Back

A first-in-class Wiskott-Aldrich syndrome protein (WASp) activator with anti-tumor activity in hematological cancers

Spriano, F.; Sartori, G.; Barnabei, L.; Arribas, A. J.; Guala, M.; Del Amo, A. M.; Tomasso, M. R.; Tarantelli, C.; Cascione, L.; Golino, G.; Riveiro, M. E.; Bortolozzi, R.; Lupia, A.; Paduano, F.; Huguet, S.; Rezai, K.; Margheriti, F.; Ventura, P.; Guarda, G.; Costa, G.; Rocca, R.; Cavalli, A.; Viola, G.; Driessen, C.; Zucca, E.; Stathis, A.; Bornhauser, B.; Alcaro, S.; Trapasso, F.; Cristobal, S.; Padrick, S. B.; Pazzi, N.; Cavalli, F.; Bertoni, F.; Gaudio, E.

2022-11-25 cancer biology
10.1101/2022.11.25.517686 bioRxiv
Show abstract

Hematological cancers are among the most common cancers in adults and in children. Despite significant improvements in therapies, many patients still succumb to the disease, therefore, novel therapies are needed. The Wiskott-Aldrich syndrome protein (WASp) family proteins regulate actin assembly in conjunction with the Arp2/3 complex, a ubiquitous nucleation factor. WASp is expressed exclusively in hematopoietic cells and exists in two allosteric conformations, auto-inhibited and active conformations. Here, we describe the development of EG-011, a first-in-class small molecule activator of the WASp auto-inhibited form. EG-011 possesses in vitro and in vivo anti-tumor activity as single agent in lymphoma, leukemia and multiple myeloma, including models of secondary resistance to PI3K, BTK and proteasome inhibitors. The in vitro activity was confirmed in a lymphoma xenograft. Actin polymerization induced by EG-011 was demonstrated with multiple techniques. Transcriptome analysis highlighted homology with drugs inducing actin polymerization. Key pointsO_LIEG-011 is a novel small molecule with anti-tumor activity in hematological cancers, including resistant lymphoma and multiple myeloma models C_LIO_LIEG-011 is a first-in-class small molecule activator of the auto-inhibited form of the Wiskott-Aldrich syndrome protein (WASp) C_LI

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.