4.7 Article

Predicting Dihydropyrimidine Dehydrogenase Deficiency and Related 5-Fluorouracil Toxicity: Opportunities and Challenges of DPYD Exon Sequencing and the Role of Phenotyping Assays

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MDPI
DOI: 10.3390/ijms232213923

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5-fluorouracil; DPYD; dihydropyrimidine dehydrogenase; next generation sequencing; polymorphism; phenotyping; genotyping

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  1. Sapienza University of Rome-Progetti di Ricerca (Piccoli, Medi)-Progetti Piccoli [2021RP12117A764C1EB2]

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NGS exon sequencing can explain approximately 42.5% of DPD deficiencies, significantly improving the prediction of DPD deficiencies, but more genotype-phenotype association data is needed for clinical use.
Deficiency of dihydropyrimidine dehydrogenase (DPD), encoded by the DPYD gene, is associated with severe toxicity induced by the anti-cancer drug 5-Fluorouracil (5-FU). DPYD genotyping of four recommended polymorphisms is widely used to predict toxicity, yet their prediction power is limited. Increasing availability of next generation sequencing (NGS) will allow us to screen rare variants, predicting a larger fraction of DPD deficiencies. Genotype-phenotype correlations were investigated by performing DPYD exon sequencing in 94 patients assessed for DPD deficiency by the 5-FU degradation rate (5-FUDR) assay. Association of common variants with 5-FUDR was analyzed with the SNPStats software. Functional interpretation of rare variants was performed by in-silico analysis (using the HSF system and PredictSNP) and literature review. A total of 23 rare variants and 8 common variants were detected. Among common variants, a significant association was found between homozygosity for the rs72728438 (c.1974+75A>G) and decreased 5-FUDR. Haplotype analysis did not detect significant associations with 5-FUDR. Overall, in our sample cohort, NGS exon sequencing allowed us to explain 42.5% of the total DPD deficiencies. NGS sharply improves prediction of DPD deficiencies, yet a broader collection of genotype-phenotype association data is needed to enable the clinical use of sequencing data.

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