Back

More than a ligand: PD-L1 promotes oncolytic virus infection via a metabolic shift that inhibits the type I interferon pathway.

Hodgins, J.; Abou-Hamad, J.; Hagerman, A.; Yakubovich, E.; Tanese De Souza, C.; Marotel, M.; Buchler, A.; Fadel, S.; Park, M.; Fong-McMaster, C.; Crupi, M. J. F.; Bell, J. C.; Harper, M.-E.; Rotstein, B.; Auer, R.; Vanderhyden, B.; Sabourin, L.; Bourgeois-Daigneault, M.-C.; Cook, D.; Ardolino, M.

2022-09-03 cancer biology
10.1101/2022.08.31.506095 bioRxiv
Show abstract

Targeting the PD-1/PD-L1 axis has transformed the field of immune-oncology. While conventional wisdom initially postulated that PD-L1 serves as the inert ligand for PD-1, an emerging body of literature suggests that PD-L1 has cell-intrinsic functions in immune and cancer cells. In line with these studies, here we show that engagement of PD-L1 via cellular ligands or agonistic antibodies, including those used in the clinic, potently inhibits the type I interferon pathway in cancer cells. Hampered type I interferon responses in PD-L1-expressing cancer cells resulted in enhanced infection with oncolytic viruses in vitro and in vivo. Consistently, PD-L1 expression marked tumor explants from cancer patients that were best infected by oncolytic viruses. Mechanistically, PD-L1 suppressed type I interferon by promoting a metabolic shift characterized by enhanced glucose uptake and glycolysis rate. Lactate generated from glycolysis was the key metabolite responsible for inhibiting type I interferon responses and enhancing oncolytic virus infection in PD-L1-expressing cells. In addition to adding mechanistic insight into PD-L1 intrinsic function and showing that PD-L1 has a broader impact on immunity and cancer biology besides acting as a ligand for PD-1, our results will also help guide the numerous efforts currently ongoing to combine PD-L1 antibodies with oncolytic virotherapy in clinical trials. Once sentence summaryPD-L1 promotes oncolytic virus efficacy.

Matching journals

The top 6 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.