recombinant murine Eltd1 grow faster and have enhanced ability to metastasize and promote systemic immune effects. Eltd1-expressing tumours have larger and better perfused vessels and tumour-endothelial cell interaction leading to the release of pro-angiogenic and immune modulating factors. The results in this study suggest that ELTD1 expression may enhance delivery of therapeutic antibodies to reverse the immunosuppression and increase response to chemotherapy and radiotherapy.
2021
Sheldon, Helen; Bridges, Esther; Silva, Ildefonso; Masiero, Massimo; Favara, David M.; Wang, Dian; Leek, Russell; Snell, Cameron; Roxanis, Ioannis; Kreuzer, Mira; Gileadi, Uzi; Buffa, Francesca M.; Banham, Alison; Harris, Adrian L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4052745
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