Back

hENT Inhibition Prevents Pyrimidine-Driven Resistance to DHODH Inhibition in Malignant Rhabdoid Tumors

Kes, M. M. G.; Perticari, G.; Kooiman, J.; Anderson, N.; Jansen, J. W. A.; Zaal, E. A.; Berkers, C. R.; Drost, J.

2026-01-27 cancer biology
10.64898/2026.01.25.701565 bioRxiv
Show abstract

Extracranial malignant rhabdoid tumors (ecMRTs) are aggressive pediatric cancers characterized by mutations in genes encoding members of the SWItch/Sucrose Non-Fermentable (SWI/SNF) chromatin remodeling complex, with limited effective treatment options. Metabolic reprogramming, including nucleotide biosynthesis, is a hallmark of cancer that represents a potential therapeutic vulnerability. Previously, we demonstrated that inhibition of the de novo pyrimidine synthesis enzyme dihydroorotate dehydrogenase (DHODH) represents a promising treatment strategy for rhabdoid tumors, including ecMRTs and atypical teratoid/rhabdoid tumors (AT/RTs). Using patient-derived tumoroid models, we now extend these findings by showing that another SWI/SNF-deficient pediatric cancer, small cell carcinoma of the ovary, hypercalcemic type (SCCOHT), is also sensitive to DHODH inhibition. Gene expression analyses further confirmed that SCCOHT and AT/RT, like ecMRT, exhibit elevated expression of de novo nucleotide synthesis genes. To determine whether metabolic features of the tumor microenvironment (TME) influence DHODH inhibitor (DHODHi) response, we profiled plasma and tumor interstitial fluid from orthotopic ecMRT-bearing mice and found that the TME was markedly enriched in nucleosides and nucleobases. Supplementation of standard culture media with these nucleosides demonstrated that pyrimidines, but not purines, can rescue ecMRT cells from DHODHi-induced growth inhibition via activation of the pyrimidine salvage pathway. This resistance mechanism was effectively reversed by co-treatment with human equilibrative nucleoside transporter (hENT) inhibitors, enhancing DHODHi sensitivity in ecMRTs. Collectively, these findings reveal a conserved metabolic vulnerability across SWI/SNF-deficient pediatric cancers and emphasize the critical importance of modeling tumor metabolism under physiologically relevant conditions to accurately identify metabolism-targeted therapeutic strategies for these currently lethal pediatric cancer types.

Matching journals

The top 9 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.