Back

Integrin blocking peptide reverses immunosuppression in experimental gliomas and improves anti-PD-1 therapy outcome

Ellert-Miklaszewska, A.; Pilanc-Kudlek, P.; Poleszak, K.; Roura, A.-J.; Cyranowski, S.; Ghosh, M.; Baluszek, S.; Pasierbinska, M.; Gielniewski, B.; Swatler, J.; Hovorova, Y.; Wojnicki, K.; Kaminska, B.

2024-08-08 cancer biology
10.1101/2024.08.06.606798 bioRxiv
Show abstract

Immune checkpoint inhibitors (ICI) presented clinical benefits in many cancer patients but invariably fail in glioblastoma (GBM), the most common and deadly primary brain tumor. Lack of ICI efficacy in GBM is attributed to the accumulation of immunosuppressive myeloid cells that create the "cold" tumor microenvironment (TME) impeding infiltration and activation of effector T cells. We developed a designer RGD peptide that hindered glioma-instigated, integrin-mediated pro-tumoral reprogramming of myeloid cells and blocked microglia-dependent invasion of human and mouse glioma cells in co-cultures in vitro. Intratumorally-delivered RGD alone did not reduce glioma growth in syngeneic mice but prevented the emergence of immunosuppressive myeloid cells and led to peritumoral blood vessels normalization. Furthermore, combining RGD with immunotherapy using PD-1 blockade reduced tumor growth, led to upsurge of proliferating, interferon-{gamma} producing CD8+T cells and depleted regulatory T cells. Transcriptomic profiles of myeloid cells were altered by the combined treatment, consistently with the restored "hot" inflammatory TME and boosted immunotherapy responses. RGD modified the phenotypes of myeloid cells in human gliomas in nude mice. Thus, combining the integrin blockade with ICI reinvigorates antitumor immunity and paves the way to improve immunotherapy outcomes in GBM.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.