Deleterious variants in dihydropyrimidine dehydrogenase (DPD, DPYD gene) can be highly predictive of clinical toxicity to the widely prescribed chemotherapeutic 5-fluorouracil (5-FU). However, there are very limited data pertaining to the functional consequences of the >450 reported no-synonymous DPYD variants. We developed a DPYD-specific variant classifier (DPYD-Varifier) using machine learning and in vitro functional data for 156 missense DPYD variants. The developed model showed 85% accuracy and outperformed other in silico prediction tools. An examination of feature importance within the model provided additional insight into functional aspects of the DPD protein relevant to 5-FU toxicity. In the absence of clinical data for unstudied variants, prediction tools like DPYD-Varifier have great potential to individualize medicine and improve the clinical decision-making process.
ASJC Scopus subject areas
- Pharmacology (medical)