Abstract 3894: DPYD-Varifier, a computational model to identify 5-FU toxicity-associated DPYD variants

Shikshya Shrestha; Cheng Zhang; Calvin R. Jerde; Hu Li; Steven M. Offer; Robert B. Diasio

doi:10.1158/1538-7445.AM2018-3894

Abstract 5-Fluorouracil (5-FU) is a cornerstone therapy for the treatment of several aggressive tumors. However, nearly 1/3 of patients receiving 5-FU experience severe (grade 3+) adverse 5-FU toxicity. Genetic variations in dihydropyrimidine dehydrogenase (DPD; DPYD gene) are major contributors of 5-FU toxicity. With continued progress in next-generation sequencing technologies, the number of reported genetic variants is substantially increasing; to date, there are more than 450 reported missense variants in the DPYD gene. Only a handful of those variants, including *2A, I560S, D949V, and rs75017182, have been established as predictors of toxicity. Because most of the remaining variants are unstudied, mainly due to their rare occurrence and unequal racial distribution, it is challenging to conduct statistically powered clinical association studies. Therefore, in vitro and computational methods to identify potential toxicity-associated variants have major appeal. The primary goal of the current study was to develop a highly accurate gene-specific in silico classifier to predict deleterious DPYD variants. For this purpose, using a recombinant cellular model, we characterized 69 missense DPYD variants reported in online databases. We then utilized DPD activity data from the 69 variants in combination with data from 87 previously characterized variants (see Offer, SM et al. Cancer Research 2013 & 2014) to develop the DPYD variant classifier model (DPYD-Varifier). DPD protein-specific biochemical and structural features and amino acid conservation scores were integrated into the model's random forest classifier-based algorithm. DPYD-Varifier showed improved accuracy (85% accurate) compared to other in silico tools. Additionally, the model provided mechanistic insights into alterations of DPD function conferred by DPYD variants. In general, deleterious variants were located in closer proximity to important binding/coordinating sites of the DPD protein. Additionally, DPYD-Varifier allowed us to estimate the cumulative allele frequency of all reported deleterious variants in various geographical/racial groups, which can substantially add to our knowledge of DPD deficiency and 5-FU toxicity observed in these populations. In conclusion, the integration of in vitro and accurate computational data from our study permitted classification of relevant DPYD variants, which could be useful to more effectively individualize 5-FU therapy in the future. Citation Format: Shikshya Shrestha, Cheng Zhang, Calvin R. Jerde, Hu Li, Steven M. Offer, Robert B. Diasio. DPYD-Varifier, a computational model to identify 5-FU toxicity-associated DPYD variants [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3894.

Abstract 3894: DPYD-Varifier, a computational model to identify 5-FU toxicity-associated DPYD variants

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