The N-terminal SAM domain of the dNTPase SAMHD1 is not required for inhibition by small molecule TH6342.

Sterile alpha motif and histidine-aspartic acid domain containing protein-1 (SAMHD1) is a deoxynucleoside triphosphate (dNTP) hydrolase that controls dNTP pools and detoxifies cancer cells of chemotherapy metabolites. TH6342 is a recently reported small molecule inhibitor of SAMHD1 that interacts with the protein and non-competitively prevents dimerisation, a prerequisite for catalysis. The binding site of TH6342 on SAMHD1 is currently unknown.

Targeting autophagy as a therapeutic strategy in pediatric acute lymphoblastic leukemia.

Autophagy is activated in response to a variety of stress conditions including anti-cancer therapies, and tumors cells often depend on autophagy for survival. In this study, we have evaluated inhibition of autophagy as therapeutic strategy in acute lymphoblastic leukemia (ALL) in children, both as a single treatment and in combination with glucocorticoid (GC) Dexamethasone (Dexa). Analysis of proteomics and RNA-seq of ALL cell lines and primary samples identified an upregulation of Vps34 and ATG14 proteins and autophagy and lysosomal pathway enrichment in a genetic subgroup with a recurrent t(12;21) translocation.

Identification and evaluation of small-molecule inhibitors against the dNTPase SAMHD1 via a comprehensive screening funnel.

SAMHD1 is a dNTP triphosphohydrolase governing nucleotide pool homeostasis and can detoxify chemotherapy metabolites controlling their clinical responses. To understand SAMHD1 biology and investigate the potential of targeting SAMHD1 as neoadjuvant to current chemotherapies, we set out to discover selective small-molecule inhibitors. Here, we report a discovery pipeline encompassing a biochemical screening campaign and a set of complementary biochemical, biophysical, and cell-based readouts for rigorous characterization of the screen output.

The drug efficacy testing in 3D cultures platform identifies effective drugs for ovarian cancer patients.

Most patients with advanced ovarian cancer (OC) relapse and progress despite systemic therapy, pointing to the need for improved and tailored therapy options. Functional precision medicine can help to identify effective therapies for individual patients in a clinically relevant timeframe. Here, we present a scalable functional precision medicine platform: DET3Ct (Drug Efficacy Testing in 3D Cultures), where the response of patient cells to drugs and drug combinations are quantified with live-cell imaging.